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Research ArticlePrecipitation Trends over Time Using Mann-Kendall andSpearmanrsquos rho Tests in Swat River Basin Pakistan
Ijaz Ahmad1 Deshan Tang1 TianFang Wang2 Mei Wang1 and Bakhtawar Wagan1
1College of Water Conservancy and Hydropower Engineering Hohai University Nanjing 210098 China2School of Earth Science and Engineering Hohai University Nanjing 210098 China
Correspondence should be addressed to Ijaz Ahmad engrijaz786gmailcom
Received 14 October 2014 Revised 12 December 2014 Accepted 16 December 2014
Academic Editor Harry D Kambezidis
Copyright copy 2015 Ijaz Ahmad et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited
Accurately predicting precipitation trends is vital in the economic development of a countryThis research investigated precipitationvariability across 15 stations in the Swat River basin Pakistan over a 51-year study period (1961ndash2011) Nonparametric Mann-Kendall (MK) and Spearmanrsquos rho (SR) statistical tests were used to detect trends in monthly seasonal and annual precipitationand the trend-free prewhitening approach was applied to eliminate serial correlation in the precipitation time series The resultshighlighted a mix of positive (increasing) and negative (decreasing) trends in monthly seasonal and annual precipitation Onestation in particular the Saidu Sharif station showed the maximum number of significant monthly precipitation events followedby Abazai Khairabad and Malakand On the seasonal time scale precipitation trends changed from the summer to the autumnseasonThe Saidu Sharif station revealed the highest positive trend (748mmyear) in annual precipitation In the entire Swat Riverbasin statistically insignificant trends were found in the subbasins for the annual precipitation series however the Lower Swatsubbasin showed the maximum quantitative increase in the precipitation at a rate of 218mmyearThe performance of theMK andSR tests was consistent at the verified significance level
1 Introduction
Rainfall and other precipitation levels are important factorsaffecting crop selection and ecological changes in a regionAccurately predicting precipitation trends can play an impor-tant role in a countryrsquos future economic development
Rahman and Begum [1] noted that predicting trendsusing precipitation time series data is more difficult thanpredicting temperature trendsThe fourth IntergovernmentalPanel on Climate Change (IPCC) reported temporal and spa-tial variation in precipitation trends throughout the latter halfof the century across Asia [2] Recently meteorologists andother researchersworldwide have paid significant attention toanalyzing precipitation time series trends Decreasing trendsin mean annual rainfall have been found in the coastal andarid plains of Pakistan [3] Northeast and North China [4 5]Madhya Pradesh India [6] and Russia [7 8] Increasingmean annual rainfall trendswere observed in the Chang Jiang
valley southeast coastal areas andWesternChina [4 5 9] andBangladesh in the summer season [10 11]
Different statistical test methods are used to detect trendsin hydrological and hydrometeorological time series theseare classified as parametric and nonparametric tests [12ndash14]Parametric tests are more powerful but require that data beindependent and normally distributed which is rarely truefor hydrological time series data For nonparametric testsdata must be independent but outliers are better toleratedThemost commonnonparametric tests forworkingwith timeseries trends are the Mann-Kendall [15 16] and Spearmanrsquosrho [17 18] testsTheMann-Kendall test is the most commonone used by researchers in studying hydrologic time seriestrends [19ndash23] less common Spearmanrsquos rho is used todetect monotonic trends in hydrometeorological data [24]In many studies Spearmanrsquos rho is used in combinationwith the Mann-Kendall test for comparison purposes [24ndash28]
Hindawi Publishing CorporationAdvances in MeteorologyVolume 2015 Article ID 431860 15 pageshttpdxdoiorg1011552015431860
2 Advances in Meteorology
Natural disasters including avalanches cyclones andstorms droughts and floods and cloudburst flash floods(CBFF) pose serious risks to Pakistani society [29ndash31]Pakistan has faced one major flood approximately every 3years creating challenges for economic development [32]In 2010 Pakistan faced the worst flood event in its history[33] Experts from the World Climate Research ProgrammeandWorld Meteorological Organization (WMO) have statedthat climate change is one of the main reasons for thisunprecedented sequence of weather events A UN scientificbody concluded that hot extremes heat waves and heavyprecipitation events will likely continue to become morefrequent in Pakistan the same body warns that floodsmay become more frequent and intense in the future [2]WMO has noted that the 2010 floods were consistent withthe sequence predicted by climate experts further statingthat current events match projections of more frequent andintense weather events due to global warming [34]
Floods in Pakistan are generally caused by concentratedheavy precipitation in watersheds sometimes augmented bysnowmelt flows causing river floods during the monsoonseason Hartmann and Andresky [35] reported that the pre-cipitation regimes in northwest areas of Pakistan are mainlycontrolled by monsoon rains from July to September theyhave become more intense in recent years Salma et al [36]analyzed Pakistan rainfall trends using analysis of variance(ANOVA) from 1976 to 2005 and concluded that while theoverall rainfall trends have declined rainfall consequencessuch as droughts and super floods have badly affected humansettlements water management and agriculture sectorsHanif et al [37] found significant precipitation changes innorthern parts of Pakistan during the summer and monsoon(July and August) seasons Significant increasing trends inprecipitation over time have been detected in northeastareas of Pakistan during the monsoon season [38] Cheemaand Hanif [39] detected increasing rainfall trends in thePunjab province of Pakistan Significant increasing trendswere detected in the northwest (Hindu Kush and SulaimanMountains) and in the east (Himalayas) areas of the IndusRiver basin insignificant negative trends were found in thenortheast (Karakorum and Transhimalaya) and lowland ofthe upper Indus River basin [35 40]
During the last week of July 2010 unprecedented rains fellin Swat andKabul river catchment areas causing catastrophicfloods in excess of 400000 cusecs exceeding the previousrecord flood set in 1929 (250000 cusecs) and impacting24 districts of the KPK province of Pakistan [32] Due tochanging weather patterns Pakistanrsquos KPK province and theSwat River area have been exposed to risks from frequentfloods and droughts in recent years [31 41] Most past studieshowever have focused on climatic trend analyses in theupper Indus River basin No precipitation trend studies havefocused on the Swat River basin which has faced frequentfloods and droughts over the years This study fills thisresearch gap
This study investigated trends and variations in precip-itation over time at the Swat River basin in Pakistan usingMann-Kendall and Spearmanrsquos rho tests This study pro-vides a broad overview of precipitation statistics including
seasonal and interannual variability over the SwatRiver basinand may help managers and agricultural planners The studyconsiders precipitation data from 51 years (1961ndash2011) at 15stations
2 Methodology
21 Study Area This study investigates the variability inprecipitation time series for a 51-year period (1961ndash2011) inthe Swat River basin in the Khyber Pakhtunkhwa (KPK)province of PakistanThe Swat River originates from the highmountains of Swat Kohistan where the mean elevation is4500m in the northwest parts of the country The river flowsthrough the Kalam valley and the Swat district then skirtsthe Lower Dir district flows through Malakand and Mardandistricts and outflows into the Kabul River
The Swat River is important for the future economicdevelopment of Pakistan There are three hydropower plantswith a combined operational capacity of 123MWon the SwatRiver At the time of this writing another hydroelectric powergeneration plant (Munda Dam) with a projected capacityof 740MW is being constructed on the Swat River Thisdam along with the hydropower generation will irrigate15100 acres of land They will also provide flood protectionto theCharsadda andNowshera districts whichwere severelyaffected by flooding in 2010
The riverrsquos catchment area is generally mountainous withelevations ranging from approximately 360m to 4500mfrom south to north Vegetation occurs between 1800mand 3400m and glaciers are visible above 4000m TheSwat River basin catchment lies between a latitude of 34∘001015840north to 35∘561015840 north and longitude 70∘591015840 east to 72∘471015840east
22 Data andMethods The total Swat River basin catchmentarea is 16750 km2 with 15 meteorological stations shown inFigure 1 The area is further divided into four subregionsupper Swat River basin (A1) Panjkora River basin (A2)Ambahar River basin (A3) and Lower Swat River basin(A4) The catchment areas for these basins are 5968 57331485 and 3564 km2 respectively To detectmonotonic trendsmonthly precipitation values were added to generate theannual and seasonal precipitation Mean precipitation valuesat corresponding stations were considered to determinesubbasin precipitation (A1 A2 A3 and A4) and precipitationacross the entire Swat River basin (A) This procedure wasadopted from Duhan and Pandey [6]
Rain gauge stations within the Swat River catchment areaare operated by PakistanMeteorological Department (PMD)Irrigation Department of KPK province (ID) and SurfaceWater Hydrology Project (SWHP) Snowy Mountains Engi-neering Corporation (SMEC) Pakistan under the MundaDam construction project collected the precipitation timeseries data from these agencies and processed it to ensurehomogeneity and quality control [42]
Mann-Kendall and Spearmanrsquos rho tests are nonpara-metric therefore data outliers do not affect the results Thehomogeneity of the precipitation time series was assessed
Advances in Meteorology 3
34∘-00998400
34∘-15998400
34∘-30998400
34∘-45998400
35∘-00998400
35∘-15998400
35∘-30998400
35∘-45998400
36∘-00998400
34∘-00998400
34∘-15998400
34∘-30998400
34∘-45998400
35∘-00998400
35∘-15998400
35∘-30998400
35∘-45998400
36∘-00998400
70∘-4
5998400
71∘-0
0998400
71∘-1
5998400
71∘-3
0998400
71∘-4
5998400
72∘-0
0998400
72∘-1
5998400
72∘-3
0998400
72∘-4
5998400
73∘-0
0998400
70∘-4
5998400
71∘-0
0998400
71∘-1
5998400
71∘-3
0998400
71∘-4
5998400
72∘-0
0998400
72∘-1
5998400
72∘-3
0998400
72∘-4
5998400
73∘-0
0998400
Afghan
istan
A3
A3
A2
A2
A1
A1
A4
A4
N
Ambahar
Abazai
ToorCamp
Dir
Drosh Kalam
Thalozom
Madyan
Khairabad
Saidu Sharif
Malakand
Mardan
RisalpurCharsadda
Kulangi
Upper Swat subbasin
Panjkora subbasin
Ambahar subbasin
Lower Swat subbasin
Figure 1 Locations of meteorological stations at Swat River basin
by applying two tests standard normal homogeneity test(SNHT) [43 44] and Buishandrsquos range (BR) test [45] ata 5 significance level for each station The precipitationtime series is considered homogenous if the critical values ofSNHT and BR statistics are less than 917 [46] and 127 155[45] respectively As Table 1 shows all the precipitation serieswere found to be homogenous
23 Statistical Tests Prior to applying MK and SR teststo identify precipitation trends over the time series fromselected stations data were tested according to the testsrsquo re-quirements The trend-free prewhitening (TFPW) approachwas applied to eliminate serial correlations in the time seriesdata The magnitude of the slope in time series data wascalculated using Senrsquos slope method The statistical methodsused are briefly discussed below
231 Autocorrelation and TFPW Removing serial depen-dence is one of the main problems in testing and interpretingtime series data Applying nonparametric tests to detecttrends can significantly affect the results Therefore all ofthe rainfall time series data was first tested for the presenceof autocorrelation coefficient (119903
1) at a 5 significance level
using a two-tailed test
1199031=
sum119899minus1
119894=1
(119883119894minus 119883) (119883
119894+1minus 119883)
sum119899
119894=1
(119883119894minus 119883)
2
(1)
The autocorrelation coefficient value of 1199031was tested against
the null hypothesis at a 95 confidence interval using a two-tailed test
1199031(95) =
minus1 plusmn 196radic(119899 minus 2)
119899 minus 1
(2)
4 Advances in Meteorology
Table 1 Results of homogeneity tests for mean annual precipitationtime series at study stations
Station SNHT Buishandrsquos range (BR) test1198790
119876radic119899 119877radic119899
Thalozom 916 108 108Drosh 906 117 147Kalam 887 087 108Dir 776 124 149Madyan 485 111 150Khairabad 192 062 093ToorCamp 620 117 154Saidu Sharif 742 118 190Malakand 257 077 086Kulangi 428 097 146Ambahar 508 109 139Abazai 686 121 140Mardan 893 108 124Charsadda 902 125 138Risalpur 724 091 125For homogenous series 119879
0lt 917119876radic119899 lt 127 and 119877radic119899 lt 155
If 1199031falls between the upper and lower limits of confidence
interval (the data are considered serially correlated) themethods of prewhitening variance correlation [47] andtrend-free prewhitening (TFPW) approach [24] have beenproposed In this study for the stations where serial cor-relations were detected in the data the TFPW approachwas applied to remove the correlation for both tests (Mann-Kendall and Spearmanrsquos rho) Other researchers [28 48ndash51]have also used this approach to eliminate serial correlation intime series data
232 The Mann-Kendall Test The rank-based nonparamet-ric Mann-Kendall [15 16] method was applied to the long-term data in this study to detect statistically significanttrends In this test the null hypothesis (H
0) was that there
has been no trend in precipitation over time the alternatehypothesis (H
1) was that there has been a trend (increasing
or decreasing) over time The mathematical equations forcalculatingMann-Kendall Statistics 119878119881(119878) and standardizedtest statistics 119885 are as follows
119878 =
119899minus1
sum
119894=1
119899
sum
119895=119894+1
sig (119883119895minus 119883119894)
sgn (119883119895minus 119883119894) =
+1 if (119883119895minus 119883119894) gt 0
0 if (119883119895minus 119883119894) = 0
minus1 if (119883119895minus 119883119894) lt 0
119881 (119878) =
1
18
[119899 (119899 minus 1) (2119899 + 5) minus
119902
sum
119901=1
119905119901(119905119901minus 1) (2119905
119901+ 5)]
119885 =
119878 minus 1
radicVAR (119878)if 119878 gt 0
0 if 119878 = 0
119878 + 1
radicVAR (119878)if 119878 lt 0
(3)
In these equations119883119894and119883
119895are the time series observations
in chronological order 119899 is the length of time series 119905119901is
the number of ties for 119901th value and 119902 is the number oftied values Positive 119885 values indicate an upward trend in thehydrologic time series negative 119885 values indicate a negativetrend If |119885| gt 119885
1minus1205722 (H0) is rejected and a statistically
significant trend exists in the hydrologic time series Thecritical value of119885
1minus1205722for a 119901 value of 005 from the standard
normal table is 196
233 Spearmanrsquos rho Test Spearmanrsquos rho [17 18] test isanother rank-based nonparametric method used for trendanalysis and was applied as a comparison with the Mann-Kendall test In this test which assumes that time seriesdata are independent and identically distributed the nullhypothesis (H
0) again indicates no trend over time the
alternate hypothesis (H1) is that a trend exists and that data
increase or decrease with 119894 [24] The test statistics 119877sp andstandardized statistics 119885sp are defined as
119877sp = 1 minus
6sum119899
119894=1
(119863119894minus 119894)2
119899 (1198992
minus 1)
119885sp = 119877spradic119899 minus 2
1 minus 1198772
sp
(4)
In these equations 119863119894is the rank of 119894th observation 119868 is the
chronological order number 119899 is the total length of the timeseries data and 119885sp is Studentrsquos 119905-distribution with (119899 minus 2)degree of freedom The positive values of 119885sp represent anincreasing trend across the hydrologic time series negativevalues represent the decreasing trends The critical value of119905 at a 005 significance level of Studentrsquos 119905-distribution tableis defined as 119905
(119899minus21minus1205722)[12] If |119885sp| gt 119905
(119899minus21minus1205722) (H0) is
rejected and a significant trend exists in the hydrologic timeseries
234 Senrsquos Slope Estimator Senrsquos nonparametric method [52]was used to estimate the magnitude of trends in the timeseries data
119879119894=
119909119895minus 119909119896
119895 minus 119896
(5)
In this equation 119909119895and 119909
119896represent data values at time 119895 and
119896 respectively Consider
119876119894=
119879(119873+1)2
119873 is odd1
2
(1198791198732
+ 119879(119873+2)2
) 119873 is even(6)
A positive119876119894value represents an increasing trend a negative
119876119894value represents a decreasing trend over time
Advances in Meteorology 5
Table 2 Summary of geographic conditions and mean annual precipitation statistics for study stations
Station Longitude Latitude Elevation (m) Mean (mm) STD 119862119904
119862119896
119862V
Thalozom 72∘-151015840 35∘-441015840 4200 7511 2099 minus0266 0082 0291Drosh 72∘-001015840 35∘-331015840 1465 4635 1537 1167 2441 0332Kalam 72∘-331015840 35∘-311015840 2000 9345 3170 minus0599 0323 0353Dir 71∘-531015840 35∘-121015840 1321 5482 1521 minus0545 0919 0285Madyan 72∘-321015840 35∘-091015840 1320 9623 2878 0240 1300 0307Khairabad 72∘-061015840 34∘-581015840 894 7037 1522 1410 4281 0216ToorCamp 71∘-421015840 34∘-501015840 854 5440 1592 minus0436 0841 0299Saidu Sharif 72∘-251015840 34∘-451015840 961 9901 3898 1842 6463 0398Malakand 71∘-461015840 34∘-381015840 603 6098 2526 2474 11668 0424Kulangi 71∘-591015840 34∘-351015840 688 6254 1925 0037 minus0170 0308Ambahar 71∘-121015840 34∘-331015840 694 4550 1485 minus0004 0764 0333Abazai 71∘-331015840 34∘-261015840 320 5007 1527 minus0093 0963 0312Mardan 71∘-581015840 34∘-181015840 283 6574 2974 0735 1392 0452Charsadda 71∘-431015840 34∘-071015840 276 5916 2074 0973 1031 0350Risalpur 71∘-541015840 34∘-061015840 309 6118 1768 0312 minus0098 0289
3 Results and Discussion
31 Preliminary Analysis The preliminary analysis for thisstudy included computing the mean standard deviationcoefficient of skewness coefficient of kurtosis and coefficientof variation in the annual precipitation time series foreach station Table 2 presents these statistical parametersfor the 51-year time period studied (1961ndash2011) The meanannual precipitation varied between 455mm in the southwestpart of the Swat River basin catchment area (Ambahar)and 9901mm in the southeast part (Saidu Sharif) As thetable shows the coefficient of skewness varied from minus0266to 2474 kurtosis varied between minus0170 and 11668 Fortime series data to be considered normally distributed thecoefficient of skewness and kurtosis must be equal to 0and 3 respectively Table 2 indicates therefore that the dataare positively skewed and not normally distributed Thecoefficient of variation the measure of dispersion around themean was also calculated to analyze the spatial variability ofannual precipitation for each station This coefficient variedbetween 216 (Khairabad) and 452 (Mardan)The averagevariation of the precipitation over the complete river basinwas 289
32 Long-Term Pattern on Seasonal and Annual Scale Long-term climatic patterns were assessed using standardizedseasonal and annual precipitation time series data Toreduce local fluctuations LOWESS [53ndash55] curves were fittedover time based on seasonal and annual precipitation timeseries data The LOWESS curve for winter precipitation(Figure 2(a)) showed a decreasing trend in the first decadeIn the second decade the trend was constant The minimumLOWESS curve value was observed in 1990 values thengradually rose through 2010 Overall the curve based onwinter season data suggested a decline in precipitation After1990 there was a gradual rise though small local fluctuationswere ignored The LOWESS curve for spring precipitation(Figure 2(b)) showed a gradual increase in the first three
decades After attaining its highest value in 1990 the valuedeclined over the last two decades
The LOWESS curve for summer precipitation showeda constant trend in the first decade and then started todecline up to 1978 (Figure 2(c)) For 1978ndash1992 the curvestarted to gradually increase through the remaining yearsThe LOWESS curve for autumn precipitation exhibited adecreasing trend through 1982 for the remaining time peri-ods there was an increase in precipitation For the annualprecipitation time series the LOWESS curve showed slightvariations in every decade but the overall trend was nearlyconstant throughout the time series Figure 2 shows theprecipitation patterns LOWESS curves are used to showpatterns and do not explain statistically significant trends inthe time series
33 Monthly Analysis The Mann-Kendall (MK) and Spear-manrsquos (SR) rho tests were applied on a monthly scale todetect trends in the precipitation series at different stationsTable 3 shows the results and illustrates that the results ofboth tests were similar to one another Monthly trend testsshowed a mix of positive and negative trends at differentstations At Thalozom statistically significant negative andpositive trends were found in April and June respectivelySignificant positive trends were detected at Dir and Droshstations in March and August no significant trends werefound for other months The Saidu Sharif station exhibitedsignificant positive trends from January to June and fromOctober to December but had negative trends in July andAugust Significant positive trends were found at most of thestations in the months of May and June significant negativetrends were seen in July and August In other stations a mixof significantly positive and negative trends occurred for afew months of the year Figure 3 shows the spatial variationin the precipitation time series for each month in the SwatRiver basin from 1961 to 2011
The magnitude of statistically significant trends on amonthly scale was determined using Senrsquos slope estimator
6 Advances in Meteorology
0
1
2
3
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
Original dataLOWESS line
minus3
minus2
minus1
(a)
Original dataLOWESS line
0
1
2
3
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
minus2
minus1
(b)
Original dataLOWESS line
0
1
2
3
4
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
minus2
minus1
(c)
Original dataLOWESS line
0
1
2
3
4
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
minus2
minus1
(d)
Original dataLOWESS line
0
1
2
3
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
minus3
minus2
minus1
(e)
Figure 2 Standardized precipitation and LOWESS trend curves at Swat River basin (a) winter (b) spring (c) summer (d) autumn and (e)annual
Advances in Meteorology 7
Table3MKandSR
tests
results
forp
recipitatio
nin
mon
thlytim
eseries
Station
Test
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Thalozom
MK
minus063
minus10
9minus042
minus219lowast
minus033
272lowast
minus080
minus094
minus029
010
146
030
SRminus044
minus10
1minus039
minus215lowast
minus040
293lowast
minus079
minus10
3minus013
028
141
013
Drosh
MK
minus008
minus024
016
minus067
063
151
minus19
4minus316lowast
minus063
040
103
001
SRminus014
minus001
008
minus079
067
173
minus18
7minus336lowast
minus050
039
101
017
Kalam
MK
minus037
minus067
033
minus221lowast
minus063
219lowast
minus115
minus10
4minus054
014
120
017
SRminus023
minus052
023
minus213lowast
minus064
229lowast
minus113
minus10
7minus043
014
091
minus066
Dir
MK
000
minus063
minus248lowast
minus021
minus079
112
minus015
003
174
minus13
1minus034
minus089
SRminus016
minus062
minus280lowast
minus018
minus10
010
7minus001
minus002
203lowast
minus16
3minus049
minus10
1
Madyan
MK
089
075
110
minus083
086
353lowast
minus312lowast
minus338lowast
minus023
190
272lowast
134
SR086
070
113
minus067
085
426lowast
minus324lowast
minus398lowast
minus016
200
301lowast
132
Khaira
bad
MK
091
minus068
minus021
minus080
201lowast
385lowast
minus312lowast
minus348lowast
minus019
268lowast
292lowast
112
SR082
minus072
minus028
minus079
204lowast
446lowast
minus334lowast
minus460lowast
minus017
308lowast
325lowast
097
ToorCa
mp
MK
192
093
045
minus070
minus044
minus086
minus291lowast
minus296lowast
minus227lowast
minus201lowast
094
028
SR17
8085
025
minus082
minus047
minus091
minus317lowast
minus361lowast
minus279lowast
minus233lowast
104
020
SaiduSh
arif
MK
274lowast
246lowast
222lowast
182
285lowast
327lowast
minus334lowast
minus309lowast
003
319lowast
357lowast
210lowast
SR302lowast
262lowast
261lowast
205lowast
324lowast
383lowast
minus360lowast
minus387lowast
020
364lowast
405lowast
217lowast
Malakand
MK
105
minus17
2minus115
010
228lowast
322lowast
minus318lowast
minus293lowast
016
350lowast
273lowast
149
SR099
minus202lowast
minus13
2022
254lowast
302lowast
minus380lowast
minus382lowast
023
397lowast
223lowast
091
Kulang
iMK
070
minus099
minus294lowast
minus14
4minus062
036
000
174
291lowast
minus16
4minus003
minus204lowast
SR059
minus10
4minus315lowast
minus14
1minus081
024
008
165
336lowast
minus18
5minus031
minus231lowast
Ambahar
MK
031
minus066
minus284lowast
minus10
5minus115
060
018
060
304lowast
minus13
6minus021
minus18
0SR
038
minus070
minus282lowast
minus111
minus118
058
019
034
356lowast
minus15
1minus029
minus201lowast
Abazai
MK
233lowast
minus025
minus091
137
292lowast
449lowast
minus262lowast
minus10
710
2331lowast
392lowast
261lowast
SR222lowast
minus029
minus090
162
289lowast
435lowast
minus307lowast
minus10
913
7385lowast
366lowast
272lowast
Mardan
MK
243lowast
134
041
001
105
070
014
minus016
100
minus058
minus13
1minus13
7SR
253lowast
134
050
011
110
072
025
minus020
088
minus051
minus115
minus115
Charsadd
aMK
232lowast
109
032
minus012
015
034
014
minus014
056
minus10
4minus217lowast
minus15
9SR
237lowast
109
026
minus024
032
044
022
minus033
043
minus097
minus204lowast
minus13
1
Risalpur
MK
191
128
006
minus027
minus033
minus037
minus006
minus063
minus026
minus14
6minus18
7minus217lowast
SR213lowast
113
006
minus036
minus017
minus025
minus005
minus072
minus026
minus15
0minus211lowast
minus216lowast
lowast
Sign
ificant
trend
at5
significance
leveloftwo-tailedtest
8 Advances in Meteorology
Jan Feb Mar Apr
May Jun Jul Aug
Sep Oct Nov Dec
N
0 5 10 25
Scale
(km)
Significant increasing trendSignificant decreasing trend
No trend
Figure 3 Location of sites with increasing decreasing and no trends at 5 significance level for the monthly precipitation time series
The results show that trends at Saidu Sharif Madyanand Kalam were more rapid (eg sharper increases anddecreases) compared to other stations The Saidu Sharifstation had the maximum negative decline in monthly pre-cipitation (183mmmonth) as well as the maximum positiveincrease (143mmmonth) during the months of July andMarch respectively Figure 4 shows the trends in maximummonthly precipitation variation at the Saidu Sharif station
34 Seasonal and Annual Analysis The MK and SR testswere also used to identify trends in seasonal and annualprecipitation between 1961 and 2011 Table 4 shows the resultsSimilar to the monthly analysis results from both statisticaltests MK and SR were consistent with one another A mixof negative and positive trends was seen at different stationsThalozom Kalam and Dir stations which had shown trends
with the monthly time scale did not exhibit statisticallysignificant trends for the seasonal and annual precipitationtime series At Madyan Khairabad and Malakand stationsthere were significant negative trends in the summer andpositive trends in the autumn Significant negative trendswere observed in the spring season only at ToorCampKulangi and Ambahar stations For the annual precipitationseries significant positive trends were detected only at SaiduSharif Mardan and Charsadda stations At other stationssignificant positive trends were seen for winter and autumnseasons and for the annual precipitation series howevernegative trends were detected in spring and summer seasonsFigure 5 presents the spatial distribution of seasonal andannual precipitation trends
The Saidu Sharif station showed the maximum positivetrend in annual precipitation series (748mmyear) across
Advances in Meteorology 9
0
100
200
300
400
500
600
700
800
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
mon
th)
Year
Saidu Sharif station(March)
(a)
0
100
200
300
400
500
600
700
800
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
mon
th)
Year
Saidu Sharif station(July)
(b)
Figure 4 Variations of monthly precipitation time series in stations with most significant trends during 1961ndash2011
Table 4 MK and SR tests results for precipitation in seasonal and annual time series
Station Test Winter Spring Summer Autumn Annual
Thalozom MK minus120 minus162 minus120 148 minus149SR minus114 minus152 minus110 135 minus145
Drosh MK 042 minus078 minus196 097 minus044SR 049 minus074 minus209lowast 127 minus048
Kalam MK minus062 minus139 minus171 160 minus110SR minus037 minus121 minus158 157 minus087
Dir MK minus028 minus148 minus047 minus076 minus138SR minus062 minus150 minus058 minus097 minus146
Madyan MK 120 003 minus258lowast 365lowast 042SR 137 033 minus244lowast 421lowast 078
Khairabad MK 026 minus065 minus302lowast 325lowast minus073SR 021 minus076 minus353lowast 364lowast minus072
ToorCamp MK minus063 minus203lowast 024 minus073 minus044SR minus096 minus217lowast 023 minus092 minus159
Saidu Sharif MK 346lowast 239lowast minus156 069 328lowast
SR 404lowast 280lowast minus156 148 278lowast
Malakand MK minus070 minus110 minus270lowast 337lowast minus119SR minus068 minus115 minus319lowast 373lowast minus140
Kulangi MK minus122 minus261lowast 031 minus099 minus144SR minus156 minus284lowast 037 minus127 minus172
Ambahar MK minus066 minus206lowast minus063 minus099 minus157SR minus076 minus224lowast minus058 minus110 minus141
Abazai MK 179 minus015 minus099 429lowast 096SR 217lowast 007 minus072 604lowast 122
Mardan MK 281lowast 145 095 minus102 259lowast
SR 310lowast 134 098 minus085 280lowast
Charsadda MK 266lowast 097 073 minus194 214lowast
SR 293lowast 088 060 minus176 217lowast
Risalpur MK 243lowast 044 minus006 minus154 198SR 254lowast 040 minus005 minus190 195
lowastSignificant trend at 5 significance level of two-tailed test
10 Advances in Meteorology
N
0 5 10 25
Scale
(km)
Significant increasing trendSignificant decreasing trend
No trend
Winter
Autumn Annual
Spring Summer
Figure 5 Location of sites with increasing decreasing and no trends at 5 significance level for the seasonal and annual precipitation timeseries
study stations from 1961 to 2011 theThalozom station showeda negative trend with a decreasing rate of 370mmyearFigure 6 displays the results of the magnitude of variationin the annual precipitation for the Saidu Sharif MardanCharsadda andThalozom stations
35 Trend Analysis over Entire River Basin The effect ofclimate change on precipitation was also analyzed for theentire Swat River basin by applying the MK and SR testson monthly seasonal and annual scale As Figure 1 showedthe entire Swat River catchment (A) is divided into foursubbasins upper subbasin (A1) Panjkora subbasin (A2)Ambahar subbasin (A3) and Lower subbasin (A4) Table 5presents trends in monthly precipitation across the subbasinsand for the full basin The table shows significant positivetrends in the months of June and November for the uppersubbasin (A1) and the entire Swat River basin (A) negativetrends were seen in these locations in July and August Inthe Panjkora subbasin (A2) statistically significant positivetrends were identified over time in June a negative trendwas seen from July to September The maximum number ofsignificant cases (8) was observed in data from the Ambaharsubbasin (A3)The Lower subbasin (A4) showed a significantpositive trend only during January no significant trendsin other months were identified As a simpler summarysignificant negative trends in precipitation over time were
seen from July to September positive trends over time wereseen in January May June and October to December indifferent Swat River subbasins
To detect precipitation trends in each subbasin and entireSwat River basin the MK and SR tests were again appliedto seasonal and annual precipitation data for the 51-yearstudy period (1961ndash2011) As Table 6 shows both testmethodsshowed similar results The upper subbasin (A1) experiencedstatistically significant negative trends in the summer andpositive trends in the autumn The Panjkora subbasin (A2)and Lower subbasin (A4) showed significant negative trendsin the summer and positive trends in the winter Significantpositive trends were found across the subbasins in winterand autumn seasons however there was a negative trendin summer at Ambahar subbasin (A3) and across the entireSwat River basin (A) For the annual and spring precipitationtime series there were no statistically significant trendsSignificant positive trendswere seen inwinter and autumn insummer negative trends were seen across different subbasinsand the full Swat River basin
The Lower subbasin exhibited the maximum positivetrend over time (218mmyear) in the weighted annualprecipitation time series the Panjkora subbasin showed anegative trend with a decreasing rate of participation at090mmyear The entire Swat River basin showed a positivetrend in precipitation (048mmyear) as shown in Table 6
Advances in Meteorology 11
Table5MKandSR
tests
results
form
onthlyprecipitatio
ntim
eseriesinentireb
asin
andsubb
asinso
fSwatRiver
Subb
asin
Test
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
A1
MK
047
010
071
minus12
3041
349lowast
minus288lowast
minus318lowast
minus018
143
250lowast
094
SR045
006
074
minus098
047
409lowast
minus299lowast
minus363lowast
minus018
159
277lowast
094
A2
MK
107
080
016
minus093
021
201lowast
minus354lowast
minus416lowast
minus202lowast
000
187
062
SR095
072
001
minus099
013
231lowast
minus386lowast
minus486lowast
minus224lowast
011
200
063
A3
MK
250lowast
102
minus036
065
297lowast
390lowast
minus297lowast
minus255lowast
minus044
305lowast
295lowast
229lowast
SR267lowast
089
minus009
070
311lowast
479lowast
minus354lowast
minus322lowast
minus052
376lowast
365lowast
260lowast
A4
MK
237lowast
088
minus006
minus050
122
164
minus063
minus083
000
020
050
minus040
SR246lowast
084
minus001
minus059
117
182
minus059
minus090
001
045
023
minus046
AMK
185
110
013
minus062
123
369lowast
minus255lowast
minus361lowast
minus065
174
268lowast
070
SR17
010
4018
minus079
127
422lowast
minus277lowast
minus401lowast
minus070
181
299lowast
073
lowast
Sign
ificant
trend
at5
significance
leveloftwo-tailedtest
12 Advances in Meteorology
0
500
1000
1500
2000
2500
3000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Saidu Sharif station
(a)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Mardan station
(b)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Charsadda station
(c)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Thalozom station
(d)
Figure 6 Variations of annual precipitation time series in stations with significant trends during 1961ndash2011
36 Comparison of Results Results from both statistical testsMK and SR were consistent with each otherThe percentagesof statistically significant cases to total tested cases for theMK and SR tests were 32 and 30 respectively showingagreement across methods This consistency in statisticalperformance was also found in other studies [24 28]
4 Discussion
This study investigated variability in monthly seasonal andannual precipitation at 15 stations in the Swat River basinover a 51-year study period (1961ndash2011) Precipitation trendswere also analyzed for each subbasin and entire Swat Riverbasin The mean annual precipitation at different stationsshowed considerable variation with a standard deviationof 1768mm from the mean annual rainfall of 694mmThe Saidu Sharif Mardan and Charsadda stations showedsignificant positive trends (increased precipitation over time)at 5 significance level in the annual precipitation series
The maximum number of significant changes in monthlyprecipitation over time was detected at Saidu Sharif Abazaiand Khairabad stations Saidu Sharif station showed themaximum increasing slope (indicating sharpest change overtime) of 748mmyear among the selected stations in the SwatRiver basin
These study results follow the same statistical trendsreported by Hartmann and Andresky [35] for northwestparts of Pakistan Findings were consistent with results fromDimri [56] Ghaffar and Javid [57] and Rasul [58] whereinthey found statistically significant increasing trends in winterprecipitation for northwest areas of Pakistan The resultsof this analysis also support finding of Hanif et al [37]wherein they found significant variations in summer seasonprecipitation These variations in precipitation trends maylead Pakistan towards more water related disasters suchas droughts and floods in the near future Basistha et al[59] proposed possible causes of the changing precipitationtrends such as global climate shifts [60] dwindling global
Advances in Meteorology 13
Table 6 MK and SR results for seasonal and annual precipitation time series in entire basin and subbasin of Swat River
Subbasin Change (mmyear) Test Winter Spring Summer Autumn Annual
A1 minus073 MK 055 minus024 minus242lowast 305lowast minus034SR 057 001 minus227lowast 347lowast 118
A2 minus090 MK 128 minus023 minus385lowast 158 minus081SR 118 minus035 minus444lowast 164 minus090
A3 030 MK 266lowast 016 minus265lowast 375lowast 024SR 295lowast 027 minus309lowast 460lowast 040
A4 218 MK 242lowast 060 minus021 024 166SR 272lowast 054 minus037 043 173
A 048 MK 214lowast minus011 minus297lowast 307lowast 042SR 225lowast minus014 minus340lowast 336lowast 038
lowastSignificant trend at 5 significance level of two-tailed test
monsoon circulation [61] decline in forest cover [62 63] landuse changes and practices (eg irrigated agriculture) [64 65]and increasing aerosols from anthropogenic activities [66]
5 Conclusions
This paper analyzed trends in monthly seasonal and annualprecipitation in the Swat River basin over the 51-year studyperiod (1961ndash2011) A mix of positive and negative trendswas observed at various stations and subbasins The monthsof June November July and August showed the maximumnumber of significant cases at various stations in monthlyprecipitation The trends were positive in May and June andwere negative in July and August This indicates a shift inprecipitation series on monthly scale Significant positivetrends were detected in winter and autumn and annuallynegative trends were seen in spring and summer seasonsSaidu Sharif Mardan and Charsadda stations exhibitedsignificant positive trends in annual precipitation at a 95confidence level the remaining stations did not experiencea statistically significant trend
For the entire Swat River basin no significant trendswere detected in any subbasin for the annual precipitationseries Seasonally winter and autumn experienced significantpositive trends and summer experienced negative trends indifferent subbasins in the Swat River basin Most statisticallysignificant trend cases under different scenarios were positive(61)The results obtainedwith theMann-Kendall (MK) andSpearmanrsquos rho tests showed agreement in their assessmentsof monthly seasonal and annual precipitation trends Thevariability of negative and positive trends at various stationspoints to the need for more detailed studies on the climatechange of this region
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgments
The authors thank Pakistan Meteorological Department(PMD) Water and Power Development Authority
(WAPDA) Pakistan and Snowy Mountains EngineeringCorporation (SMEC) for providing cost-free data for thisstudy
References
[1] M D Rahman and M Begum ldquoApplication of non parametrictest for trend detection of rainfall in the largest Island ofBangladeshrdquo ARPN Journal of Earth Sciences vol 2 no 2 pp40ndash44 2013
[2] IPCCThePhysical Science Basis Contribution ofWorkingGroupI to the Fourth Assessment Report of the Intergovernmental Panelon Climate Change Cambridge University Press CambridgeUK 2007
[3] A B Farooq and A H Khan ldquoClimate change perspectivein Pakistanrdquo in Proceedings of the Capacity Building APNWorkshop on Global Change Research pp 39ndash46 IslamabadPakistan 2004
[4] Z Z Hu S Yang and R Wu ldquoLong-term climate variationsin China and global warming signalsrdquo Journal of GeophysicalResearch vol 108 no D19 2003
[5] P Zhai and X Pan ldquoTrends in temperature extremes during1951ndash1999 in Chinardquo Geophysical Research Letters vol 30 no17 p 1913 2003
[6] D Duhan and A Pandey ldquoStatistical analysis of long termspatial and temporal trends of precipitation during 1901ndash2002at Madhya Pradesh Indiardquo Atmospheric Research vol 122 pp136ndash149 2013
[7] B J Peterson RM Holmes JWMcClelland et al ldquoIncreasingriver discharge to the Arctic oceanrdquo Science vol 298 no 5601pp 2171ndash2173 2002
[8] N I Savelieva I P Semiletov L N Vasilevskaya and S PPugach ldquoA climate shift in seasonal values of meteorologicaland hydrological parameters for Northeastern Asiardquo Progress inOceanography vol 47 no 2ndash4 pp 279ndash297 2000
[9] Y F Shi Y P Shen and R J Hu ldquoPreliminary study on signalimpact and foreground of climatic shift from warm-dry towarm-humid in Northwest Chinardquo Journal of Glaciology andGeocryology vol 24 pp 219ndash226 2002 (Chinese)
[10] S Farhana and M M Rahman ldquoCharacterizing rainfall trendin Bangladesh by temporal statistics analysisrdquo in Proceedings ofthe 4th Annual Paper Meet and 1st Civil Engineering CongressDhaka Bangladesh 2011
[11] R H Rimi S H Rahman S Karmakar and S G HussainldquoTrend analysis of climate change and investigation on its
14 Advances in Meteorology
probable impacts on rice production at Satkhira BangladeshrdquoPakistan Journal of Meteorology vol 6 no 11 pp 37ndash50 2014
[12] E R Dahmen and M J Hall Screening of Hydrological DataTests for Stationarity and Relative Consistency Publication 49ILRI Wageningen The Netherlands 1990
[13] Q Zhang C Liu C-Y Xu Y Xu and T Jiang ldquoObserved trendsof annual maximumwater level and streamflow during past 130years in the Yangtze River basin Chinardquo Journal of Hydrologyvol 324 no 1-4 pp 255ndash265 2006
[14] H Chen S Guo C-Y Xu and V P Singh ldquoHistorical tem-poral trends of hydro-climatic variables and runoff responseto climate variability and their relevance in water resourcemanagement in the Hanjiang basinrdquo Journal of Hydrology vol344 no 3-4 pp 171ndash184 2007
[15] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 pp 245ndash259 1945
[16] M G Kendall Rank CorrelationMethods Griffin London UK1975
[17] E L Lehmann Nonparametrics Statistical Methods Based onRanks Holden-Day San Francisco Calif USA 1975
[18] R Sneyers ldquoOn the statistical analysis of series of observationsrdquoTechnical Note 143 WMO no 415 World MeteorologicalOrganization 1990
[19] A Longobardi and P Villani ldquoTrend analysis of annual andseasonal rainfall time series in the Mediterranean areardquo Inter-national Journal of Climatology vol 30 no 10 pp 1538ndash15462010
[20] Z YanmingW Jun andW Xinhua ldquoStudy on the change trendof precipitation and temperature in Kunming city based onMann-Kendall analysisrdquo in Future Computer CommunicationControl and Automation vol 119 of Advances in Intelligent andSoft Computing pp 505ndash513 Springer Berlin Germany 2011
[21] X L Yang L R Xu K K Liu C H Li J Hu and X H XialdquoTrend in temperature and precipitation in the ZhangweinanRiver Basin during the last 53 yearsrdquo Procedia EnvironmentalSciences vol 13 pp 1966ndash1974 1966
[22] Z F Yang Y Yan and Q Liu ldquoThe relationship of streamflow-precipitation-temperature in the Yellow River Basin of Chinaduring 1961ndash2000rdquo Procedia Environmental Sciences vol 13 pp2336ndash2345 2012
[23] Q-X Wang X-H Fan Z-D Qin and M-B Wang ldquoChangetrends of temperature and precipitation in the Loess PlateauRegion of China 1961ndash2010rdquo Global and Planetary Change vol92-93 pp 138ndash147 2012
[24] S Yue P Pilon and G Cavadias ldquoPower of the Mann-Kendalland Spearmanrsquos rho tests for detecting monotonic trends inhydrological seriesrdquo Journal of Hydrology vol 259 no 1ndash4 pp254ndash271 2002
[25] E Kahya and S Kalaycı ldquoTrend analysis of streamflow inTurkeyrdquo Journal of Hydrology vol 289 pp 128ndash144 2004
[26] Z L Li Z X Xu J Y Li and Z J Li ldquoShift trend and stepchanges for runoff time series in the Shiyang River BasinNorthwest Chinardquo Hydrological Processes vol 22 no 23 pp4639ndash4646 2008
[27] C Yaning X Changchun H Xingming et al ldquoFifty-yearclimate change and its effect on annual runoff in the TarimRiverBasin Chinardquo Quaternary International vol 208 no 1-2 pp53ndash61 2009
[28] M Shadmani SMarofi andMRoknian ldquoTrend analysis in ref-erence evapotranspiration usingMann-Kendall and SpearmanrsquosRho tests in arid regions of IranrdquoWater Resources Managementvol 26 no 1 pp 211ndash224 2012
[29] H Rehman and A Kamal ldquoIndus Basin River system-floodingand flood mitigationrdquo 2005 httparchiveriversymposiumcom2005indexphpelement=38
[30] Pakistan Meteorological Department (PMD) National PlanStrengthening National Capacities for Multi-hazard EarlyWarn-ing amp Response System 2006
[31] National Disaster Management Authority (NDMA) 2007National Disaster Risk Management Framework Governmentof Pakistan httpwwwndmagovpknew
[32] N H Hashimi Q T M Siddiqui A R Ghumman M AKamal and H R Mughal ldquoA critical analysis of 2010 floods inPakistanrdquo African Journal of Agricultural Research vol 7 no 7pp 1054ndash1067 2012
[33] FFC ldquoFederal Flood Commission of Pakistanrdquo Annual FloodReport-2010 2011 httpwwwffcgovpkdownloadfloodarc-hieveAnnualreport2010pdf
[34] N Gronewold and Climatewire ldquoIs the Flooding in Pakistan aClimate Change Disasterrdquo WMN 2010 httpwwwscientific-americancomarticleis-the-flooding-in-pakist
[35] H Hartmann and L Andresky ldquoFlooding in the Indus Riverbasinmdasha spatiotemporal analysis of precipitation recordsrdquoGlobal and Planetary Change vol 107 pp 25ndash35 2013
[36] S Salma S Rehman andM A Shah ldquoRainfall trends in differ-ent climate zones of Pakistanrdquo Pakistan Journal of Meteorologyvol 9 no 17 pp 37ndash47 2012
[37] M Hanif A H Khan and S Adnan ldquoLatitudinal precipitationcharacteristics and trends in Pakistanrdquo Journal ofHydrology vol492 pp 266ndash272 2013
[38] A Imran Q Zaman and M Afzal ldquoTemporal trends in thepeak monsoonal precipitation events over Northeast PakistanrdquoPakistan Journal of Meteorology vol 10 no 19 pp 19ndash30 2013
[39] S B Cheema and M Hanif ldquoSeasonal precipitation variationover Punjab provincerdquo Pakistan Journal of Meteorology vol 10no 19 pp 61ndash82 2013
[40] H Hartmann and H Buchanan ldquoTrends in extreme precipita-tion events in the indus River Basin and flooding in PakistanrdquoAtmosphere-Ocean vol 52 no 1 pp 77ndash91 2014
[41] ldquoProvincial Disaster Management Authority (PDMA 2012)Monsoon Contingency Plan-Khyber-Pakhtunkhwardquo 2012httpwwwndmagovpkDocumentsContingency Plan2012CP KPpdf
[42] Snowy Mountains Engineering Corporation Munda DamConstruction Project Detailed Design Report SMEC LahorePakistan 2014
[43] H Alexandersson ldquoA homogeneity test applied to precipitationdatardquo Journal of Climatology vol 6 no 6 pp 661ndash675 1986
[44] HAlexandersson andAMoberg ldquoHomogenization of Swedishtemperature data Part I homogeneity test for linear trendsrdquoInternational Journal of Climatology vol 17 no 1 pp 25ndash341997
[45] T A Buishand ldquoSome methods for testing the homogeneity ofrainfall recordsrdquo Journal of Hydrology vol 58 no 1-2 pp 11ndash271982
[46] M N Khaliq and T B M J Ouarda ldquoOn the critical values ofthe standard normal homogeneity test (SNHT)rdquo InternationalJournal of Climatology vol 27 no 5 pp 681ndash687 2007
[47] K H Hamed and A Ramachandra Rao ldquoA modified Mann-Kendall trend test for autocorrelated datardquo Journal of Hydrologyvol 204 no 1ndash4 pp 182ndash196 1998
[48] B Onoz and M Bayazit ldquoBlock bootstrap for Mann-Kendalltrend test of serially dependent datardquoHydrological Processes vol26 no 23 pp 3552ndash3560 2012
Advances in Meteorology 15
[49] M Yaseen H A Bhatti T Rientjes G Nabi and M LatifldquoTemporal and spatial variations in summer flows of upperIndus Basin Pakistanrdquo inProceedings of the 72ndAnnual Sessionof Pakistan Engineering Congress Paper no 747 pp 315ndash3342013
[50] G C Blain ldquoThe Mann-Kendall test the need to consider theinteraction between serial correlation and trendrdquo AgriculturalEngineering vol 35 no 4 2013
[51] M Yaseen T Rientjes G Nabi H ur-Rehman and M LatifldquoAssessment of recent temperature trends inManglawatershedrdquoJournal of Himalayan Earth Sciences vol 47 no 1 pp 107ndash1212014
[52] P K Sen ldquoEstimates of the regression coefficient based onKendallrsquos taurdquo Journal of the American Statistical Associationvol 63 no 324 pp 1379ndash1389 1968
[53] W S Cleveland ldquoRobust locally weighted regression andsmoothing scatterplotsrdquoThe Journal of the American StatisticalAssociation vol 74 no 368 pp 829ndash836 1979
[54] W S Cleveland ldquoGraphs in scientific publicationsrdquoThe Ameri-can Statistician vol 38 no 4 pp 261ndash269 1984
[55] D R Helsel and R M Hirsch ldquoStatistical methods in waterresourcesrdquo inTechniques ofWater Resources Investigations Book4 chapter A3 p 522 US Geological Survey 2002
[56] A P Dimri ldquoSurface and upper air fields during extreme winterprecipitation over the western Himalayasrdquo Pure and AppliedGeophysics vol 163 no 8 pp 1679ndash1698 2006
[57] A Ghaffar and M Javid ldquoImpact of global warming onmonsoon variability in Pakistanrdquo The Journal of Animal andPlant Sciences vol 21 no 1 pp 107ndash110 2011
[58] G Rasul ldquoClimate Data and Modelling Analysis of the IndusRegionrdquo Pakistan Meteorological Department (PMD) 2012httpwwfpakorgccappdfClimate Data Modelling20An-alysis20of20the20Indus20Ecoregionpdf
[59] A Basistha D S Arya and N K Goel ldquoAnalysis of historicalchanges in rainfall in the Indian Himalayasrdquo InternationalJournal of Climatology vol 29 no 4 pp 555ndash572 2009
[60] P G Baines ldquoThe late 1960s global climate shift and its influenceon the Southern Hemisphererdquo in Proceedings of 8 ICSHMO pp1477ndash1482 INPE Foz do Iguacu Brazil 2006
[61] K Duan and T Yao ldquoMonsoon variability in the Himalayasunder the condition of global warmingrdquo Journal of the Mete-orological Society of Japan vol 81 no 2 pp 251ndash257 2003
[62] U S Nair R O Lawton R M Welch and R A Pielke SrldquoImpact of land use on Costa Rican tropical montane cloudforests sensitivity of cumulus cloud field characteristics tolowland deforestationrdquo Journal of Geophysical Research D vol108 no 7 pp 4206ndash4219 2003
[63] R Avissar and D Werth ldquoGlobal hydroclimatological tele-connections resulting from tropical deforestationrdquo Journal ofHydrometeorology vol 6 no 2 pp 134ndash145 2005
[64] R A Pielke Sr J Adegoke A Beltran-Przekurat et al ldquoAnoverview of regional land-use and land-cover impacts onrainfallrdquo Tellus B Chemical and Physical Meteorology vol 59no 3 pp 587ndash601 2007
[65] N Ramankutty C Delire and P Snyder ldquoFeedbacks betweenagriculture and climate an illustration of the potential unin-tended consequences of human land use activitiesrdquo Global andPlanetary Change vol 54 no 1-2 pp 79ndash93 2006
[66] V Ramanathan C Chung D Kim et al ldquoAtmospheric brownclouds impacts on South Asian climate and hydrological cyclerdquoProceedings of the National Academy of Sciences of the UnitedStates of America vol 102 no 15 pp 5326ndash5333 2005
Submit your manuscripts athttpwwwhindawicom
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Geological ResearchJournal of
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Geology Advances in
2 Advances in Meteorology
Natural disasters including avalanches cyclones andstorms droughts and floods and cloudburst flash floods(CBFF) pose serious risks to Pakistani society [29ndash31]Pakistan has faced one major flood approximately every 3years creating challenges for economic development [32]In 2010 Pakistan faced the worst flood event in its history[33] Experts from the World Climate Research ProgrammeandWorld Meteorological Organization (WMO) have statedthat climate change is one of the main reasons for thisunprecedented sequence of weather events A UN scientificbody concluded that hot extremes heat waves and heavyprecipitation events will likely continue to become morefrequent in Pakistan the same body warns that floodsmay become more frequent and intense in the future [2]WMO has noted that the 2010 floods were consistent withthe sequence predicted by climate experts further statingthat current events match projections of more frequent andintense weather events due to global warming [34]
Floods in Pakistan are generally caused by concentratedheavy precipitation in watersheds sometimes augmented bysnowmelt flows causing river floods during the monsoonseason Hartmann and Andresky [35] reported that the pre-cipitation regimes in northwest areas of Pakistan are mainlycontrolled by monsoon rains from July to September theyhave become more intense in recent years Salma et al [36]analyzed Pakistan rainfall trends using analysis of variance(ANOVA) from 1976 to 2005 and concluded that while theoverall rainfall trends have declined rainfall consequencessuch as droughts and super floods have badly affected humansettlements water management and agriculture sectorsHanif et al [37] found significant precipitation changes innorthern parts of Pakistan during the summer and monsoon(July and August) seasons Significant increasing trends inprecipitation over time have been detected in northeastareas of Pakistan during the monsoon season [38] Cheemaand Hanif [39] detected increasing rainfall trends in thePunjab province of Pakistan Significant increasing trendswere detected in the northwest (Hindu Kush and SulaimanMountains) and in the east (Himalayas) areas of the IndusRiver basin insignificant negative trends were found in thenortheast (Karakorum and Transhimalaya) and lowland ofthe upper Indus River basin [35 40]
During the last week of July 2010 unprecedented rains fellin Swat andKabul river catchment areas causing catastrophicfloods in excess of 400000 cusecs exceeding the previousrecord flood set in 1929 (250000 cusecs) and impacting24 districts of the KPK province of Pakistan [32] Due tochanging weather patterns Pakistanrsquos KPK province and theSwat River area have been exposed to risks from frequentfloods and droughts in recent years [31 41] Most past studieshowever have focused on climatic trend analyses in theupper Indus River basin No precipitation trend studies havefocused on the Swat River basin which has faced frequentfloods and droughts over the years This study fills thisresearch gap
This study investigated trends and variations in precip-itation over time at the Swat River basin in Pakistan usingMann-Kendall and Spearmanrsquos rho tests This study pro-vides a broad overview of precipitation statistics including
seasonal and interannual variability over the SwatRiver basinand may help managers and agricultural planners The studyconsiders precipitation data from 51 years (1961ndash2011) at 15stations
2 Methodology
21 Study Area This study investigates the variability inprecipitation time series for a 51-year period (1961ndash2011) inthe Swat River basin in the Khyber Pakhtunkhwa (KPK)province of PakistanThe Swat River originates from the highmountains of Swat Kohistan where the mean elevation is4500m in the northwest parts of the country The river flowsthrough the Kalam valley and the Swat district then skirtsthe Lower Dir district flows through Malakand and Mardandistricts and outflows into the Kabul River
The Swat River is important for the future economicdevelopment of Pakistan There are three hydropower plantswith a combined operational capacity of 123MWon the SwatRiver At the time of this writing another hydroelectric powergeneration plant (Munda Dam) with a projected capacityof 740MW is being constructed on the Swat River Thisdam along with the hydropower generation will irrigate15100 acres of land They will also provide flood protectionto theCharsadda andNowshera districts whichwere severelyaffected by flooding in 2010
The riverrsquos catchment area is generally mountainous withelevations ranging from approximately 360m to 4500mfrom south to north Vegetation occurs between 1800mand 3400m and glaciers are visible above 4000m TheSwat River basin catchment lies between a latitude of 34∘001015840north to 35∘561015840 north and longitude 70∘591015840 east to 72∘471015840east
22 Data andMethods The total Swat River basin catchmentarea is 16750 km2 with 15 meteorological stations shown inFigure 1 The area is further divided into four subregionsupper Swat River basin (A1) Panjkora River basin (A2)Ambahar River basin (A3) and Lower Swat River basin(A4) The catchment areas for these basins are 5968 57331485 and 3564 km2 respectively To detectmonotonic trendsmonthly precipitation values were added to generate theannual and seasonal precipitation Mean precipitation valuesat corresponding stations were considered to determinesubbasin precipitation (A1 A2 A3 and A4) and precipitationacross the entire Swat River basin (A) This procedure wasadopted from Duhan and Pandey [6]
Rain gauge stations within the Swat River catchment areaare operated by PakistanMeteorological Department (PMD)Irrigation Department of KPK province (ID) and SurfaceWater Hydrology Project (SWHP) Snowy Mountains Engi-neering Corporation (SMEC) Pakistan under the MundaDam construction project collected the precipitation timeseries data from these agencies and processed it to ensurehomogeneity and quality control [42]
Mann-Kendall and Spearmanrsquos rho tests are nonpara-metric therefore data outliers do not affect the results Thehomogeneity of the precipitation time series was assessed
Advances in Meteorology 3
34∘-00998400
34∘-15998400
34∘-30998400
34∘-45998400
35∘-00998400
35∘-15998400
35∘-30998400
35∘-45998400
36∘-00998400
34∘-00998400
34∘-15998400
34∘-30998400
34∘-45998400
35∘-00998400
35∘-15998400
35∘-30998400
35∘-45998400
36∘-00998400
70∘-4
5998400
71∘-0
0998400
71∘-1
5998400
71∘-3
0998400
71∘-4
5998400
72∘-0
0998400
72∘-1
5998400
72∘-3
0998400
72∘-4
5998400
73∘-0
0998400
70∘-4
5998400
71∘-0
0998400
71∘-1
5998400
71∘-3
0998400
71∘-4
5998400
72∘-0
0998400
72∘-1
5998400
72∘-3
0998400
72∘-4
5998400
73∘-0
0998400
Afghan
istan
A3
A3
A2
A2
A1
A1
A4
A4
N
Ambahar
Abazai
ToorCamp
Dir
Drosh Kalam
Thalozom
Madyan
Khairabad
Saidu Sharif
Malakand
Mardan
RisalpurCharsadda
Kulangi
Upper Swat subbasin
Panjkora subbasin
Ambahar subbasin
Lower Swat subbasin
Figure 1 Locations of meteorological stations at Swat River basin
by applying two tests standard normal homogeneity test(SNHT) [43 44] and Buishandrsquos range (BR) test [45] ata 5 significance level for each station The precipitationtime series is considered homogenous if the critical values ofSNHT and BR statistics are less than 917 [46] and 127 155[45] respectively As Table 1 shows all the precipitation serieswere found to be homogenous
23 Statistical Tests Prior to applying MK and SR teststo identify precipitation trends over the time series fromselected stations data were tested according to the testsrsquo re-quirements The trend-free prewhitening (TFPW) approachwas applied to eliminate serial correlations in the time seriesdata The magnitude of the slope in time series data wascalculated using Senrsquos slope method The statistical methodsused are briefly discussed below
231 Autocorrelation and TFPW Removing serial depen-dence is one of the main problems in testing and interpretingtime series data Applying nonparametric tests to detecttrends can significantly affect the results Therefore all ofthe rainfall time series data was first tested for the presenceof autocorrelation coefficient (119903
1) at a 5 significance level
using a two-tailed test
1199031=
sum119899minus1
119894=1
(119883119894minus 119883) (119883
119894+1minus 119883)
sum119899
119894=1
(119883119894minus 119883)
2
(1)
The autocorrelation coefficient value of 1199031was tested against
the null hypothesis at a 95 confidence interval using a two-tailed test
1199031(95) =
minus1 plusmn 196radic(119899 minus 2)
119899 minus 1
(2)
4 Advances in Meteorology
Table 1 Results of homogeneity tests for mean annual precipitationtime series at study stations
Station SNHT Buishandrsquos range (BR) test1198790
119876radic119899 119877radic119899
Thalozom 916 108 108Drosh 906 117 147Kalam 887 087 108Dir 776 124 149Madyan 485 111 150Khairabad 192 062 093ToorCamp 620 117 154Saidu Sharif 742 118 190Malakand 257 077 086Kulangi 428 097 146Ambahar 508 109 139Abazai 686 121 140Mardan 893 108 124Charsadda 902 125 138Risalpur 724 091 125For homogenous series 119879
0lt 917119876radic119899 lt 127 and 119877radic119899 lt 155
If 1199031falls between the upper and lower limits of confidence
interval (the data are considered serially correlated) themethods of prewhitening variance correlation [47] andtrend-free prewhitening (TFPW) approach [24] have beenproposed In this study for the stations where serial cor-relations were detected in the data the TFPW approachwas applied to remove the correlation for both tests (Mann-Kendall and Spearmanrsquos rho) Other researchers [28 48ndash51]have also used this approach to eliminate serial correlation intime series data
232 The Mann-Kendall Test The rank-based nonparamet-ric Mann-Kendall [15 16] method was applied to the long-term data in this study to detect statistically significanttrends In this test the null hypothesis (H
0) was that there
has been no trend in precipitation over time the alternatehypothesis (H
1) was that there has been a trend (increasing
or decreasing) over time The mathematical equations forcalculatingMann-Kendall Statistics 119878119881(119878) and standardizedtest statistics 119885 are as follows
119878 =
119899minus1
sum
119894=1
119899
sum
119895=119894+1
sig (119883119895minus 119883119894)
sgn (119883119895minus 119883119894) =
+1 if (119883119895minus 119883119894) gt 0
0 if (119883119895minus 119883119894) = 0
minus1 if (119883119895minus 119883119894) lt 0
119881 (119878) =
1
18
[119899 (119899 minus 1) (2119899 + 5) minus
119902
sum
119901=1
119905119901(119905119901minus 1) (2119905
119901+ 5)]
119885 =
119878 minus 1
radicVAR (119878)if 119878 gt 0
0 if 119878 = 0
119878 + 1
radicVAR (119878)if 119878 lt 0
(3)
In these equations119883119894and119883
119895are the time series observations
in chronological order 119899 is the length of time series 119905119901is
the number of ties for 119901th value and 119902 is the number oftied values Positive 119885 values indicate an upward trend in thehydrologic time series negative 119885 values indicate a negativetrend If |119885| gt 119885
1minus1205722 (H0) is rejected and a statistically
significant trend exists in the hydrologic time series Thecritical value of119885
1minus1205722for a 119901 value of 005 from the standard
normal table is 196
233 Spearmanrsquos rho Test Spearmanrsquos rho [17 18] test isanother rank-based nonparametric method used for trendanalysis and was applied as a comparison with the Mann-Kendall test In this test which assumes that time seriesdata are independent and identically distributed the nullhypothesis (H
0) again indicates no trend over time the
alternate hypothesis (H1) is that a trend exists and that data
increase or decrease with 119894 [24] The test statistics 119877sp andstandardized statistics 119885sp are defined as
119877sp = 1 minus
6sum119899
119894=1
(119863119894minus 119894)2
119899 (1198992
minus 1)
119885sp = 119877spradic119899 minus 2
1 minus 1198772
sp
(4)
In these equations 119863119894is the rank of 119894th observation 119868 is the
chronological order number 119899 is the total length of the timeseries data and 119885sp is Studentrsquos 119905-distribution with (119899 minus 2)degree of freedom The positive values of 119885sp represent anincreasing trend across the hydrologic time series negativevalues represent the decreasing trends The critical value of119905 at a 005 significance level of Studentrsquos 119905-distribution tableis defined as 119905
(119899minus21minus1205722)[12] If |119885sp| gt 119905
(119899minus21minus1205722) (H0) is
rejected and a significant trend exists in the hydrologic timeseries
234 Senrsquos Slope Estimator Senrsquos nonparametric method [52]was used to estimate the magnitude of trends in the timeseries data
119879119894=
119909119895minus 119909119896
119895 minus 119896
(5)
In this equation 119909119895and 119909
119896represent data values at time 119895 and
119896 respectively Consider
119876119894=
119879(119873+1)2
119873 is odd1
2
(1198791198732
+ 119879(119873+2)2
) 119873 is even(6)
A positive119876119894value represents an increasing trend a negative
119876119894value represents a decreasing trend over time
Advances in Meteorology 5
Table 2 Summary of geographic conditions and mean annual precipitation statistics for study stations
Station Longitude Latitude Elevation (m) Mean (mm) STD 119862119904
119862119896
119862V
Thalozom 72∘-151015840 35∘-441015840 4200 7511 2099 minus0266 0082 0291Drosh 72∘-001015840 35∘-331015840 1465 4635 1537 1167 2441 0332Kalam 72∘-331015840 35∘-311015840 2000 9345 3170 minus0599 0323 0353Dir 71∘-531015840 35∘-121015840 1321 5482 1521 minus0545 0919 0285Madyan 72∘-321015840 35∘-091015840 1320 9623 2878 0240 1300 0307Khairabad 72∘-061015840 34∘-581015840 894 7037 1522 1410 4281 0216ToorCamp 71∘-421015840 34∘-501015840 854 5440 1592 minus0436 0841 0299Saidu Sharif 72∘-251015840 34∘-451015840 961 9901 3898 1842 6463 0398Malakand 71∘-461015840 34∘-381015840 603 6098 2526 2474 11668 0424Kulangi 71∘-591015840 34∘-351015840 688 6254 1925 0037 minus0170 0308Ambahar 71∘-121015840 34∘-331015840 694 4550 1485 minus0004 0764 0333Abazai 71∘-331015840 34∘-261015840 320 5007 1527 minus0093 0963 0312Mardan 71∘-581015840 34∘-181015840 283 6574 2974 0735 1392 0452Charsadda 71∘-431015840 34∘-071015840 276 5916 2074 0973 1031 0350Risalpur 71∘-541015840 34∘-061015840 309 6118 1768 0312 minus0098 0289
3 Results and Discussion
31 Preliminary Analysis The preliminary analysis for thisstudy included computing the mean standard deviationcoefficient of skewness coefficient of kurtosis and coefficientof variation in the annual precipitation time series foreach station Table 2 presents these statistical parametersfor the 51-year time period studied (1961ndash2011) The meanannual precipitation varied between 455mm in the southwestpart of the Swat River basin catchment area (Ambahar)and 9901mm in the southeast part (Saidu Sharif) As thetable shows the coefficient of skewness varied from minus0266to 2474 kurtosis varied between minus0170 and 11668 Fortime series data to be considered normally distributed thecoefficient of skewness and kurtosis must be equal to 0and 3 respectively Table 2 indicates therefore that the dataare positively skewed and not normally distributed Thecoefficient of variation the measure of dispersion around themean was also calculated to analyze the spatial variability ofannual precipitation for each station This coefficient variedbetween 216 (Khairabad) and 452 (Mardan)The averagevariation of the precipitation over the complete river basinwas 289
32 Long-Term Pattern on Seasonal and Annual Scale Long-term climatic patterns were assessed using standardizedseasonal and annual precipitation time series data Toreduce local fluctuations LOWESS [53ndash55] curves were fittedover time based on seasonal and annual precipitation timeseries data The LOWESS curve for winter precipitation(Figure 2(a)) showed a decreasing trend in the first decadeIn the second decade the trend was constant The minimumLOWESS curve value was observed in 1990 values thengradually rose through 2010 Overall the curve based onwinter season data suggested a decline in precipitation After1990 there was a gradual rise though small local fluctuationswere ignored The LOWESS curve for spring precipitation(Figure 2(b)) showed a gradual increase in the first three
decades After attaining its highest value in 1990 the valuedeclined over the last two decades
The LOWESS curve for summer precipitation showeda constant trend in the first decade and then started todecline up to 1978 (Figure 2(c)) For 1978ndash1992 the curvestarted to gradually increase through the remaining yearsThe LOWESS curve for autumn precipitation exhibited adecreasing trend through 1982 for the remaining time peri-ods there was an increase in precipitation For the annualprecipitation time series the LOWESS curve showed slightvariations in every decade but the overall trend was nearlyconstant throughout the time series Figure 2 shows theprecipitation patterns LOWESS curves are used to showpatterns and do not explain statistically significant trends inthe time series
33 Monthly Analysis The Mann-Kendall (MK) and Spear-manrsquos (SR) rho tests were applied on a monthly scale todetect trends in the precipitation series at different stationsTable 3 shows the results and illustrates that the results ofboth tests were similar to one another Monthly trend testsshowed a mix of positive and negative trends at differentstations At Thalozom statistically significant negative andpositive trends were found in April and June respectivelySignificant positive trends were detected at Dir and Droshstations in March and August no significant trends werefound for other months The Saidu Sharif station exhibitedsignificant positive trends from January to June and fromOctober to December but had negative trends in July andAugust Significant positive trends were found at most of thestations in the months of May and June significant negativetrends were seen in July and August In other stations a mixof significantly positive and negative trends occurred for afew months of the year Figure 3 shows the spatial variationin the precipitation time series for each month in the SwatRiver basin from 1961 to 2011
The magnitude of statistically significant trends on amonthly scale was determined using Senrsquos slope estimator
6 Advances in Meteorology
0
1
2
3
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
Original dataLOWESS line
minus3
minus2
minus1
(a)
Original dataLOWESS line
0
1
2
3
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
minus2
minus1
(b)
Original dataLOWESS line
0
1
2
3
4
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
minus2
minus1
(c)
Original dataLOWESS line
0
1
2
3
4
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
minus2
minus1
(d)
Original dataLOWESS line
0
1
2
3
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
minus3
minus2
minus1
(e)
Figure 2 Standardized precipitation and LOWESS trend curves at Swat River basin (a) winter (b) spring (c) summer (d) autumn and (e)annual
Advances in Meteorology 7
Table3MKandSR
tests
results
forp
recipitatio
nin
mon
thlytim
eseries
Station
Test
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Thalozom
MK
minus063
minus10
9minus042
minus219lowast
minus033
272lowast
minus080
minus094
minus029
010
146
030
SRminus044
minus10
1minus039
minus215lowast
minus040
293lowast
minus079
minus10
3minus013
028
141
013
Drosh
MK
minus008
minus024
016
minus067
063
151
minus19
4minus316lowast
minus063
040
103
001
SRminus014
minus001
008
minus079
067
173
minus18
7minus336lowast
minus050
039
101
017
Kalam
MK
minus037
minus067
033
minus221lowast
minus063
219lowast
minus115
minus10
4minus054
014
120
017
SRminus023
minus052
023
minus213lowast
minus064
229lowast
minus113
minus10
7minus043
014
091
minus066
Dir
MK
000
minus063
minus248lowast
minus021
minus079
112
minus015
003
174
minus13
1minus034
minus089
SRminus016
minus062
minus280lowast
minus018
minus10
010
7minus001
minus002
203lowast
minus16
3minus049
minus10
1
Madyan
MK
089
075
110
minus083
086
353lowast
minus312lowast
minus338lowast
minus023
190
272lowast
134
SR086
070
113
minus067
085
426lowast
minus324lowast
minus398lowast
minus016
200
301lowast
132
Khaira
bad
MK
091
minus068
minus021
minus080
201lowast
385lowast
minus312lowast
minus348lowast
minus019
268lowast
292lowast
112
SR082
minus072
minus028
minus079
204lowast
446lowast
minus334lowast
minus460lowast
minus017
308lowast
325lowast
097
ToorCa
mp
MK
192
093
045
minus070
minus044
minus086
minus291lowast
minus296lowast
minus227lowast
minus201lowast
094
028
SR17
8085
025
minus082
minus047
minus091
minus317lowast
minus361lowast
minus279lowast
minus233lowast
104
020
SaiduSh
arif
MK
274lowast
246lowast
222lowast
182
285lowast
327lowast
minus334lowast
minus309lowast
003
319lowast
357lowast
210lowast
SR302lowast
262lowast
261lowast
205lowast
324lowast
383lowast
minus360lowast
minus387lowast
020
364lowast
405lowast
217lowast
Malakand
MK
105
minus17
2minus115
010
228lowast
322lowast
minus318lowast
minus293lowast
016
350lowast
273lowast
149
SR099
minus202lowast
minus13
2022
254lowast
302lowast
minus380lowast
minus382lowast
023
397lowast
223lowast
091
Kulang
iMK
070
minus099
minus294lowast
minus14
4minus062
036
000
174
291lowast
minus16
4minus003
minus204lowast
SR059
minus10
4minus315lowast
minus14
1minus081
024
008
165
336lowast
minus18
5minus031
minus231lowast
Ambahar
MK
031
minus066
minus284lowast
minus10
5minus115
060
018
060
304lowast
minus13
6minus021
minus18
0SR
038
minus070
minus282lowast
minus111
minus118
058
019
034
356lowast
minus15
1minus029
minus201lowast
Abazai
MK
233lowast
minus025
minus091
137
292lowast
449lowast
minus262lowast
minus10
710
2331lowast
392lowast
261lowast
SR222lowast
minus029
minus090
162
289lowast
435lowast
minus307lowast
minus10
913
7385lowast
366lowast
272lowast
Mardan
MK
243lowast
134
041
001
105
070
014
minus016
100
minus058
minus13
1minus13
7SR
253lowast
134
050
011
110
072
025
minus020
088
minus051
minus115
minus115
Charsadd
aMK
232lowast
109
032
minus012
015
034
014
minus014
056
minus10
4minus217lowast
minus15
9SR
237lowast
109
026
minus024
032
044
022
minus033
043
minus097
minus204lowast
minus13
1
Risalpur
MK
191
128
006
minus027
minus033
minus037
minus006
minus063
minus026
minus14
6minus18
7minus217lowast
SR213lowast
113
006
minus036
minus017
minus025
minus005
minus072
minus026
minus15
0minus211lowast
minus216lowast
lowast
Sign
ificant
trend
at5
significance
leveloftwo-tailedtest
8 Advances in Meteorology
Jan Feb Mar Apr
May Jun Jul Aug
Sep Oct Nov Dec
N
0 5 10 25
Scale
(km)
Significant increasing trendSignificant decreasing trend
No trend
Figure 3 Location of sites with increasing decreasing and no trends at 5 significance level for the monthly precipitation time series
The results show that trends at Saidu Sharif Madyanand Kalam were more rapid (eg sharper increases anddecreases) compared to other stations The Saidu Sharifstation had the maximum negative decline in monthly pre-cipitation (183mmmonth) as well as the maximum positiveincrease (143mmmonth) during the months of July andMarch respectively Figure 4 shows the trends in maximummonthly precipitation variation at the Saidu Sharif station
34 Seasonal and Annual Analysis The MK and SR testswere also used to identify trends in seasonal and annualprecipitation between 1961 and 2011 Table 4 shows the resultsSimilar to the monthly analysis results from both statisticaltests MK and SR were consistent with one another A mixof negative and positive trends was seen at different stationsThalozom Kalam and Dir stations which had shown trends
with the monthly time scale did not exhibit statisticallysignificant trends for the seasonal and annual precipitationtime series At Madyan Khairabad and Malakand stationsthere were significant negative trends in the summer andpositive trends in the autumn Significant negative trendswere observed in the spring season only at ToorCampKulangi and Ambahar stations For the annual precipitationseries significant positive trends were detected only at SaiduSharif Mardan and Charsadda stations At other stationssignificant positive trends were seen for winter and autumnseasons and for the annual precipitation series howevernegative trends were detected in spring and summer seasonsFigure 5 presents the spatial distribution of seasonal andannual precipitation trends
The Saidu Sharif station showed the maximum positivetrend in annual precipitation series (748mmyear) across
Advances in Meteorology 9
0
100
200
300
400
500
600
700
800
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
mon
th)
Year
Saidu Sharif station(March)
(a)
0
100
200
300
400
500
600
700
800
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
mon
th)
Year
Saidu Sharif station(July)
(b)
Figure 4 Variations of monthly precipitation time series in stations with most significant trends during 1961ndash2011
Table 4 MK and SR tests results for precipitation in seasonal and annual time series
Station Test Winter Spring Summer Autumn Annual
Thalozom MK minus120 minus162 minus120 148 minus149SR minus114 minus152 minus110 135 minus145
Drosh MK 042 minus078 minus196 097 minus044SR 049 minus074 minus209lowast 127 minus048
Kalam MK minus062 minus139 minus171 160 minus110SR minus037 minus121 minus158 157 minus087
Dir MK minus028 minus148 minus047 minus076 minus138SR minus062 minus150 minus058 minus097 minus146
Madyan MK 120 003 minus258lowast 365lowast 042SR 137 033 minus244lowast 421lowast 078
Khairabad MK 026 minus065 minus302lowast 325lowast minus073SR 021 minus076 minus353lowast 364lowast minus072
ToorCamp MK minus063 minus203lowast 024 minus073 minus044SR minus096 minus217lowast 023 minus092 minus159
Saidu Sharif MK 346lowast 239lowast minus156 069 328lowast
SR 404lowast 280lowast minus156 148 278lowast
Malakand MK minus070 minus110 minus270lowast 337lowast minus119SR minus068 minus115 minus319lowast 373lowast minus140
Kulangi MK minus122 minus261lowast 031 minus099 minus144SR minus156 minus284lowast 037 minus127 minus172
Ambahar MK minus066 minus206lowast minus063 minus099 minus157SR minus076 minus224lowast minus058 minus110 minus141
Abazai MK 179 minus015 minus099 429lowast 096SR 217lowast 007 minus072 604lowast 122
Mardan MK 281lowast 145 095 minus102 259lowast
SR 310lowast 134 098 minus085 280lowast
Charsadda MK 266lowast 097 073 minus194 214lowast
SR 293lowast 088 060 minus176 217lowast
Risalpur MK 243lowast 044 minus006 minus154 198SR 254lowast 040 minus005 minus190 195
lowastSignificant trend at 5 significance level of two-tailed test
10 Advances in Meteorology
N
0 5 10 25
Scale
(km)
Significant increasing trendSignificant decreasing trend
No trend
Winter
Autumn Annual
Spring Summer
Figure 5 Location of sites with increasing decreasing and no trends at 5 significance level for the seasonal and annual precipitation timeseries
study stations from 1961 to 2011 theThalozom station showeda negative trend with a decreasing rate of 370mmyearFigure 6 displays the results of the magnitude of variationin the annual precipitation for the Saidu Sharif MardanCharsadda andThalozom stations
35 Trend Analysis over Entire River Basin The effect ofclimate change on precipitation was also analyzed for theentire Swat River basin by applying the MK and SR testson monthly seasonal and annual scale As Figure 1 showedthe entire Swat River catchment (A) is divided into foursubbasins upper subbasin (A1) Panjkora subbasin (A2)Ambahar subbasin (A3) and Lower subbasin (A4) Table 5presents trends in monthly precipitation across the subbasinsand for the full basin The table shows significant positivetrends in the months of June and November for the uppersubbasin (A1) and the entire Swat River basin (A) negativetrends were seen in these locations in July and August Inthe Panjkora subbasin (A2) statistically significant positivetrends were identified over time in June a negative trendwas seen from July to September The maximum number ofsignificant cases (8) was observed in data from the Ambaharsubbasin (A3)The Lower subbasin (A4) showed a significantpositive trend only during January no significant trendsin other months were identified As a simpler summarysignificant negative trends in precipitation over time were
seen from July to September positive trends over time wereseen in January May June and October to December indifferent Swat River subbasins
To detect precipitation trends in each subbasin and entireSwat River basin the MK and SR tests were again appliedto seasonal and annual precipitation data for the 51-yearstudy period (1961ndash2011) As Table 6 shows both testmethodsshowed similar results The upper subbasin (A1) experiencedstatistically significant negative trends in the summer andpositive trends in the autumn The Panjkora subbasin (A2)and Lower subbasin (A4) showed significant negative trendsin the summer and positive trends in the winter Significantpositive trends were found across the subbasins in winterand autumn seasons however there was a negative trendin summer at Ambahar subbasin (A3) and across the entireSwat River basin (A) For the annual and spring precipitationtime series there were no statistically significant trendsSignificant positive trendswere seen inwinter and autumn insummer negative trends were seen across different subbasinsand the full Swat River basin
The Lower subbasin exhibited the maximum positivetrend over time (218mmyear) in the weighted annualprecipitation time series the Panjkora subbasin showed anegative trend with a decreasing rate of participation at090mmyear The entire Swat River basin showed a positivetrend in precipitation (048mmyear) as shown in Table 6
Advances in Meteorology 11
Table5MKandSR
tests
results
form
onthlyprecipitatio
ntim
eseriesinentireb
asin
andsubb
asinso
fSwatRiver
Subb
asin
Test
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
A1
MK
047
010
071
minus12
3041
349lowast
minus288lowast
minus318lowast
minus018
143
250lowast
094
SR045
006
074
minus098
047
409lowast
minus299lowast
minus363lowast
minus018
159
277lowast
094
A2
MK
107
080
016
minus093
021
201lowast
minus354lowast
minus416lowast
minus202lowast
000
187
062
SR095
072
001
minus099
013
231lowast
minus386lowast
minus486lowast
minus224lowast
011
200
063
A3
MK
250lowast
102
minus036
065
297lowast
390lowast
minus297lowast
minus255lowast
minus044
305lowast
295lowast
229lowast
SR267lowast
089
minus009
070
311lowast
479lowast
minus354lowast
minus322lowast
minus052
376lowast
365lowast
260lowast
A4
MK
237lowast
088
minus006
minus050
122
164
minus063
minus083
000
020
050
minus040
SR246lowast
084
minus001
minus059
117
182
minus059
minus090
001
045
023
minus046
AMK
185
110
013
minus062
123
369lowast
minus255lowast
minus361lowast
minus065
174
268lowast
070
SR17
010
4018
minus079
127
422lowast
minus277lowast
minus401lowast
minus070
181
299lowast
073
lowast
Sign
ificant
trend
at5
significance
leveloftwo-tailedtest
12 Advances in Meteorology
0
500
1000
1500
2000
2500
3000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Saidu Sharif station
(a)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Mardan station
(b)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Charsadda station
(c)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Thalozom station
(d)
Figure 6 Variations of annual precipitation time series in stations with significant trends during 1961ndash2011
36 Comparison of Results Results from both statistical testsMK and SR were consistent with each otherThe percentagesof statistically significant cases to total tested cases for theMK and SR tests were 32 and 30 respectively showingagreement across methods This consistency in statisticalperformance was also found in other studies [24 28]
4 Discussion
This study investigated variability in monthly seasonal andannual precipitation at 15 stations in the Swat River basinover a 51-year study period (1961ndash2011) Precipitation trendswere also analyzed for each subbasin and entire Swat Riverbasin The mean annual precipitation at different stationsshowed considerable variation with a standard deviationof 1768mm from the mean annual rainfall of 694mmThe Saidu Sharif Mardan and Charsadda stations showedsignificant positive trends (increased precipitation over time)at 5 significance level in the annual precipitation series
The maximum number of significant changes in monthlyprecipitation over time was detected at Saidu Sharif Abazaiand Khairabad stations Saidu Sharif station showed themaximum increasing slope (indicating sharpest change overtime) of 748mmyear among the selected stations in the SwatRiver basin
These study results follow the same statistical trendsreported by Hartmann and Andresky [35] for northwestparts of Pakistan Findings were consistent with results fromDimri [56] Ghaffar and Javid [57] and Rasul [58] whereinthey found statistically significant increasing trends in winterprecipitation for northwest areas of Pakistan The resultsof this analysis also support finding of Hanif et al [37]wherein they found significant variations in summer seasonprecipitation These variations in precipitation trends maylead Pakistan towards more water related disasters suchas droughts and floods in the near future Basistha et al[59] proposed possible causes of the changing precipitationtrends such as global climate shifts [60] dwindling global
Advances in Meteorology 13
Table 6 MK and SR results for seasonal and annual precipitation time series in entire basin and subbasin of Swat River
Subbasin Change (mmyear) Test Winter Spring Summer Autumn Annual
A1 minus073 MK 055 minus024 minus242lowast 305lowast minus034SR 057 001 minus227lowast 347lowast 118
A2 minus090 MK 128 minus023 minus385lowast 158 minus081SR 118 minus035 minus444lowast 164 minus090
A3 030 MK 266lowast 016 minus265lowast 375lowast 024SR 295lowast 027 minus309lowast 460lowast 040
A4 218 MK 242lowast 060 minus021 024 166SR 272lowast 054 minus037 043 173
A 048 MK 214lowast minus011 minus297lowast 307lowast 042SR 225lowast minus014 minus340lowast 336lowast 038
lowastSignificant trend at 5 significance level of two-tailed test
monsoon circulation [61] decline in forest cover [62 63] landuse changes and practices (eg irrigated agriculture) [64 65]and increasing aerosols from anthropogenic activities [66]
5 Conclusions
This paper analyzed trends in monthly seasonal and annualprecipitation in the Swat River basin over the 51-year studyperiod (1961ndash2011) A mix of positive and negative trendswas observed at various stations and subbasins The monthsof June November July and August showed the maximumnumber of significant cases at various stations in monthlyprecipitation The trends were positive in May and June andwere negative in July and August This indicates a shift inprecipitation series on monthly scale Significant positivetrends were detected in winter and autumn and annuallynegative trends were seen in spring and summer seasonsSaidu Sharif Mardan and Charsadda stations exhibitedsignificant positive trends in annual precipitation at a 95confidence level the remaining stations did not experiencea statistically significant trend
For the entire Swat River basin no significant trendswere detected in any subbasin for the annual precipitationseries Seasonally winter and autumn experienced significantpositive trends and summer experienced negative trends indifferent subbasins in the Swat River basin Most statisticallysignificant trend cases under different scenarios were positive(61)The results obtainedwith theMann-Kendall (MK) andSpearmanrsquos rho tests showed agreement in their assessmentsof monthly seasonal and annual precipitation trends Thevariability of negative and positive trends at various stationspoints to the need for more detailed studies on the climatechange of this region
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgments
The authors thank Pakistan Meteorological Department(PMD) Water and Power Development Authority
(WAPDA) Pakistan and Snowy Mountains EngineeringCorporation (SMEC) for providing cost-free data for thisstudy
References
[1] M D Rahman and M Begum ldquoApplication of non parametrictest for trend detection of rainfall in the largest Island ofBangladeshrdquo ARPN Journal of Earth Sciences vol 2 no 2 pp40ndash44 2013
[2] IPCCThePhysical Science Basis Contribution ofWorkingGroupI to the Fourth Assessment Report of the Intergovernmental Panelon Climate Change Cambridge University Press CambridgeUK 2007
[3] A B Farooq and A H Khan ldquoClimate change perspectivein Pakistanrdquo in Proceedings of the Capacity Building APNWorkshop on Global Change Research pp 39ndash46 IslamabadPakistan 2004
[4] Z Z Hu S Yang and R Wu ldquoLong-term climate variationsin China and global warming signalsrdquo Journal of GeophysicalResearch vol 108 no D19 2003
[5] P Zhai and X Pan ldquoTrends in temperature extremes during1951ndash1999 in Chinardquo Geophysical Research Letters vol 30 no17 p 1913 2003
[6] D Duhan and A Pandey ldquoStatistical analysis of long termspatial and temporal trends of precipitation during 1901ndash2002at Madhya Pradesh Indiardquo Atmospheric Research vol 122 pp136ndash149 2013
[7] B J Peterson RM Holmes JWMcClelland et al ldquoIncreasingriver discharge to the Arctic oceanrdquo Science vol 298 no 5601pp 2171ndash2173 2002
[8] N I Savelieva I P Semiletov L N Vasilevskaya and S PPugach ldquoA climate shift in seasonal values of meteorologicaland hydrological parameters for Northeastern Asiardquo Progress inOceanography vol 47 no 2ndash4 pp 279ndash297 2000
[9] Y F Shi Y P Shen and R J Hu ldquoPreliminary study on signalimpact and foreground of climatic shift from warm-dry towarm-humid in Northwest Chinardquo Journal of Glaciology andGeocryology vol 24 pp 219ndash226 2002 (Chinese)
[10] S Farhana and M M Rahman ldquoCharacterizing rainfall trendin Bangladesh by temporal statistics analysisrdquo in Proceedings ofthe 4th Annual Paper Meet and 1st Civil Engineering CongressDhaka Bangladesh 2011
[11] R H Rimi S H Rahman S Karmakar and S G HussainldquoTrend analysis of climate change and investigation on its
14 Advances in Meteorology
probable impacts on rice production at Satkhira BangladeshrdquoPakistan Journal of Meteorology vol 6 no 11 pp 37ndash50 2014
[12] E R Dahmen and M J Hall Screening of Hydrological DataTests for Stationarity and Relative Consistency Publication 49ILRI Wageningen The Netherlands 1990
[13] Q Zhang C Liu C-Y Xu Y Xu and T Jiang ldquoObserved trendsof annual maximumwater level and streamflow during past 130years in the Yangtze River basin Chinardquo Journal of Hydrologyvol 324 no 1-4 pp 255ndash265 2006
[14] H Chen S Guo C-Y Xu and V P Singh ldquoHistorical tem-poral trends of hydro-climatic variables and runoff responseto climate variability and their relevance in water resourcemanagement in the Hanjiang basinrdquo Journal of Hydrology vol344 no 3-4 pp 171ndash184 2007
[15] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 pp 245ndash259 1945
[16] M G Kendall Rank CorrelationMethods Griffin London UK1975
[17] E L Lehmann Nonparametrics Statistical Methods Based onRanks Holden-Day San Francisco Calif USA 1975
[18] R Sneyers ldquoOn the statistical analysis of series of observationsrdquoTechnical Note 143 WMO no 415 World MeteorologicalOrganization 1990
[19] A Longobardi and P Villani ldquoTrend analysis of annual andseasonal rainfall time series in the Mediterranean areardquo Inter-national Journal of Climatology vol 30 no 10 pp 1538ndash15462010
[20] Z YanmingW Jun andW Xinhua ldquoStudy on the change trendof precipitation and temperature in Kunming city based onMann-Kendall analysisrdquo in Future Computer CommunicationControl and Automation vol 119 of Advances in Intelligent andSoft Computing pp 505ndash513 Springer Berlin Germany 2011
[21] X L Yang L R Xu K K Liu C H Li J Hu and X H XialdquoTrend in temperature and precipitation in the ZhangweinanRiver Basin during the last 53 yearsrdquo Procedia EnvironmentalSciences vol 13 pp 1966ndash1974 1966
[22] Z F Yang Y Yan and Q Liu ldquoThe relationship of streamflow-precipitation-temperature in the Yellow River Basin of Chinaduring 1961ndash2000rdquo Procedia Environmental Sciences vol 13 pp2336ndash2345 2012
[23] Q-X Wang X-H Fan Z-D Qin and M-B Wang ldquoChangetrends of temperature and precipitation in the Loess PlateauRegion of China 1961ndash2010rdquo Global and Planetary Change vol92-93 pp 138ndash147 2012
[24] S Yue P Pilon and G Cavadias ldquoPower of the Mann-Kendalland Spearmanrsquos rho tests for detecting monotonic trends inhydrological seriesrdquo Journal of Hydrology vol 259 no 1ndash4 pp254ndash271 2002
[25] E Kahya and S Kalaycı ldquoTrend analysis of streamflow inTurkeyrdquo Journal of Hydrology vol 289 pp 128ndash144 2004
[26] Z L Li Z X Xu J Y Li and Z J Li ldquoShift trend and stepchanges for runoff time series in the Shiyang River BasinNorthwest Chinardquo Hydrological Processes vol 22 no 23 pp4639ndash4646 2008
[27] C Yaning X Changchun H Xingming et al ldquoFifty-yearclimate change and its effect on annual runoff in the TarimRiverBasin Chinardquo Quaternary International vol 208 no 1-2 pp53ndash61 2009
[28] M Shadmani SMarofi andMRoknian ldquoTrend analysis in ref-erence evapotranspiration usingMann-Kendall and SpearmanrsquosRho tests in arid regions of IranrdquoWater Resources Managementvol 26 no 1 pp 211ndash224 2012
[29] H Rehman and A Kamal ldquoIndus Basin River system-floodingand flood mitigationrdquo 2005 httparchiveriversymposiumcom2005indexphpelement=38
[30] Pakistan Meteorological Department (PMD) National PlanStrengthening National Capacities for Multi-hazard EarlyWarn-ing amp Response System 2006
[31] National Disaster Management Authority (NDMA) 2007National Disaster Risk Management Framework Governmentof Pakistan httpwwwndmagovpknew
[32] N H Hashimi Q T M Siddiqui A R Ghumman M AKamal and H R Mughal ldquoA critical analysis of 2010 floods inPakistanrdquo African Journal of Agricultural Research vol 7 no 7pp 1054ndash1067 2012
[33] FFC ldquoFederal Flood Commission of Pakistanrdquo Annual FloodReport-2010 2011 httpwwwffcgovpkdownloadfloodarc-hieveAnnualreport2010pdf
[34] N Gronewold and Climatewire ldquoIs the Flooding in Pakistan aClimate Change Disasterrdquo WMN 2010 httpwwwscientific-americancomarticleis-the-flooding-in-pakist
[35] H Hartmann and L Andresky ldquoFlooding in the Indus Riverbasinmdasha spatiotemporal analysis of precipitation recordsrdquoGlobal and Planetary Change vol 107 pp 25ndash35 2013
[36] S Salma S Rehman andM A Shah ldquoRainfall trends in differ-ent climate zones of Pakistanrdquo Pakistan Journal of Meteorologyvol 9 no 17 pp 37ndash47 2012
[37] M Hanif A H Khan and S Adnan ldquoLatitudinal precipitationcharacteristics and trends in Pakistanrdquo Journal ofHydrology vol492 pp 266ndash272 2013
[38] A Imran Q Zaman and M Afzal ldquoTemporal trends in thepeak monsoonal precipitation events over Northeast PakistanrdquoPakistan Journal of Meteorology vol 10 no 19 pp 19ndash30 2013
[39] S B Cheema and M Hanif ldquoSeasonal precipitation variationover Punjab provincerdquo Pakistan Journal of Meteorology vol 10no 19 pp 61ndash82 2013
[40] H Hartmann and H Buchanan ldquoTrends in extreme precipita-tion events in the indus River Basin and flooding in PakistanrdquoAtmosphere-Ocean vol 52 no 1 pp 77ndash91 2014
[41] ldquoProvincial Disaster Management Authority (PDMA 2012)Monsoon Contingency Plan-Khyber-Pakhtunkhwardquo 2012httpwwwndmagovpkDocumentsContingency Plan2012CP KPpdf
[42] Snowy Mountains Engineering Corporation Munda DamConstruction Project Detailed Design Report SMEC LahorePakistan 2014
[43] H Alexandersson ldquoA homogeneity test applied to precipitationdatardquo Journal of Climatology vol 6 no 6 pp 661ndash675 1986
[44] HAlexandersson andAMoberg ldquoHomogenization of Swedishtemperature data Part I homogeneity test for linear trendsrdquoInternational Journal of Climatology vol 17 no 1 pp 25ndash341997
[45] T A Buishand ldquoSome methods for testing the homogeneity ofrainfall recordsrdquo Journal of Hydrology vol 58 no 1-2 pp 11ndash271982
[46] M N Khaliq and T B M J Ouarda ldquoOn the critical values ofthe standard normal homogeneity test (SNHT)rdquo InternationalJournal of Climatology vol 27 no 5 pp 681ndash687 2007
[47] K H Hamed and A Ramachandra Rao ldquoA modified Mann-Kendall trend test for autocorrelated datardquo Journal of Hydrologyvol 204 no 1ndash4 pp 182ndash196 1998
[48] B Onoz and M Bayazit ldquoBlock bootstrap for Mann-Kendalltrend test of serially dependent datardquoHydrological Processes vol26 no 23 pp 3552ndash3560 2012
Advances in Meteorology 15
[49] M Yaseen H A Bhatti T Rientjes G Nabi and M LatifldquoTemporal and spatial variations in summer flows of upperIndus Basin Pakistanrdquo inProceedings of the 72ndAnnual Sessionof Pakistan Engineering Congress Paper no 747 pp 315ndash3342013
[50] G C Blain ldquoThe Mann-Kendall test the need to consider theinteraction between serial correlation and trendrdquo AgriculturalEngineering vol 35 no 4 2013
[51] M Yaseen T Rientjes G Nabi H ur-Rehman and M LatifldquoAssessment of recent temperature trends inManglawatershedrdquoJournal of Himalayan Earth Sciences vol 47 no 1 pp 107ndash1212014
[52] P K Sen ldquoEstimates of the regression coefficient based onKendallrsquos taurdquo Journal of the American Statistical Associationvol 63 no 324 pp 1379ndash1389 1968
[53] W S Cleveland ldquoRobust locally weighted regression andsmoothing scatterplotsrdquoThe Journal of the American StatisticalAssociation vol 74 no 368 pp 829ndash836 1979
[54] W S Cleveland ldquoGraphs in scientific publicationsrdquoThe Ameri-can Statistician vol 38 no 4 pp 261ndash269 1984
[55] D R Helsel and R M Hirsch ldquoStatistical methods in waterresourcesrdquo inTechniques ofWater Resources Investigations Book4 chapter A3 p 522 US Geological Survey 2002
[56] A P Dimri ldquoSurface and upper air fields during extreme winterprecipitation over the western Himalayasrdquo Pure and AppliedGeophysics vol 163 no 8 pp 1679ndash1698 2006
[57] A Ghaffar and M Javid ldquoImpact of global warming onmonsoon variability in Pakistanrdquo The Journal of Animal andPlant Sciences vol 21 no 1 pp 107ndash110 2011
[58] G Rasul ldquoClimate Data and Modelling Analysis of the IndusRegionrdquo Pakistan Meteorological Department (PMD) 2012httpwwfpakorgccappdfClimate Data Modelling20An-alysis20of20the20Indus20Ecoregionpdf
[59] A Basistha D S Arya and N K Goel ldquoAnalysis of historicalchanges in rainfall in the Indian Himalayasrdquo InternationalJournal of Climatology vol 29 no 4 pp 555ndash572 2009
[60] P G Baines ldquoThe late 1960s global climate shift and its influenceon the Southern Hemisphererdquo in Proceedings of 8 ICSHMO pp1477ndash1482 INPE Foz do Iguacu Brazil 2006
[61] K Duan and T Yao ldquoMonsoon variability in the Himalayasunder the condition of global warmingrdquo Journal of the Mete-orological Society of Japan vol 81 no 2 pp 251ndash257 2003
[62] U S Nair R O Lawton R M Welch and R A Pielke SrldquoImpact of land use on Costa Rican tropical montane cloudforests sensitivity of cumulus cloud field characteristics tolowland deforestationrdquo Journal of Geophysical Research D vol108 no 7 pp 4206ndash4219 2003
[63] R Avissar and D Werth ldquoGlobal hydroclimatological tele-connections resulting from tropical deforestationrdquo Journal ofHydrometeorology vol 6 no 2 pp 134ndash145 2005
[64] R A Pielke Sr J Adegoke A Beltran-Przekurat et al ldquoAnoverview of regional land-use and land-cover impacts onrainfallrdquo Tellus B Chemical and Physical Meteorology vol 59no 3 pp 587ndash601 2007
[65] N Ramankutty C Delire and P Snyder ldquoFeedbacks betweenagriculture and climate an illustration of the potential unin-tended consequences of human land use activitiesrdquo Global andPlanetary Change vol 54 no 1-2 pp 79ndash93 2006
[66] V Ramanathan C Chung D Kim et al ldquoAtmospheric brownclouds impacts on South Asian climate and hydrological cyclerdquoProceedings of the National Academy of Sciences of the UnitedStates of America vol 102 no 15 pp 5326ndash5333 2005
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ClimatologyJournal of
EcologyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
EarthquakesJournal of
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Applied ampEnvironmentalSoil Science
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Mining
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
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International Journal of
Geophysics
OceanographyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal ofPetroleum Engineering
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
GeochemistryHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Atmospheric SciencesInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OceanographyHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Advances in
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MineralogyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MeteorologyAdvances in
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Paleontology JournalHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geological ResearchJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geology Advances in
Advances in Meteorology 3
34∘-00998400
34∘-15998400
34∘-30998400
34∘-45998400
35∘-00998400
35∘-15998400
35∘-30998400
35∘-45998400
36∘-00998400
34∘-00998400
34∘-15998400
34∘-30998400
34∘-45998400
35∘-00998400
35∘-15998400
35∘-30998400
35∘-45998400
36∘-00998400
70∘-4
5998400
71∘-0
0998400
71∘-1
5998400
71∘-3
0998400
71∘-4
5998400
72∘-0
0998400
72∘-1
5998400
72∘-3
0998400
72∘-4
5998400
73∘-0
0998400
70∘-4
5998400
71∘-0
0998400
71∘-1
5998400
71∘-3
0998400
71∘-4
5998400
72∘-0
0998400
72∘-1
5998400
72∘-3
0998400
72∘-4
5998400
73∘-0
0998400
Afghan
istan
A3
A3
A2
A2
A1
A1
A4
A4
N
Ambahar
Abazai
ToorCamp
Dir
Drosh Kalam
Thalozom
Madyan
Khairabad
Saidu Sharif
Malakand
Mardan
RisalpurCharsadda
Kulangi
Upper Swat subbasin
Panjkora subbasin
Ambahar subbasin
Lower Swat subbasin
Figure 1 Locations of meteorological stations at Swat River basin
by applying two tests standard normal homogeneity test(SNHT) [43 44] and Buishandrsquos range (BR) test [45] ata 5 significance level for each station The precipitationtime series is considered homogenous if the critical values ofSNHT and BR statistics are less than 917 [46] and 127 155[45] respectively As Table 1 shows all the precipitation serieswere found to be homogenous
23 Statistical Tests Prior to applying MK and SR teststo identify precipitation trends over the time series fromselected stations data were tested according to the testsrsquo re-quirements The trend-free prewhitening (TFPW) approachwas applied to eliminate serial correlations in the time seriesdata The magnitude of the slope in time series data wascalculated using Senrsquos slope method The statistical methodsused are briefly discussed below
231 Autocorrelation and TFPW Removing serial depen-dence is one of the main problems in testing and interpretingtime series data Applying nonparametric tests to detecttrends can significantly affect the results Therefore all ofthe rainfall time series data was first tested for the presenceof autocorrelation coefficient (119903
1) at a 5 significance level
using a two-tailed test
1199031=
sum119899minus1
119894=1
(119883119894minus 119883) (119883
119894+1minus 119883)
sum119899
119894=1
(119883119894minus 119883)
2
(1)
The autocorrelation coefficient value of 1199031was tested against
the null hypothesis at a 95 confidence interval using a two-tailed test
1199031(95) =
minus1 plusmn 196radic(119899 minus 2)
119899 minus 1
(2)
4 Advances in Meteorology
Table 1 Results of homogeneity tests for mean annual precipitationtime series at study stations
Station SNHT Buishandrsquos range (BR) test1198790
119876radic119899 119877radic119899
Thalozom 916 108 108Drosh 906 117 147Kalam 887 087 108Dir 776 124 149Madyan 485 111 150Khairabad 192 062 093ToorCamp 620 117 154Saidu Sharif 742 118 190Malakand 257 077 086Kulangi 428 097 146Ambahar 508 109 139Abazai 686 121 140Mardan 893 108 124Charsadda 902 125 138Risalpur 724 091 125For homogenous series 119879
0lt 917119876radic119899 lt 127 and 119877radic119899 lt 155
If 1199031falls between the upper and lower limits of confidence
interval (the data are considered serially correlated) themethods of prewhitening variance correlation [47] andtrend-free prewhitening (TFPW) approach [24] have beenproposed In this study for the stations where serial cor-relations were detected in the data the TFPW approachwas applied to remove the correlation for both tests (Mann-Kendall and Spearmanrsquos rho) Other researchers [28 48ndash51]have also used this approach to eliminate serial correlation intime series data
232 The Mann-Kendall Test The rank-based nonparamet-ric Mann-Kendall [15 16] method was applied to the long-term data in this study to detect statistically significanttrends In this test the null hypothesis (H
0) was that there
has been no trend in precipitation over time the alternatehypothesis (H
1) was that there has been a trend (increasing
or decreasing) over time The mathematical equations forcalculatingMann-Kendall Statistics 119878119881(119878) and standardizedtest statistics 119885 are as follows
119878 =
119899minus1
sum
119894=1
119899
sum
119895=119894+1
sig (119883119895minus 119883119894)
sgn (119883119895minus 119883119894) =
+1 if (119883119895minus 119883119894) gt 0
0 if (119883119895minus 119883119894) = 0
minus1 if (119883119895minus 119883119894) lt 0
119881 (119878) =
1
18
[119899 (119899 minus 1) (2119899 + 5) minus
119902
sum
119901=1
119905119901(119905119901minus 1) (2119905
119901+ 5)]
119885 =
119878 minus 1
radicVAR (119878)if 119878 gt 0
0 if 119878 = 0
119878 + 1
radicVAR (119878)if 119878 lt 0
(3)
In these equations119883119894and119883
119895are the time series observations
in chronological order 119899 is the length of time series 119905119901is
the number of ties for 119901th value and 119902 is the number oftied values Positive 119885 values indicate an upward trend in thehydrologic time series negative 119885 values indicate a negativetrend If |119885| gt 119885
1minus1205722 (H0) is rejected and a statistically
significant trend exists in the hydrologic time series Thecritical value of119885
1minus1205722for a 119901 value of 005 from the standard
normal table is 196
233 Spearmanrsquos rho Test Spearmanrsquos rho [17 18] test isanother rank-based nonparametric method used for trendanalysis and was applied as a comparison with the Mann-Kendall test In this test which assumes that time seriesdata are independent and identically distributed the nullhypothesis (H
0) again indicates no trend over time the
alternate hypothesis (H1) is that a trend exists and that data
increase or decrease with 119894 [24] The test statistics 119877sp andstandardized statistics 119885sp are defined as
119877sp = 1 minus
6sum119899
119894=1
(119863119894minus 119894)2
119899 (1198992
minus 1)
119885sp = 119877spradic119899 minus 2
1 minus 1198772
sp
(4)
In these equations 119863119894is the rank of 119894th observation 119868 is the
chronological order number 119899 is the total length of the timeseries data and 119885sp is Studentrsquos 119905-distribution with (119899 minus 2)degree of freedom The positive values of 119885sp represent anincreasing trend across the hydrologic time series negativevalues represent the decreasing trends The critical value of119905 at a 005 significance level of Studentrsquos 119905-distribution tableis defined as 119905
(119899minus21minus1205722)[12] If |119885sp| gt 119905
(119899minus21minus1205722) (H0) is
rejected and a significant trend exists in the hydrologic timeseries
234 Senrsquos Slope Estimator Senrsquos nonparametric method [52]was used to estimate the magnitude of trends in the timeseries data
119879119894=
119909119895minus 119909119896
119895 minus 119896
(5)
In this equation 119909119895and 119909
119896represent data values at time 119895 and
119896 respectively Consider
119876119894=
119879(119873+1)2
119873 is odd1
2
(1198791198732
+ 119879(119873+2)2
) 119873 is even(6)
A positive119876119894value represents an increasing trend a negative
119876119894value represents a decreasing trend over time
Advances in Meteorology 5
Table 2 Summary of geographic conditions and mean annual precipitation statistics for study stations
Station Longitude Latitude Elevation (m) Mean (mm) STD 119862119904
119862119896
119862V
Thalozom 72∘-151015840 35∘-441015840 4200 7511 2099 minus0266 0082 0291Drosh 72∘-001015840 35∘-331015840 1465 4635 1537 1167 2441 0332Kalam 72∘-331015840 35∘-311015840 2000 9345 3170 minus0599 0323 0353Dir 71∘-531015840 35∘-121015840 1321 5482 1521 minus0545 0919 0285Madyan 72∘-321015840 35∘-091015840 1320 9623 2878 0240 1300 0307Khairabad 72∘-061015840 34∘-581015840 894 7037 1522 1410 4281 0216ToorCamp 71∘-421015840 34∘-501015840 854 5440 1592 minus0436 0841 0299Saidu Sharif 72∘-251015840 34∘-451015840 961 9901 3898 1842 6463 0398Malakand 71∘-461015840 34∘-381015840 603 6098 2526 2474 11668 0424Kulangi 71∘-591015840 34∘-351015840 688 6254 1925 0037 minus0170 0308Ambahar 71∘-121015840 34∘-331015840 694 4550 1485 minus0004 0764 0333Abazai 71∘-331015840 34∘-261015840 320 5007 1527 minus0093 0963 0312Mardan 71∘-581015840 34∘-181015840 283 6574 2974 0735 1392 0452Charsadda 71∘-431015840 34∘-071015840 276 5916 2074 0973 1031 0350Risalpur 71∘-541015840 34∘-061015840 309 6118 1768 0312 minus0098 0289
3 Results and Discussion
31 Preliminary Analysis The preliminary analysis for thisstudy included computing the mean standard deviationcoefficient of skewness coefficient of kurtosis and coefficientof variation in the annual precipitation time series foreach station Table 2 presents these statistical parametersfor the 51-year time period studied (1961ndash2011) The meanannual precipitation varied between 455mm in the southwestpart of the Swat River basin catchment area (Ambahar)and 9901mm in the southeast part (Saidu Sharif) As thetable shows the coefficient of skewness varied from minus0266to 2474 kurtosis varied between minus0170 and 11668 Fortime series data to be considered normally distributed thecoefficient of skewness and kurtosis must be equal to 0and 3 respectively Table 2 indicates therefore that the dataare positively skewed and not normally distributed Thecoefficient of variation the measure of dispersion around themean was also calculated to analyze the spatial variability ofannual precipitation for each station This coefficient variedbetween 216 (Khairabad) and 452 (Mardan)The averagevariation of the precipitation over the complete river basinwas 289
32 Long-Term Pattern on Seasonal and Annual Scale Long-term climatic patterns were assessed using standardizedseasonal and annual precipitation time series data Toreduce local fluctuations LOWESS [53ndash55] curves were fittedover time based on seasonal and annual precipitation timeseries data The LOWESS curve for winter precipitation(Figure 2(a)) showed a decreasing trend in the first decadeIn the second decade the trend was constant The minimumLOWESS curve value was observed in 1990 values thengradually rose through 2010 Overall the curve based onwinter season data suggested a decline in precipitation After1990 there was a gradual rise though small local fluctuationswere ignored The LOWESS curve for spring precipitation(Figure 2(b)) showed a gradual increase in the first three
decades After attaining its highest value in 1990 the valuedeclined over the last two decades
The LOWESS curve for summer precipitation showeda constant trend in the first decade and then started todecline up to 1978 (Figure 2(c)) For 1978ndash1992 the curvestarted to gradually increase through the remaining yearsThe LOWESS curve for autumn precipitation exhibited adecreasing trend through 1982 for the remaining time peri-ods there was an increase in precipitation For the annualprecipitation time series the LOWESS curve showed slightvariations in every decade but the overall trend was nearlyconstant throughout the time series Figure 2 shows theprecipitation patterns LOWESS curves are used to showpatterns and do not explain statistically significant trends inthe time series
33 Monthly Analysis The Mann-Kendall (MK) and Spear-manrsquos (SR) rho tests were applied on a monthly scale todetect trends in the precipitation series at different stationsTable 3 shows the results and illustrates that the results ofboth tests were similar to one another Monthly trend testsshowed a mix of positive and negative trends at differentstations At Thalozom statistically significant negative andpositive trends were found in April and June respectivelySignificant positive trends were detected at Dir and Droshstations in March and August no significant trends werefound for other months The Saidu Sharif station exhibitedsignificant positive trends from January to June and fromOctober to December but had negative trends in July andAugust Significant positive trends were found at most of thestations in the months of May and June significant negativetrends were seen in July and August In other stations a mixof significantly positive and negative trends occurred for afew months of the year Figure 3 shows the spatial variationin the precipitation time series for each month in the SwatRiver basin from 1961 to 2011
The magnitude of statistically significant trends on amonthly scale was determined using Senrsquos slope estimator
6 Advances in Meteorology
0
1
2
3
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
Original dataLOWESS line
minus3
minus2
minus1
(a)
Original dataLOWESS line
0
1
2
3
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
minus2
minus1
(b)
Original dataLOWESS line
0
1
2
3
4
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
minus2
minus1
(c)
Original dataLOWESS line
0
1
2
3
4
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
minus2
minus1
(d)
Original dataLOWESS line
0
1
2
3
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
minus3
minus2
minus1
(e)
Figure 2 Standardized precipitation and LOWESS trend curves at Swat River basin (a) winter (b) spring (c) summer (d) autumn and (e)annual
Advances in Meteorology 7
Table3MKandSR
tests
results
forp
recipitatio
nin
mon
thlytim
eseries
Station
Test
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Thalozom
MK
minus063
minus10
9minus042
minus219lowast
minus033
272lowast
minus080
minus094
minus029
010
146
030
SRminus044
minus10
1minus039
minus215lowast
minus040
293lowast
minus079
minus10
3minus013
028
141
013
Drosh
MK
minus008
minus024
016
minus067
063
151
minus19
4minus316lowast
minus063
040
103
001
SRminus014
minus001
008
minus079
067
173
minus18
7minus336lowast
minus050
039
101
017
Kalam
MK
minus037
minus067
033
minus221lowast
minus063
219lowast
minus115
minus10
4minus054
014
120
017
SRminus023
minus052
023
minus213lowast
minus064
229lowast
minus113
minus10
7minus043
014
091
minus066
Dir
MK
000
minus063
minus248lowast
minus021
minus079
112
minus015
003
174
minus13
1minus034
minus089
SRminus016
minus062
minus280lowast
minus018
minus10
010
7minus001
minus002
203lowast
minus16
3minus049
minus10
1
Madyan
MK
089
075
110
minus083
086
353lowast
minus312lowast
minus338lowast
minus023
190
272lowast
134
SR086
070
113
minus067
085
426lowast
minus324lowast
minus398lowast
minus016
200
301lowast
132
Khaira
bad
MK
091
minus068
minus021
minus080
201lowast
385lowast
minus312lowast
minus348lowast
minus019
268lowast
292lowast
112
SR082
minus072
minus028
minus079
204lowast
446lowast
minus334lowast
minus460lowast
minus017
308lowast
325lowast
097
ToorCa
mp
MK
192
093
045
minus070
minus044
minus086
minus291lowast
minus296lowast
minus227lowast
minus201lowast
094
028
SR17
8085
025
minus082
minus047
minus091
minus317lowast
minus361lowast
minus279lowast
minus233lowast
104
020
SaiduSh
arif
MK
274lowast
246lowast
222lowast
182
285lowast
327lowast
minus334lowast
minus309lowast
003
319lowast
357lowast
210lowast
SR302lowast
262lowast
261lowast
205lowast
324lowast
383lowast
minus360lowast
minus387lowast
020
364lowast
405lowast
217lowast
Malakand
MK
105
minus17
2minus115
010
228lowast
322lowast
minus318lowast
minus293lowast
016
350lowast
273lowast
149
SR099
minus202lowast
minus13
2022
254lowast
302lowast
minus380lowast
minus382lowast
023
397lowast
223lowast
091
Kulang
iMK
070
minus099
minus294lowast
minus14
4minus062
036
000
174
291lowast
minus16
4minus003
minus204lowast
SR059
minus10
4minus315lowast
minus14
1minus081
024
008
165
336lowast
minus18
5minus031
minus231lowast
Ambahar
MK
031
minus066
minus284lowast
minus10
5minus115
060
018
060
304lowast
minus13
6minus021
minus18
0SR
038
minus070
minus282lowast
minus111
minus118
058
019
034
356lowast
minus15
1minus029
minus201lowast
Abazai
MK
233lowast
minus025
minus091
137
292lowast
449lowast
minus262lowast
minus10
710
2331lowast
392lowast
261lowast
SR222lowast
minus029
minus090
162
289lowast
435lowast
minus307lowast
minus10
913
7385lowast
366lowast
272lowast
Mardan
MK
243lowast
134
041
001
105
070
014
minus016
100
minus058
minus13
1minus13
7SR
253lowast
134
050
011
110
072
025
minus020
088
minus051
minus115
minus115
Charsadd
aMK
232lowast
109
032
minus012
015
034
014
minus014
056
minus10
4minus217lowast
minus15
9SR
237lowast
109
026
minus024
032
044
022
minus033
043
minus097
minus204lowast
minus13
1
Risalpur
MK
191
128
006
minus027
minus033
minus037
minus006
minus063
minus026
minus14
6minus18
7minus217lowast
SR213lowast
113
006
minus036
minus017
minus025
minus005
minus072
minus026
minus15
0minus211lowast
minus216lowast
lowast
Sign
ificant
trend
at5
significance
leveloftwo-tailedtest
8 Advances in Meteorology
Jan Feb Mar Apr
May Jun Jul Aug
Sep Oct Nov Dec
N
0 5 10 25
Scale
(km)
Significant increasing trendSignificant decreasing trend
No trend
Figure 3 Location of sites with increasing decreasing and no trends at 5 significance level for the monthly precipitation time series
The results show that trends at Saidu Sharif Madyanand Kalam were more rapid (eg sharper increases anddecreases) compared to other stations The Saidu Sharifstation had the maximum negative decline in monthly pre-cipitation (183mmmonth) as well as the maximum positiveincrease (143mmmonth) during the months of July andMarch respectively Figure 4 shows the trends in maximummonthly precipitation variation at the Saidu Sharif station
34 Seasonal and Annual Analysis The MK and SR testswere also used to identify trends in seasonal and annualprecipitation between 1961 and 2011 Table 4 shows the resultsSimilar to the monthly analysis results from both statisticaltests MK and SR were consistent with one another A mixof negative and positive trends was seen at different stationsThalozom Kalam and Dir stations which had shown trends
with the monthly time scale did not exhibit statisticallysignificant trends for the seasonal and annual precipitationtime series At Madyan Khairabad and Malakand stationsthere were significant negative trends in the summer andpositive trends in the autumn Significant negative trendswere observed in the spring season only at ToorCampKulangi and Ambahar stations For the annual precipitationseries significant positive trends were detected only at SaiduSharif Mardan and Charsadda stations At other stationssignificant positive trends were seen for winter and autumnseasons and for the annual precipitation series howevernegative trends were detected in spring and summer seasonsFigure 5 presents the spatial distribution of seasonal andannual precipitation trends
The Saidu Sharif station showed the maximum positivetrend in annual precipitation series (748mmyear) across
Advances in Meteorology 9
0
100
200
300
400
500
600
700
800
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
mon
th)
Year
Saidu Sharif station(March)
(a)
0
100
200
300
400
500
600
700
800
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
mon
th)
Year
Saidu Sharif station(July)
(b)
Figure 4 Variations of monthly precipitation time series in stations with most significant trends during 1961ndash2011
Table 4 MK and SR tests results for precipitation in seasonal and annual time series
Station Test Winter Spring Summer Autumn Annual
Thalozom MK minus120 minus162 minus120 148 minus149SR minus114 minus152 minus110 135 minus145
Drosh MK 042 minus078 minus196 097 minus044SR 049 minus074 minus209lowast 127 minus048
Kalam MK minus062 minus139 minus171 160 minus110SR minus037 minus121 minus158 157 minus087
Dir MK minus028 minus148 minus047 minus076 minus138SR minus062 minus150 minus058 minus097 minus146
Madyan MK 120 003 minus258lowast 365lowast 042SR 137 033 minus244lowast 421lowast 078
Khairabad MK 026 minus065 minus302lowast 325lowast minus073SR 021 minus076 minus353lowast 364lowast minus072
ToorCamp MK minus063 minus203lowast 024 minus073 minus044SR minus096 minus217lowast 023 minus092 minus159
Saidu Sharif MK 346lowast 239lowast minus156 069 328lowast
SR 404lowast 280lowast minus156 148 278lowast
Malakand MK minus070 minus110 minus270lowast 337lowast minus119SR minus068 minus115 minus319lowast 373lowast minus140
Kulangi MK minus122 minus261lowast 031 minus099 minus144SR minus156 minus284lowast 037 minus127 minus172
Ambahar MK minus066 minus206lowast minus063 minus099 minus157SR minus076 minus224lowast minus058 minus110 minus141
Abazai MK 179 minus015 minus099 429lowast 096SR 217lowast 007 minus072 604lowast 122
Mardan MK 281lowast 145 095 minus102 259lowast
SR 310lowast 134 098 minus085 280lowast
Charsadda MK 266lowast 097 073 minus194 214lowast
SR 293lowast 088 060 minus176 217lowast
Risalpur MK 243lowast 044 minus006 minus154 198SR 254lowast 040 minus005 minus190 195
lowastSignificant trend at 5 significance level of two-tailed test
10 Advances in Meteorology
N
0 5 10 25
Scale
(km)
Significant increasing trendSignificant decreasing trend
No trend
Winter
Autumn Annual
Spring Summer
Figure 5 Location of sites with increasing decreasing and no trends at 5 significance level for the seasonal and annual precipitation timeseries
study stations from 1961 to 2011 theThalozom station showeda negative trend with a decreasing rate of 370mmyearFigure 6 displays the results of the magnitude of variationin the annual precipitation for the Saidu Sharif MardanCharsadda andThalozom stations
35 Trend Analysis over Entire River Basin The effect ofclimate change on precipitation was also analyzed for theentire Swat River basin by applying the MK and SR testson monthly seasonal and annual scale As Figure 1 showedthe entire Swat River catchment (A) is divided into foursubbasins upper subbasin (A1) Panjkora subbasin (A2)Ambahar subbasin (A3) and Lower subbasin (A4) Table 5presents trends in monthly precipitation across the subbasinsand for the full basin The table shows significant positivetrends in the months of June and November for the uppersubbasin (A1) and the entire Swat River basin (A) negativetrends were seen in these locations in July and August Inthe Panjkora subbasin (A2) statistically significant positivetrends were identified over time in June a negative trendwas seen from July to September The maximum number ofsignificant cases (8) was observed in data from the Ambaharsubbasin (A3)The Lower subbasin (A4) showed a significantpositive trend only during January no significant trendsin other months were identified As a simpler summarysignificant negative trends in precipitation over time were
seen from July to September positive trends over time wereseen in January May June and October to December indifferent Swat River subbasins
To detect precipitation trends in each subbasin and entireSwat River basin the MK and SR tests were again appliedto seasonal and annual precipitation data for the 51-yearstudy period (1961ndash2011) As Table 6 shows both testmethodsshowed similar results The upper subbasin (A1) experiencedstatistically significant negative trends in the summer andpositive trends in the autumn The Panjkora subbasin (A2)and Lower subbasin (A4) showed significant negative trendsin the summer and positive trends in the winter Significantpositive trends were found across the subbasins in winterand autumn seasons however there was a negative trendin summer at Ambahar subbasin (A3) and across the entireSwat River basin (A) For the annual and spring precipitationtime series there were no statistically significant trendsSignificant positive trendswere seen inwinter and autumn insummer negative trends were seen across different subbasinsand the full Swat River basin
The Lower subbasin exhibited the maximum positivetrend over time (218mmyear) in the weighted annualprecipitation time series the Panjkora subbasin showed anegative trend with a decreasing rate of participation at090mmyear The entire Swat River basin showed a positivetrend in precipitation (048mmyear) as shown in Table 6
Advances in Meteorology 11
Table5MKandSR
tests
results
form
onthlyprecipitatio
ntim
eseriesinentireb
asin
andsubb
asinso
fSwatRiver
Subb
asin
Test
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
A1
MK
047
010
071
minus12
3041
349lowast
minus288lowast
minus318lowast
minus018
143
250lowast
094
SR045
006
074
minus098
047
409lowast
minus299lowast
minus363lowast
minus018
159
277lowast
094
A2
MK
107
080
016
minus093
021
201lowast
minus354lowast
minus416lowast
minus202lowast
000
187
062
SR095
072
001
minus099
013
231lowast
minus386lowast
minus486lowast
minus224lowast
011
200
063
A3
MK
250lowast
102
minus036
065
297lowast
390lowast
minus297lowast
minus255lowast
minus044
305lowast
295lowast
229lowast
SR267lowast
089
minus009
070
311lowast
479lowast
minus354lowast
minus322lowast
minus052
376lowast
365lowast
260lowast
A4
MK
237lowast
088
minus006
minus050
122
164
minus063
minus083
000
020
050
minus040
SR246lowast
084
minus001
minus059
117
182
minus059
minus090
001
045
023
minus046
AMK
185
110
013
minus062
123
369lowast
minus255lowast
minus361lowast
minus065
174
268lowast
070
SR17
010
4018
minus079
127
422lowast
minus277lowast
minus401lowast
minus070
181
299lowast
073
lowast
Sign
ificant
trend
at5
significance
leveloftwo-tailedtest
12 Advances in Meteorology
0
500
1000
1500
2000
2500
3000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Saidu Sharif station
(a)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Mardan station
(b)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Charsadda station
(c)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Thalozom station
(d)
Figure 6 Variations of annual precipitation time series in stations with significant trends during 1961ndash2011
36 Comparison of Results Results from both statistical testsMK and SR were consistent with each otherThe percentagesof statistically significant cases to total tested cases for theMK and SR tests were 32 and 30 respectively showingagreement across methods This consistency in statisticalperformance was also found in other studies [24 28]
4 Discussion
This study investigated variability in monthly seasonal andannual precipitation at 15 stations in the Swat River basinover a 51-year study period (1961ndash2011) Precipitation trendswere also analyzed for each subbasin and entire Swat Riverbasin The mean annual precipitation at different stationsshowed considerable variation with a standard deviationof 1768mm from the mean annual rainfall of 694mmThe Saidu Sharif Mardan and Charsadda stations showedsignificant positive trends (increased precipitation over time)at 5 significance level in the annual precipitation series
The maximum number of significant changes in monthlyprecipitation over time was detected at Saidu Sharif Abazaiand Khairabad stations Saidu Sharif station showed themaximum increasing slope (indicating sharpest change overtime) of 748mmyear among the selected stations in the SwatRiver basin
These study results follow the same statistical trendsreported by Hartmann and Andresky [35] for northwestparts of Pakistan Findings were consistent with results fromDimri [56] Ghaffar and Javid [57] and Rasul [58] whereinthey found statistically significant increasing trends in winterprecipitation for northwest areas of Pakistan The resultsof this analysis also support finding of Hanif et al [37]wherein they found significant variations in summer seasonprecipitation These variations in precipitation trends maylead Pakistan towards more water related disasters suchas droughts and floods in the near future Basistha et al[59] proposed possible causes of the changing precipitationtrends such as global climate shifts [60] dwindling global
Advances in Meteorology 13
Table 6 MK and SR results for seasonal and annual precipitation time series in entire basin and subbasin of Swat River
Subbasin Change (mmyear) Test Winter Spring Summer Autumn Annual
A1 minus073 MK 055 minus024 minus242lowast 305lowast minus034SR 057 001 minus227lowast 347lowast 118
A2 minus090 MK 128 minus023 minus385lowast 158 minus081SR 118 minus035 minus444lowast 164 minus090
A3 030 MK 266lowast 016 minus265lowast 375lowast 024SR 295lowast 027 minus309lowast 460lowast 040
A4 218 MK 242lowast 060 minus021 024 166SR 272lowast 054 minus037 043 173
A 048 MK 214lowast minus011 minus297lowast 307lowast 042SR 225lowast minus014 minus340lowast 336lowast 038
lowastSignificant trend at 5 significance level of two-tailed test
monsoon circulation [61] decline in forest cover [62 63] landuse changes and practices (eg irrigated agriculture) [64 65]and increasing aerosols from anthropogenic activities [66]
5 Conclusions
This paper analyzed trends in monthly seasonal and annualprecipitation in the Swat River basin over the 51-year studyperiod (1961ndash2011) A mix of positive and negative trendswas observed at various stations and subbasins The monthsof June November July and August showed the maximumnumber of significant cases at various stations in monthlyprecipitation The trends were positive in May and June andwere negative in July and August This indicates a shift inprecipitation series on monthly scale Significant positivetrends were detected in winter and autumn and annuallynegative trends were seen in spring and summer seasonsSaidu Sharif Mardan and Charsadda stations exhibitedsignificant positive trends in annual precipitation at a 95confidence level the remaining stations did not experiencea statistically significant trend
For the entire Swat River basin no significant trendswere detected in any subbasin for the annual precipitationseries Seasonally winter and autumn experienced significantpositive trends and summer experienced negative trends indifferent subbasins in the Swat River basin Most statisticallysignificant trend cases under different scenarios were positive(61)The results obtainedwith theMann-Kendall (MK) andSpearmanrsquos rho tests showed agreement in their assessmentsof monthly seasonal and annual precipitation trends Thevariability of negative and positive trends at various stationspoints to the need for more detailed studies on the climatechange of this region
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgments
The authors thank Pakistan Meteorological Department(PMD) Water and Power Development Authority
(WAPDA) Pakistan and Snowy Mountains EngineeringCorporation (SMEC) for providing cost-free data for thisstudy
References
[1] M D Rahman and M Begum ldquoApplication of non parametrictest for trend detection of rainfall in the largest Island ofBangladeshrdquo ARPN Journal of Earth Sciences vol 2 no 2 pp40ndash44 2013
[2] IPCCThePhysical Science Basis Contribution ofWorkingGroupI to the Fourth Assessment Report of the Intergovernmental Panelon Climate Change Cambridge University Press CambridgeUK 2007
[3] A B Farooq and A H Khan ldquoClimate change perspectivein Pakistanrdquo in Proceedings of the Capacity Building APNWorkshop on Global Change Research pp 39ndash46 IslamabadPakistan 2004
[4] Z Z Hu S Yang and R Wu ldquoLong-term climate variationsin China and global warming signalsrdquo Journal of GeophysicalResearch vol 108 no D19 2003
[5] P Zhai and X Pan ldquoTrends in temperature extremes during1951ndash1999 in Chinardquo Geophysical Research Letters vol 30 no17 p 1913 2003
[6] D Duhan and A Pandey ldquoStatistical analysis of long termspatial and temporal trends of precipitation during 1901ndash2002at Madhya Pradesh Indiardquo Atmospheric Research vol 122 pp136ndash149 2013
[7] B J Peterson RM Holmes JWMcClelland et al ldquoIncreasingriver discharge to the Arctic oceanrdquo Science vol 298 no 5601pp 2171ndash2173 2002
[8] N I Savelieva I P Semiletov L N Vasilevskaya and S PPugach ldquoA climate shift in seasonal values of meteorologicaland hydrological parameters for Northeastern Asiardquo Progress inOceanography vol 47 no 2ndash4 pp 279ndash297 2000
[9] Y F Shi Y P Shen and R J Hu ldquoPreliminary study on signalimpact and foreground of climatic shift from warm-dry towarm-humid in Northwest Chinardquo Journal of Glaciology andGeocryology vol 24 pp 219ndash226 2002 (Chinese)
[10] S Farhana and M M Rahman ldquoCharacterizing rainfall trendin Bangladesh by temporal statistics analysisrdquo in Proceedings ofthe 4th Annual Paper Meet and 1st Civil Engineering CongressDhaka Bangladesh 2011
[11] R H Rimi S H Rahman S Karmakar and S G HussainldquoTrend analysis of climate change and investigation on its
14 Advances in Meteorology
probable impacts on rice production at Satkhira BangladeshrdquoPakistan Journal of Meteorology vol 6 no 11 pp 37ndash50 2014
[12] E R Dahmen and M J Hall Screening of Hydrological DataTests for Stationarity and Relative Consistency Publication 49ILRI Wageningen The Netherlands 1990
[13] Q Zhang C Liu C-Y Xu Y Xu and T Jiang ldquoObserved trendsof annual maximumwater level and streamflow during past 130years in the Yangtze River basin Chinardquo Journal of Hydrologyvol 324 no 1-4 pp 255ndash265 2006
[14] H Chen S Guo C-Y Xu and V P Singh ldquoHistorical tem-poral trends of hydro-climatic variables and runoff responseto climate variability and their relevance in water resourcemanagement in the Hanjiang basinrdquo Journal of Hydrology vol344 no 3-4 pp 171ndash184 2007
[15] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 pp 245ndash259 1945
[16] M G Kendall Rank CorrelationMethods Griffin London UK1975
[17] E L Lehmann Nonparametrics Statistical Methods Based onRanks Holden-Day San Francisco Calif USA 1975
[18] R Sneyers ldquoOn the statistical analysis of series of observationsrdquoTechnical Note 143 WMO no 415 World MeteorologicalOrganization 1990
[19] A Longobardi and P Villani ldquoTrend analysis of annual andseasonal rainfall time series in the Mediterranean areardquo Inter-national Journal of Climatology vol 30 no 10 pp 1538ndash15462010
[20] Z YanmingW Jun andW Xinhua ldquoStudy on the change trendof precipitation and temperature in Kunming city based onMann-Kendall analysisrdquo in Future Computer CommunicationControl and Automation vol 119 of Advances in Intelligent andSoft Computing pp 505ndash513 Springer Berlin Germany 2011
[21] X L Yang L R Xu K K Liu C H Li J Hu and X H XialdquoTrend in temperature and precipitation in the ZhangweinanRiver Basin during the last 53 yearsrdquo Procedia EnvironmentalSciences vol 13 pp 1966ndash1974 1966
[22] Z F Yang Y Yan and Q Liu ldquoThe relationship of streamflow-precipitation-temperature in the Yellow River Basin of Chinaduring 1961ndash2000rdquo Procedia Environmental Sciences vol 13 pp2336ndash2345 2012
[23] Q-X Wang X-H Fan Z-D Qin and M-B Wang ldquoChangetrends of temperature and precipitation in the Loess PlateauRegion of China 1961ndash2010rdquo Global and Planetary Change vol92-93 pp 138ndash147 2012
[24] S Yue P Pilon and G Cavadias ldquoPower of the Mann-Kendalland Spearmanrsquos rho tests for detecting monotonic trends inhydrological seriesrdquo Journal of Hydrology vol 259 no 1ndash4 pp254ndash271 2002
[25] E Kahya and S Kalaycı ldquoTrend analysis of streamflow inTurkeyrdquo Journal of Hydrology vol 289 pp 128ndash144 2004
[26] Z L Li Z X Xu J Y Li and Z J Li ldquoShift trend and stepchanges for runoff time series in the Shiyang River BasinNorthwest Chinardquo Hydrological Processes vol 22 no 23 pp4639ndash4646 2008
[27] C Yaning X Changchun H Xingming et al ldquoFifty-yearclimate change and its effect on annual runoff in the TarimRiverBasin Chinardquo Quaternary International vol 208 no 1-2 pp53ndash61 2009
[28] M Shadmani SMarofi andMRoknian ldquoTrend analysis in ref-erence evapotranspiration usingMann-Kendall and SpearmanrsquosRho tests in arid regions of IranrdquoWater Resources Managementvol 26 no 1 pp 211ndash224 2012
[29] H Rehman and A Kamal ldquoIndus Basin River system-floodingand flood mitigationrdquo 2005 httparchiveriversymposiumcom2005indexphpelement=38
[30] Pakistan Meteorological Department (PMD) National PlanStrengthening National Capacities for Multi-hazard EarlyWarn-ing amp Response System 2006
[31] National Disaster Management Authority (NDMA) 2007National Disaster Risk Management Framework Governmentof Pakistan httpwwwndmagovpknew
[32] N H Hashimi Q T M Siddiqui A R Ghumman M AKamal and H R Mughal ldquoA critical analysis of 2010 floods inPakistanrdquo African Journal of Agricultural Research vol 7 no 7pp 1054ndash1067 2012
[33] FFC ldquoFederal Flood Commission of Pakistanrdquo Annual FloodReport-2010 2011 httpwwwffcgovpkdownloadfloodarc-hieveAnnualreport2010pdf
[34] N Gronewold and Climatewire ldquoIs the Flooding in Pakistan aClimate Change Disasterrdquo WMN 2010 httpwwwscientific-americancomarticleis-the-flooding-in-pakist
[35] H Hartmann and L Andresky ldquoFlooding in the Indus Riverbasinmdasha spatiotemporal analysis of precipitation recordsrdquoGlobal and Planetary Change vol 107 pp 25ndash35 2013
[36] S Salma S Rehman andM A Shah ldquoRainfall trends in differ-ent climate zones of Pakistanrdquo Pakistan Journal of Meteorologyvol 9 no 17 pp 37ndash47 2012
[37] M Hanif A H Khan and S Adnan ldquoLatitudinal precipitationcharacteristics and trends in Pakistanrdquo Journal ofHydrology vol492 pp 266ndash272 2013
[38] A Imran Q Zaman and M Afzal ldquoTemporal trends in thepeak monsoonal precipitation events over Northeast PakistanrdquoPakistan Journal of Meteorology vol 10 no 19 pp 19ndash30 2013
[39] S B Cheema and M Hanif ldquoSeasonal precipitation variationover Punjab provincerdquo Pakistan Journal of Meteorology vol 10no 19 pp 61ndash82 2013
[40] H Hartmann and H Buchanan ldquoTrends in extreme precipita-tion events in the indus River Basin and flooding in PakistanrdquoAtmosphere-Ocean vol 52 no 1 pp 77ndash91 2014
[41] ldquoProvincial Disaster Management Authority (PDMA 2012)Monsoon Contingency Plan-Khyber-Pakhtunkhwardquo 2012httpwwwndmagovpkDocumentsContingency Plan2012CP KPpdf
[42] Snowy Mountains Engineering Corporation Munda DamConstruction Project Detailed Design Report SMEC LahorePakistan 2014
[43] H Alexandersson ldquoA homogeneity test applied to precipitationdatardquo Journal of Climatology vol 6 no 6 pp 661ndash675 1986
[44] HAlexandersson andAMoberg ldquoHomogenization of Swedishtemperature data Part I homogeneity test for linear trendsrdquoInternational Journal of Climatology vol 17 no 1 pp 25ndash341997
[45] T A Buishand ldquoSome methods for testing the homogeneity ofrainfall recordsrdquo Journal of Hydrology vol 58 no 1-2 pp 11ndash271982
[46] M N Khaliq and T B M J Ouarda ldquoOn the critical values ofthe standard normal homogeneity test (SNHT)rdquo InternationalJournal of Climatology vol 27 no 5 pp 681ndash687 2007
[47] K H Hamed and A Ramachandra Rao ldquoA modified Mann-Kendall trend test for autocorrelated datardquo Journal of Hydrologyvol 204 no 1ndash4 pp 182ndash196 1998
[48] B Onoz and M Bayazit ldquoBlock bootstrap for Mann-Kendalltrend test of serially dependent datardquoHydrological Processes vol26 no 23 pp 3552ndash3560 2012
Advances in Meteorology 15
[49] M Yaseen H A Bhatti T Rientjes G Nabi and M LatifldquoTemporal and spatial variations in summer flows of upperIndus Basin Pakistanrdquo inProceedings of the 72ndAnnual Sessionof Pakistan Engineering Congress Paper no 747 pp 315ndash3342013
[50] G C Blain ldquoThe Mann-Kendall test the need to consider theinteraction between serial correlation and trendrdquo AgriculturalEngineering vol 35 no 4 2013
[51] M Yaseen T Rientjes G Nabi H ur-Rehman and M LatifldquoAssessment of recent temperature trends inManglawatershedrdquoJournal of Himalayan Earth Sciences vol 47 no 1 pp 107ndash1212014
[52] P K Sen ldquoEstimates of the regression coefficient based onKendallrsquos taurdquo Journal of the American Statistical Associationvol 63 no 324 pp 1379ndash1389 1968
[53] W S Cleveland ldquoRobust locally weighted regression andsmoothing scatterplotsrdquoThe Journal of the American StatisticalAssociation vol 74 no 368 pp 829ndash836 1979
[54] W S Cleveland ldquoGraphs in scientific publicationsrdquoThe Ameri-can Statistician vol 38 no 4 pp 261ndash269 1984
[55] D R Helsel and R M Hirsch ldquoStatistical methods in waterresourcesrdquo inTechniques ofWater Resources Investigations Book4 chapter A3 p 522 US Geological Survey 2002
[56] A P Dimri ldquoSurface and upper air fields during extreme winterprecipitation over the western Himalayasrdquo Pure and AppliedGeophysics vol 163 no 8 pp 1679ndash1698 2006
[57] A Ghaffar and M Javid ldquoImpact of global warming onmonsoon variability in Pakistanrdquo The Journal of Animal andPlant Sciences vol 21 no 1 pp 107ndash110 2011
[58] G Rasul ldquoClimate Data and Modelling Analysis of the IndusRegionrdquo Pakistan Meteorological Department (PMD) 2012httpwwfpakorgccappdfClimate Data Modelling20An-alysis20of20the20Indus20Ecoregionpdf
[59] A Basistha D S Arya and N K Goel ldquoAnalysis of historicalchanges in rainfall in the Indian Himalayasrdquo InternationalJournal of Climatology vol 29 no 4 pp 555ndash572 2009
[60] P G Baines ldquoThe late 1960s global climate shift and its influenceon the Southern Hemisphererdquo in Proceedings of 8 ICSHMO pp1477ndash1482 INPE Foz do Iguacu Brazil 2006
[61] K Duan and T Yao ldquoMonsoon variability in the Himalayasunder the condition of global warmingrdquo Journal of the Mete-orological Society of Japan vol 81 no 2 pp 251ndash257 2003
[62] U S Nair R O Lawton R M Welch and R A Pielke SrldquoImpact of land use on Costa Rican tropical montane cloudforests sensitivity of cumulus cloud field characteristics tolowland deforestationrdquo Journal of Geophysical Research D vol108 no 7 pp 4206ndash4219 2003
[63] R Avissar and D Werth ldquoGlobal hydroclimatological tele-connections resulting from tropical deforestationrdquo Journal ofHydrometeorology vol 6 no 2 pp 134ndash145 2005
[64] R A Pielke Sr J Adegoke A Beltran-Przekurat et al ldquoAnoverview of regional land-use and land-cover impacts onrainfallrdquo Tellus B Chemical and Physical Meteorology vol 59no 3 pp 587ndash601 2007
[65] N Ramankutty C Delire and P Snyder ldquoFeedbacks betweenagriculture and climate an illustration of the potential unin-tended consequences of human land use activitiesrdquo Global andPlanetary Change vol 54 no 1-2 pp 79ndash93 2006
[66] V Ramanathan C Chung D Kim et al ldquoAtmospheric brownclouds impacts on South Asian climate and hydrological cyclerdquoProceedings of the National Academy of Sciences of the UnitedStates of America vol 102 no 15 pp 5326ndash5333 2005
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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International Journal of
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GeochemistryHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Geological ResearchJournal of
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Geology Advances in
4 Advances in Meteorology
Table 1 Results of homogeneity tests for mean annual precipitationtime series at study stations
Station SNHT Buishandrsquos range (BR) test1198790
119876radic119899 119877radic119899
Thalozom 916 108 108Drosh 906 117 147Kalam 887 087 108Dir 776 124 149Madyan 485 111 150Khairabad 192 062 093ToorCamp 620 117 154Saidu Sharif 742 118 190Malakand 257 077 086Kulangi 428 097 146Ambahar 508 109 139Abazai 686 121 140Mardan 893 108 124Charsadda 902 125 138Risalpur 724 091 125For homogenous series 119879
0lt 917119876radic119899 lt 127 and 119877radic119899 lt 155
If 1199031falls between the upper and lower limits of confidence
interval (the data are considered serially correlated) themethods of prewhitening variance correlation [47] andtrend-free prewhitening (TFPW) approach [24] have beenproposed In this study for the stations where serial cor-relations were detected in the data the TFPW approachwas applied to remove the correlation for both tests (Mann-Kendall and Spearmanrsquos rho) Other researchers [28 48ndash51]have also used this approach to eliminate serial correlation intime series data
232 The Mann-Kendall Test The rank-based nonparamet-ric Mann-Kendall [15 16] method was applied to the long-term data in this study to detect statistically significanttrends In this test the null hypothesis (H
0) was that there
has been no trend in precipitation over time the alternatehypothesis (H
1) was that there has been a trend (increasing
or decreasing) over time The mathematical equations forcalculatingMann-Kendall Statistics 119878119881(119878) and standardizedtest statistics 119885 are as follows
119878 =
119899minus1
sum
119894=1
119899
sum
119895=119894+1
sig (119883119895minus 119883119894)
sgn (119883119895minus 119883119894) =
+1 if (119883119895minus 119883119894) gt 0
0 if (119883119895minus 119883119894) = 0
minus1 if (119883119895minus 119883119894) lt 0
119881 (119878) =
1
18
[119899 (119899 minus 1) (2119899 + 5) minus
119902
sum
119901=1
119905119901(119905119901minus 1) (2119905
119901+ 5)]
119885 =
119878 minus 1
radicVAR (119878)if 119878 gt 0
0 if 119878 = 0
119878 + 1
radicVAR (119878)if 119878 lt 0
(3)
In these equations119883119894and119883
119895are the time series observations
in chronological order 119899 is the length of time series 119905119901is
the number of ties for 119901th value and 119902 is the number oftied values Positive 119885 values indicate an upward trend in thehydrologic time series negative 119885 values indicate a negativetrend If |119885| gt 119885
1minus1205722 (H0) is rejected and a statistically
significant trend exists in the hydrologic time series Thecritical value of119885
1minus1205722for a 119901 value of 005 from the standard
normal table is 196
233 Spearmanrsquos rho Test Spearmanrsquos rho [17 18] test isanother rank-based nonparametric method used for trendanalysis and was applied as a comparison with the Mann-Kendall test In this test which assumes that time seriesdata are independent and identically distributed the nullhypothesis (H
0) again indicates no trend over time the
alternate hypothesis (H1) is that a trend exists and that data
increase or decrease with 119894 [24] The test statistics 119877sp andstandardized statistics 119885sp are defined as
119877sp = 1 minus
6sum119899
119894=1
(119863119894minus 119894)2
119899 (1198992
minus 1)
119885sp = 119877spradic119899 minus 2
1 minus 1198772
sp
(4)
In these equations 119863119894is the rank of 119894th observation 119868 is the
chronological order number 119899 is the total length of the timeseries data and 119885sp is Studentrsquos 119905-distribution with (119899 minus 2)degree of freedom The positive values of 119885sp represent anincreasing trend across the hydrologic time series negativevalues represent the decreasing trends The critical value of119905 at a 005 significance level of Studentrsquos 119905-distribution tableis defined as 119905
(119899minus21minus1205722)[12] If |119885sp| gt 119905
(119899minus21minus1205722) (H0) is
rejected and a significant trend exists in the hydrologic timeseries
234 Senrsquos Slope Estimator Senrsquos nonparametric method [52]was used to estimate the magnitude of trends in the timeseries data
119879119894=
119909119895minus 119909119896
119895 minus 119896
(5)
In this equation 119909119895and 119909
119896represent data values at time 119895 and
119896 respectively Consider
119876119894=
119879(119873+1)2
119873 is odd1
2
(1198791198732
+ 119879(119873+2)2
) 119873 is even(6)
A positive119876119894value represents an increasing trend a negative
119876119894value represents a decreasing trend over time
Advances in Meteorology 5
Table 2 Summary of geographic conditions and mean annual precipitation statistics for study stations
Station Longitude Latitude Elevation (m) Mean (mm) STD 119862119904
119862119896
119862V
Thalozom 72∘-151015840 35∘-441015840 4200 7511 2099 minus0266 0082 0291Drosh 72∘-001015840 35∘-331015840 1465 4635 1537 1167 2441 0332Kalam 72∘-331015840 35∘-311015840 2000 9345 3170 minus0599 0323 0353Dir 71∘-531015840 35∘-121015840 1321 5482 1521 minus0545 0919 0285Madyan 72∘-321015840 35∘-091015840 1320 9623 2878 0240 1300 0307Khairabad 72∘-061015840 34∘-581015840 894 7037 1522 1410 4281 0216ToorCamp 71∘-421015840 34∘-501015840 854 5440 1592 minus0436 0841 0299Saidu Sharif 72∘-251015840 34∘-451015840 961 9901 3898 1842 6463 0398Malakand 71∘-461015840 34∘-381015840 603 6098 2526 2474 11668 0424Kulangi 71∘-591015840 34∘-351015840 688 6254 1925 0037 minus0170 0308Ambahar 71∘-121015840 34∘-331015840 694 4550 1485 minus0004 0764 0333Abazai 71∘-331015840 34∘-261015840 320 5007 1527 minus0093 0963 0312Mardan 71∘-581015840 34∘-181015840 283 6574 2974 0735 1392 0452Charsadda 71∘-431015840 34∘-071015840 276 5916 2074 0973 1031 0350Risalpur 71∘-541015840 34∘-061015840 309 6118 1768 0312 minus0098 0289
3 Results and Discussion
31 Preliminary Analysis The preliminary analysis for thisstudy included computing the mean standard deviationcoefficient of skewness coefficient of kurtosis and coefficientof variation in the annual precipitation time series foreach station Table 2 presents these statistical parametersfor the 51-year time period studied (1961ndash2011) The meanannual precipitation varied between 455mm in the southwestpart of the Swat River basin catchment area (Ambahar)and 9901mm in the southeast part (Saidu Sharif) As thetable shows the coefficient of skewness varied from minus0266to 2474 kurtosis varied between minus0170 and 11668 Fortime series data to be considered normally distributed thecoefficient of skewness and kurtosis must be equal to 0and 3 respectively Table 2 indicates therefore that the dataare positively skewed and not normally distributed Thecoefficient of variation the measure of dispersion around themean was also calculated to analyze the spatial variability ofannual precipitation for each station This coefficient variedbetween 216 (Khairabad) and 452 (Mardan)The averagevariation of the precipitation over the complete river basinwas 289
32 Long-Term Pattern on Seasonal and Annual Scale Long-term climatic patterns were assessed using standardizedseasonal and annual precipitation time series data Toreduce local fluctuations LOWESS [53ndash55] curves were fittedover time based on seasonal and annual precipitation timeseries data The LOWESS curve for winter precipitation(Figure 2(a)) showed a decreasing trend in the first decadeIn the second decade the trend was constant The minimumLOWESS curve value was observed in 1990 values thengradually rose through 2010 Overall the curve based onwinter season data suggested a decline in precipitation After1990 there was a gradual rise though small local fluctuationswere ignored The LOWESS curve for spring precipitation(Figure 2(b)) showed a gradual increase in the first three
decades After attaining its highest value in 1990 the valuedeclined over the last two decades
The LOWESS curve for summer precipitation showeda constant trend in the first decade and then started todecline up to 1978 (Figure 2(c)) For 1978ndash1992 the curvestarted to gradually increase through the remaining yearsThe LOWESS curve for autumn precipitation exhibited adecreasing trend through 1982 for the remaining time peri-ods there was an increase in precipitation For the annualprecipitation time series the LOWESS curve showed slightvariations in every decade but the overall trend was nearlyconstant throughout the time series Figure 2 shows theprecipitation patterns LOWESS curves are used to showpatterns and do not explain statistically significant trends inthe time series
33 Monthly Analysis The Mann-Kendall (MK) and Spear-manrsquos (SR) rho tests were applied on a monthly scale todetect trends in the precipitation series at different stationsTable 3 shows the results and illustrates that the results ofboth tests were similar to one another Monthly trend testsshowed a mix of positive and negative trends at differentstations At Thalozom statistically significant negative andpositive trends were found in April and June respectivelySignificant positive trends were detected at Dir and Droshstations in March and August no significant trends werefound for other months The Saidu Sharif station exhibitedsignificant positive trends from January to June and fromOctober to December but had negative trends in July andAugust Significant positive trends were found at most of thestations in the months of May and June significant negativetrends were seen in July and August In other stations a mixof significantly positive and negative trends occurred for afew months of the year Figure 3 shows the spatial variationin the precipitation time series for each month in the SwatRiver basin from 1961 to 2011
The magnitude of statistically significant trends on amonthly scale was determined using Senrsquos slope estimator
6 Advances in Meteorology
0
1
2
3
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
Original dataLOWESS line
minus3
minus2
minus1
(a)
Original dataLOWESS line
0
1
2
3
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
minus2
minus1
(b)
Original dataLOWESS line
0
1
2
3
4
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
minus2
minus1
(c)
Original dataLOWESS line
0
1
2
3
4
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
minus2
minus1
(d)
Original dataLOWESS line
0
1
2
3
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
minus3
minus2
minus1
(e)
Figure 2 Standardized precipitation and LOWESS trend curves at Swat River basin (a) winter (b) spring (c) summer (d) autumn and (e)annual
Advances in Meteorology 7
Table3MKandSR
tests
results
forp
recipitatio
nin
mon
thlytim
eseries
Station
Test
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Thalozom
MK
minus063
minus10
9minus042
minus219lowast
minus033
272lowast
minus080
minus094
minus029
010
146
030
SRminus044
minus10
1minus039
minus215lowast
minus040
293lowast
minus079
minus10
3minus013
028
141
013
Drosh
MK
minus008
minus024
016
minus067
063
151
minus19
4minus316lowast
minus063
040
103
001
SRminus014
minus001
008
minus079
067
173
minus18
7minus336lowast
minus050
039
101
017
Kalam
MK
minus037
minus067
033
minus221lowast
minus063
219lowast
minus115
minus10
4minus054
014
120
017
SRminus023
minus052
023
minus213lowast
minus064
229lowast
minus113
minus10
7minus043
014
091
minus066
Dir
MK
000
minus063
minus248lowast
minus021
minus079
112
minus015
003
174
minus13
1minus034
minus089
SRminus016
minus062
minus280lowast
minus018
minus10
010
7minus001
minus002
203lowast
minus16
3minus049
minus10
1
Madyan
MK
089
075
110
minus083
086
353lowast
minus312lowast
minus338lowast
minus023
190
272lowast
134
SR086
070
113
minus067
085
426lowast
minus324lowast
minus398lowast
minus016
200
301lowast
132
Khaira
bad
MK
091
minus068
minus021
minus080
201lowast
385lowast
minus312lowast
minus348lowast
minus019
268lowast
292lowast
112
SR082
minus072
minus028
minus079
204lowast
446lowast
minus334lowast
minus460lowast
minus017
308lowast
325lowast
097
ToorCa
mp
MK
192
093
045
minus070
minus044
minus086
minus291lowast
minus296lowast
minus227lowast
minus201lowast
094
028
SR17
8085
025
minus082
minus047
minus091
minus317lowast
minus361lowast
minus279lowast
minus233lowast
104
020
SaiduSh
arif
MK
274lowast
246lowast
222lowast
182
285lowast
327lowast
minus334lowast
minus309lowast
003
319lowast
357lowast
210lowast
SR302lowast
262lowast
261lowast
205lowast
324lowast
383lowast
minus360lowast
minus387lowast
020
364lowast
405lowast
217lowast
Malakand
MK
105
minus17
2minus115
010
228lowast
322lowast
minus318lowast
minus293lowast
016
350lowast
273lowast
149
SR099
minus202lowast
minus13
2022
254lowast
302lowast
minus380lowast
minus382lowast
023
397lowast
223lowast
091
Kulang
iMK
070
minus099
minus294lowast
minus14
4minus062
036
000
174
291lowast
minus16
4minus003
minus204lowast
SR059
minus10
4minus315lowast
minus14
1minus081
024
008
165
336lowast
minus18
5minus031
minus231lowast
Ambahar
MK
031
minus066
minus284lowast
minus10
5minus115
060
018
060
304lowast
minus13
6minus021
minus18
0SR
038
minus070
minus282lowast
minus111
minus118
058
019
034
356lowast
minus15
1minus029
minus201lowast
Abazai
MK
233lowast
minus025
minus091
137
292lowast
449lowast
minus262lowast
minus10
710
2331lowast
392lowast
261lowast
SR222lowast
minus029
minus090
162
289lowast
435lowast
minus307lowast
minus10
913
7385lowast
366lowast
272lowast
Mardan
MK
243lowast
134
041
001
105
070
014
minus016
100
minus058
minus13
1minus13
7SR
253lowast
134
050
011
110
072
025
minus020
088
minus051
minus115
minus115
Charsadd
aMK
232lowast
109
032
minus012
015
034
014
minus014
056
minus10
4minus217lowast
minus15
9SR
237lowast
109
026
minus024
032
044
022
minus033
043
minus097
minus204lowast
minus13
1
Risalpur
MK
191
128
006
minus027
minus033
minus037
minus006
minus063
minus026
minus14
6minus18
7minus217lowast
SR213lowast
113
006
minus036
minus017
minus025
minus005
minus072
minus026
minus15
0minus211lowast
minus216lowast
lowast
Sign
ificant
trend
at5
significance
leveloftwo-tailedtest
8 Advances in Meteorology
Jan Feb Mar Apr
May Jun Jul Aug
Sep Oct Nov Dec
N
0 5 10 25
Scale
(km)
Significant increasing trendSignificant decreasing trend
No trend
Figure 3 Location of sites with increasing decreasing and no trends at 5 significance level for the monthly precipitation time series
The results show that trends at Saidu Sharif Madyanand Kalam were more rapid (eg sharper increases anddecreases) compared to other stations The Saidu Sharifstation had the maximum negative decline in monthly pre-cipitation (183mmmonth) as well as the maximum positiveincrease (143mmmonth) during the months of July andMarch respectively Figure 4 shows the trends in maximummonthly precipitation variation at the Saidu Sharif station
34 Seasonal and Annual Analysis The MK and SR testswere also used to identify trends in seasonal and annualprecipitation between 1961 and 2011 Table 4 shows the resultsSimilar to the monthly analysis results from both statisticaltests MK and SR were consistent with one another A mixof negative and positive trends was seen at different stationsThalozom Kalam and Dir stations which had shown trends
with the monthly time scale did not exhibit statisticallysignificant trends for the seasonal and annual precipitationtime series At Madyan Khairabad and Malakand stationsthere were significant negative trends in the summer andpositive trends in the autumn Significant negative trendswere observed in the spring season only at ToorCampKulangi and Ambahar stations For the annual precipitationseries significant positive trends were detected only at SaiduSharif Mardan and Charsadda stations At other stationssignificant positive trends were seen for winter and autumnseasons and for the annual precipitation series howevernegative trends were detected in spring and summer seasonsFigure 5 presents the spatial distribution of seasonal andannual precipitation trends
The Saidu Sharif station showed the maximum positivetrend in annual precipitation series (748mmyear) across
Advances in Meteorology 9
0
100
200
300
400
500
600
700
800
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
mon
th)
Year
Saidu Sharif station(March)
(a)
0
100
200
300
400
500
600
700
800
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
mon
th)
Year
Saidu Sharif station(July)
(b)
Figure 4 Variations of monthly precipitation time series in stations with most significant trends during 1961ndash2011
Table 4 MK and SR tests results for precipitation in seasonal and annual time series
Station Test Winter Spring Summer Autumn Annual
Thalozom MK minus120 minus162 minus120 148 minus149SR minus114 minus152 minus110 135 minus145
Drosh MK 042 minus078 minus196 097 minus044SR 049 minus074 minus209lowast 127 minus048
Kalam MK minus062 minus139 minus171 160 minus110SR minus037 minus121 minus158 157 minus087
Dir MK minus028 minus148 minus047 minus076 minus138SR minus062 minus150 minus058 minus097 minus146
Madyan MK 120 003 minus258lowast 365lowast 042SR 137 033 minus244lowast 421lowast 078
Khairabad MK 026 minus065 minus302lowast 325lowast minus073SR 021 minus076 minus353lowast 364lowast minus072
ToorCamp MK minus063 minus203lowast 024 minus073 minus044SR minus096 minus217lowast 023 minus092 minus159
Saidu Sharif MK 346lowast 239lowast minus156 069 328lowast
SR 404lowast 280lowast minus156 148 278lowast
Malakand MK minus070 minus110 minus270lowast 337lowast minus119SR minus068 minus115 minus319lowast 373lowast minus140
Kulangi MK minus122 minus261lowast 031 minus099 minus144SR minus156 minus284lowast 037 minus127 minus172
Ambahar MK minus066 minus206lowast minus063 minus099 minus157SR minus076 minus224lowast minus058 minus110 minus141
Abazai MK 179 minus015 minus099 429lowast 096SR 217lowast 007 minus072 604lowast 122
Mardan MK 281lowast 145 095 minus102 259lowast
SR 310lowast 134 098 minus085 280lowast
Charsadda MK 266lowast 097 073 minus194 214lowast
SR 293lowast 088 060 minus176 217lowast
Risalpur MK 243lowast 044 minus006 minus154 198SR 254lowast 040 minus005 minus190 195
lowastSignificant trend at 5 significance level of two-tailed test
10 Advances in Meteorology
N
0 5 10 25
Scale
(km)
Significant increasing trendSignificant decreasing trend
No trend
Winter
Autumn Annual
Spring Summer
Figure 5 Location of sites with increasing decreasing and no trends at 5 significance level for the seasonal and annual precipitation timeseries
study stations from 1961 to 2011 theThalozom station showeda negative trend with a decreasing rate of 370mmyearFigure 6 displays the results of the magnitude of variationin the annual precipitation for the Saidu Sharif MardanCharsadda andThalozom stations
35 Trend Analysis over Entire River Basin The effect ofclimate change on precipitation was also analyzed for theentire Swat River basin by applying the MK and SR testson monthly seasonal and annual scale As Figure 1 showedthe entire Swat River catchment (A) is divided into foursubbasins upper subbasin (A1) Panjkora subbasin (A2)Ambahar subbasin (A3) and Lower subbasin (A4) Table 5presents trends in monthly precipitation across the subbasinsand for the full basin The table shows significant positivetrends in the months of June and November for the uppersubbasin (A1) and the entire Swat River basin (A) negativetrends were seen in these locations in July and August Inthe Panjkora subbasin (A2) statistically significant positivetrends were identified over time in June a negative trendwas seen from July to September The maximum number ofsignificant cases (8) was observed in data from the Ambaharsubbasin (A3)The Lower subbasin (A4) showed a significantpositive trend only during January no significant trendsin other months were identified As a simpler summarysignificant negative trends in precipitation over time were
seen from July to September positive trends over time wereseen in January May June and October to December indifferent Swat River subbasins
To detect precipitation trends in each subbasin and entireSwat River basin the MK and SR tests were again appliedto seasonal and annual precipitation data for the 51-yearstudy period (1961ndash2011) As Table 6 shows both testmethodsshowed similar results The upper subbasin (A1) experiencedstatistically significant negative trends in the summer andpositive trends in the autumn The Panjkora subbasin (A2)and Lower subbasin (A4) showed significant negative trendsin the summer and positive trends in the winter Significantpositive trends were found across the subbasins in winterand autumn seasons however there was a negative trendin summer at Ambahar subbasin (A3) and across the entireSwat River basin (A) For the annual and spring precipitationtime series there were no statistically significant trendsSignificant positive trendswere seen inwinter and autumn insummer negative trends were seen across different subbasinsand the full Swat River basin
The Lower subbasin exhibited the maximum positivetrend over time (218mmyear) in the weighted annualprecipitation time series the Panjkora subbasin showed anegative trend with a decreasing rate of participation at090mmyear The entire Swat River basin showed a positivetrend in precipitation (048mmyear) as shown in Table 6
Advances in Meteorology 11
Table5MKandSR
tests
results
form
onthlyprecipitatio
ntim
eseriesinentireb
asin
andsubb
asinso
fSwatRiver
Subb
asin
Test
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
A1
MK
047
010
071
minus12
3041
349lowast
minus288lowast
minus318lowast
minus018
143
250lowast
094
SR045
006
074
minus098
047
409lowast
minus299lowast
minus363lowast
minus018
159
277lowast
094
A2
MK
107
080
016
minus093
021
201lowast
minus354lowast
minus416lowast
minus202lowast
000
187
062
SR095
072
001
minus099
013
231lowast
minus386lowast
minus486lowast
minus224lowast
011
200
063
A3
MK
250lowast
102
minus036
065
297lowast
390lowast
minus297lowast
minus255lowast
minus044
305lowast
295lowast
229lowast
SR267lowast
089
minus009
070
311lowast
479lowast
minus354lowast
minus322lowast
minus052
376lowast
365lowast
260lowast
A4
MK
237lowast
088
minus006
minus050
122
164
minus063
minus083
000
020
050
minus040
SR246lowast
084
minus001
minus059
117
182
minus059
minus090
001
045
023
minus046
AMK
185
110
013
minus062
123
369lowast
minus255lowast
minus361lowast
minus065
174
268lowast
070
SR17
010
4018
minus079
127
422lowast
minus277lowast
minus401lowast
minus070
181
299lowast
073
lowast
Sign
ificant
trend
at5
significance
leveloftwo-tailedtest
12 Advances in Meteorology
0
500
1000
1500
2000
2500
3000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Saidu Sharif station
(a)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Mardan station
(b)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Charsadda station
(c)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Thalozom station
(d)
Figure 6 Variations of annual precipitation time series in stations with significant trends during 1961ndash2011
36 Comparison of Results Results from both statistical testsMK and SR were consistent with each otherThe percentagesof statistically significant cases to total tested cases for theMK and SR tests were 32 and 30 respectively showingagreement across methods This consistency in statisticalperformance was also found in other studies [24 28]
4 Discussion
This study investigated variability in monthly seasonal andannual precipitation at 15 stations in the Swat River basinover a 51-year study period (1961ndash2011) Precipitation trendswere also analyzed for each subbasin and entire Swat Riverbasin The mean annual precipitation at different stationsshowed considerable variation with a standard deviationof 1768mm from the mean annual rainfall of 694mmThe Saidu Sharif Mardan and Charsadda stations showedsignificant positive trends (increased precipitation over time)at 5 significance level in the annual precipitation series
The maximum number of significant changes in monthlyprecipitation over time was detected at Saidu Sharif Abazaiand Khairabad stations Saidu Sharif station showed themaximum increasing slope (indicating sharpest change overtime) of 748mmyear among the selected stations in the SwatRiver basin
These study results follow the same statistical trendsreported by Hartmann and Andresky [35] for northwestparts of Pakistan Findings were consistent with results fromDimri [56] Ghaffar and Javid [57] and Rasul [58] whereinthey found statistically significant increasing trends in winterprecipitation for northwest areas of Pakistan The resultsof this analysis also support finding of Hanif et al [37]wherein they found significant variations in summer seasonprecipitation These variations in precipitation trends maylead Pakistan towards more water related disasters suchas droughts and floods in the near future Basistha et al[59] proposed possible causes of the changing precipitationtrends such as global climate shifts [60] dwindling global
Advances in Meteorology 13
Table 6 MK and SR results for seasonal and annual precipitation time series in entire basin and subbasin of Swat River
Subbasin Change (mmyear) Test Winter Spring Summer Autumn Annual
A1 minus073 MK 055 minus024 minus242lowast 305lowast minus034SR 057 001 minus227lowast 347lowast 118
A2 minus090 MK 128 minus023 minus385lowast 158 minus081SR 118 minus035 minus444lowast 164 minus090
A3 030 MK 266lowast 016 minus265lowast 375lowast 024SR 295lowast 027 minus309lowast 460lowast 040
A4 218 MK 242lowast 060 minus021 024 166SR 272lowast 054 minus037 043 173
A 048 MK 214lowast minus011 minus297lowast 307lowast 042SR 225lowast minus014 minus340lowast 336lowast 038
lowastSignificant trend at 5 significance level of two-tailed test
monsoon circulation [61] decline in forest cover [62 63] landuse changes and practices (eg irrigated agriculture) [64 65]and increasing aerosols from anthropogenic activities [66]
5 Conclusions
This paper analyzed trends in monthly seasonal and annualprecipitation in the Swat River basin over the 51-year studyperiod (1961ndash2011) A mix of positive and negative trendswas observed at various stations and subbasins The monthsof June November July and August showed the maximumnumber of significant cases at various stations in monthlyprecipitation The trends were positive in May and June andwere negative in July and August This indicates a shift inprecipitation series on monthly scale Significant positivetrends were detected in winter and autumn and annuallynegative trends were seen in spring and summer seasonsSaidu Sharif Mardan and Charsadda stations exhibitedsignificant positive trends in annual precipitation at a 95confidence level the remaining stations did not experiencea statistically significant trend
For the entire Swat River basin no significant trendswere detected in any subbasin for the annual precipitationseries Seasonally winter and autumn experienced significantpositive trends and summer experienced negative trends indifferent subbasins in the Swat River basin Most statisticallysignificant trend cases under different scenarios were positive(61)The results obtainedwith theMann-Kendall (MK) andSpearmanrsquos rho tests showed agreement in their assessmentsof monthly seasonal and annual precipitation trends Thevariability of negative and positive trends at various stationspoints to the need for more detailed studies on the climatechange of this region
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgments
The authors thank Pakistan Meteorological Department(PMD) Water and Power Development Authority
(WAPDA) Pakistan and Snowy Mountains EngineeringCorporation (SMEC) for providing cost-free data for thisstudy
References
[1] M D Rahman and M Begum ldquoApplication of non parametrictest for trend detection of rainfall in the largest Island ofBangladeshrdquo ARPN Journal of Earth Sciences vol 2 no 2 pp40ndash44 2013
[2] IPCCThePhysical Science Basis Contribution ofWorkingGroupI to the Fourth Assessment Report of the Intergovernmental Panelon Climate Change Cambridge University Press CambridgeUK 2007
[3] A B Farooq and A H Khan ldquoClimate change perspectivein Pakistanrdquo in Proceedings of the Capacity Building APNWorkshop on Global Change Research pp 39ndash46 IslamabadPakistan 2004
[4] Z Z Hu S Yang and R Wu ldquoLong-term climate variationsin China and global warming signalsrdquo Journal of GeophysicalResearch vol 108 no D19 2003
[5] P Zhai and X Pan ldquoTrends in temperature extremes during1951ndash1999 in Chinardquo Geophysical Research Letters vol 30 no17 p 1913 2003
[6] D Duhan and A Pandey ldquoStatistical analysis of long termspatial and temporal trends of precipitation during 1901ndash2002at Madhya Pradesh Indiardquo Atmospheric Research vol 122 pp136ndash149 2013
[7] B J Peterson RM Holmes JWMcClelland et al ldquoIncreasingriver discharge to the Arctic oceanrdquo Science vol 298 no 5601pp 2171ndash2173 2002
[8] N I Savelieva I P Semiletov L N Vasilevskaya and S PPugach ldquoA climate shift in seasonal values of meteorologicaland hydrological parameters for Northeastern Asiardquo Progress inOceanography vol 47 no 2ndash4 pp 279ndash297 2000
[9] Y F Shi Y P Shen and R J Hu ldquoPreliminary study on signalimpact and foreground of climatic shift from warm-dry towarm-humid in Northwest Chinardquo Journal of Glaciology andGeocryology vol 24 pp 219ndash226 2002 (Chinese)
[10] S Farhana and M M Rahman ldquoCharacterizing rainfall trendin Bangladesh by temporal statistics analysisrdquo in Proceedings ofthe 4th Annual Paper Meet and 1st Civil Engineering CongressDhaka Bangladesh 2011
[11] R H Rimi S H Rahman S Karmakar and S G HussainldquoTrend analysis of climate change and investigation on its
14 Advances in Meteorology
probable impacts on rice production at Satkhira BangladeshrdquoPakistan Journal of Meteorology vol 6 no 11 pp 37ndash50 2014
[12] E R Dahmen and M J Hall Screening of Hydrological DataTests for Stationarity and Relative Consistency Publication 49ILRI Wageningen The Netherlands 1990
[13] Q Zhang C Liu C-Y Xu Y Xu and T Jiang ldquoObserved trendsof annual maximumwater level and streamflow during past 130years in the Yangtze River basin Chinardquo Journal of Hydrologyvol 324 no 1-4 pp 255ndash265 2006
[14] H Chen S Guo C-Y Xu and V P Singh ldquoHistorical tem-poral trends of hydro-climatic variables and runoff responseto climate variability and their relevance in water resourcemanagement in the Hanjiang basinrdquo Journal of Hydrology vol344 no 3-4 pp 171ndash184 2007
[15] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 pp 245ndash259 1945
[16] M G Kendall Rank CorrelationMethods Griffin London UK1975
[17] E L Lehmann Nonparametrics Statistical Methods Based onRanks Holden-Day San Francisco Calif USA 1975
[18] R Sneyers ldquoOn the statistical analysis of series of observationsrdquoTechnical Note 143 WMO no 415 World MeteorologicalOrganization 1990
[19] A Longobardi and P Villani ldquoTrend analysis of annual andseasonal rainfall time series in the Mediterranean areardquo Inter-national Journal of Climatology vol 30 no 10 pp 1538ndash15462010
[20] Z YanmingW Jun andW Xinhua ldquoStudy on the change trendof precipitation and temperature in Kunming city based onMann-Kendall analysisrdquo in Future Computer CommunicationControl and Automation vol 119 of Advances in Intelligent andSoft Computing pp 505ndash513 Springer Berlin Germany 2011
[21] X L Yang L R Xu K K Liu C H Li J Hu and X H XialdquoTrend in temperature and precipitation in the ZhangweinanRiver Basin during the last 53 yearsrdquo Procedia EnvironmentalSciences vol 13 pp 1966ndash1974 1966
[22] Z F Yang Y Yan and Q Liu ldquoThe relationship of streamflow-precipitation-temperature in the Yellow River Basin of Chinaduring 1961ndash2000rdquo Procedia Environmental Sciences vol 13 pp2336ndash2345 2012
[23] Q-X Wang X-H Fan Z-D Qin and M-B Wang ldquoChangetrends of temperature and precipitation in the Loess PlateauRegion of China 1961ndash2010rdquo Global and Planetary Change vol92-93 pp 138ndash147 2012
[24] S Yue P Pilon and G Cavadias ldquoPower of the Mann-Kendalland Spearmanrsquos rho tests for detecting monotonic trends inhydrological seriesrdquo Journal of Hydrology vol 259 no 1ndash4 pp254ndash271 2002
[25] E Kahya and S Kalaycı ldquoTrend analysis of streamflow inTurkeyrdquo Journal of Hydrology vol 289 pp 128ndash144 2004
[26] Z L Li Z X Xu J Y Li and Z J Li ldquoShift trend and stepchanges for runoff time series in the Shiyang River BasinNorthwest Chinardquo Hydrological Processes vol 22 no 23 pp4639ndash4646 2008
[27] C Yaning X Changchun H Xingming et al ldquoFifty-yearclimate change and its effect on annual runoff in the TarimRiverBasin Chinardquo Quaternary International vol 208 no 1-2 pp53ndash61 2009
[28] M Shadmani SMarofi andMRoknian ldquoTrend analysis in ref-erence evapotranspiration usingMann-Kendall and SpearmanrsquosRho tests in arid regions of IranrdquoWater Resources Managementvol 26 no 1 pp 211ndash224 2012
[29] H Rehman and A Kamal ldquoIndus Basin River system-floodingand flood mitigationrdquo 2005 httparchiveriversymposiumcom2005indexphpelement=38
[30] Pakistan Meteorological Department (PMD) National PlanStrengthening National Capacities for Multi-hazard EarlyWarn-ing amp Response System 2006
[31] National Disaster Management Authority (NDMA) 2007National Disaster Risk Management Framework Governmentof Pakistan httpwwwndmagovpknew
[32] N H Hashimi Q T M Siddiqui A R Ghumman M AKamal and H R Mughal ldquoA critical analysis of 2010 floods inPakistanrdquo African Journal of Agricultural Research vol 7 no 7pp 1054ndash1067 2012
[33] FFC ldquoFederal Flood Commission of Pakistanrdquo Annual FloodReport-2010 2011 httpwwwffcgovpkdownloadfloodarc-hieveAnnualreport2010pdf
[34] N Gronewold and Climatewire ldquoIs the Flooding in Pakistan aClimate Change Disasterrdquo WMN 2010 httpwwwscientific-americancomarticleis-the-flooding-in-pakist
[35] H Hartmann and L Andresky ldquoFlooding in the Indus Riverbasinmdasha spatiotemporal analysis of precipitation recordsrdquoGlobal and Planetary Change vol 107 pp 25ndash35 2013
[36] S Salma S Rehman andM A Shah ldquoRainfall trends in differ-ent climate zones of Pakistanrdquo Pakistan Journal of Meteorologyvol 9 no 17 pp 37ndash47 2012
[37] M Hanif A H Khan and S Adnan ldquoLatitudinal precipitationcharacteristics and trends in Pakistanrdquo Journal ofHydrology vol492 pp 266ndash272 2013
[38] A Imran Q Zaman and M Afzal ldquoTemporal trends in thepeak monsoonal precipitation events over Northeast PakistanrdquoPakistan Journal of Meteorology vol 10 no 19 pp 19ndash30 2013
[39] S B Cheema and M Hanif ldquoSeasonal precipitation variationover Punjab provincerdquo Pakistan Journal of Meteorology vol 10no 19 pp 61ndash82 2013
[40] H Hartmann and H Buchanan ldquoTrends in extreme precipita-tion events in the indus River Basin and flooding in PakistanrdquoAtmosphere-Ocean vol 52 no 1 pp 77ndash91 2014
[41] ldquoProvincial Disaster Management Authority (PDMA 2012)Monsoon Contingency Plan-Khyber-Pakhtunkhwardquo 2012httpwwwndmagovpkDocumentsContingency Plan2012CP KPpdf
[42] Snowy Mountains Engineering Corporation Munda DamConstruction Project Detailed Design Report SMEC LahorePakistan 2014
[43] H Alexandersson ldquoA homogeneity test applied to precipitationdatardquo Journal of Climatology vol 6 no 6 pp 661ndash675 1986
[44] HAlexandersson andAMoberg ldquoHomogenization of Swedishtemperature data Part I homogeneity test for linear trendsrdquoInternational Journal of Climatology vol 17 no 1 pp 25ndash341997
[45] T A Buishand ldquoSome methods for testing the homogeneity ofrainfall recordsrdquo Journal of Hydrology vol 58 no 1-2 pp 11ndash271982
[46] M N Khaliq and T B M J Ouarda ldquoOn the critical values ofthe standard normal homogeneity test (SNHT)rdquo InternationalJournal of Climatology vol 27 no 5 pp 681ndash687 2007
[47] K H Hamed and A Ramachandra Rao ldquoA modified Mann-Kendall trend test for autocorrelated datardquo Journal of Hydrologyvol 204 no 1ndash4 pp 182ndash196 1998
[48] B Onoz and M Bayazit ldquoBlock bootstrap for Mann-Kendalltrend test of serially dependent datardquoHydrological Processes vol26 no 23 pp 3552ndash3560 2012
Advances in Meteorology 15
[49] M Yaseen H A Bhatti T Rientjes G Nabi and M LatifldquoTemporal and spatial variations in summer flows of upperIndus Basin Pakistanrdquo inProceedings of the 72ndAnnual Sessionof Pakistan Engineering Congress Paper no 747 pp 315ndash3342013
[50] G C Blain ldquoThe Mann-Kendall test the need to consider theinteraction between serial correlation and trendrdquo AgriculturalEngineering vol 35 no 4 2013
[51] M Yaseen T Rientjes G Nabi H ur-Rehman and M LatifldquoAssessment of recent temperature trends inManglawatershedrdquoJournal of Himalayan Earth Sciences vol 47 no 1 pp 107ndash1212014
[52] P K Sen ldquoEstimates of the regression coefficient based onKendallrsquos taurdquo Journal of the American Statistical Associationvol 63 no 324 pp 1379ndash1389 1968
[53] W S Cleveland ldquoRobust locally weighted regression andsmoothing scatterplotsrdquoThe Journal of the American StatisticalAssociation vol 74 no 368 pp 829ndash836 1979
[54] W S Cleveland ldquoGraphs in scientific publicationsrdquoThe Ameri-can Statistician vol 38 no 4 pp 261ndash269 1984
[55] D R Helsel and R M Hirsch ldquoStatistical methods in waterresourcesrdquo inTechniques ofWater Resources Investigations Book4 chapter A3 p 522 US Geological Survey 2002
[56] A P Dimri ldquoSurface and upper air fields during extreme winterprecipitation over the western Himalayasrdquo Pure and AppliedGeophysics vol 163 no 8 pp 1679ndash1698 2006
[57] A Ghaffar and M Javid ldquoImpact of global warming onmonsoon variability in Pakistanrdquo The Journal of Animal andPlant Sciences vol 21 no 1 pp 107ndash110 2011
[58] G Rasul ldquoClimate Data and Modelling Analysis of the IndusRegionrdquo Pakistan Meteorological Department (PMD) 2012httpwwfpakorgccappdfClimate Data Modelling20An-alysis20of20the20Indus20Ecoregionpdf
[59] A Basistha D S Arya and N K Goel ldquoAnalysis of historicalchanges in rainfall in the Indian Himalayasrdquo InternationalJournal of Climatology vol 29 no 4 pp 555ndash572 2009
[60] P G Baines ldquoThe late 1960s global climate shift and its influenceon the Southern Hemisphererdquo in Proceedings of 8 ICSHMO pp1477ndash1482 INPE Foz do Iguacu Brazil 2006
[61] K Duan and T Yao ldquoMonsoon variability in the Himalayasunder the condition of global warmingrdquo Journal of the Mete-orological Society of Japan vol 81 no 2 pp 251ndash257 2003
[62] U S Nair R O Lawton R M Welch and R A Pielke SrldquoImpact of land use on Costa Rican tropical montane cloudforests sensitivity of cumulus cloud field characteristics tolowland deforestationrdquo Journal of Geophysical Research D vol108 no 7 pp 4206ndash4219 2003
[63] R Avissar and D Werth ldquoGlobal hydroclimatological tele-connections resulting from tropical deforestationrdquo Journal ofHydrometeorology vol 6 no 2 pp 134ndash145 2005
[64] R A Pielke Sr J Adegoke A Beltran-Przekurat et al ldquoAnoverview of regional land-use and land-cover impacts onrainfallrdquo Tellus B Chemical and Physical Meteorology vol 59no 3 pp 587ndash601 2007
[65] N Ramankutty C Delire and P Snyder ldquoFeedbacks betweenagriculture and climate an illustration of the potential unin-tended consequences of human land use activitiesrdquo Global andPlanetary Change vol 54 no 1-2 pp 79ndash93 2006
[66] V Ramanathan C Chung D Kim et al ldquoAtmospheric brownclouds impacts on South Asian climate and hydrological cyclerdquoProceedings of the National Academy of Sciences of the UnitedStates of America vol 102 no 15 pp 5326ndash5333 2005
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Geological ResearchJournal of
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Geology Advances in
Advances in Meteorology 5
Table 2 Summary of geographic conditions and mean annual precipitation statistics for study stations
Station Longitude Latitude Elevation (m) Mean (mm) STD 119862119904
119862119896
119862V
Thalozom 72∘-151015840 35∘-441015840 4200 7511 2099 minus0266 0082 0291Drosh 72∘-001015840 35∘-331015840 1465 4635 1537 1167 2441 0332Kalam 72∘-331015840 35∘-311015840 2000 9345 3170 minus0599 0323 0353Dir 71∘-531015840 35∘-121015840 1321 5482 1521 minus0545 0919 0285Madyan 72∘-321015840 35∘-091015840 1320 9623 2878 0240 1300 0307Khairabad 72∘-061015840 34∘-581015840 894 7037 1522 1410 4281 0216ToorCamp 71∘-421015840 34∘-501015840 854 5440 1592 minus0436 0841 0299Saidu Sharif 72∘-251015840 34∘-451015840 961 9901 3898 1842 6463 0398Malakand 71∘-461015840 34∘-381015840 603 6098 2526 2474 11668 0424Kulangi 71∘-591015840 34∘-351015840 688 6254 1925 0037 minus0170 0308Ambahar 71∘-121015840 34∘-331015840 694 4550 1485 minus0004 0764 0333Abazai 71∘-331015840 34∘-261015840 320 5007 1527 minus0093 0963 0312Mardan 71∘-581015840 34∘-181015840 283 6574 2974 0735 1392 0452Charsadda 71∘-431015840 34∘-071015840 276 5916 2074 0973 1031 0350Risalpur 71∘-541015840 34∘-061015840 309 6118 1768 0312 minus0098 0289
3 Results and Discussion
31 Preliminary Analysis The preliminary analysis for thisstudy included computing the mean standard deviationcoefficient of skewness coefficient of kurtosis and coefficientof variation in the annual precipitation time series foreach station Table 2 presents these statistical parametersfor the 51-year time period studied (1961ndash2011) The meanannual precipitation varied between 455mm in the southwestpart of the Swat River basin catchment area (Ambahar)and 9901mm in the southeast part (Saidu Sharif) As thetable shows the coefficient of skewness varied from minus0266to 2474 kurtosis varied between minus0170 and 11668 Fortime series data to be considered normally distributed thecoefficient of skewness and kurtosis must be equal to 0and 3 respectively Table 2 indicates therefore that the dataare positively skewed and not normally distributed Thecoefficient of variation the measure of dispersion around themean was also calculated to analyze the spatial variability ofannual precipitation for each station This coefficient variedbetween 216 (Khairabad) and 452 (Mardan)The averagevariation of the precipitation over the complete river basinwas 289
32 Long-Term Pattern on Seasonal and Annual Scale Long-term climatic patterns were assessed using standardizedseasonal and annual precipitation time series data Toreduce local fluctuations LOWESS [53ndash55] curves were fittedover time based on seasonal and annual precipitation timeseries data The LOWESS curve for winter precipitation(Figure 2(a)) showed a decreasing trend in the first decadeIn the second decade the trend was constant The minimumLOWESS curve value was observed in 1990 values thengradually rose through 2010 Overall the curve based onwinter season data suggested a decline in precipitation After1990 there was a gradual rise though small local fluctuationswere ignored The LOWESS curve for spring precipitation(Figure 2(b)) showed a gradual increase in the first three
decades After attaining its highest value in 1990 the valuedeclined over the last two decades
The LOWESS curve for summer precipitation showeda constant trend in the first decade and then started todecline up to 1978 (Figure 2(c)) For 1978ndash1992 the curvestarted to gradually increase through the remaining yearsThe LOWESS curve for autumn precipitation exhibited adecreasing trend through 1982 for the remaining time peri-ods there was an increase in precipitation For the annualprecipitation time series the LOWESS curve showed slightvariations in every decade but the overall trend was nearlyconstant throughout the time series Figure 2 shows theprecipitation patterns LOWESS curves are used to showpatterns and do not explain statistically significant trends inthe time series
33 Monthly Analysis The Mann-Kendall (MK) and Spear-manrsquos (SR) rho tests were applied on a monthly scale todetect trends in the precipitation series at different stationsTable 3 shows the results and illustrates that the results ofboth tests were similar to one another Monthly trend testsshowed a mix of positive and negative trends at differentstations At Thalozom statistically significant negative andpositive trends were found in April and June respectivelySignificant positive trends were detected at Dir and Droshstations in March and August no significant trends werefound for other months The Saidu Sharif station exhibitedsignificant positive trends from January to June and fromOctober to December but had negative trends in July andAugust Significant positive trends were found at most of thestations in the months of May and June significant negativetrends were seen in July and August In other stations a mixof significantly positive and negative trends occurred for afew months of the year Figure 3 shows the spatial variationin the precipitation time series for each month in the SwatRiver basin from 1961 to 2011
The magnitude of statistically significant trends on amonthly scale was determined using Senrsquos slope estimator
6 Advances in Meteorology
0
1
2
3
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
Original dataLOWESS line
minus3
minus2
minus1
(a)
Original dataLOWESS line
0
1
2
3
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
minus2
minus1
(b)
Original dataLOWESS line
0
1
2
3
4
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
minus2
minus1
(c)
Original dataLOWESS line
0
1
2
3
4
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
minus2
minus1
(d)
Original dataLOWESS line
0
1
2
3
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
minus3
minus2
minus1
(e)
Figure 2 Standardized precipitation and LOWESS trend curves at Swat River basin (a) winter (b) spring (c) summer (d) autumn and (e)annual
Advances in Meteorology 7
Table3MKandSR
tests
results
forp
recipitatio
nin
mon
thlytim
eseries
Station
Test
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Thalozom
MK
minus063
minus10
9minus042
minus219lowast
minus033
272lowast
minus080
minus094
minus029
010
146
030
SRminus044
minus10
1minus039
minus215lowast
minus040
293lowast
minus079
minus10
3minus013
028
141
013
Drosh
MK
minus008
minus024
016
minus067
063
151
minus19
4minus316lowast
minus063
040
103
001
SRminus014
minus001
008
minus079
067
173
minus18
7minus336lowast
minus050
039
101
017
Kalam
MK
minus037
minus067
033
minus221lowast
minus063
219lowast
minus115
minus10
4minus054
014
120
017
SRminus023
minus052
023
minus213lowast
minus064
229lowast
minus113
minus10
7minus043
014
091
minus066
Dir
MK
000
minus063
minus248lowast
minus021
minus079
112
minus015
003
174
minus13
1minus034
minus089
SRminus016
minus062
minus280lowast
minus018
minus10
010
7minus001
minus002
203lowast
minus16
3minus049
minus10
1
Madyan
MK
089
075
110
minus083
086
353lowast
minus312lowast
minus338lowast
minus023
190
272lowast
134
SR086
070
113
minus067
085
426lowast
minus324lowast
minus398lowast
minus016
200
301lowast
132
Khaira
bad
MK
091
minus068
minus021
minus080
201lowast
385lowast
minus312lowast
minus348lowast
minus019
268lowast
292lowast
112
SR082
minus072
minus028
minus079
204lowast
446lowast
minus334lowast
minus460lowast
minus017
308lowast
325lowast
097
ToorCa
mp
MK
192
093
045
minus070
minus044
minus086
minus291lowast
minus296lowast
minus227lowast
minus201lowast
094
028
SR17
8085
025
minus082
minus047
minus091
minus317lowast
minus361lowast
minus279lowast
minus233lowast
104
020
SaiduSh
arif
MK
274lowast
246lowast
222lowast
182
285lowast
327lowast
minus334lowast
minus309lowast
003
319lowast
357lowast
210lowast
SR302lowast
262lowast
261lowast
205lowast
324lowast
383lowast
minus360lowast
minus387lowast
020
364lowast
405lowast
217lowast
Malakand
MK
105
minus17
2minus115
010
228lowast
322lowast
minus318lowast
minus293lowast
016
350lowast
273lowast
149
SR099
minus202lowast
minus13
2022
254lowast
302lowast
minus380lowast
minus382lowast
023
397lowast
223lowast
091
Kulang
iMK
070
minus099
minus294lowast
minus14
4minus062
036
000
174
291lowast
minus16
4minus003
minus204lowast
SR059
minus10
4minus315lowast
minus14
1minus081
024
008
165
336lowast
minus18
5minus031
minus231lowast
Ambahar
MK
031
minus066
minus284lowast
minus10
5minus115
060
018
060
304lowast
minus13
6minus021
minus18
0SR
038
minus070
minus282lowast
minus111
minus118
058
019
034
356lowast
minus15
1minus029
minus201lowast
Abazai
MK
233lowast
minus025
minus091
137
292lowast
449lowast
minus262lowast
minus10
710
2331lowast
392lowast
261lowast
SR222lowast
minus029
minus090
162
289lowast
435lowast
minus307lowast
minus10
913
7385lowast
366lowast
272lowast
Mardan
MK
243lowast
134
041
001
105
070
014
minus016
100
minus058
minus13
1minus13
7SR
253lowast
134
050
011
110
072
025
minus020
088
minus051
minus115
minus115
Charsadd
aMK
232lowast
109
032
minus012
015
034
014
minus014
056
minus10
4minus217lowast
minus15
9SR
237lowast
109
026
minus024
032
044
022
minus033
043
minus097
minus204lowast
minus13
1
Risalpur
MK
191
128
006
minus027
minus033
minus037
minus006
minus063
minus026
minus14
6minus18
7minus217lowast
SR213lowast
113
006
minus036
minus017
minus025
minus005
minus072
minus026
minus15
0minus211lowast
minus216lowast
lowast
Sign
ificant
trend
at5
significance
leveloftwo-tailedtest
8 Advances in Meteorology
Jan Feb Mar Apr
May Jun Jul Aug
Sep Oct Nov Dec
N
0 5 10 25
Scale
(km)
Significant increasing trendSignificant decreasing trend
No trend
Figure 3 Location of sites with increasing decreasing and no trends at 5 significance level for the monthly precipitation time series
The results show that trends at Saidu Sharif Madyanand Kalam were more rapid (eg sharper increases anddecreases) compared to other stations The Saidu Sharifstation had the maximum negative decline in monthly pre-cipitation (183mmmonth) as well as the maximum positiveincrease (143mmmonth) during the months of July andMarch respectively Figure 4 shows the trends in maximummonthly precipitation variation at the Saidu Sharif station
34 Seasonal and Annual Analysis The MK and SR testswere also used to identify trends in seasonal and annualprecipitation between 1961 and 2011 Table 4 shows the resultsSimilar to the monthly analysis results from both statisticaltests MK and SR were consistent with one another A mixof negative and positive trends was seen at different stationsThalozom Kalam and Dir stations which had shown trends
with the monthly time scale did not exhibit statisticallysignificant trends for the seasonal and annual precipitationtime series At Madyan Khairabad and Malakand stationsthere were significant negative trends in the summer andpositive trends in the autumn Significant negative trendswere observed in the spring season only at ToorCampKulangi and Ambahar stations For the annual precipitationseries significant positive trends were detected only at SaiduSharif Mardan and Charsadda stations At other stationssignificant positive trends were seen for winter and autumnseasons and for the annual precipitation series howevernegative trends were detected in spring and summer seasonsFigure 5 presents the spatial distribution of seasonal andannual precipitation trends
The Saidu Sharif station showed the maximum positivetrend in annual precipitation series (748mmyear) across
Advances in Meteorology 9
0
100
200
300
400
500
600
700
800
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
mon
th)
Year
Saidu Sharif station(March)
(a)
0
100
200
300
400
500
600
700
800
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
mon
th)
Year
Saidu Sharif station(July)
(b)
Figure 4 Variations of monthly precipitation time series in stations with most significant trends during 1961ndash2011
Table 4 MK and SR tests results for precipitation in seasonal and annual time series
Station Test Winter Spring Summer Autumn Annual
Thalozom MK minus120 minus162 minus120 148 minus149SR minus114 minus152 minus110 135 minus145
Drosh MK 042 minus078 minus196 097 minus044SR 049 minus074 minus209lowast 127 minus048
Kalam MK minus062 minus139 minus171 160 minus110SR minus037 minus121 minus158 157 minus087
Dir MK minus028 minus148 minus047 minus076 minus138SR minus062 minus150 minus058 minus097 minus146
Madyan MK 120 003 minus258lowast 365lowast 042SR 137 033 minus244lowast 421lowast 078
Khairabad MK 026 minus065 minus302lowast 325lowast minus073SR 021 minus076 minus353lowast 364lowast minus072
ToorCamp MK minus063 minus203lowast 024 minus073 minus044SR minus096 minus217lowast 023 minus092 minus159
Saidu Sharif MK 346lowast 239lowast minus156 069 328lowast
SR 404lowast 280lowast minus156 148 278lowast
Malakand MK minus070 minus110 minus270lowast 337lowast minus119SR minus068 minus115 minus319lowast 373lowast minus140
Kulangi MK minus122 minus261lowast 031 minus099 minus144SR minus156 minus284lowast 037 minus127 minus172
Ambahar MK minus066 minus206lowast minus063 minus099 minus157SR minus076 minus224lowast minus058 minus110 minus141
Abazai MK 179 minus015 minus099 429lowast 096SR 217lowast 007 minus072 604lowast 122
Mardan MK 281lowast 145 095 minus102 259lowast
SR 310lowast 134 098 minus085 280lowast
Charsadda MK 266lowast 097 073 minus194 214lowast
SR 293lowast 088 060 minus176 217lowast
Risalpur MK 243lowast 044 minus006 minus154 198SR 254lowast 040 minus005 minus190 195
lowastSignificant trend at 5 significance level of two-tailed test
10 Advances in Meteorology
N
0 5 10 25
Scale
(km)
Significant increasing trendSignificant decreasing trend
No trend
Winter
Autumn Annual
Spring Summer
Figure 5 Location of sites with increasing decreasing and no trends at 5 significance level for the seasonal and annual precipitation timeseries
study stations from 1961 to 2011 theThalozom station showeda negative trend with a decreasing rate of 370mmyearFigure 6 displays the results of the magnitude of variationin the annual precipitation for the Saidu Sharif MardanCharsadda andThalozom stations
35 Trend Analysis over Entire River Basin The effect ofclimate change on precipitation was also analyzed for theentire Swat River basin by applying the MK and SR testson monthly seasonal and annual scale As Figure 1 showedthe entire Swat River catchment (A) is divided into foursubbasins upper subbasin (A1) Panjkora subbasin (A2)Ambahar subbasin (A3) and Lower subbasin (A4) Table 5presents trends in monthly precipitation across the subbasinsand for the full basin The table shows significant positivetrends in the months of June and November for the uppersubbasin (A1) and the entire Swat River basin (A) negativetrends were seen in these locations in July and August Inthe Panjkora subbasin (A2) statistically significant positivetrends were identified over time in June a negative trendwas seen from July to September The maximum number ofsignificant cases (8) was observed in data from the Ambaharsubbasin (A3)The Lower subbasin (A4) showed a significantpositive trend only during January no significant trendsin other months were identified As a simpler summarysignificant negative trends in precipitation over time were
seen from July to September positive trends over time wereseen in January May June and October to December indifferent Swat River subbasins
To detect precipitation trends in each subbasin and entireSwat River basin the MK and SR tests were again appliedto seasonal and annual precipitation data for the 51-yearstudy period (1961ndash2011) As Table 6 shows both testmethodsshowed similar results The upper subbasin (A1) experiencedstatistically significant negative trends in the summer andpositive trends in the autumn The Panjkora subbasin (A2)and Lower subbasin (A4) showed significant negative trendsin the summer and positive trends in the winter Significantpositive trends were found across the subbasins in winterand autumn seasons however there was a negative trendin summer at Ambahar subbasin (A3) and across the entireSwat River basin (A) For the annual and spring precipitationtime series there were no statistically significant trendsSignificant positive trendswere seen inwinter and autumn insummer negative trends were seen across different subbasinsand the full Swat River basin
The Lower subbasin exhibited the maximum positivetrend over time (218mmyear) in the weighted annualprecipitation time series the Panjkora subbasin showed anegative trend with a decreasing rate of participation at090mmyear The entire Swat River basin showed a positivetrend in precipitation (048mmyear) as shown in Table 6
Advances in Meteorology 11
Table5MKandSR
tests
results
form
onthlyprecipitatio
ntim
eseriesinentireb
asin
andsubb
asinso
fSwatRiver
Subb
asin
Test
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
A1
MK
047
010
071
minus12
3041
349lowast
minus288lowast
minus318lowast
minus018
143
250lowast
094
SR045
006
074
minus098
047
409lowast
minus299lowast
minus363lowast
minus018
159
277lowast
094
A2
MK
107
080
016
minus093
021
201lowast
minus354lowast
minus416lowast
minus202lowast
000
187
062
SR095
072
001
minus099
013
231lowast
minus386lowast
minus486lowast
minus224lowast
011
200
063
A3
MK
250lowast
102
minus036
065
297lowast
390lowast
minus297lowast
minus255lowast
minus044
305lowast
295lowast
229lowast
SR267lowast
089
minus009
070
311lowast
479lowast
minus354lowast
minus322lowast
minus052
376lowast
365lowast
260lowast
A4
MK
237lowast
088
minus006
minus050
122
164
minus063
minus083
000
020
050
minus040
SR246lowast
084
minus001
minus059
117
182
minus059
minus090
001
045
023
minus046
AMK
185
110
013
minus062
123
369lowast
minus255lowast
minus361lowast
minus065
174
268lowast
070
SR17
010
4018
minus079
127
422lowast
minus277lowast
minus401lowast
minus070
181
299lowast
073
lowast
Sign
ificant
trend
at5
significance
leveloftwo-tailedtest
12 Advances in Meteorology
0
500
1000
1500
2000
2500
3000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Saidu Sharif station
(a)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Mardan station
(b)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Charsadda station
(c)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Thalozom station
(d)
Figure 6 Variations of annual precipitation time series in stations with significant trends during 1961ndash2011
36 Comparison of Results Results from both statistical testsMK and SR were consistent with each otherThe percentagesof statistically significant cases to total tested cases for theMK and SR tests were 32 and 30 respectively showingagreement across methods This consistency in statisticalperformance was also found in other studies [24 28]
4 Discussion
This study investigated variability in monthly seasonal andannual precipitation at 15 stations in the Swat River basinover a 51-year study period (1961ndash2011) Precipitation trendswere also analyzed for each subbasin and entire Swat Riverbasin The mean annual precipitation at different stationsshowed considerable variation with a standard deviationof 1768mm from the mean annual rainfall of 694mmThe Saidu Sharif Mardan and Charsadda stations showedsignificant positive trends (increased precipitation over time)at 5 significance level in the annual precipitation series
The maximum number of significant changes in monthlyprecipitation over time was detected at Saidu Sharif Abazaiand Khairabad stations Saidu Sharif station showed themaximum increasing slope (indicating sharpest change overtime) of 748mmyear among the selected stations in the SwatRiver basin
These study results follow the same statistical trendsreported by Hartmann and Andresky [35] for northwestparts of Pakistan Findings were consistent with results fromDimri [56] Ghaffar and Javid [57] and Rasul [58] whereinthey found statistically significant increasing trends in winterprecipitation for northwest areas of Pakistan The resultsof this analysis also support finding of Hanif et al [37]wherein they found significant variations in summer seasonprecipitation These variations in precipitation trends maylead Pakistan towards more water related disasters suchas droughts and floods in the near future Basistha et al[59] proposed possible causes of the changing precipitationtrends such as global climate shifts [60] dwindling global
Advances in Meteorology 13
Table 6 MK and SR results for seasonal and annual precipitation time series in entire basin and subbasin of Swat River
Subbasin Change (mmyear) Test Winter Spring Summer Autumn Annual
A1 minus073 MK 055 minus024 minus242lowast 305lowast minus034SR 057 001 minus227lowast 347lowast 118
A2 minus090 MK 128 minus023 minus385lowast 158 minus081SR 118 minus035 minus444lowast 164 minus090
A3 030 MK 266lowast 016 minus265lowast 375lowast 024SR 295lowast 027 minus309lowast 460lowast 040
A4 218 MK 242lowast 060 minus021 024 166SR 272lowast 054 minus037 043 173
A 048 MK 214lowast minus011 minus297lowast 307lowast 042SR 225lowast minus014 minus340lowast 336lowast 038
lowastSignificant trend at 5 significance level of two-tailed test
monsoon circulation [61] decline in forest cover [62 63] landuse changes and practices (eg irrigated agriculture) [64 65]and increasing aerosols from anthropogenic activities [66]
5 Conclusions
This paper analyzed trends in monthly seasonal and annualprecipitation in the Swat River basin over the 51-year studyperiod (1961ndash2011) A mix of positive and negative trendswas observed at various stations and subbasins The monthsof June November July and August showed the maximumnumber of significant cases at various stations in monthlyprecipitation The trends were positive in May and June andwere negative in July and August This indicates a shift inprecipitation series on monthly scale Significant positivetrends were detected in winter and autumn and annuallynegative trends were seen in spring and summer seasonsSaidu Sharif Mardan and Charsadda stations exhibitedsignificant positive trends in annual precipitation at a 95confidence level the remaining stations did not experiencea statistically significant trend
For the entire Swat River basin no significant trendswere detected in any subbasin for the annual precipitationseries Seasonally winter and autumn experienced significantpositive trends and summer experienced negative trends indifferent subbasins in the Swat River basin Most statisticallysignificant trend cases under different scenarios were positive(61)The results obtainedwith theMann-Kendall (MK) andSpearmanrsquos rho tests showed agreement in their assessmentsof monthly seasonal and annual precipitation trends Thevariability of negative and positive trends at various stationspoints to the need for more detailed studies on the climatechange of this region
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgments
The authors thank Pakistan Meteorological Department(PMD) Water and Power Development Authority
(WAPDA) Pakistan and Snowy Mountains EngineeringCorporation (SMEC) for providing cost-free data for thisstudy
References
[1] M D Rahman and M Begum ldquoApplication of non parametrictest for trend detection of rainfall in the largest Island ofBangladeshrdquo ARPN Journal of Earth Sciences vol 2 no 2 pp40ndash44 2013
[2] IPCCThePhysical Science Basis Contribution ofWorkingGroupI to the Fourth Assessment Report of the Intergovernmental Panelon Climate Change Cambridge University Press CambridgeUK 2007
[3] A B Farooq and A H Khan ldquoClimate change perspectivein Pakistanrdquo in Proceedings of the Capacity Building APNWorkshop on Global Change Research pp 39ndash46 IslamabadPakistan 2004
[4] Z Z Hu S Yang and R Wu ldquoLong-term climate variationsin China and global warming signalsrdquo Journal of GeophysicalResearch vol 108 no D19 2003
[5] P Zhai and X Pan ldquoTrends in temperature extremes during1951ndash1999 in Chinardquo Geophysical Research Letters vol 30 no17 p 1913 2003
[6] D Duhan and A Pandey ldquoStatistical analysis of long termspatial and temporal trends of precipitation during 1901ndash2002at Madhya Pradesh Indiardquo Atmospheric Research vol 122 pp136ndash149 2013
[7] B J Peterson RM Holmes JWMcClelland et al ldquoIncreasingriver discharge to the Arctic oceanrdquo Science vol 298 no 5601pp 2171ndash2173 2002
[8] N I Savelieva I P Semiletov L N Vasilevskaya and S PPugach ldquoA climate shift in seasonal values of meteorologicaland hydrological parameters for Northeastern Asiardquo Progress inOceanography vol 47 no 2ndash4 pp 279ndash297 2000
[9] Y F Shi Y P Shen and R J Hu ldquoPreliminary study on signalimpact and foreground of climatic shift from warm-dry towarm-humid in Northwest Chinardquo Journal of Glaciology andGeocryology vol 24 pp 219ndash226 2002 (Chinese)
[10] S Farhana and M M Rahman ldquoCharacterizing rainfall trendin Bangladesh by temporal statistics analysisrdquo in Proceedings ofthe 4th Annual Paper Meet and 1st Civil Engineering CongressDhaka Bangladesh 2011
[11] R H Rimi S H Rahman S Karmakar and S G HussainldquoTrend analysis of climate change and investigation on its
14 Advances in Meteorology
probable impacts on rice production at Satkhira BangladeshrdquoPakistan Journal of Meteorology vol 6 no 11 pp 37ndash50 2014
[12] E R Dahmen and M J Hall Screening of Hydrological DataTests for Stationarity and Relative Consistency Publication 49ILRI Wageningen The Netherlands 1990
[13] Q Zhang C Liu C-Y Xu Y Xu and T Jiang ldquoObserved trendsof annual maximumwater level and streamflow during past 130years in the Yangtze River basin Chinardquo Journal of Hydrologyvol 324 no 1-4 pp 255ndash265 2006
[14] H Chen S Guo C-Y Xu and V P Singh ldquoHistorical tem-poral trends of hydro-climatic variables and runoff responseto climate variability and their relevance in water resourcemanagement in the Hanjiang basinrdquo Journal of Hydrology vol344 no 3-4 pp 171ndash184 2007
[15] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 pp 245ndash259 1945
[16] M G Kendall Rank CorrelationMethods Griffin London UK1975
[17] E L Lehmann Nonparametrics Statistical Methods Based onRanks Holden-Day San Francisco Calif USA 1975
[18] R Sneyers ldquoOn the statistical analysis of series of observationsrdquoTechnical Note 143 WMO no 415 World MeteorologicalOrganization 1990
[19] A Longobardi and P Villani ldquoTrend analysis of annual andseasonal rainfall time series in the Mediterranean areardquo Inter-national Journal of Climatology vol 30 no 10 pp 1538ndash15462010
[20] Z YanmingW Jun andW Xinhua ldquoStudy on the change trendof precipitation and temperature in Kunming city based onMann-Kendall analysisrdquo in Future Computer CommunicationControl and Automation vol 119 of Advances in Intelligent andSoft Computing pp 505ndash513 Springer Berlin Germany 2011
[21] X L Yang L R Xu K K Liu C H Li J Hu and X H XialdquoTrend in temperature and precipitation in the ZhangweinanRiver Basin during the last 53 yearsrdquo Procedia EnvironmentalSciences vol 13 pp 1966ndash1974 1966
[22] Z F Yang Y Yan and Q Liu ldquoThe relationship of streamflow-precipitation-temperature in the Yellow River Basin of Chinaduring 1961ndash2000rdquo Procedia Environmental Sciences vol 13 pp2336ndash2345 2012
[23] Q-X Wang X-H Fan Z-D Qin and M-B Wang ldquoChangetrends of temperature and precipitation in the Loess PlateauRegion of China 1961ndash2010rdquo Global and Planetary Change vol92-93 pp 138ndash147 2012
[24] S Yue P Pilon and G Cavadias ldquoPower of the Mann-Kendalland Spearmanrsquos rho tests for detecting monotonic trends inhydrological seriesrdquo Journal of Hydrology vol 259 no 1ndash4 pp254ndash271 2002
[25] E Kahya and S Kalaycı ldquoTrend analysis of streamflow inTurkeyrdquo Journal of Hydrology vol 289 pp 128ndash144 2004
[26] Z L Li Z X Xu J Y Li and Z J Li ldquoShift trend and stepchanges for runoff time series in the Shiyang River BasinNorthwest Chinardquo Hydrological Processes vol 22 no 23 pp4639ndash4646 2008
[27] C Yaning X Changchun H Xingming et al ldquoFifty-yearclimate change and its effect on annual runoff in the TarimRiverBasin Chinardquo Quaternary International vol 208 no 1-2 pp53ndash61 2009
[28] M Shadmani SMarofi andMRoknian ldquoTrend analysis in ref-erence evapotranspiration usingMann-Kendall and SpearmanrsquosRho tests in arid regions of IranrdquoWater Resources Managementvol 26 no 1 pp 211ndash224 2012
[29] H Rehman and A Kamal ldquoIndus Basin River system-floodingand flood mitigationrdquo 2005 httparchiveriversymposiumcom2005indexphpelement=38
[30] Pakistan Meteorological Department (PMD) National PlanStrengthening National Capacities for Multi-hazard EarlyWarn-ing amp Response System 2006
[31] National Disaster Management Authority (NDMA) 2007National Disaster Risk Management Framework Governmentof Pakistan httpwwwndmagovpknew
[32] N H Hashimi Q T M Siddiqui A R Ghumman M AKamal and H R Mughal ldquoA critical analysis of 2010 floods inPakistanrdquo African Journal of Agricultural Research vol 7 no 7pp 1054ndash1067 2012
[33] FFC ldquoFederal Flood Commission of Pakistanrdquo Annual FloodReport-2010 2011 httpwwwffcgovpkdownloadfloodarc-hieveAnnualreport2010pdf
[34] N Gronewold and Climatewire ldquoIs the Flooding in Pakistan aClimate Change Disasterrdquo WMN 2010 httpwwwscientific-americancomarticleis-the-flooding-in-pakist
[35] H Hartmann and L Andresky ldquoFlooding in the Indus Riverbasinmdasha spatiotemporal analysis of precipitation recordsrdquoGlobal and Planetary Change vol 107 pp 25ndash35 2013
[36] S Salma S Rehman andM A Shah ldquoRainfall trends in differ-ent climate zones of Pakistanrdquo Pakistan Journal of Meteorologyvol 9 no 17 pp 37ndash47 2012
[37] M Hanif A H Khan and S Adnan ldquoLatitudinal precipitationcharacteristics and trends in Pakistanrdquo Journal ofHydrology vol492 pp 266ndash272 2013
[38] A Imran Q Zaman and M Afzal ldquoTemporal trends in thepeak monsoonal precipitation events over Northeast PakistanrdquoPakistan Journal of Meteorology vol 10 no 19 pp 19ndash30 2013
[39] S B Cheema and M Hanif ldquoSeasonal precipitation variationover Punjab provincerdquo Pakistan Journal of Meteorology vol 10no 19 pp 61ndash82 2013
[40] H Hartmann and H Buchanan ldquoTrends in extreme precipita-tion events in the indus River Basin and flooding in PakistanrdquoAtmosphere-Ocean vol 52 no 1 pp 77ndash91 2014
[41] ldquoProvincial Disaster Management Authority (PDMA 2012)Monsoon Contingency Plan-Khyber-Pakhtunkhwardquo 2012httpwwwndmagovpkDocumentsContingency Plan2012CP KPpdf
[42] Snowy Mountains Engineering Corporation Munda DamConstruction Project Detailed Design Report SMEC LahorePakistan 2014
[43] H Alexandersson ldquoA homogeneity test applied to precipitationdatardquo Journal of Climatology vol 6 no 6 pp 661ndash675 1986
[44] HAlexandersson andAMoberg ldquoHomogenization of Swedishtemperature data Part I homogeneity test for linear trendsrdquoInternational Journal of Climatology vol 17 no 1 pp 25ndash341997
[45] T A Buishand ldquoSome methods for testing the homogeneity ofrainfall recordsrdquo Journal of Hydrology vol 58 no 1-2 pp 11ndash271982
[46] M N Khaliq and T B M J Ouarda ldquoOn the critical values ofthe standard normal homogeneity test (SNHT)rdquo InternationalJournal of Climatology vol 27 no 5 pp 681ndash687 2007
[47] K H Hamed and A Ramachandra Rao ldquoA modified Mann-Kendall trend test for autocorrelated datardquo Journal of Hydrologyvol 204 no 1ndash4 pp 182ndash196 1998
[48] B Onoz and M Bayazit ldquoBlock bootstrap for Mann-Kendalltrend test of serially dependent datardquoHydrological Processes vol26 no 23 pp 3552ndash3560 2012
Advances in Meteorology 15
[49] M Yaseen H A Bhatti T Rientjes G Nabi and M LatifldquoTemporal and spatial variations in summer flows of upperIndus Basin Pakistanrdquo inProceedings of the 72ndAnnual Sessionof Pakistan Engineering Congress Paper no 747 pp 315ndash3342013
[50] G C Blain ldquoThe Mann-Kendall test the need to consider theinteraction between serial correlation and trendrdquo AgriculturalEngineering vol 35 no 4 2013
[51] M Yaseen T Rientjes G Nabi H ur-Rehman and M LatifldquoAssessment of recent temperature trends inManglawatershedrdquoJournal of Himalayan Earth Sciences vol 47 no 1 pp 107ndash1212014
[52] P K Sen ldquoEstimates of the regression coefficient based onKendallrsquos taurdquo Journal of the American Statistical Associationvol 63 no 324 pp 1379ndash1389 1968
[53] W S Cleveland ldquoRobust locally weighted regression andsmoothing scatterplotsrdquoThe Journal of the American StatisticalAssociation vol 74 no 368 pp 829ndash836 1979
[54] W S Cleveland ldquoGraphs in scientific publicationsrdquoThe Ameri-can Statistician vol 38 no 4 pp 261ndash269 1984
[55] D R Helsel and R M Hirsch ldquoStatistical methods in waterresourcesrdquo inTechniques ofWater Resources Investigations Book4 chapter A3 p 522 US Geological Survey 2002
[56] A P Dimri ldquoSurface and upper air fields during extreme winterprecipitation over the western Himalayasrdquo Pure and AppliedGeophysics vol 163 no 8 pp 1679ndash1698 2006
[57] A Ghaffar and M Javid ldquoImpact of global warming onmonsoon variability in Pakistanrdquo The Journal of Animal andPlant Sciences vol 21 no 1 pp 107ndash110 2011
[58] G Rasul ldquoClimate Data and Modelling Analysis of the IndusRegionrdquo Pakistan Meteorological Department (PMD) 2012httpwwfpakorgccappdfClimate Data Modelling20An-alysis20of20the20Indus20Ecoregionpdf
[59] A Basistha D S Arya and N K Goel ldquoAnalysis of historicalchanges in rainfall in the Indian Himalayasrdquo InternationalJournal of Climatology vol 29 no 4 pp 555ndash572 2009
[60] P G Baines ldquoThe late 1960s global climate shift and its influenceon the Southern Hemisphererdquo in Proceedings of 8 ICSHMO pp1477ndash1482 INPE Foz do Iguacu Brazil 2006
[61] K Duan and T Yao ldquoMonsoon variability in the Himalayasunder the condition of global warmingrdquo Journal of the Mete-orological Society of Japan vol 81 no 2 pp 251ndash257 2003
[62] U S Nair R O Lawton R M Welch and R A Pielke SrldquoImpact of land use on Costa Rican tropical montane cloudforests sensitivity of cumulus cloud field characteristics tolowland deforestationrdquo Journal of Geophysical Research D vol108 no 7 pp 4206ndash4219 2003
[63] R Avissar and D Werth ldquoGlobal hydroclimatological tele-connections resulting from tropical deforestationrdquo Journal ofHydrometeorology vol 6 no 2 pp 134ndash145 2005
[64] R A Pielke Sr J Adegoke A Beltran-Przekurat et al ldquoAnoverview of regional land-use and land-cover impacts onrainfallrdquo Tellus B Chemical and Physical Meteorology vol 59no 3 pp 587ndash601 2007
[65] N Ramankutty C Delire and P Snyder ldquoFeedbacks betweenagriculture and climate an illustration of the potential unin-tended consequences of human land use activitiesrdquo Global andPlanetary Change vol 54 no 1-2 pp 79ndash93 2006
[66] V Ramanathan C Chung D Kim et al ldquoAtmospheric brownclouds impacts on South Asian climate and hydrological cyclerdquoProceedings of the National Academy of Sciences of the UnitedStates of America vol 102 no 15 pp 5326ndash5333 2005
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Applied ampEnvironmentalSoil Science
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Mining
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Journal of
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International Journal of
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GeochemistryHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Atmospheric SciencesInternational Journal of
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OceanographyHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Advances in
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MineralogyInternational Journal of
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Paleontology JournalHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Geological ResearchJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geology Advances in
6 Advances in Meteorology
0
1
2
3
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
Original dataLOWESS line
minus3
minus2
minus1
(a)
Original dataLOWESS line
0
1
2
3
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
minus2
minus1
(b)
Original dataLOWESS line
0
1
2
3
4
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
minus2
minus1
(c)
Original dataLOWESS line
0
1
2
3
4
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
minus2
minus1
(d)
Original dataLOWESS line
0
1
2
3
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
Year
minus3
minus2
minus1
(e)
Figure 2 Standardized precipitation and LOWESS trend curves at Swat River basin (a) winter (b) spring (c) summer (d) autumn and (e)annual
Advances in Meteorology 7
Table3MKandSR
tests
results
forp
recipitatio
nin
mon
thlytim
eseries
Station
Test
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Thalozom
MK
minus063
minus10
9minus042
minus219lowast
minus033
272lowast
minus080
minus094
minus029
010
146
030
SRminus044
minus10
1minus039
minus215lowast
minus040
293lowast
minus079
minus10
3minus013
028
141
013
Drosh
MK
minus008
minus024
016
minus067
063
151
minus19
4minus316lowast
minus063
040
103
001
SRminus014
minus001
008
minus079
067
173
minus18
7minus336lowast
minus050
039
101
017
Kalam
MK
minus037
minus067
033
minus221lowast
minus063
219lowast
minus115
minus10
4minus054
014
120
017
SRminus023
minus052
023
minus213lowast
minus064
229lowast
minus113
minus10
7minus043
014
091
minus066
Dir
MK
000
minus063
minus248lowast
minus021
minus079
112
minus015
003
174
minus13
1minus034
minus089
SRminus016
minus062
minus280lowast
minus018
minus10
010
7minus001
minus002
203lowast
minus16
3minus049
minus10
1
Madyan
MK
089
075
110
minus083
086
353lowast
minus312lowast
minus338lowast
minus023
190
272lowast
134
SR086
070
113
minus067
085
426lowast
minus324lowast
minus398lowast
minus016
200
301lowast
132
Khaira
bad
MK
091
minus068
minus021
minus080
201lowast
385lowast
minus312lowast
minus348lowast
minus019
268lowast
292lowast
112
SR082
minus072
minus028
minus079
204lowast
446lowast
minus334lowast
minus460lowast
minus017
308lowast
325lowast
097
ToorCa
mp
MK
192
093
045
minus070
minus044
minus086
minus291lowast
minus296lowast
minus227lowast
minus201lowast
094
028
SR17
8085
025
minus082
minus047
minus091
minus317lowast
minus361lowast
minus279lowast
minus233lowast
104
020
SaiduSh
arif
MK
274lowast
246lowast
222lowast
182
285lowast
327lowast
minus334lowast
minus309lowast
003
319lowast
357lowast
210lowast
SR302lowast
262lowast
261lowast
205lowast
324lowast
383lowast
minus360lowast
minus387lowast
020
364lowast
405lowast
217lowast
Malakand
MK
105
minus17
2minus115
010
228lowast
322lowast
minus318lowast
minus293lowast
016
350lowast
273lowast
149
SR099
minus202lowast
minus13
2022
254lowast
302lowast
minus380lowast
minus382lowast
023
397lowast
223lowast
091
Kulang
iMK
070
minus099
minus294lowast
minus14
4minus062
036
000
174
291lowast
minus16
4minus003
minus204lowast
SR059
minus10
4minus315lowast
minus14
1minus081
024
008
165
336lowast
minus18
5minus031
minus231lowast
Ambahar
MK
031
minus066
minus284lowast
minus10
5minus115
060
018
060
304lowast
minus13
6minus021
minus18
0SR
038
minus070
minus282lowast
minus111
minus118
058
019
034
356lowast
minus15
1minus029
minus201lowast
Abazai
MK
233lowast
minus025
minus091
137
292lowast
449lowast
minus262lowast
minus10
710
2331lowast
392lowast
261lowast
SR222lowast
minus029
minus090
162
289lowast
435lowast
minus307lowast
minus10
913
7385lowast
366lowast
272lowast
Mardan
MK
243lowast
134
041
001
105
070
014
minus016
100
minus058
minus13
1minus13
7SR
253lowast
134
050
011
110
072
025
minus020
088
minus051
minus115
minus115
Charsadd
aMK
232lowast
109
032
minus012
015
034
014
minus014
056
minus10
4minus217lowast
minus15
9SR
237lowast
109
026
minus024
032
044
022
minus033
043
minus097
minus204lowast
minus13
1
Risalpur
MK
191
128
006
minus027
minus033
minus037
minus006
minus063
minus026
minus14
6minus18
7minus217lowast
SR213lowast
113
006
minus036
minus017
minus025
minus005
minus072
minus026
minus15
0minus211lowast
minus216lowast
lowast
Sign
ificant
trend
at5
significance
leveloftwo-tailedtest
8 Advances in Meteorology
Jan Feb Mar Apr
May Jun Jul Aug
Sep Oct Nov Dec
N
0 5 10 25
Scale
(km)
Significant increasing trendSignificant decreasing trend
No trend
Figure 3 Location of sites with increasing decreasing and no trends at 5 significance level for the monthly precipitation time series
The results show that trends at Saidu Sharif Madyanand Kalam were more rapid (eg sharper increases anddecreases) compared to other stations The Saidu Sharifstation had the maximum negative decline in monthly pre-cipitation (183mmmonth) as well as the maximum positiveincrease (143mmmonth) during the months of July andMarch respectively Figure 4 shows the trends in maximummonthly precipitation variation at the Saidu Sharif station
34 Seasonal and Annual Analysis The MK and SR testswere also used to identify trends in seasonal and annualprecipitation between 1961 and 2011 Table 4 shows the resultsSimilar to the monthly analysis results from both statisticaltests MK and SR were consistent with one another A mixof negative and positive trends was seen at different stationsThalozom Kalam and Dir stations which had shown trends
with the monthly time scale did not exhibit statisticallysignificant trends for the seasonal and annual precipitationtime series At Madyan Khairabad and Malakand stationsthere were significant negative trends in the summer andpositive trends in the autumn Significant negative trendswere observed in the spring season only at ToorCampKulangi and Ambahar stations For the annual precipitationseries significant positive trends were detected only at SaiduSharif Mardan and Charsadda stations At other stationssignificant positive trends were seen for winter and autumnseasons and for the annual precipitation series howevernegative trends were detected in spring and summer seasonsFigure 5 presents the spatial distribution of seasonal andannual precipitation trends
The Saidu Sharif station showed the maximum positivetrend in annual precipitation series (748mmyear) across
Advances in Meteorology 9
0
100
200
300
400
500
600
700
800
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
mon
th)
Year
Saidu Sharif station(March)
(a)
0
100
200
300
400
500
600
700
800
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
mon
th)
Year
Saidu Sharif station(July)
(b)
Figure 4 Variations of monthly precipitation time series in stations with most significant trends during 1961ndash2011
Table 4 MK and SR tests results for precipitation in seasonal and annual time series
Station Test Winter Spring Summer Autumn Annual
Thalozom MK minus120 minus162 minus120 148 minus149SR minus114 minus152 minus110 135 minus145
Drosh MK 042 minus078 minus196 097 minus044SR 049 minus074 minus209lowast 127 minus048
Kalam MK minus062 minus139 minus171 160 minus110SR minus037 minus121 minus158 157 minus087
Dir MK minus028 minus148 minus047 minus076 minus138SR minus062 minus150 minus058 minus097 minus146
Madyan MK 120 003 minus258lowast 365lowast 042SR 137 033 minus244lowast 421lowast 078
Khairabad MK 026 minus065 minus302lowast 325lowast minus073SR 021 minus076 minus353lowast 364lowast minus072
ToorCamp MK minus063 minus203lowast 024 minus073 minus044SR minus096 minus217lowast 023 minus092 minus159
Saidu Sharif MK 346lowast 239lowast minus156 069 328lowast
SR 404lowast 280lowast minus156 148 278lowast
Malakand MK minus070 minus110 minus270lowast 337lowast minus119SR minus068 minus115 minus319lowast 373lowast minus140
Kulangi MK minus122 minus261lowast 031 minus099 minus144SR minus156 minus284lowast 037 minus127 minus172
Ambahar MK minus066 minus206lowast minus063 minus099 minus157SR minus076 minus224lowast minus058 minus110 minus141
Abazai MK 179 minus015 minus099 429lowast 096SR 217lowast 007 minus072 604lowast 122
Mardan MK 281lowast 145 095 minus102 259lowast
SR 310lowast 134 098 minus085 280lowast
Charsadda MK 266lowast 097 073 minus194 214lowast
SR 293lowast 088 060 minus176 217lowast
Risalpur MK 243lowast 044 minus006 minus154 198SR 254lowast 040 minus005 minus190 195
lowastSignificant trend at 5 significance level of two-tailed test
10 Advances in Meteorology
N
0 5 10 25
Scale
(km)
Significant increasing trendSignificant decreasing trend
No trend
Winter
Autumn Annual
Spring Summer
Figure 5 Location of sites with increasing decreasing and no trends at 5 significance level for the seasonal and annual precipitation timeseries
study stations from 1961 to 2011 theThalozom station showeda negative trend with a decreasing rate of 370mmyearFigure 6 displays the results of the magnitude of variationin the annual precipitation for the Saidu Sharif MardanCharsadda andThalozom stations
35 Trend Analysis over Entire River Basin The effect ofclimate change on precipitation was also analyzed for theentire Swat River basin by applying the MK and SR testson monthly seasonal and annual scale As Figure 1 showedthe entire Swat River catchment (A) is divided into foursubbasins upper subbasin (A1) Panjkora subbasin (A2)Ambahar subbasin (A3) and Lower subbasin (A4) Table 5presents trends in monthly precipitation across the subbasinsand for the full basin The table shows significant positivetrends in the months of June and November for the uppersubbasin (A1) and the entire Swat River basin (A) negativetrends were seen in these locations in July and August Inthe Panjkora subbasin (A2) statistically significant positivetrends were identified over time in June a negative trendwas seen from July to September The maximum number ofsignificant cases (8) was observed in data from the Ambaharsubbasin (A3)The Lower subbasin (A4) showed a significantpositive trend only during January no significant trendsin other months were identified As a simpler summarysignificant negative trends in precipitation over time were
seen from July to September positive trends over time wereseen in January May June and October to December indifferent Swat River subbasins
To detect precipitation trends in each subbasin and entireSwat River basin the MK and SR tests were again appliedto seasonal and annual precipitation data for the 51-yearstudy period (1961ndash2011) As Table 6 shows both testmethodsshowed similar results The upper subbasin (A1) experiencedstatistically significant negative trends in the summer andpositive trends in the autumn The Panjkora subbasin (A2)and Lower subbasin (A4) showed significant negative trendsin the summer and positive trends in the winter Significantpositive trends were found across the subbasins in winterand autumn seasons however there was a negative trendin summer at Ambahar subbasin (A3) and across the entireSwat River basin (A) For the annual and spring precipitationtime series there were no statistically significant trendsSignificant positive trendswere seen inwinter and autumn insummer negative trends were seen across different subbasinsand the full Swat River basin
The Lower subbasin exhibited the maximum positivetrend over time (218mmyear) in the weighted annualprecipitation time series the Panjkora subbasin showed anegative trend with a decreasing rate of participation at090mmyear The entire Swat River basin showed a positivetrend in precipitation (048mmyear) as shown in Table 6
Advances in Meteorology 11
Table5MKandSR
tests
results
form
onthlyprecipitatio
ntim
eseriesinentireb
asin
andsubb
asinso
fSwatRiver
Subb
asin
Test
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
A1
MK
047
010
071
minus12
3041
349lowast
minus288lowast
minus318lowast
minus018
143
250lowast
094
SR045
006
074
minus098
047
409lowast
minus299lowast
minus363lowast
minus018
159
277lowast
094
A2
MK
107
080
016
minus093
021
201lowast
minus354lowast
minus416lowast
minus202lowast
000
187
062
SR095
072
001
minus099
013
231lowast
minus386lowast
minus486lowast
minus224lowast
011
200
063
A3
MK
250lowast
102
minus036
065
297lowast
390lowast
minus297lowast
minus255lowast
minus044
305lowast
295lowast
229lowast
SR267lowast
089
minus009
070
311lowast
479lowast
minus354lowast
minus322lowast
minus052
376lowast
365lowast
260lowast
A4
MK
237lowast
088
minus006
minus050
122
164
minus063
minus083
000
020
050
minus040
SR246lowast
084
minus001
minus059
117
182
minus059
minus090
001
045
023
minus046
AMK
185
110
013
minus062
123
369lowast
minus255lowast
minus361lowast
minus065
174
268lowast
070
SR17
010
4018
minus079
127
422lowast
minus277lowast
minus401lowast
minus070
181
299lowast
073
lowast
Sign
ificant
trend
at5
significance
leveloftwo-tailedtest
12 Advances in Meteorology
0
500
1000
1500
2000
2500
3000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Saidu Sharif station
(a)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Mardan station
(b)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Charsadda station
(c)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Thalozom station
(d)
Figure 6 Variations of annual precipitation time series in stations with significant trends during 1961ndash2011
36 Comparison of Results Results from both statistical testsMK and SR were consistent with each otherThe percentagesof statistically significant cases to total tested cases for theMK and SR tests were 32 and 30 respectively showingagreement across methods This consistency in statisticalperformance was also found in other studies [24 28]
4 Discussion
This study investigated variability in monthly seasonal andannual precipitation at 15 stations in the Swat River basinover a 51-year study period (1961ndash2011) Precipitation trendswere also analyzed for each subbasin and entire Swat Riverbasin The mean annual precipitation at different stationsshowed considerable variation with a standard deviationof 1768mm from the mean annual rainfall of 694mmThe Saidu Sharif Mardan and Charsadda stations showedsignificant positive trends (increased precipitation over time)at 5 significance level in the annual precipitation series
The maximum number of significant changes in monthlyprecipitation over time was detected at Saidu Sharif Abazaiand Khairabad stations Saidu Sharif station showed themaximum increasing slope (indicating sharpest change overtime) of 748mmyear among the selected stations in the SwatRiver basin
These study results follow the same statistical trendsreported by Hartmann and Andresky [35] for northwestparts of Pakistan Findings were consistent with results fromDimri [56] Ghaffar and Javid [57] and Rasul [58] whereinthey found statistically significant increasing trends in winterprecipitation for northwest areas of Pakistan The resultsof this analysis also support finding of Hanif et al [37]wherein they found significant variations in summer seasonprecipitation These variations in precipitation trends maylead Pakistan towards more water related disasters suchas droughts and floods in the near future Basistha et al[59] proposed possible causes of the changing precipitationtrends such as global climate shifts [60] dwindling global
Advances in Meteorology 13
Table 6 MK and SR results for seasonal and annual precipitation time series in entire basin and subbasin of Swat River
Subbasin Change (mmyear) Test Winter Spring Summer Autumn Annual
A1 minus073 MK 055 minus024 minus242lowast 305lowast minus034SR 057 001 minus227lowast 347lowast 118
A2 minus090 MK 128 minus023 minus385lowast 158 minus081SR 118 minus035 minus444lowast 164 minus090
A3 030 MK 266lowast 016 minus265lowast 375lowast 024SR 295lowast 027 minus309lowast 460lowast 040
A4 218 MK 242lowast 060 minus021 024 166SR 272lowast 054 minus037 043 173
A 048 MK 214lowast minus011 minus297lowast 307lowast 042SR 225lowast minus014 minus340lowast 336lowast 038
lowastSignificant trend at 5 significance level of two-tailed test
monsoon circulation [61] decline in forest cover [62 63] landuse changes and practices (eg irrigated agriculture) [64 65]and increasing aerosols from anthropogenic activities [66]
5 Conclusions
This paper analyzed trends in monthly seasonal and annualprecipitation in the Swat River basin over the 51-year studyperiod (1961ndash2011) A mix of positive and negative trendswas observed at various stations and subbasins The monthsof June November July and August showed the maximumnumber of significant cases at various stations in monthlyprecipitation The trends were positive in May and June andwere negative in July and August This indicates a shift inprecipitation series on monthly scale Significant positivetrends were detected in winter and autumn and annuallynegative trends were seen in spring and summer seasonsSaidu Sharif Mardan and Charsadda stations exhibitedsignificant positive trends in annual precipitation at a 95confidence level the remaining stations did not experiencea statistically significant trend
For the entire Swat River basin no significant trendswere detected in any subbasin for the annual precipitationseries Seasonally winter and autumn experienced significantpositive trends and summer experienced negative trends indifferent subbasins in the Swat River basin Most statisticallysignificant trend cases under different scenarios were positive(61)The results obtainedwith theMann-Kendall (MK) andSpearmanrsquos rho tests showed agreement in their assessmentsof monthly seasonal and annual precipitation trends Thevariability of negative and positive trends at various stationspoints to the need for more detailed studies on the climatechange of this region
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgments
The authors thank Pakistan Meteorological Department(PMD) Water and Power Development Authority
(WAPDA) Pakistan and Snowy Mountains EngineeringCorporation (SMEC) for providing cost-free data for thisstudy
References
[1] M D Rahman and M Begum ldquoApplication of non parametrictest for trend detection of rainfall in the largest Island ofBangladeshrdquo ARPN Journal of Earth Sciences vol 2 no 2 pp40ndash44 2013
[2] IPCCThePhysical Science Basis Contribution ofWorkingGroupI to the Fourth Assessment Report of the Intergovernmental Panelon Climate Change Cambridge University Press CambridgeUK 2007
[3] A B Farooq and A H Khan ldquoClimate change perspectivein Pakistanrdquo in Proceedings of the Capacity Building APNWorkshop on Global Change Research pp 39ndash46 IslamabadPakistan 2004
[4] Z Z Hu S Yang and R Wu ldquoLong-term climate variationsin China and global warming signalsrdquo Journal of GeophysicalResearch vol 108 no D19 2003
[5] P Zhai and X Pan ldquoTrends in temperature extremes during1951ndash1999 in Chinardquo Geophysical Research Letters vol 30 no17 p 1913 2003
[6] D Duhan and A Pandey ldquoStatistical analysis of long termspatial and temporal trends of precipitation during 1901ndash2002at Madhya Pradesh Indiardquo Atmospheric Research vol 122 pp136ndash149 2013
[7] B J Peterson RM Holmes JWMcClelland et al ldquoIncreasingriver discharge to the Arctic oceanrdquo Science vol 298 no 5601pp 2171ndash2173 2002
[8] N I Savelieva I P Semiletov L N Vasilevskaya and S PPugach ldquoA climate shift in seasonal values of meteorologicaland hydrological parameters for Northeastern Asiardquo Progress inOceanography vol 47 no 2ndash4 pp 279ndash297 2000
[9] Y F Shi Y P Shen and R J Hu ldquoPreliminary study on signalimpact and foreground of climatic shift from warm-dry towarm-humid in Northwest Chinardquo Journal of Glaciology andGeocryology vol 24 pp 219ndash226 2002 (Chinese)
[10] S Farhana and M M Rahman ldquoCharacterizing rainfall trendin Bangladesh by temporal statistics analysisrdquo in Proceedings ofthe 4th Annual Paper Meet and 1st Civil Engineering CongressDhaka Bangladesh 2011
[11] R H Rimi S H Rahman S Karmakar and S G HussainldquoTrend analysis of climate change and investigation on its
14 Advances in Meteorology
probable impacts on rice production at Satkhira BangladeshrdquoPakistan Journal of Meteorology vol 6 no 11 pp 37ndash50 2014
[12] E R Dahmen and M J Hall Screening of Hydrological DataTests for Stationarity and Relative Consistency Publication 49ILRI Wageningen The Netherlands 1990
[13] Q Zhang C Liu C-Y Xu Y Xu and T Jiang ldquoObserved trendsof annual maximumwater level and streamflow during past 130years in the Yangtze River basin Chinardquo Journal of Hydrologyvol 324 no 1-4 pp 255ndash265 2006
[14] H Chen S Guo C-Y Xu and V P Singh ldquoHistorical tem-poral trends of hydro-climatic variables and runoff responseto climate variability and their relevance in water resourcemanagement in the Hanjiang basinrdquo Journal of Hydrology vol344 no 3-4 pp 171ndash184 2007
[15] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 pp 245ndash259 1945
[16] M G Kendall Rank CorrelationMethods Griffin London UK1975
[17] E L Lehmann Nonparametrics Statistical Methods Based onRanks Holden-Day San Francisco Calif USA 1975
[18] R Sneyers ldquoOn the statistical analysis of series of observationsrdquoTechnical Note 143 WMO no 415 World MeteorologicalOrganization 1990
[19] A Longobardi and P Villani ldquoTrend analysis of annual andseasonal rainfall time series in the Mediterranean areardquo Inter-national Journal of Climatology vol 30 no 10 pp 1538ndash15462010
[20] Z YanmingW Jun andW Xinhua ldquoStudy on the change trendof precipitation and temperature in Kunming city based onMann-Kendall analysisrdquo in Future Computer CommunicationControl and Automation vol 119 of Advances in Intelligent andSoft Computing pp 505ndash513 Springer Berlin Germany 2011
[21] X L Yang L R Xu K K Liu C H Li J Hu and X H XialdquoTrend in temperature and precipitation in the ZhangweinanRiver Basin during the last 53 yearsrdquo Procedia EnvironmentalSciences vol 13 pp 1966ndash1974 1966
[22] Z F Yang Y Yan and Q Liu ldquoThe relationship of streamflow-precipitation-temperature in the Yellow River Basin of Chinaduring 1961ndash2000rdquo Procedia Environmental Sciences vol 13 pp2336ndash2345 2012
[23] Q-X Wang X-H Fan Z-D Qin and M-B Wang ldquoChangetrends of temperature and precipitation in the Loess PlateauRegion of China 1961ndash2010rdquo Global and Planetary Change vol92-93 pp 138ndash147 2012
[24] S Yue P Pilon and G Cavadias ldquoPower of the Mann-Kendalland Spearmanrsquos rho tests for detecting monotonic trends inhydrological seriesrdquo Journal of Hydrology vol 259 no 1ndash4 pp254ndash271 2002
[25] E Kahya and S Kalaycı ldquoTrend analysis of streamflow inTurkeyrdquo Journal of Hydrology vol 289 pp 128ndash144 2004
[26] Z L Li Z X Xu J Y Li and Z J Li ldquoShift trend and stepchanges for runoff time series in the Shiyang River BasinNorthwest Chinardquo Hydrological Processes vol 22 no 23 pp4639ndash4646 2008
[27] C Yaning X Changchun H Xingming et al ldquoFifty-yearclimate change and its effect on annual runoff in the TarimRiverBasin Chinardquo Quaternary International vol 208 no 1-2 pp53ndash61 2009
[28] M Shadmani SMarofi andMRoknian ldquoTrend analysis in ref-erence evapotranspiration usingMann-Kendall and SpearmanrsquosRho tests in arid regions of IranrdquoWater Resources Managementvol 26 no 1 pp 211ndash224 2012
[29] H Rehman and A Kamal ldquoIndus Basin River system-floodingand flood mitigationrdquo 2005 httparchiveriversymposiumcom2005indexphpelement=38
[30] Pakistan Meteorological Department (PMD) National PlanStrengthening National Capacities for Multi-hazard EarlyWarn-ing amp Response System 2006
[31] National Disaster Management Authority (NDMA) 2007National Disaster Risk Management Framework Governmentof Pakistan httpwwwndmagovpknew
[32] N H Hashimi Q T M Siddiqui A R Ghumman M AKamal and H R Mughal ldquoA critical analysis of 2010 floods inPakistanrdquo African Journal of Agricultural Research vol 7 no 7pp 1054ndash1067 2012
[33] FFC ldquoFederal Flood Commission of Pakistanrdquo Annual FloodReport-2010 2011 httpwwwffcgovpkdownloadfloodarc-hieveAnnualreport2010pdf
[34] N Gronewold and Climatewire ldquoIs the Flooding in Pakistan aClimate Change Disasterrdquo WMN 2010 httpwwwscientific-americancomarticleis-the-flooding-in-pakist
[35] H Hartmann and L Andresky ldquoFlooding in the Indus Riverbasinmdasha spatiotemporal analysis of precipitation recordsrdquoGlobal and Planetary Change vol 107 pp 25ndash35 2013
[36] S Salma S Rehman andM A Shah ldquoRainfall trends in differ-ent climate zones of Pakistanrdquo Pakistan Journal of Meteorologyvol 9 no 17 pp 37ndash47 2012
[37] M Hanif A H Khan and S Adnan ldquoLatitudinal precipitationcharacteristics and trends in Pakistanrdquo Journal ofHydrology vol492 pp 266ndash272 2013
[38] A Imran Q Zaman and M Afzal ldquoTemporal trends in thepeak monsoonal precipitation events over Northeast PakistanrdquoPakistan Journal of Meteorology vol 10 no 19 pp 19ndash30 2013
[39] S B Cheema and M Hanif ldquoSeasonal precipitation variationover Punjab provincerdquo Pakistan Journal of Meteorology vol 10no 19 pp 61ndash82 2013
[40] H Hartmann and H Buchanan ldquoTrends in extreme precipita-tion events in the indus River Basin and flooding in PakistanrdquoAtmosphere-Ocean vol 52 no 1 pp 77ndash91 2014
[41] ldquoProvincial Disaster Management Authority (PDMA 2012)Monsoon Contingency Plan-Khyber-Pakhtunkhwardquo 2012httpwwwndmagovpkDocumentsContingency Plan2012CP KPpdf
[42] Snowy Mountains Engineering Corporation Munda DamConstruction Project Detailed Design Report SMEC LahorePakistan 2014
[43] H Alexandersson ldquoA homogeneity test applied to precipitationdatardquo Journal of Climatology vol 6 no 6 pp 661ndash675 1986
[44] HAlexandersson andAMoberg ldquoHomogenization of Swedishtemperature data Part I homogeneity test for linear trendsrdquoInternational Journal of Climatology vol 17 no 1 pp 25ndash341997
[45] T A Buishand ldquoSome methods for testing the homogeneity ofrainfall recordsrdquo Journal of Hydrology vol 58 no 1-2 pp 11ndash271982
[46] M N Khaliq and T B M J Ouarda ldquoOn the critical values ofthe standard normal homogeneity test (SNHT)rdquo InternationalJournal of Climatology vol 27 no 5 pp 681ndash687 2007
[47] K H Hamed and A Ramachandra Rao ldquoA modified Mann-Kendall trend test for autocorrelated datardquo Journal of Hydrologyvol 204 no 1ndash4 pp 182ndash196 1998
[48] B Onoz and M Bayazit ldquoBlock bootstrap for Mann-Kendalltrend test of serially dependent datardquoHydrological Processes vol26 no 23 pp 3552ndash3560 2012
Advances in Meteorology 15
[49] M Yaseen H A Bhatti T Rientjes G Nabi and M LatifldquoTemporal and spatial variations in summer flows of upperIndus Basin Pakistanrdquo inProceedings of the 72ndAnnual Sessionof Pakistan Engineering Congress Paper no 747 pp 315ndash3342013
[50] G C Blain ldquoThe Mann-Kendall test the need to consider theinteraction between serial correlation and trendrdquo AgriculturalEngineering vol 35 no 4 2013
[51] M Yaseen T Rientjes G Nabi H ur-Rehman and M LatifldquoAssessment of recent temperature trends inManglawatershedrdquoJournal of Himalayan Earth Sciences vol 47 no 1 pp 107ndash1212014
[52] P K Sen ldquoEstimates of the regression coefficient based onKendallrsquos taurdquo Journal of the American Statistical Associationvol 63 no 324 pp 1379ndash1389 1968
[53] W S Cleveland ldquoRobust locally weighted regression andsmoothing scatterplotsrdquoThe Journal of the American StatisticalAssociation vol 74 no 368 pp 829ndash836 1979
[54] W S Cleveland ldquoGraphs in scientific publicationsrdquoThe Ameri-can Statistician vol 38 no 4 pp 261ndash269 1984
[55] D R Helsel and R M Hirsch ldquoStatistical methods in waterresourcesrdquo inTechniques ofWater Resources Investigations Book4 chapter A3 p 522 US Geological Survey 2002
[56] A P Dimri ldquoSurface and upper air fields during extreme winterprecipitation over the western Himalayasrdquo Pure and AppliedGeophysics vol 163 no 8 pp 1679ndash1698 2006
[57] A Ghaffar and M Javid ldquoImpact of global warming onmonsoon variability in Pakistanrdquo The Journal of Animal andPlant Sciences vol 21 no 1 pp 107ndash110 2011
[58] G Rasul ldquoClimate Data and Modelling Analysis of the IndusRegionrdquo Pakistan Meteorological Department (PMD) 2012httpwwfpakorgccappdfClimate Data Modelling20An-alysis20of20the20Indus20Ecoregionpdf
[59] A Basistha D S Arya and N K Goel ldquoAnalysis of historicalchanges in rainfall in the Indian Himalayasrdquo InternationalJournal of Climatology vol 29 no 4 pp 555ndash572 2009
[60] P G Baines ldquoThe late 1960s global climate shift and its influenceon the Southern Hemisphererdquo in Proceedings of 8 ICSHMO pp1477ndash1482 INPE Foz do Iguacu Brazil 2006
[61] K Duan and T Yao ldquoMonsoon variability in the Himalayasunder the condition of global warmingrdquo Journal of the Mete-orological Society of Japan vol 81 no 2 pp 251ndash257 2003
[62] U S Nair R O Lawton R M Welch and R A Pielke SrldquoImpact of land use on Costa Rican tropical montane cloudforests sensitivity of cumulus cloud field characteristics tolowland deforestationrdquo Journal of Geophysical Research D vol108 no 7 pp 4206ndash4219 2003
[63] R Avissar and D Werth ldquoGlobal hydroclimatological tele-connections resulting from tropical deforestationrdquo Journal ofHydrometeorology vol 6 no 2 pp 134ndash145 2005
[64] R A Pielke Sr J Adegoke A Beltran-Przekurat et al ldquoAnoverview of regional land-use and land-cover impacts onrainfallrdquo Tellus B Chemical and Physical Meteorology vol 59no 3 pp 587ndash601 2007
[65] N Ramankutty C Delire and P Snyder ldquoFeedbacks betweenagriculture and climate an illustration of the potential unin-tended consequences of human land use activitiesrdquo Global andPlanetary Change vol 54 no 1-2 pp 79ndash93 2006
[66] V Ramanathan C Chung D Kim et al ldquoAtmospheric brownclouds impacts on South Asian climate and hydrological cyclerdquoProceedings of the National Academy of Sciences of the UnitedStates of America vol 102 no 15 pp 5326ndash5333 2005
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
EarthquakesJournal of
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Hindawi Publishing Corporationhttpwwwhindawicom
Applied ampEnvironmentalSoil Science
Volume 2014
Mining
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Hindawi Publishing Corporation httpwwwhindawicom Volume 2014
International Journal of
Geophysics
OceanographyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal ofPetroleum Engineering
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
GeochemistryHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Atmospheric SciencesInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OceanographyHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Advances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MineralogyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MeteorologyAdvances in
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Paleontology JournalHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geological ResearchJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geology Advances in
Advances in Meteorology 7
Table3MKandSR
tests
results
forp
recipitatio
nin
mon
thlytim
eseries
Station
Test
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Thalozom
MK
minus063
minus10
9minus042
minus219lowast
minus033
272lowast
minus080
minus094
minus029
010
146
030
SRminus044
minus10
1minus039
minus215lowast
minus040
293lowast
minus079
minus10
3minus013
028
141
013
Drosh
MK
minus008
minus024
016
minus067
063
151
minus19
4minus316lowast
minus063
040
103
001
SRminus014
minus001
008
minus079
067
173
minus18
7minus336lowast
minus050
039
101
017
Kalam
MK
minus037
minus067
033
minus221lowast
minus063
219lowast
minus115
minus10
4minus054
014
120
017
SRminus023
minus052
023
minus213lowast
minus064
229lowast
minus113
minus10
7minus043
014
091
minus066
Dir
MK
000
minus063
minus248lowast
minus021
minus079
112
minus015
003
174
minus13
1minus034
minus089
SRminus016
minus062
minus280lowast
minus018
minus10
010
7minus001
minus002
203lowast
minus16
3minus049
minus10
1
Madyan
MK
089
075
110
minus083
086
353lowast
minus312lowast
minus338lowast
minus023
190
272lowast
134
SR086
070
113
minus067
085
426lowast
minus324lowast
minus398lowast
minus016
200
301lowast
132
Khaira
bad
MK
091
minus068
minus021
minus080
201lowast
385lowast
minus312lowast
minus348lowast
minus019
268lowast
292lowast
112
SR082
minus072
minus028
minus079
204lowast
446lowast
minus334lowast
minus460lowast
minus017
308lowast
325lowast
097
ToorCa
mp
MK
192
093
045
minus070
minus044
minus086
minus291lowast
minus296lowast
minus227lowast
minus201lowast
094
028
SR17
8085
025
minus082
minus047
minus091
minus317lowast
minus361lowast
minus279lowast
minus233lowast
104
020
SaiduSh
arif
MK
274lowast
246lowast
222lowast
182
285lowast
327lowast
minus334lowast
minus309lowast
003
319lowast
357lowast
210lowast
SR302lowast
262lowast
261lowast
205lowast
324lowast
383lowast
minus360lowast
minus387lowast
020
364lowast
405lowast
217lowast
Malakand
MK
105
minus17
2minus115
010
228lowast
322lowast
minus318lowast
minus293lowast
016
350lowast
273lowast
149
SR099
minus202lowast
minus13
2022
254lowast
302lowast
minus380lowast
minus382lowast
023
397lowast
223lowast
091
Kulang
iMK
070
minus099
minus294lowast
minus14
4minus062
036
000
174
291lowast
minus16
4minus003
minus204lowast
SR059
minus10
4minus315lowast
minus14
1minus081
024
008
165
336lowast
minus18
5minus031
minus231lowast
Ambahar
MK
031
minus066
minus284lowast
minus10
5minus115
060
018
060
304lowast
minus13
6minus021
minus18
0SR
038
minus070
minus282lowast
minus111
minus118
058
019
034
356lowast
minus15
1minus029
minus201lowast
Abazai
MK
233lowast
minus025
minus091
137
292lowast
449lowast
minus262lowast
minus10
710
2331lowast
392lowast
261lowast
SR222lowast
minus029
minus090
162
289lowast
435lowast
minus307lowast
minus10
913
7385lowast
366lowast
272lowast
Mardan
MK
243lowast
134
041
001
105
070
014
minus016
100
minus058
minus13
1minus13
7SR
253lowast
134
050
011
110
072
025
minus020
088
minus051
minus115
minus115
Charsadd
aMK
232lowast
109
032
minus012
015
034
014
minus014
056
minus10
4minus217lowast
minus15
9SR
237lowast
109
026
minus024
032
044
022
minus033
043
minus097
minus204lowast
minus13
1
Risalpur
MK
191
128
006
minus027
minus033
minus037
minus006
minus063
minus026
minus14
6minus18
7minus217lowast
SR213lowast
113
006
minus036
minus017
minus025
minus005
minus072
minus026
minus15
0minus211lowast
minus216lowast
lowast
Sign
ificant
trend
at5
significance
leveloftwo-tailedtest
8 Advances in Meteorology
Jan Feb Mar Apr
May Jun Jul Aug
Sep Oct Nov Dec
N
0 5 10 25
Scale
(km)
Significant increasing trendSignificant decreasing trend
No trend
Figure 3 Location of sites with increasing decreasing and no trends at 5 significance level for the monthly precipitation time series
The results show that trends at Saidu Sharif Madyanand Kalam were more rapid (eg sharper increases anddecreases) compared to other stations The Saidu Sharifstation had the maximum negative decline in monthly pre-cipitation (183mmmonth) as well as the maximum positiveincrease (143mmmonth) during the months of July andMarch respectively Figure 4 shows the trends in maximummonthly precipitation variation at the Saidu Sharif station
34 Seasonal and Annual Analysis The MK and SR testswere also used to identify trends in seasonal and annualprecipitation between 1961 and 2011 Table 4 shows the resultsSimilar to the monthly analysis results from both statisticaltests MK and SR were consistent with one another A mixof negative and positive trends was seen at different stationsThalozom Kalam and Dir stations which had shown trends
with the monthly time scale did not exhibit statisticallysignificant trends for the seasonal and annual precipitationtime series At Madyan Khairabad and Malakand stationsthere were significant negative trends in the summer andpositive trends in the autumn Significant negative trendswere observed in the spring season only at ToorCampKulangi and Ambahar stations For the annual precipitationseries significant positive trends were detected only at SaiduSharif Mardan and Charsadda stations At other stationssignificant positive trends were seen for winter and autumnseasons and for the annual precipitation series howevernegative trends were detected in spring and summer seasonsFigure 5 presents the spatial distribution of seasonal andannual precipitation trends
The Saidu Sharif station showed the maximum positivetrend in annual precipitation series (748mmyear) across
Advances in Meteorology 9
0
100
200
300
400
500
600
700
800
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
mon
th)
Year
Saidu Sharif station(March)
(a)
0
100
200
300
400
500
600
700
800
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
mon
th)
Year
Saidu Sharif station(July)
(b)
Figure 4 Variations of monthly precipitation time series in stations with most significant trends during 1961ndash2011
Table 4 MK and SR tests results for precipitation in seasonal and annual time series
Station Test Winter Spring Summer Autumn Annual
Thalozom MK minus120 minus162 minus120 148 minus149SR minus114 minus152 minus110 135 minus145
Drosh MK 042 minus078 minus196 097 minus044SR 049 minus074 minus209lowast 127 minus048
Kalam MK minus062 minus139 minus171 160 minus110SR minus037 minus121 minus158 157 minus087
Dir MK minus028 minus148 minus047 minus076 minus138SR minus062 minus150 minus058 minus097 minus146
Madyan MK 120 003 minus258lowast 365lowast 042SR 137 033 minus244lowast 421lowast 078
Khairabad MK 026 minus065 minus302lowast 325lowast minus073SR 021 minus076 minus353lowast 364lowast minus072
ToorCamp MK minus063 minus203lowast 024 minus073 minus044SR minus096 minus217lowast 023 minus092 minus159
Saidu Sharif MK 346lowast 239lowast minus156 069 328lowast
SR 404lowast 280lowast minus156 148 278lowast
Malakand MK minus070 minus110 minus270lowast 337lowast minus119SR minus068 minus115 minus319lowast 373lowast minus140
Kulangi MK minus122 minus261lowast 031 minus099 minus144SR minus156 minus284lowast 037 minus127 minus172
Ambahar MK minus066 minus206lowast minus063 minus099 minus157SR minus076 minus224lowast minus058 minus110 minus141
Abazai MK 179 minus015 minus099 429lowast 096SR 217lowast 007 minus072 604lowast 122
Mardan MK 281lowast 145 095 minus102 259lowast
SR 310lowast 134 098 minus085 280lowast
Charsadda MK 266lowast 097 073 minus194 214lowast
SR 293lowast 088 060 minus176 217lowast
Risalpur MK 243lowast 044 minus006 minus154 198SR 254lowast 040 minus005 minus190 195
lowastSignificant trend at 5 significance level of two-tailed test
10 Advances in Meteorology
N
0 5 10 25
Scale
(km)
Significant increasing trendSignificant decreasing trend
No trend
Winter
Autumn Annual
Spring Summer
Figure 5 Location of sites with increasing decreasing and no trends at 5 significance level for the seasonal and annual precipitation timeseries
study stations from 1961 to 2011 theThalozom station showeda negative trend with a decreasing rate of 370mmyearFigure 6 displays the results of the magnitude of variationin the annual precipitation for the Saidu Sharif MardanCharsadda andThalozom stations
35 Trend Analysis over Entire River Basin The effect ofclimate change on precipitation was also analyzed for theentire Swat River basin by applying the MK and SR testson monthly seasonal and annual scale As Figure 1 showedthe entire Swat River catchment (A) is divided into foursubbasins upper subbasin (A1) Panjkora subbasin (A2)Ambahar subbasin (A3) and Lower subbasin (A4) Table 5presents trends in monthly precipitation across the subbasinsand for the full basin The table shows significant positivetrends in the months of June and November for the uppersubbasin (A1) and the entire Swat River basin (A) negativetrends were seen in these locations in July and August Inthe Panjkora subbasin (A2) statistically significant positivetrends were identified over time in June a negative trendwas seen from July to September The maximum number ofsignificant cases (8) was observed in data from the Ambaharsubbasin (A3)The Lower subbasin (A4) showed a significantpositive trend only during January no significant trendsin other months were identified As a simpler summarysignificant negative trends in precipitation over time were
seen from July to September positive trends over time wereseen in January May June and October to December indifferent Swat River subbasins
To detect precipitation trends in each subbasin and entireSwat River basin the MK and SR tests were again appliedto seasonal and annual precipitation data for the 51-yearstudy period (1961ndash2011) As Table 6 shows both testmethodsshowed similar results The upper subbasin (A1) experiencedstatistically significant negative trends in the summer andpositive trends in the autumn The Panjkora subbasin (A2)and Lower subbasin (A4) showed significant negative trendsin the summer and positive trends in the winter Significantpositive trends were found across the subbasins in winterand autumn seasons however there was a negative trendin summer at Ambahar subbasin (A3) and across the entireSwat River basin (A) For the annual and spring precipitationtime series there were no statistically significant trendsSignificant positive trendswere seen inwinter and autumn insummer negative trends were seen across different subbasinsand the full Swat River basin
The Lower subbasin exhibited the maximum positivetrend over time (218mmyear) in the weighted annualprecipitation time series the Panjkora subbasin showed anegative trend with a decreasing rate of participation at090mmyear The entire Swat River basin showed a positivetrend in precipitation (048mmyear) as shown in Table 6
Advances in Meteorology 11
Table5MKandSR
tests
results
form
onthlyprecipitatio
ntim
eseriesinentireb
asin
andsubb
asinso
fSwatRiver
Subb
asin
Test
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
A1
MK
047
010
071
minus12
3041
349lowast
minus288lowast
minus318lowast
minus018
143
250lowast
094
SR045
006
074
minus098
047
409lowast
minus299lowast
minus363lowast
minus018
159
277lowast
094
A2
MK
107
080
016
minus093
021
201lowast
minus354lowast
minus416lowast
minus202lowast
000
187
062
SR095
072
001
minus099
013
231lowast
minus386lowast
minus486lowast
minus224lowast
011
200
063
A3
MK
250lowast
102
minus036
065
297lowast
390lowast
minus297lowast
minus255lowast
minus044
305lowast
295lowast
229lowast
SR267lowast
089
minus009
070
311lowast
479lowast
minus354lowast
minus322lowast
minus052
376lowast
365lowast
260lowast
A4
MK
237lowast
088
minus006
minus050
122
164
minus063
minus083
000
020
050
minus040
SR246lowast
084
minus001
minus059
117
182
minus059
minus090
001
045
023
minus046
AMK
185
110
013
minus062
123
369lowast
minus255lowast
minus361lowast
minus065
174
268lowast
070
SR17
010
4018
minus079
127
422lowast
minus277lowast
minus401lowast
minus070
181
299lowast
073
lowast
Sign
ificant
trend
at5
significance
leveloftwo-tailedtest
12 Advances in Meteorology
0
500
1000
1500
2000
2500
3000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Saidu Sharif station
(a)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Mardan station
(b)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Charsadda station
(c)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Thalozom station
(d)
Figure 6 Variations of annual precipitation time series in stations with significant trends during 1961ndash2011
36 Comparison of Results Results from both statistical testsMK and SR were consistent with each otherThe percentagesof statistically significant cases to total tested cases for theMK and SR tests were 32 and 30 respectively showingagreement across methods This consistency in statisticalperformance was also found in other studies [24 28]
4 Discussion
This study investigated variability in monthly seasonal andannual precipitation at 15 stations in the Swat River basinover a 51-year study period (1961ndash2011) Precipitation trendswere also analyzed for each subbasin and entire Swat Riverbasin The mean annual precipitation at different stationsshowed considerable variation with a standard deviationof 1768mm from the mean annual rainfall of 694mmThe Saidu Sharif Mardan and Charsadda stations showedsignificant positive trends (increased precipitation over time)at 5 significance level in the annual precipitation series
The maximum number of significant changes in monthlyprecipitation over time was detected at Saidu Sharif Abazaiand Khairabad stations Saidu Sharif station showed themaximum increasing slope (indicating sharpest change overtime) of 748mmyear among the selected stations in the SwatRiver basin
These study results follow the same statistical trendsreported by Hartmann and Andresky [35] for northwestparts of Pakistan Findings were consistent with results fromDimri [56] Ghaffar and Javid [57] and Rasul [58] whereinthey found statistically significant increasing trends in winterprecipitation for northwest areas of Pakistan The resultsof this analysis also support finding of Hanif et al [37]wherein they found significant variations in summer seasonprecipitation These variations in precipitation trends maylead Pakistan towards more water related disasters suchas droughts and floods in the near future Basistha et al[59] proposed possible causes of the changing precipitationtrends such as global climate shifts [60] dwindling global
Advances in Meteorology 13
Table 6 MK and SR results for seasonal and annual precipitation time series in entire basin and subbasin of Swat River
Subbasin Change (mmyear) Test Winter Spring Summer Autumn Annual
A1 minus073 MK 055 minus024 minus242lowast 305lowast minus034SR 057 001 minus227lowast 347lowast 118
A2 minus090 MK 128 minus023 minus385lowast 158 minus081SR 118 minus035 minus444lowast 164 minus090
A3 030 MK 266lowast 016 minus265lowast 375lowast 024SR 295lowast 027 minus309lowast 460lowast 040
A4 218 MK 242lowast 060 minus021 024 166SR 272lowast 054 minus037 043 173
A 048 MK 214lowast minus011 minus297lowast 307lowast 042SR 225lowast minus014 minus340lowast 336lowast 038
lowastSignificant trend at 5 significance level of two-tailed test
monsoon circulation [61] decline in forest cover [62 63] landuse changes and practices (eg irrigated agriculture) [64 65]and increasing aerosols from anthropogenic activities [66]
5 Conclusions
This paper analyzed trends in monthly seasonal and annualprecipitation in the Swat River basin over the 51-year studyperiod (1961ndash2011) A mix of positive and negative trendswas observed at various stations and subbasins The monthsof June November July and August showed the maximumnumber of significant cases at various stations in monthlyprecipitation The trends were positive in May and June andwere negative in July and August This indicates a shift inprecipitation series on monthly scale Significant positivetrends were detected in winter and autumn and annuallynegative trends were seen in spring and summer seasonsSaidu Sharif Mardan and Charsadda stations exhibitedsignificant positive trends in annual precipitation at a 95confidence level the remaining stations did not experiencea statistically significant trend
For the entire Swat River basin no significant trendswere detected in any subbasin for the annual precipitationseries Seasonally winter and autumn experienced significantpositive trends and summer experienced negative trends indifferent subbasins in the Swat River basin Most statisticallysignificant trend cases under different scenarios were positive(61)The results obtainedwith theMann-Kendall (MK) andSpearmanrsquos rho tests showed agreement in their assessmentsof monthly seasonal and annual precipitation trends Thevariability of negative and positive trends at various stationspoints to the need for more detailed studies on the climatechange of this region
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgments
The authors thank Pakistan Meteorological Department(PMD) Water and Power Development Authority
(WAPDA) Pakistan and Snowy Mountains EngineeringCorporation (SMEC) for providing cost-free data for thisstudy
References
[1] M D Rahman and M Begum ldquoApplication of non parametrictest for trend detection of rainfall in the largest Island ofBangladeshrdquo ARPN Journal of Earth Sciences vol 2 no 2 pp40ndash44 2013
[2] IPCCThePhysical Science Basis Contribution ofWorkingGroupI to the Fourth Assessment Report of the Intergovernmental Panelon Climate Change Cambridge University Press CambridgeUK 2007
[3] A B Farooq and A H Khan ldquoClimate change perspectivein Pakistanrdquo in Proceedings of the Capacity Building APNWorkshop on Global Change Research pp 39ndash46 IslamabadPakistan 2004
[4] Z Z Hu S Yang and R Wu ldquoLong-term climate variationsin China and global warming signalsrdquo Journal of GeophysicalResearch vol 108 no D19 2003
[5] P Zhai and X Pan ldquoTrends in temperature extremes during1951ndash1999 in Chinardquo Geophysical Research Letters vol 30 no17 p 1913 2003
[6] D Duhan and A Pandey ldquoStatistical analysis of long termspatial and temporal trends of precipitation during 1901ndash2002at Madhya Pradesh Indiardquo Atmospheric Research vol 122 pp136ndash149 2013
[7] B J Peterson RM Holmes JWMcClelland et al ldquoIncreasingriver discharge to the Arctic oceanrdquo Science vol 298 no 5601pp 2171ndash2173 2002
[8] N I Savelieva I P Semiletov L N Vasilevskaya and S PPugach ldquoA climate shift in seasonal values of meteorologicaland hydrological parameters for Northeastern Asiardquo Progress inOceanography vol 47 no 2ndash4 pp 279ndash297 2000
[9] Y F Shi Y P Shen and R J Hu ldquoPreliminary study on signalimpact and foreground of climatic shift from warm-dry towarm-humid in Northwest Chinardquo Journal of Glaciology andGeocryology vol 24 pp 219ndash226 2002 (Chinese)
[10] S Farhana and M M Rahman ldquoCharacterizing rainfall trendin Bangladesh by temporal statistics analysisrdquo in Proceedings ofthe 4th Annual Paper Meet and 1st Civil Engineering CongressDhaka Bangladesh 2011
[11] R H Rimi S H Rahman S Karmakar and S G HussainldquoTrend analysis of climate change and investigation on its
14 Advances in Meteorology
probable impacts on rice production at Satkhira BangladeshrdquoPakistan Journal of Meteorology vol 6 no 11 pp 37ndash50 2014
[12] E R Dahmen and M J Hall Screening of Hydrological DataTests for Stationarity and Relative Consistency Publication 49ILRI Wageningen The Netherlands 1990
[13] Q Zhang C Liu C-Y Xu Y Xu and T Jiang ldquoObserved trendsof annual maximumwater level and streamflow during past 130years in the Yangtze River basin Chinardquo Journal of Hydrologyvol 324 no 1-4 pp 255ndash265 2006
[14] H Chen S Guo C-Y Xu and V P Singh ldquoHistorical tem-poral trends of hydro-climatic variables and runoff responseto climate variability and their relevance in water resourcemanagement in the Hanjiang basinrdquo Journal of Hydrology vol344 no 3-4 pp 171ndash184 2007
[15] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 pp 245ndash259 1945
[16] M G Kendall Rank CorrelationMethods Griffin London UK1975
[17] E L Lehmann Nonparametrics Statistical Methods Based onRanks Holden-Day San Francisco Calif USA 1975
[18] R Sneyers ldquoOn the statistical analysis of series of observationsrdquoTechnical Note 143 WMO no 415 World MeteorologicalOrganization 1990
[19] A Longobardi and P Villani ldquoTrend analysis of annual andseasonal rainfall time series in the Mediterranean areardquo Inter-national Journal of Climatology vol 30 no 10 pp 1538ndash15462010
[20] Z YanmingW Jun andW Xinhua ldquoStudy on the change trendof precipitation and temperature in Kunming city based onMann-Kendall analysisrdquo in Future Computer CommunicationControl and Automation vol 119 of Advances in Intelligent andSoft Computing pp 505ndash513 Springer Berlin Germany 2011
[21] X L Yang L R Xu K K Liu C H Li J Hu and X H XialdquoTrend in temperature and precipitation in the ZhangweinanRiver Basin during the last 53 yearsrdquo Procedia EnvironmentalSciences vol 13 pp 1966ndash1974 1966
[22] Z F Yang Y Yan and Q Liu ldquoThe relationship of streamflow-precipitation-temperature in the Yellow River Basin of Chinaduring 1961ndash2000rdquo Procedia Environmental Sciences vol 13 pp2336ndash2345 2012
[23] Q-X Wang X-H Fan Z-D Qin and M-B Wang ldquoChangetrends of temperature and precipitation in the Loess PlateauRegion of China 1961ndash2010rdquo Global and Planetary Change vol92-93 pp 138ndash147 2012
[24] S Yue P Pilon and G Cavadias ldquoPower of the Mann-Kendalland Spearmanrsquos rho tests for detecting monotonic trends inhydrological seriesrdquo Journal of Hydrology vol 259 no 1ndash4 pp254ndash271 2002
[25] E Kahya and S Kalaycı ldquoTrend analysis of streamflow inTurkeyrdquo Journal of Hydrology vol 289 pp 128ndash144 2004
[26] Z L Li Z X Xu J Y Li and Z J Li ldquoShift trend and stepchanges for runoff time series in the Shiyang River BasinNorthwest Chinardquo Hydrological Processes vol 22 no 23 pp4639ndash4646 2008
[27] C Yaning X Changchun H Xingming et al ldquoFifty-yearclimate change and its effect on annual runoff in the TarimRiverBasin Chinardquo Quaternary International vol 208 no 1-2 pp53ndash61 2009
[28] M Shadmani SMarofi andMRoknian ldquoTrend analysis in ref-erence evapotranspiration usingMann-Kendall and SpearmanrsquosRho tests in arid regions of IranrdquoWater Resources Managementvol 26 no 1 pp 211ndash224 2012
[29] H Rehman and A Kamal ldquoIndus Basin River system-floodingand flood mitigationrdquo 2005 httparchiveriversymposiumcom2005indexphpelement=38
[30] Pakistan Meteorological Department (PMD) National PlanStrengthening National Capacities for Multi-hazard EarlyWarn-ing amp Response System 2006
[31] National Disaster Management Authority (NDMA) 2007National Disaster Risk Management Framework Governmentof Pakistan httpwwwndmagovpknew
[32] N H Hashimi Q T M Siddiqui A R Ghumman M AKamal and H R Mughal ldquoA critical analysis of 2010 floods inPakistanrdquo African Journal of Agricultural Research vol 7 no 7pp 1054ndash1067 2012
[33] FFC ldquoFederal Flood Commission of Pakistanrdquo Annual FloodReport-2010 2011 httpwwwffcgovpkdownloadfloodarc-hieveAnnualreport2010pdf
[34] N Gronewold and Climatewire ldquoIs the Flooding in Pakistan aClimate Change Disasterrdquo WMN 2010 httpwwwscientific-americancomarticleis-the-flooding-in-pakist
[35] H Hartmann and L Andresky ldquoFlooding in the Indus Riverbasinmdasha spatiotemporal analysis of precipitation recordsrdquoGlobal and Planetary Change vol 107 pp 25ndash35 2013
[36] S Salma S Rehman andM A Shah ldquoRainfall trends in differ-ent climate zones of Pakistanrdquo Pakistan Journal of Meteorologyvol 9 no 17 pp 37ndash47 2012
[37] M Hanif A H Khan and S Adnan ldquoLatitudinal precipitationcharacteristics and trends in Pakistanrdquo Journal ofHydrology vol492 pp 266ndash272 2013
[38] A Imran Q Zaman and M Afzal ldquoTemporal trends in thepeak monsoonal precipitation events over Northeast PakistanrdquoPakistan Journal of Meteorology vol 10 no 19 pp 19ndash30 2013
[39] S B Cheema and M Hanif ldquoSeasonal precipitation variationover Punjab provincerdquo Pakistan Journal of Meteorology vol 10no 19 pp 61ndash82 2013
[40] H Hartmann and H Buchanan ldquoTrends in extreme precipita-tion events in the indus River Basin and flooding in PakistanrdquoAtmosphere-Ocean vol 52 no 1 pp 77ndash91 2014
[41] ldquoProvincial Disaster Management Authority (PDMA 2012)Monsoon Contingency Plan-Khyber-Pakhtunkhwardquo 2012httpwwwndmagovpkDocumentsContingency Plan2012CP KPpdf
[42] Snowy Mountains Engineering Corporation Munda DamConstruction Project Detailed Design Report SMEC LahorePakistan 2014
[43] H Alexandersson ldquoA homogeneity test applied to precipitationdatardquo Journal of Climatology vol 6 no 6 pp 661ndash675 1986
[44] HAlexandersson andAMoberg ldquoHomogenization of Swedishtemperature data Part I homogeneity test for linear trendsrdquoInternational Journal of Climatology vol 17 no 1 pp 25ndash341997
[45] T A Buishand ldquoSome methods for testing the homogeneity ofrainfall recordsrdquo Journal of Hydrology vol 58 no 1-2 pp 11ndash271982
[46] M N Khaliq and T B M J Ouarda ldquoOn the critical values ofthe standard normal homogeneity test (SNHT)rdquo InternationalJournal of Climatology vol 27 no 5 pp 681ndash687 2007
[47] K H Hamed and A Ramachandra Rao ldquoA modified Mann-Kendall trend test for autocorrelated datardquo Journal of Hydrologyvol 204 no 1ndash4 pp 182ndash196 1998
[48] B Onoz and M Bayazit ldquoBlock bootstrap for Mann-Kendalltrend test of serially dependent datardquoHydrological Processes vol26 no 23 pp 3552ndash3560 2012
Advances in Meteorology 15
[49] M Yaseen H A Bhatti T Rientjes G Nabi and M LatifldquoTemporal and spatial variations in summer flows of upperIndus Basin Pakistanrdquo inProceedings of the 72ndAnnual Sessionof Pakistan Engineering Congress Paper no 747 pp 315ndash3342013
[50] G C Blain ldquoThe Mann-Kendall test the need to consider theinteraction between serial correlation and trendrdquo AgriculturalEngineering vol 35 no 4 2013
[51] M Yaseen T Rientjes G Nabi H ur-Rehman and M LatifldquoAssessment of recent temperature trends inManglawatershedrdquoJournal of Himalayan Earth Sciences vol 47 no 1 pp 107ndash1212014
[52] P K Sen ldquoEstimates of the regression coefficient based onKendallrsquos taurdquo Journal of the American Statistical Associationvol 63 no 324 pp 1379ndash1389 1968
[53] W S Cleveland ldquoRobust locally weighted regression andsmoothing scatterplotsrdquoThe Journal of the American StatisticalAssociation vol 74 no 368 pp 829ndash836 1979
[54] W S Cleveland ldquoGraphs in scientific publicationsrdquoThe Ameri-can Statistician vol 38 no 4 pp 261ndash269 1984
[55] D R Helsel and R M Hirsch ldquoStatistical methods in waterresourcesrdquo inTechniques ofWater Resources Investigations Book4 chapter A3 p 522 US Geological Survey 2002
[56] A P Dimri ldquoSurface and upper air fields during extreme winterprecipitation over the western Himalayasrdquo Pure and AppliedGeophysics vol 163 no 8 pp 1679ndash1698 2006
[57] A Ghaffar and M Javid ldquoImpact of global warming onmonsoon variability in Pakistanrdquo The Journal of Animal andPlant Sciences vol 21 no 1 pp 107ndash110 2011
[58] G Rasul ldquoClimate Data and Modelling Analysis of the IndusRegionrdquo Pakistan Meteorological Department (PMD) 2012httpwwfpakorgccappdfClimate Data Modelling20An-alysis20of20the20Indus20Ecoregionpdf
[59] A Basistha D S Arya and N K Goel ldquoAnalysis of historicalchanges in rainfall in the Indian Himalayasrdquo InternationalJournal of Climatology vol 29 no 4 pp 555ndash572 2009
[60] P G Baines ldquoThe late 1960s global climate shift and its influenceon the Southern Hemisphererdquo in Proceedings of 8 ICSHMO pp1477ndash1482 INPE Foz do Iguacu Brazil 2006
[61] K Duan and T Yao ldquoMonsoon variability in the Himalayasunder the condition of global warmingrdquo Journal of the Mete-orological Society of Japan vol 81 no 2 pp 251ndash257 2003
[62] U S Nair R O Lawton R M Welch and R A Pielke SrldquoImpact of land use on Costa Rican tropical montane cloudforests sensitivity of cumulus cloud field characteristics tolowland deforestationrdquo Journal of Geophysical Research D vol108 no 7 pp 4206ndash4219 2003
[63] R Avissar and D Werth ldquoGlobal hydroclimatological tele-connections resulting from tropical deforestationrdquo Journal ofHydrometeorology vol 6 no 2 pp 134ndash145 2005
[64] R A Pielke Sr J Adegoke A Beltran-Przekurat et al ldquoAnoverview of regional land-use and land-cover impacts onrainfallrdquo Tellus B Chemical and Physical Meteorology vol 59no 3 pp 587ndash601 2007
[65] N Ramankutty C Delire and P Snyder ldquoFeedbacks betweenagriculture and climate an illustration of the potential unin-tended consequences of human land use activitiesrdquo Global andPlanetary Change vol 54 no 1-2 pp 79ndash93 2006
[66] V Ramanathan C Chung D Kim et al ldquoAtmospheric brownclouds impacts on South Asian climate and hydrological cyclerdquoProceedings of the National Academy of Sciences of the UnitedStates of America vol 102 no 15 pp 5326ndash5333 2005
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ClimatologyJournal of
EcologyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
EarthquakesJournal of
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Hindawi Publishing Corporationhttpwwwhindawicom
Applied ampEnvironmentalSoil Science
Volume 2014
Mining
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Hindawi Publishing Corporation httpwwwhindawicom Volume 2014
International Journal of
Geophysics
OceanographyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal ofPetroleum Engineering
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
GeochemistryHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Atmospheric SciencesInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OceanographyHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Advances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MineralogyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MeteorologyAdvances in
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Paleontology JournalHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geological ResearchJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geology Advances in
8 Advances in Meteorology
Jan Feb Mar Apr
May Jun Jul Aug
Sep Oct Nov Dec
N
0 5 10 25
Scale
(km)
Significant increasing trendSignificant decreasing trend
No trend
Figure 3 Location of sites with increasing decreasing and no trends at 5 significance level for the monthly precipitation time series
The results show that trends at Saidu Sharif Madyanand Kalam were more rapid (eg sharper increases anddecreases) compared to other stations The Saidu Sharifstation had the maximum negative decline in monthly pre-cipitation (183mmmonth) as well as the maximum positiveincrease (143mmmonth) during the months of July andMarch respectively Figure 4 shows the trends in maximummonthly precipitation variation at the Saidu Sharif station
34 Seasonal and Annual Analysis The MK and SR testswere also used to identify trends in seasonal and annualprecipitation between 1961 and 2011 Table 4 shows the resultsSimilar to the monthly analysis results from both statisticaltests MK and SR were consistent with one another A mixof negative and positive trends was seen at different stationsThalozom Kalam and Dir stations which had shown trends
with the monthly time scale did not exhibit statisticallysignificant trends for the seasonal and annual precipitationtime series At Madyan Khairabad and Malakand stationsthere were significant negative trends in the summer andpositive trends in the autumn Significant negative trendswere observed in the spring season only at ToorCampKulangi and Ambahar stations For the annual precipitationseries significant positive trends were detected only at SaiduSharif Mardan and Charsadda stations At other stationssignificant positive trends were seen for winter and autumnseasons and for the annual precipitation series howevernegative trends were detected in spring and summer seasonsFigure 5 presents the spatial distribution of seasonal andannual precipitation trends
The Saidu Sharif station showed the maximum positivetrend in annual precipitation series (748mmyear) across
Advances in Meteorology 9
0
100
200
300
400
500
600
700
800
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
mon
th)
Year
Saidu Sharif station(March)
(a)
0
100
200
300
400
500
600
700
800
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
mon
th)
Year
Saidu Sharif station(July)
(b)
Figure 4 Variations of monthly precipitation time series in stations with most significant trends during 1961ndash2011
Table 4 MK and SR tests results for precipitation in seasonal and annual time series
Station Test Winter Spring Summer Autumn Annual
Thalozom MK minus120 minus162 minus120 148 minus149SR minus114 minus152 minus110 135 minus145
Drosh MK 042 minus078 minus196 097 minus044SR 049 minus074 minus209lowast 127 minus048
Kalam MK minus062 minus139 minus171 160 minus110SR minus037 minus121 minus158 157 minus087
Dir MK minus028 minus148 minus047 minus076 minus138SR minus062 minus150 minus058 minus097 minus146
Madyan MK 120 003 minus258lowast 365lowast 042SR 137 033 minus244lowast 421lowast 078
Khairabad MK 026 minus065 minus302lowast 325lowast minus073SR 021 minus076 minus353lowast 364lowast minus072
ToorCamp MK minus063 minus203lowast 024 minus073 minus044SR minus096 minus217lowast 023 minus092 minus159
Saidu Sharif MK 346lowast 239lowast minus156 069 328lowast
SR 404lowast 280lowast minus156 148 278lowast
Malakand MK minus070 minus110 minus270lowast 337lowast minus119SR minus068 minus115 minus319lowast 373lowast minus140
Kulangi MK minus122 minus261lowast 031 minus099 minus144SR minus156 minus284lowast 037 minus127 minus172
Ambahar MK minus066 minus206lowast minus063 minus099 minus157SR minus076 minus224lowast minus058 minus110 minus141
Abazai MK 179 minus015 minus099 429lowast 096SR 217lowast 007 minus072 604lowast 122
Mardan MK 281lowast 145 095 minus102 259lowast
SR 310lowast 134 098 minus085 280lowast
Charsadda MK 266lowast 097 073 minus194 214lowast
SR 293lowast 088 060 minus176 217lowast
Risalpur MK 243lowast 044 minus006 minus154 198SR 254lowast 040 minus005 minus190 195
lowastSignificant trend at 5 significance level of two-tailed test
10 Advances in Meteorology
N
0 5 10 25
Scale
(km)
Significant increasing trendSignificant decreasing trend
No trend
Winter
Autumn Annual
Spring Summer
Figure 5 Location of sites with increasing decreasing and no trends at 5 significance level for the seasonal and annual precipitation timeseries
study stations from 1961 to 2011 theThalozom station showeda negative trend with a decreasing rate of 370mmyearFigure 6 displays the results of the magnitude of variationin the annual precipitation for the Saidu Sharif MardanCharsadda andThalozom stations
35 Trend Analysis over Entire River Basin The effect ofclimate change on precipitation was also analyzed for theentire Swat River basin by applying the MK and SR testson monthly seasonal and annual scale As Figure 1 showedthe entire Swat River catchment (A) is divided into foursubbasins upper subbasin (A1) Panjkora subbasin (A2)Ambahar subbasin (A3) and Lower subbasin (A4) Table 5presents trends in monthly precipitation across the subbasinsand for the full basin The table shows significant positivetrends in the months of June and November for the uppersubbasin (A1) and the entire Swat River basin (A) negativetrends were seen in these locations in July and August Inthe Panjkora subbasin (A2) statistically significant positivetrends were identified over time in June a negative trendwas seen from July to September The maximum number ofsignificant cases (8) was observed in data from the Ambaharsubbasin (A3)The Lower subbasin (A4) showed a significantpositive trend only during January no significant trendsin other months were identified As a simpler summarysignificant negative trends in precipitation over time were
seen from July to September positive trends over time wereseen in January May June and October to December indifferent Swat River subbasins
To detect precipitation trends in each subbasin and entireSwat River basin the MK and SR tests were again appliedto seasonal and annual precipitation data for the 51-yearstudy period (1961ndash2011) As Table 6 shows both testmethodsshowed similar results The upper subbasin (A1) experiencedstatistically significant negative trends in the summer andpositive trends in the autumn The Panjkora subbasin (A2)and Lower subbasin (A4) showed significant negative trendsin the summer and positive trends in the winter Significantpositive trends were found across the subbasins in winterand autumn seasons however there was a negative trendin summer at Ambahar subbasin (A3) and across the entireSwat River basin (A) For the annual and spring precipitationtime series there were no statistically significant trendsSignificant positive trendswere seen inwinter and autumn insummer negative trends were seen across different subbasinsand the full Swat River basin
The Lower subbasin exhibited the maximum positivetrend over time (218mmyear) in the weighted annualprecipitation time series the Panjkora subbasin showed anegative trend with a decreasing rate of participation at090mmyear The entire Swat River basin showed a positivetrend in precipitation (048mmyear) as shown in Table 6
Advances in Meteorology 11
Table5MKandSR
tests
results
form
onthlyprecipitatio
ntim
eseriesinentireb
asin
andsubb
asinso
fSwatRiver
Subb
asin
Test
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
A1
MK
047
010
071
minus12
3041
349lowast
minus288lowast
minus318lowast
minus018
143
250lowast
094
SR045
006
074
minus098
047
409lowast
minus299lowast
minus363lowast
minus018
159
277lowast
094
A2
MK
107
080
016
minus093
021
201lowast
minus354lowast
minus416lowast
minus202lowast
000
187
062
SR095
072
001
minus099
013
231lowast
minus386lowast
minus486lowast
minus224lowast
011
200
063
A3
MK
250lowast
102
minus036
065
297lowast
390lowast
minus297lowast
minus255lowast
minus044
305lowast
295lowast
229lowast
SR267lowast
089
minus009
070
311lowast
479lowast
minus354lowast
minus322lowast
minus052
376lowast
365lowast
260lowast
A4
MK
237lowast
088
minus006
minus050
122
164
minus063
minus083
000
020
050
minus040
SR246lowast
084
minus001
minus059
117
182
minus059
minus090
001
045
023
minus046
AMK
185
110
013
minus062
123
369lowast
minus255lowast
minus361lowast
minus065
174
268lowast
070
SR17
010
4018
minus079
127
422lowast
minus277lowast
minus401lowast
minus070
181
299lowast
073
lowast
Sign
ificant
trend
at5
significance
leveloftwo-tailedtest
12 Advances in Meteorology
0
500
1000
1500
2000
2500
3000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Saidu Sharif station
(a)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Mardan station
(b)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Charsadda station
(c)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Thalozom station
(d)
Figure 6 Variations of annual precipitation time series in stations with significant trends during 1961ndash2011
36 Comparison of Results Results from both statistical testsMK and SR were consistent with each otherThe percentagesof statistically significant cases to total tested cases for theMK and SR tests were 32 and 30 respectively showingagreement across methods This consistency in statisticalperformance was also found in other studies [24 28]
4 Discussion
This study investigated variability in monthly seasonal andannual precipitation at 15 stations in the Swat River basinover a 51-year study period (1961ndash2011) Precipitation trendswere also analyzed for each subbasin and entire Swat Riverbasin The mean annual precipitation at different stationsshowed considerable variation with a standard deviationof 1768mm from the mean annual rainfall of 694mmThe Saidu Sharif Mardan and Charsadda stations showedsignificant positive trends (increased precipitation over time)at 5 significance level in the annual precipitation series
The maximum number of significant changes in monthlyprecipitation over time was detected at Saidu Sharif Abazaiand Khairabad stations Saidu Sharif station showed themaximum increasing slope (indicating sharpest change overtime) of 748mmyear among the selected stations in the SwatRiver basin
These study results follow the same statistical trendsreported by Hartmann and Andresky [35] for northwestparts of Pakistan Findings were consistent with results fromDimri [56] Ghaffar and Javid [57] and Rasul [58] whereinthey found statistically significant increasing trends in winterprecipitation for northwest areas of Pakistan The resultsof this analysis also support finding of Hanif et al [37]wherein they found significant variations in summer seasonprecipitation These variations in precipitation trends maylead Pakistan towards more water related disasters suchas droughts and floods in the near future Basistha et al[59] proposed possible causes of the changing precipitationtrends such as global climate shifts [60] dwindling global
Advances in Meteorology 13
Table 6 MK and SR results for seasonal and annual precipitation time series in entire basin and subbasin of Swat River
Subbasin Change (mmyear) Test Winter Spring Summer Autumn Annual
A1 minus073 MK 055 minus024 minus242lowast 305lowast minus034SR 057 001 minus227lowast 347lowast 118
A2 minus090 MK 128 minus023 minus385lowast 158 minus081SR 118 minus035 minus444lowast 164 minus090
A3 030 MK 266lowast 016 minus265lowast 375lowast 024SR 295lowast 027 minus309lowast 460lowast 040
A4 218 MK 242lowast 060 minus021 024 166SR 272lowast 054 minus037 043 173
A 048 MK 214lowast minus011 minus297lowast 307lowast 042SR 225lowast minus014 minus340lowast 336lowast 038
lowastSignificant trend at 5 significance level of two-tailed test
monsoon circulation [61] decline in forest cover [62 63] landuse changes and practices (eg irrigated agriculture) [64 65]and increasing aerosols from anthropogenic activities [66]
5 Conclusions
This paper analyzed trends in monthly seasonal and annualprecipitation in the Swat River basin over the 51-year studyperiod (1961ndash2011) A mix of positive and negative trendswas observed at various stations and subbasins The monthsof June November July and August showed the maximumnumber of significant cases at various stations in monthlyprecipitation The trends were positive in May and June andwere negative in July and August This indicates a shift inprecipitation series on monthly scale Significant positivetrends were detected in winter and autumn and annuallynegative trends were seen in spring and summer seasonsSaidu Sharif Mardan and Charsadda stations exhibitedsignificant positive trends in annual precipitation at a 95confidence level the remaining stations did not experiencea statistically significant trend
For the entire Swat River basin no significant trendswere detected in any subbasin for the annual precipitationseries Seasonally winter and autumn experienced significantpositive trends and summer experienced negative trends indifferent subbasins in the Swat River basin Most statisticallysignificant trend cases under different scenarios were positive(61)The results obtainedwith theMann-Kendall (MK) andSpearmanrsquos rho tests showed agreement in their assessmentsof monthly seasonal and annual precipitation trends Thevariability of negative and positive trends at various stationspoints to the need for more detailed studies on the climatechange of this region
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgments
The authors thank Pakistan Meteorological Department(PMD) Water and Power Development Authority
(WAPDA) Pakistan and Snowy Mountains EngineeringCorporation (SMEC) for providing cost-free data for thisstudy
References
[1] M D Rahman and M Begum ldquoApplication of non parametrictest for trend detection of rainfall in the largest Island ofBangladeshrdquo ARPN Journal of Earth Sciences vol 2 no 2 pp40ndash44 2013
[2] IPCCThePhysical Science Basis Contribution ofWorkingGroupI to the Fourth Assessment Report of the Intergovernmental Panelon Climate Change Cambridge University Press CambridgeUK 2007
[3] A B Farooq and A H Khan ldquoClimate change perspectivein Pakistanrdquo in Proceedings of the Capacity Building APNWorkshop on Global Change Research pp 39ndash46 IslamabadPakistan 2004
[4] Z Z Hu S Yang and R Wu ldquoLong-term climate variationsin China and global warming signalsrdquo Journal of GeophysicalResearch vol 108 no D19 2003
[5] P Zhai and X Pan ldquoTrends in temperature extremes during1951ndash1999 in Chinardquo Geophysical Research Letters vol 30 no17 p 1913 2003
[6] D Duhan and A Pandey ldquoStatistical analysis of long termspatial and temporal trends of precipitation during 1901ndash2002at Madhya Pradesh Indiardquo Atmospheric Research vol 122 pp136ndash149 2013
[7] B J Peterson RM Holmes JWMcClelland et al ldquoIncreasingriver discharge to the Arctic oceanrdquo Science vol 298 no 5601pp 2171ndash2173 2002
[8] N I Savelieva I P Semiletov L N Vasilevskaya and S PPugach ldquoA climate shift in seasonal values of meteorologicaland hydrological parameters for Northeastern Asiardquo Progress inOceanography vol 47 no 2ndash4 pp 279ndash297 2000
[9] Y F Shi Y P Shen and R J Hu ldquoPreliminary study on signalimpact and foreground of climatic shift from warm-dry towarm-humid in Northwest Chinardquo Journal of Glaciology andGeocryology vol 24 pp 219ndash226 2002 (Chinese)
[10] S Farhana and M M Rahman ldquoCharacterizing rainfall trendin Bangladesh by temporal statistics analysisrdquo in Proceedings ofthe 4th Annual Paper Meet and 1st Civil Engineering CongressDhaka Bangladesh 2011
[11] R H Rimi S H Rahman S Karmakar and S G HussainldquoTrend analysis of climate change and investigation on its
14 Advances in Meteorology
probable impacts on rice production at Satkhira BangladeshrdquoPakistan Journal of Meteorology vol 6 no 11 pp 37ndash50 2014
[12] E R Dahmen and M J Hall Screening of Hydrological DataTests for Stationarity and Relative Consistency Publication 49ILRI Wageningen The Netherlands 1990
[13] Q Zhang C Liu C-Y Xu Y Xu and T Jiang ldquoObserved trendsof annual maximumwater level and streamflow during past 130years in the Yangtze River basin Chinardquo Journal of Hydrologyvol 324 no 1-4 pp 255ndash265 2006
[14] H Chen S Guo C-Y Xu and V P Singh ldquoHistorical tem-poral trends of hydro-climatic variables and runoff responseto climate variability and their relevance in water resourcemanagement in the Hanjiang basinrdquo Journal of Hydrology vol344 no 3-4 pp 171ndash184 2007
[15] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 pp 245ndash259 1945
[16] M G Kendall Rank CorrelationMethods Griffin London UK1975
[17] E L Lehmann Nonparametrics Statistical Methods Based onRanks Holden-Day San Francisco Calif USA 1975
[18] R Sneyers ldquoOn the statistical analysis of series of observationsrdquoTechnical Note 143 WMO no 415 World MeteorologicalOrganization 1990
[19] A Longobardi and P Villani ldquoTrend analysis of annual andseasonal rainfall time series in the Mediterranean areardquo Inter-national Journal of Climatology vol 30 no 10 pp 1538ndash15462010
[20] Z YanmingW Jun andW Xinhua ldquoStudy on the change trendof precipitation and temperature in Kunming city based onMann-Kendall analysisrdquo in Future Computer CommunicationControl and Automation vol 119 of Advances in Intelligent andSoft Computing pp 505ndash513 Springer Berlin Germany 2011
[21] X L Yang L R Xu K K Liu C H Li J Hu and X H XialdquoTrend in temperature and precipitation in the ZhangweinanRiver Basin during the last 53 yearsrdquo Procedia EnvironmentalSciences vol 13 pp 1966ndash1974 1966
[22] Z F Yang Y Yan and Q Liu ldquoThe relationship of streamflow-precipitation-temperature in the Yellow River Basin of Chinaduring 1961ndash2000rdquo Procedia Environmental Sciences vol 13 pp2336ndash2345 2012
[23] Q-X Wang X-H Fan Z-D Qin and M-B Wang ldquoChangetrends of temperature and precipitation in the Loess PlateauRegion of China 1961ndash2010rdquo Global and Planetary Change vol92-93 pp 138ndash147 2012
[24] S Yue P Pilon and G Cavadias ldquoPower of the Mann-Kendalland Spearmanrsquos rho tests for detecting monotonic trends inhydrological seriesrdquo Journal of Hydrology vol 259 no 1ndash4 pp254ndash271 2002
[25] E Kahya and S Kalaycı ldquoTrend analysis of streamflow inTurkeyrdquo Journal of Hydrology vol 289 pp 128ndash144 2004
[26] Z L Li Z X Xu J Y Li and Z J Li ldquoShift trend and stepchanges for runoff time series in the Shiyang River BasinNorthwest Chinardquo Hydrological Processes vol 22 no 23 pp4639ndash4646 2008
[27] C Yaning X Changchun H Xingming et al ldquoFifty-yearclimate change and its effect on annual runoff in the TarimRiverBasin Chinardquo Quaternary International vol 208 no 1-2 pp53ndash61 2009
[28] M Shadmani SMarofi andMRoknian ldquoTrend analysis in ref-erence evapotranspiration usingMann-Kendall and SpearmanrsquosRho tests in arid regions of IranrdquoWater Resources Managementvol 26 no 1 pp 211ndash224 2012
[29] H Rehman and A Kamal ldquoIndus Basin River system-floodingand flood mitigationrdquo 2005 httparchiveriversymposiumcom2005indexphpelement=38
[30] Pakistan Meteorological Department (PMD) National PlanStrengthening National Capacities for Multi-hazard EarlyWarn-ing amp Response System 2006
[31] National Disaster Management Authority (NDMA) 2007National Disaster Risk Management Framework Governmentof Pakistan httpwwwndmagovpknew
[32] N H Hashimi Q T M Siddiqui A R Ghumman M AKamal and H R Mughal ldquoA critical analysis of 2010 floods inPakistanrdquo African Journal of Agricultural Research vol 7 no 7pp 1054ndash1067 2012
[33] FFC ldquoFederal Flood Commission of Pakistanrdquo Annual FloodReport-2010 2011 httpwwwffcgovpkdownloadfloodarc-hieveAnnualreport2010pdf
[34] N Gronewold and Climatewire ldquoIs the Flooding in Pakistan aClimate Change Disasterrdquo WMN 2010 httpwwwscientific-americancomarticleis-the-flooding-in-pakist
[35] H Hartmann and L Andresky ldquoFlooding in the Indus Riverbasinmdasha spatiotemporal analysis of precipitation recordsrdquoGlobal and Planetary Change vol 107 pp 25ndash35 2013
[36] S Salma S Rehman andM A Shah ldquoRainfall trends in differ-ent climate zones of Pakistanrdquo Pakistan Journal of Meteorologyvol 9 no 17 pp 37ndash47 2012
[37] M Hanif A H Khan and S Adnan ldquoLatitudinal precipitationcharacteristics and trends in Pakistanrdquo Journal ofHydrology vol492 pp 266ndash272 2013
[38] A Imran Q Zaman and M Afzal ldquoTemporal trends in thepeak monsoonal precipitation events over Northeast PakistanrdquoPakistan Journal of Meteorology vol 10 no 19 pp 19ndash30 2013
[39] S B Cheema and M Hanif ldquoSeasonal precipitation variationover Punjab provincerdquo Pakistan Journal of Meteorology vol 10no 19 pp 61ndash82 2013
[40] H Hartmann and H Buchanan ldquoTrends in extreme precipita-tion events in the indus River Basin and flooding in PakistanrdquoAtmosphere-Ocean vol 52 no 1 pp 77ndash91 2014
[41] ldquoProvincial Disaster Management Authority (PDMA 2012)Monsoon Contingency Plan-Khyber-Pakhtunkhwardquo 2012httpwwwndmagovpkDocumentsContingency Plan2012CP KPpdf
[42] Snowy Mountains Engineering Corporation Munda DamConstruction Project Detailed Design Report SMEC LahorePakistan 2014
[43] H Alexandersson ldquoA homogeneity test applied to precipitationdatardquo Journal of Climatology vol 6 no 6 pp 661ndash675 1986
[44] HAlexandersson andAMoberg ldquoHomogenization of Swedishtemperature data Part I homogeneity test for linear trendsrdquoInternational Journal of Climatology vol 17 no 1 pp 25ndash341997
[45] T A Buishand ldquoSome methods for testing the homogeneity ofrainfall recordsrdquo Journal of Hydrology vol 58 no 1-2 pp 11ndash271982
[46] M N Khaliq and T B M J Ouarda ldquoOn the critical values ofthe standard normal homogeneity test (SNHT)rdquo InternationalJournal of Climatology vol 27 no 5 pp 681ndash687 2007
[47] K H Hamed and A Ramachandra Rao ldquoA modified Mann-Kendall trend test for autocorrelated datardquo Journal of Hydrologyvol 204 no 1ndash4 pp 182ndash196 1998
[48] B Onoz and M Bayazit ldquoBlock bootstrap for Mann-Kendalltrend test of serially dependent datardquoHydrological Processes vol26 no 23 pp 3552ndash3560 2012
Advances in Meteorology 15
[49] M Yaseen H A Bhatti T Rientjes G Nabi and M LatifldquoTemporal and spatial variations in summer flows of upperIndus Basin Pakistanrdquo inProceedings of the 72ndAnnual Sessionof Pakistan Engineering Congress Paper no 747 pp 315ndash3342013
[50] G C Blain ldquoThe Mann-Kendall test the need to consider theinteraction between serial correlation and trendrdquo AgriculturalEngineering vol 35 no 4 2013
[51] M Yaseen T Rientjes G Nabi H ur-Rehman and M LatifldquoAssessment of recent temperature trends inManglawatershedrdquoJournal of Himalayan Earth Sciences vol 47 no 1 pp 107ndash1212014
[52] P K Sen ldquoEstimates of the regression coefficient based onKendallrsquos taurdquo Journal of the American Statistical Associationvol 63 no 324 pp 1379ndash1389 1968
[53] W S Cleveland ldquoRobust locally weighted regression andsmoothing scatterplotsrdquoThe Journal of the American StatisticalAssociation vol 74 no 368 pp 829ndash836 1979
[54] W S Cleveland ldquoGraphs in scientific publicationsrdquoThe Ameri-can Statistician vol 38 no 4 pp 261ndash269 1984
[55] D R Helsel and R M Hirsch ldquoStatistical methods in waterresourcesrdquo inTechniques ofWater Resources Investigations Book4 chapter A3 p 522 US Geological Survey 2002
[56] A P Dimri ldquoSurface and upper air fields during extreme winterprecipitation over the western Himalayasrdquo Pure and AppliedGeophysics vol 163 no 8 pp 1679ndash1698 2006
[57] A Ghaffar and M Javid ldquoImpact of global warming onmonsoon variability in Pakistanrdquo The Journal of Animal andPlant Sciences vol 21 no 1 pp 107ndash110 2011
[58] G Rasul ldquoClimate Data and Modelling Analysis of the IndusRegionrdquo Pakistan Meteorological Department (PMD) 2012httpwwfpakorgccappdfClimate Data Modelling20An-alysis20of20the20Indus20Ecoregionpdf
[59] A Basistha D S Arya and N K Goel ldquoAnalysis of historicalchanges in rainfall in the Indian Himalayasrdquo InternationalJournal of Climatology vol 29 no 4 pp 555ndash572 2009
[60] P G Baines ldquoThe late 1960s global climate shift and its influenceon the Southern Hemisphererdquo in Proceedings of 8 ICSHMO pp1477ndash1482 INPE Foz do Iguacu Brazil 2006
[61] K Duan and T Yao ldquoMonsoon variability in the Himalayasunder the condition of global warmingrdquo Journal of the Mete-orological Society of Japan vol 81 no 2 pp 251ndash257 2003
[62] U S Nair R O Lawton R M Welch and R A Pielke SrldquoImpact of land use on Costa Rican tropical montane cloudforests sensitivity of cumulus cloud field characteristics tolowland deforestationrdquo Journal of Geophysical Research D vol108 no 7 pp 4206ndash4219 2003
[63] R Avissar and D Werth ldquoGlobal hydroclimatological tele-connections resulting from tropical deforestationrdquo Journal ofHydrometeorology vol 6 no 2 pp 134ndash145 2005
[64] R A Pielke Sr J Adegoke A Beltran-Przekurat et al ldquoAnoverview of regional land-use and land-cover impacts onrainfallrdquo Tellus B Chemical and Physical Meteorology vol 59no 3 pp 587ndash601 2007
[65] N Ramankutty C Delire and P Snyder ldquoFeedbacks betweenagriculture and climate an illustration of the potential unin-tended consequences of human land use activitiesrdquo Global andPlanetary Change vol 54 no 1-2 pp 79ndash93 2006
[66] V Ramanathan C Chung D Kim et al ldquoAtmospheric brownclouds impacts on South Asian climate and hydrological cyclerdquoProceedings of the National Academy of Sciences of the UnitedStates of America vol 102 no 15 pp 5326ndash5333 2005
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
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Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
EarthquakesJournal of
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Hindawi Publishing Corporationhttpwwwhindawicom
Applied ampEnvironmentalSoil Science
Volume 2014
Mining
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Hindawi Publishing Corporation httpwwwhindawicom Volume 2014
International Journal of
Geophysics
OceanographyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal ofPetroleum Engineering
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
GeochemistryHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Atmospheric SciencesInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OceanographyHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Advances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MineralogyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MeteorologyAdvances in
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Paleontology JournalHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geological ResearchJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geology Advances in
Advances in Meteorology 9
0
100
200
300
400
500
600
700
800
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
mon
th)
Year
Saidu Sharif station(March)
(a)
0
100
200
300
400
500
600
700
800
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
mon
th)
Year
Saidu Sharif station(July)
(b)
Figure 4 Variations of monthly precipitation time series in stations with most significant trends during 1961ndash2011
Table 4 MK and SR tests results for precipitation in seasonal and annual time series
Station Test Winter Spring Summer Autumn Annual
Thalozom MK minus120 minus162 minus120 148 minus149SR minus114 minus152 minus110 135 minus145
Drosh MK 042 minus078 minus196 097 minus044SR 049 minus074 minus209lowast 127 minus048
Kalam MK minus062 minus139 minus171 160 minus110SR minus037 minus121 minus158 157 minus087
Dir MK minus028 minus148 minus047 minus076 minus138SR minus062 minus150 minus058 minus097 minus146
Madyan MK 120 003 minus258lowast 365lowast 042SR 137 033 minus244lowast 421lowast 078
Khairabad MK 026 minus065 minus302lowast 325lowast minus073SR 021 minus076 minus353lowast 364lowast minus072
ToorCamp MK minus063 minus203lowast 024 minus073 minus044SR minus096 minus217lowast 023 minus092 minus159
Saidu Sharif MK 346lowast 239lowast minus156 069 328lowast
SR 404lowast 280lowast minus156 148 278lowast
Malakand MK minus070 minus110 minus270lowast 337lowast minus119SR minus068 minus115 minus319lowast 373lowast minus140
Kulangi MK minus122 minus261lowast 031 minus099 minus144SR minus156 minus284lowast 037 minus127 minus172
Ambahar MK minus066 minus206lowast minus063 minus099 minus157SR minus076 minus224lowast minus058 minus110 minus141
Abazai MK 179 minus015 minus099 429lowast 096SR 217lowast 007 minus072 604lowast 122
Mardan MK 281lowast 145 095 minus102 259lowast
SR 310lowast 134 098 minus085 280lowast
Charsadda MK 266lowast 097 073 minus194 214lowast
SR 293lowast 088 060 minus176 217lowast
Risalpur MK 243lowast 044 minus006 minus154 198SR 254lowast 040 minus005 minus190 195
lowastSignificant trend at 5 significance level of two-tailed test
10 Advances in Meteorology
N
0 5 10 25
Scale
(km)
Significant increasing trendSignificant decreasing trend
No trend
Winter
Autumn Annual
Spring Summer
Figure 5 Location of sites with increasing decreasing and no trends at 5 significance level for the seasonal and annual precipitation timeseries
study stations from 1961 to 2011 theThalozom station showeda negative trend with a decreasing rate of 370mmyearFigure 6 displays the results of the magnitude of variationin the annual precipitation for the Saidu Sharif MardanCharsadda andThalozom stations
35 Trend Analysis over Entire River Basin The effect ofclimate change on precipitation was also analyzed for theentire Swat River basin by applying the MK and SR testson monthly seasonal and annual scale As Figure 1 showedthe entire Swat River catchment (A) is divided into foursubbasins upper subbasin (A1) Panjkora subbasin (A2)Ambahar subbasin (A3) and Lower subbasin (A4) Table 5presents trends in monthly precipitation across the subbasinsand for the full basin The table shows significant positivetrends in the months of June and November for the uppersubbasin (A1) and the entire Swat River basin (A) negativetrends were seen in these locations in July and August Inthe Panjkora subbasin (A2) statistically significant positivetrends were identified over time in June a negative trendwas seen from July to September The maximum number ofsignificant cases (8) was observed in data from the Ambaharsubbasin (A3)The Lower subbasin (A4) showed a significantpositive trend only during January no significant trendsin other months were identified As a simpler summarysignificant negative trends in precipitation over time were
seen from July to September positive trends over time wereseen in January May June and October to December indifferent Swat River subbasins
To detect precipitation trends in each subbasin and entireSwat River basin the MK and SR tests were again appliedto seasonal and annual precipitation data for the 51-yearstudy period (1961ndash2011) As Table 6 shows both testmethodsshowed similar results The upper subbasin (A1) experiencedstatistically significant negative trends in the summer andpositive trends in the autumn The Panjkora subbasin (A2)and Lower subbasin (A4) showed significant negative trendsin the summer and positive trends in the winter Significantpositive trends were found across the subbasins in winterand autumn seasons however there was a negative trendin summer at Ambahar subbasin (A3) and across the entireSwat River basin (A) For the annual and spring precipitationtime series there were no statistically significant trendsSignificant positive trendswere seen inwinter and autumn insummer negative trends were seen across different subbasinsand the full Swat River basin
The Lower subbasin exhibited the maximum positivetrend over time (218mmyear) in the weighted annualprecipitation time series the Panjkora subbasin showed anegative trend with a decreasing rate of participation at090mmyear The entire Swat River basin showed a positivetrend in precipitation (048mmyear) as shown in Table 6
Advances in Meteorology 11
Table5MKandSR
tests
results
form
onthlyprecipitatio
ntim
eseriesinentireb
asin
andsubb
asinso
fSwatRiver
Subb
asin
Test
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
A1
MK
047
010
071
minus12
3041
349lowast
minus288lowast
minus318lowast
minus018
143
250lowast
094
SR045
006
074
minus098
047
409lowast
minus299lowast
minus363lowast
minus018
159
277lowast
094
A2
MK
107
080
016
minus093
021
201lowast
minus354lowast
minus416lowast
minus202lowast
000
187
062
SR095
072
001
minus099
013
231lowast
minus386lowast
minus486lowast
minus224lowast
011
200
063
A3
MK
250lowast
102
minus036
065
297lowast
390lowast
minus297lowast
minus255lowast
minus044
305lowast
295lowast
229lowast
SR267lowast
089
minus009
070
311lowast
479lowast
minus354lowast
minus322lowast
minus052
376lowast
365lowast
260lowast
A4
MK
237lowast
088
minus006
minus050
122
164
minus063
minus083
000
020
050
minus040
SR246lowast
084
minus001
minus059
117
182
minus059
minus090
001
045
023
minus046
AMK
185
110
013
minus062
123
369lowast
minus255lowast
minus361lowast
minus065
174
268lowast
070
SR17
010
4018
minus079
127
422lowast
minus277lowast
minus401lowast
minus070
181
299lowast
073
lowast
Sign
ificant
trend
at5
significance
leveloftwo-tailedtest
12 Advances in Meteorology
0
500
1000
1500
2000
2500
3000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Saidu Sharif station
(a)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Mardan station
(b)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Charsadda station
(c)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Thalozom station
(d)
Figure 6 Variations of annual precipitation time series in stations with significant trends during 1961ndash2011
36 Comparison of Results Results from both statistical testsMK and SR were consistent with each otherThe percentagesof statistically significant cases to total tested cases for theMK and SR tests were 32 and 30 respectively showingagreement across methods This consistency in statisticalperformance was also found in other studies [24 28]
4 Discussion
This study investigated variability in monthly seasonal andannual precipitation at 15 stations in the Swat River basinover a 51-year study period (1961ndash2011) Precipitation trendswere also analyzed for each subbasin and entire Swat Riverbasin The mean annual precipitation at different stationsshowed considerable variation with a standard deviationof 1768mm from the mean annual rainfall of 694mmThe Saidu Sharif Mardan and Charsadda stations showedsignificant positive trends (increased precipitation over time)at 5 significance level in the annual precipitation series
The maximum number of significant changes in monthlyprecipitation over time was detected at Saidu Sharif Abazaiand Khairabad stations Saidu Sharif station showed themaximum increasing slope (indicating sharpest change overtime) of 748mmyear among the selected stations in the SwatRiver basin
These study results follow the same statistical trendsreported by Hartmann and Andresky [35] for northwestparts of Pakistan Findings were consistent with results fromDimri [56] Ghaffar and Javid [57] and Rasul [58] whereinthey found statistically significant increasing trends in winterprecipitation for northwest areas of Pakistan The resultsof this analysis also support finding of Hanif et al [37]wherein they found significant variations in summer seasonprecipitation These variations in precipitation trends maylead Pakistan towards more water related disasters suchas droughts and floods in the near future Basistha et al[59] proposed possible causes of the changing precipitationtrends such as global climate shifts [60] dwindling global
Advances in Meteorology 13
Table 6 MK and SR results for seasonal and annual precipitation time series in entire basin and subbasin of Swat River
Subbasin Change (mmyear) Test Winter Spring Summer Autumn Annual
A1 minus073 MK 055 minus024 minus242lowast 305lowast minus034SR 057 001 minus227lowast 347lowast 118
A2 minus090 MK 128 minus023 minus385lowast 158 minus081SR 118 minus035 minus444lowast 164 minus090
A3 030 MK 266lowast 016 minus265lowast 375lowast 024SR 295lowast 027 minus309lowast 460lowast 040
A4 218 MK 242lowast 060 minus021 024 166SR 272lowast 054 minus037 043 173
A 048 MK 214lowast minus011 minus297lowast 307lowast 042SR 225lowast minus014 minus340lowast 336lowast 038
lowastSignificant trend at 5 significance level of two-tailed test
monsoon circulation [61] decline in forest cover [62 63] landuse changes and practices (eg irrigated agriculture) [64 65]and increasing aerosols from anthropogenic activities [66]
5 Conclusions
This paper analyzed trends in monthly seasonal and annualprecipitation in the Swat River basin over the 51-year studyperiod (1961ndash2011) A mix of positive and negative trendswas observed at various stations and subbasins The monthsof June November July and August showed the maximumnumber of significant cases at various stations in monthlyprecipitation The trends were positive in May and June andwere negative in July and August This indicates a shift inprecipitation series on monthly scale Significant positivetrends were detected in winter and autumn and annuallynegative trends were seen in spring and summer seasonsSaidu Sharif Mardan and Charsadda stations exhibitedsignificant positive trends in annual precipitation at a 95confidence level the remaining stations did not experiencea statistically significant trend
For the entire Swat River basin no significant trendswere detected in any subbasin for the annual precipitationseries Seasonally winter and autumn experienced significantpositive trends and summer experienced negative trends indifferent subbasins in the Swat River basin Most statisticallysignificant trend cases under different scenarios were positive(61)The results obtainedwith theMann-Kendall (MK) andSpearmanrsquos rho tests showed agreement in their assessmentsof monthly seasonal and annual precipitation trends Thevariability of negative and positive trends at various stationspoints to the need for more detailed studies on the climatechange of this region
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgments
The authors thank Pakistan Meteorological Department(PMD) Water and Power Development Authority
(WAPDA) Pakistan and Snowy Mountains EngineeringCorporation (SMEC) for providing cost-free data for thisstudy
References
[1] M D Rahman and M Begum ldquoApplication of non parametrictest for trend detection of rainfall in the largest Island ofBangladeshrdquo ARPN Journal of Earth Sciences vol 2 no 2 pp40ndash44 2013
[2] IPCCThePhysical Science Basis Contribution ofWorkingGroupI to the Fourth Assessment Report of the Intergovernmental Panelon Climate Change Cambridge University Press CambridgeUK 2007
[3] A B Farooq and A H Khan ldquoClimate change perspectivein Pakistanrdquo in Proceedings of the Capacity Building APNWorkshop on Global Change Research pp 39ndash46 IslamabadPakistan 2004
[4] Z Z Hu S Yang and R Wu ldquoLong-term climate variationsin China and global warming signalsrdquo Journal of GeophysicalResearch vol 108 no D19 2003
[5] P Zhai and X Pan ldquoTrends in temperature extremes during1951ndash1999 in Chinardquo Geophysical Research Letters vol 30 no17 p 1913 2003
[6] D Duhan and A Pandey ldquoStatistical analysis of long termspatial and temporal trends of precipitation during 1901ndash2002at Madhya Pradesh Indiardquo Atmospheric Research vol 122 pp136ndash149 2013
[7] B J Peterson RM Holmes JWMcClelland et al ldquoIncreasingriver discharge to the Arctic oceanrdquo Science vol 298 no 5601pp 2171ndash2173 2002
[8] N I Savelieva I P Semiletov L N Vasilevskaya and S PPugach ldquoA climate shift in seasonal values of meteorologicaland hydrological parameters for Northeastern Asiardquo Progress inOceanography vol 47 no 2ndash4 pp 279ndash297 2000
[9] Y F Shi Y P Shen and R J Hu ldquoPreliminary study on signalimpact and foreground of climatic shift from warm-dry towarm-humid in Northwest Chinardquo Journal of Glaciology andGeocryology vol 24 pp 219ndash226 2002 (Chinese)
[10] S Farhana and M M Rahman ldquoCharacterizing rainfall trendin Bangladesh by temporal statistics analysisrdquo in Proceedings ofthe 4th Annual Paper Meet and 1st Civil Engineering CongressDhaka Bangladesh 2011
[11] R H Rimi S H Rahman S Karmakar and S G HussainldquoTrend analysis of climate change and investigation on its
14 Advances in Meteorology
probable impacts on rice production at Satkhira BangladeshrdquoPakistan Journal of Meteorology vol 6 no 11 pp 37ndash50 2014
[12] E R Dahmen and M J Hall Screening of Hydrological DataTests for Stationarity and Relative Consistency Publication 49ILRI Wageningen The Netherlands 1990
[13] Q Zhang C Liu C-Y Xu Y Xu and T Jiang ldquoObserved trendsof annual maximumwater level and streamflow during past 130years in the Yangtze River basin Chinardquo Journal of Hydrologyvol 324 no 1-4 pp 255ndash265 2006
[14] H Chen S Guo C-Y Xu and V P Singh ldquoHistorical tem-poral trends of hydro-climatic variables and runoff responseto climate variability and their relevance in water resourcemanagement in the Hanjiang basinrdquo Journal of Hydrology vol344 no 3-4 pp 171ndash184 2007
[15] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 pp 245ndash259 1945
[16] M G Kendall Rank CorrelationMethods Griffin London UK1975
[17] E L Lehmann Nonparametrics Statistical Methods Based onRanks Holden-Day San Francisco Calif USA 1975
[18] R Sneyers ldquoOn the statistical analysis of series of observationsrdquoTechnical Note 143 WMO no 415 World MeteorologicalOrganization 1990
[19] A Longobardi and P Villani ldquoTrend analysis of annual andseasonal rainfall time series in the Mediterranean areardquo Inter-national Journal of Climatology vol 30 no 10 pp 1538ndash15462010
[20] Z YanmingW Jun andW Xinhua ldquoStudy on the change trendof precipitation and temperature in Kunming city based onMann-Kendall analysisrdquo in Future Computer CommunicationControl and Automation vol 119 of Advances in Intelligent andSoft Computing pp 505ndash513 Springer Berlin Germany 2011
[21] X L Yang L R Xu K K Liu C H Li J Hu and X H XialdquoTrend in temperature and precipitation in the ZhangweinanRiver Basin during the last 53 yearsrdquo Procedia EnvironmentalSciences vol 13 pp 1966ndash1974 1966
[22] Z F Yang Y Yan and Q Liu ldquoThe relationship of streamflow-precipitation-temperature in the Yellow River Basin of Chinaduring 1961ndash2000rdquo Procedia Environmental Sciences vol 13 pp2336ndash2345 2012
[23] Q-X Wang X-H Fan Z-D Qin and M-B Wang ldquoChangetrends of temperature and precipitation in the Loess PlateauRegion of China 1961ndash2010rdquo Global and Planetary Change vol92-93 pp 138ndash147 2012
[24] S Yue P Pilon and G Cavadias ldquoPower of the Mann-Kendalland Spearmanrsquos rho tests for detecting monotonic trends inhydrological seriesrdquo Journal of Hydrology vol 259 no 1ndash4 pp254ndash271 2002
[25] E Kahya and S Kalaycı ldquoTrend analysis of streamflow inTurkeyrdquo Journal of Hydrology vol 289 pp 128ndash144 2004
[26] Z L Li Z X Xu J Y Li and Z J Li ldquoShift trend and stepchanges for runoff time series in the Shiyang River BasinNorthwest Chinardquo Hydrological Processes vol 22 no 23 pp4639ndash4646 2008
[27] C Yaning X Changchun H Xingming et al ldquoFifty-yearclimate change and its effect on annual runoff in the TarimRiverBasin Chinardquo Quaternary International vol 208 no 1-2 pp53ndash61 2009
[28] M Shadmani SMarofi andMRoknian ldquoTrend analysis in ref-erence evapotranspiration usingMann-Kendall and SpearmanrsquosRho tests in arid regions of IranrdquoWater Resources Managementvol 26 no 1 pp 211ndash224 2012
[29] H Rehman and A Kamal ldquoIndus Basin River system-floodingand flood mitigationrdquo 2005 httparchiveriversymposiumcom2005indexphpelement=38
[30] Pakistan Meteorological Department (PMD) National PlanStrengthening National Capacities for Multi-hazard EarlyWarn-ing amp Response System 2006
[31] National Disaster Management Authority (NDMA) 2007National Disaster Risk Management Framework Governmentof Pakistan httpwwwndmagovpknew
[32] N H Hashimi Q T M Siddiqui A R Ghumman M AKamal and H R Mughal ldquoA critical analysis of 2010 floods inPakistanrdquo African Journal of Agricultural Research vol 7 no 7pp 1054ndash1067 2012
[33] FFC ldquoFederal Flood Commission of Pakistanrdquo Annual FloodReport-2010 2011 httpwwwffcgovpkdownloadfloodarc-hieveAnnualreport2010pdf
[34] N Gronewold and Climatewire ldquoIs the Flooding in Pakistan aClimate Change Disasterrdquo WMN 2010 httpwwwscientific-americancomarticleis-the-flooding-in-pakist
[35] H Hartmann and L Andresky ldquoFlooding in the Indus Riverbasinmdasha spatiotemporal analysis of precipitation recordsrdquoGlobal and Planetary Change vol 107 pp 25ndash35 2013
[36] S Salma S Rehman andM A Shah ldquoRainfall trends in differ-ent climate zones of Pakistanrdquo Pakistan Journal of Meteorologyvol 9 no 17 pp 37ndash47 2012
[37] M Hanif A H Khan and S Adnan ldquoLatitudinal precipitationcharacteristics and trends in Pakistanrdquo Journal ofHydrology vol492 pp 266ndash272 2013
[38] A Imran Q Zaman and M Afzal ldquoTemporal trends in thepeak monsoonal precipitation events over Northeast PakistanrdquoPakistan Journal of Meteorology vol 10 no 19 pp 19ndash30 2013
[39] S B Cheema and M Hanif ldquoSeasonal precipitation variationover Punjab provincerdquo Pakistan Journal of Meteorology vol 10no 19 pp 61ndash82 2013
[40] H Hartmann and H Buchanan ldquoTrends in extreme precipita-tion events in the indus River Basin and flooding in PakistanrdquoAtmosphere-Ocean vol 52 no 1 pp 77ndash91 2014
[41] ldquoProvincial Disaster Management Authority (PDMA 2012)Monsoon Contingency Plan-Khyber-Pakhtunkhwardquo 2012httpwwwndmagovpkDocumentsContingency Plan2012CP KPpdf
[42] Snowy Mountains Engineering Corporation Munda DamConstruction Project Detailed Design Report SMEC LahorePakistan 2014
[43] H Alexandersson ldquoA homogeneity test applied to precipitationdatardquo Journal of Climatology vol 6 no 6 pp 661ndash675 1986
[44] HAlexandersson andAMoberg ldquoHomogenization of Swedishtemperature data Part I homogeneity test for linear trendsrdquoInternational Journal of Climatology vol 17 no 1 pp 25ndash341997
[45] T A Buishand ldquoSome methods for testing the homogeneity ofrainfall recordsrdquo Journal of Hydrology vol 58 no 1-2 pp 11ndash271982
[46] M N Khaliq and T B M J Ouarda ldquoOn the critical values ofthe standard normal homogeneity test (SNHT)rdquo InternationalJournal of Climatology vol 27 no 5 pp 681ndash687 2007
[47] K H Hamed and A Ramachandra Rao ldquoA modified Mann-Kendall trend test for autocorrelated datardquo Journal of Hydrologyvol 204 no 1ndash4 pp 182ndash196 1998
[48] B Onoz and M Bayazit ldquoBlock bootstrap for Mann-Kendalltrend test of serially dependent datardquoHydrological Processes vol26 no 23 pp 3552ndash3560 2012
Advances in Meteorology 15
[49] M Yaseen H A Bhatti T Rientjes G Nabi and M LatifldquoTemporal and spatial variations in summer flows of upperIndus Basin Pakistanrdquo inProceedings of the 72ndAnnual Sessionof Pakistan Engineering Congress Paper no 747 pp 315ndash3342013
[50] G C Blain ldquoThe Mann-Kendall test the need to consider theinteraction between serial correlation and trendrdquo AgriculturalEngineering vol 35 no 4 2013
[51] M Yaseen T Rientjes G Nabi H ur-Rehman and M LatifldquoAssessment of recent temperature trends inManglawatershedrdquoJournal of Himalayan Earth Sciences vol 47 no 1 pp 107ndash1212014
[52] P K Sen ldquoEstimates of the regression coefficient based onKendallrsquos taurdquo Journal of the American Statistical Associationvol 63 no 324 pp 1379ndash1389 1968
[53] W S Cleveland ldquoRobust locally weighted regression andsmoothing scatterplotsrdquoThe Journal of the American StatisticalAssociation vol 74 no 368 pp 829ndash836 1979
[54] W S Cleveland ldquoGraphs in scientific publicationsrdquoThe Ameri-can Statistician vol 38 no 4 pp 261ndash269 1984
[55] D R Helsel and R M Hirsch ldquoStatistical methods in waterresourcesrdquo inTechniques ofWater Resources Investigations Book4 chapter A3 p 522 US Geological Survey 2002
[56] A P Dimri ldquoSurface and upper air fields during extreme winterprecipitation over the western Himalayasrdquo Pure and AppliedGeophysics vol 163 no 8 pp 1679ndash1698 2006
[57] A Ghaffar and M Javid ldquoImpact of global warming onmonsoon variability in Pakistanrdquo The Journal of Animal andPlant Sciences vol 21 no 1 pp 107ndash110 2011
[58] G Rasul ldquoClimate Data and Modelling Analysis of the IndusRegionrdquo Pakistan Meteorological Department (PMD) 2012httpwwfpakorgccappdfClimate Data Modelling20An-alysis20of20the20Indus20Ecoregionpdf
[59] A Basistha D S Arya and N K Goel ldquoAnalysis of historicalchanges in rainfall in the Indian Himalayasrdquo InternationalJournal of Climatology vol 29 no 4 pp 555ndash572 2009
[60] P G Baines ldquoThe late 1960s global climate shift and its influenceon the Southern Hemisphererdquo in Proceedings of 8 ICSHMO pp1477ndash1482 INPE Foz do Iguacu Brazil 2006
[61] K Duan and T Yao ldquoMonsoon variability in the Himalayasunder the condition of global warmingrdquo Journal of the Mete-orological Society of Japan vol 81 no 2 pp 251ndash257 2003
[62] U S Nair R O Lawton R M Welch and R A Pielke SrldquoImpact of land use on Costa Rican tropical montane cloudforests sensitivity of cumulus cloud field characteristics tolowland deforestationrdquo Journal of Geophysical Research D vol108 no 7 pp 4206ndash4219 2003
[63] R Avissar and D Werth ldquoGlobal hydroclimatological tele-connections resulting from tropical deforestationrdquo Journal ofHydrometeorology vol 6 no 2 pp 134ndash145 2005
[64] R A Pielke Sr J Adegoke A Beltran-Przekurat et al ldquoAnoverview of regional land-use and land-cover impacts onrainfallrdquo Tellus B Chemical and Physical Meteorology vol 59no 3 pp 587ndash601 2007
[65] N Ramankutty C Delire and P Snyder ldquoFeedbacks betweenagriculture and climate an illustration of the potential unin-tended consequences of human land use activitiesrdquo Global andPlanetary Change vol 54 no 1-2 pp 79ndash93 2006
[66] V Ramanathan C Chung D Kim et al ldquoAtmospheric brownclouds impacts on South Asian climate and hydrological cyclerdquoProceedings of the National Academy of Sciences of the UnitedStates of America vol 102 no 15 pp 5326ndash5333 2005
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ClimatologyJournal of
EcologyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
EarthquakesJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom
Applied ampEnvironmentalSoil Science
Volume 2014
Mining
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Hindawi Publishing Corporation httpwwwhindawicom Volume 2014
International Journal of
Geophysics
OceanographyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal ofPetroleum Engineering
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
GeochemistryHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Atmospheric SciencesInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OceanographyHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Advances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MineralogyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MeteorologyAdvances in
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Paleontology JournalHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geological ResearchJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geology Advances in
10 Advances in Meteorology
N
0 5 10 25
Scale
(km)
Significant increasing trendSignificant decreasing trend
No trend
Winter
Autumn Annual
Spring Summer
Figure 5 Location of sites with increasing decreasing and no trends at 5 significance level for the seasonal and annual precipitation timeseries
study stations from 1961 to 2011 theThalozom station showeda negative trend with a decreasing rate of 370mmyearFigure 6 displays the results of the magnitude of variationin the annual precipitation for the Saidu Sharif MardanCharsadda andThalozom stations
35 Trend Analysis over Entire River Basin The effect ofclimate change on precipitation was also analyzed for theentire Swat River basin by applying the MK and SR testson monthly seasonal and annual scale As Figure 1 showedthe entire Swat River catchment (A) is divided into foursubbasins upper subbasin (A1) Panjkora subbasin (A2)Ambahar subbasin (A3) and Lower subbasin (A4) Table 5presents trends in monthly precipitation across the subbasinsand for the full basin The table shows significant positivetrends in the months of June and November for the uppersubbasin (A1) and the entire Swat River basin (A) negativetrends were seen in these locations in July and August Inthe Panjkora subbasin (A2) statistically significant positivetrends were identified over time in June a negative trendwas seen from July to September The maximum number ofsignificant cases (8) was observed in data from the Ambaharsubbasin (A3)The Lower subbasin (A4) showed a significantpositive trend only during January no significant trendsin other months were identified As a simpler summarysignificant negative trends in precipitation over time were
seen from July to September positive trends over time wereseen in January May June and October to December indifferent Swat River subbasins
To detect precipitation trends in each subbasin and entireSwat River basin the MK and SR tests were again appliedto seasonal and annual precipitation data for the 51-yearstudy period (1961ndash2011) As Table 6 shows both testmethodsshowed similar results The upper subbasin (A1) experiencedstatistically significant negative trends in the summer andpositive trends in the autumn The Panjkora subbasin (A2)and Lower subbasin (A4) showed significant negative trendsin the summer and positive trends in the winter Significantpositive trends were found across the subbasins in winterand autumn seasons however there was a negative trendin summer at Ambahar subbasin (A3) and across the entireSwat River basin (A) For the annual and spring precipitationtime series there were no statistically significant trendsSignificant positive trendswere seen inwinter and autumn insummer negative trends were seen across different subbasinsand the full Swat River basin
The Lower subbasin exhibited the maximum positivetrend over time (218mmyear) in the weighted annualprecipitation time series the Panjkora subbasin showed anegative trend with a decreasing rate of participation at090mmyear The entire Swat River basin showed a positivetrend in precipitation (048mmyear) as shown in Table 6
Advances in Meteorology 11
Table5MKandSR
tests
results
form
onthlyprecipitatio
ntim
eseriesinentireb
asin
andsubb
asinso
fSwatRiver
Subb
asin
Test
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
A1
MK
047
010
071
minus12
3041
349lowast
minus288lowast
minus318lowast
minus018
143
250lowast
094
SR045
006
074
minus098
047
409lowast
minus299lowast
minus363lowast
minus018
159
277lowast
094
A2
MK
107
080
016
minus093
021
201lowast
minus354lowast
minus416lowast
minus202lowast
000
187
062
SR095
072
001
minus099
013
231lowast
minus386lowast
minus486lowast
minus224lowast
011
200
063
A3
MK
250lowast
102
minus036
065
297lowast
390lowast
minus297lowast
minus255lowast
minus044
305lowast
295lowast
229lowast
SR267lowast
089
minus009
070
311lowast
479lowast
minus354lowast
minus322lowast
minus052
376lowast
365lowast
260lowast
A4
MK
237lowast
088
minus006
minus050
122
164
minus063
minus083
000
020
050
minus040
SR246lowast
084
minus001
minus059
117
182
minus059
minus090
001
045
023
minus046
AMK
185
110
013
minus062
123
369lowast
minus255lowast
minus361lowast
minus065
174
268lowast
070
SR17
010
4018
minus079
127
422lowast
minus277lowast
minus401lowast
minus070
181
299lowast
073
lowast
Sign
ificant
trend
at5
significance
leveloftwo-tailedtest
12 Advances in Meteorology
0
500
1000
1500
2000
2500
3000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Saidu Sharif station
(a)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Mardan station
(b)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Charsadda station
(c)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Thalozom station
(d)
Figure 6 Variations of annual precipitation time series in stations with significant trends during 1961ndash2011
36 Comparison of Results Results from both statistical testsMK and SR were consistent with each otherThe percentagesof statistically significant cases to total tested cases for theMK and SR tests were 32 and 30 respectively showingagreement across methods This consistency in statisticalperformance was also found in other studies [24 28]
4 Discussion
This study investigated variability in monthly seasonal andannual precipitation at 15 stations in the Swat River basinover a 51-year study period (1961ndash2011) Precipitation trendswere also analyzed for each subbasin and entire Swat Riverbasin The mean annual precipitation at different stationsshowed considerable variation with a standard deviationof 1768mm from the mean annual rainfall of 694mmThe Saidu Sharif Mardan and Charsadda stations showedsignificant positive trends (increased precipitation over time)at 5 significance level in the annual precipitation series
The maximum number of significant changes in monthlyprecipitation over time was detected at Saidu Sharif Abazaiand Khairabad stations Saidu Sharif station showed themaximum increasing slope (indicating sharpest change overtime) of 748mmyear among the selected stations in the SwatRiver basin
These study results follow the same statistical trendsreported by Hartmann and Andresky [35] for northwestparts of Pakistan Findings were consistent with results fromDimri [56] Ghaffar and Javid [57] and Rasul [58] whereinthey found statistically significant increasing trends in winterprecipitation for northwest areas of Pakistan The resultsof this analysis also support finding of Hanif et al [37]wherein they found significant variations in summer seasonprecipitation These variations in precipitation trends maylead Pakistan towards more water related disasters suchas droughts and floods in the near future Basistha et al[59] proposed possible causes of the changing precipitationtrends such as global climate shifts [60] dwindling global
Advances in Meteorology 13
Table 6 MK and SR results for seasonal and annual precipitation time series in entire basin and subbasin of Swat River
Subbasin Change (mmyear) Test Winter Spring Summer Autumn Annual
A1 minus073 MK 055 minus024 minus242lowast 305lowast minus034SR 057 001 minus227lowast 347lowast 118
A2 minus090 MK 128 minus023 minus385lowast 158 minus081SR 118 minus035 minus444lowast 164 minus090
A3 030 MK 266lowast 016 minus265lowast 375lowast 024SR 295lowast 027 minus309lowast 460lowast 040
A4 218 MK 242lowast 060 minus021 024 166SR 272lowast 054 minus037 043 173
A 048 MK 214lowast minus011 minus297lowast 307lowast 042SR 225lowast minus014 minus340lowast 336lowast 038
lowastSignificant trend at 5 significance level of two-tailed test
monsoon circulation [61] decline in forest cover [62 63] landuse changes and practices (eg irrigated agriculture) [64 65]and increasing aerosols from anthropogenic activities [66]
5 Conclusions
This paper analyzed trends in monthly seasonal and annualprecipitation in the Swat River basin over the 51-year studyperiod (1961ndash2011) A mix of positive and negative trendswas observed at various stations and subbasins The monthsof June November July and August showed the maximumnumber of significant cases at various stations in monthlyprecipitation The trends were positive in May and June andwere negative in July and August This indicates a shift inprecipitation series on monthly scale Significant positivetrends were detected in winter and autumn and annuallynegative trends were seen in spring and summer seasonsSaidu Sharif Mardan and Charsadda stations exhibitedsignificant positive trends in annual precipitation at a 95confidence level the remaining stations did not experiencea statistically significant trend
For the entire Swat River basin no significant trendswere detected in any subbasin for the annual precipitationseries Seasonally winter and autumn experienced significantpositive trends and summer experienced negative trends indifferent subbasins in the Swat River basin Most statisticallysignificant trend cases under different scenarios were positive(61)The results obtainedwith theMann-Kendall (MK) andSpearmanrsquos rho tests showed agreement in their assessmentsof monthly seasonal and annual precipitation trends Thevariability of negative and positive trends at various stationspoints to the need for more detailed studies on the climatechange of this region
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgments
The authors thank Pakistan Meteorological Department(PMD) Water and Power Development Authority
(WAPDA) Pakistan and Snowy Mountains EngineeringCorporation (SMEC) for providing cost-free data for thisstudy
References
[1] M D Rahman and M Begum ldquoApplication of non parametrictest for trend detection of rainfall in the largest Island ofBangladeshrdquo ARPN Journal of Earth Sciences vol 2 no 2 pp40ndash44 2013
[2] IPCCThePhysical Science Basis Contribution ofWorkingGroupI to the Fourth Assessment Report of the Intergovernmental Panelon Climate Change Cambridge University Press CambridgeUK 2007
[3] A B Farooq and A H Khan ldquoClimate change perspectivein Pakistanrdquo in Proceedings of the Capacity Building APNWorkshop on Global Change Research pp 39ndash46 IslamabadPakistan 2004
[4] Z Z Hu S Yang and R Wu ldquoLong-term climate variationsin China and global warming signalsrdquo Journal of GeophysicalResearch vol 108 no D19 2003
[5] P Zhai and X Pan ldquoTrends in temperature extremes during1951ndash1999 in Chinardquo Geophysical Research Letters vol 30 no17 p 1913 2003
[6] D Duhan and A Pandey ldquoStatistical analysis of long termspatial and temporal trends of precipitation during 1901ndash2002at Madhya Pradesh Indiardquo Atmospheric Research vol 122 pp136ndash149 2013
[7] B J Peterson RM Holmes JWMcClelland et al ldquoIncreasingriver discharge to the Arctic oceanrdquo Science vol 298 no 5601pp 2171ndash2173 2002
[8] N I Savelieva I P Semiletov L N Vasilevskaya and S PPugach ldquoA climate shift in seasonal values of meteorologicaland hydrological parameters for Northeastern Asiardquo Progress inOceanography vol 47 no 2ndash4 pp 279ndash297 2000
[9] Y F Shi Y P Shen and R J Hu ldquoPreliminary study on signalimpact and foreground of climatic shift from warm-dry towarm-humid in Northwest Chinardquo Journal of Glaciology andGeocryology vol 24 pp 219ndash226 2002 (Chinese)
[10] S Farhana and M M Rahman ldquoCharacterizing rainfall trendin Bangladesh by temporal statistics analysisrdquo in Proceedings ofthe 4th Annual Paper Meet and 1st Civil Engineering CongressDhaka Bangladesh 2011
[11] R H Rimi S H Rahman S Karmakar and S G HussainldquoTrend analysis of climate change and investigation on its
14 Advances in Meteorology
probable impacts on rice production at Satkhira BangladeshrdquoPakistan Journal of Meteorology vol 6 no 11 pp 37ndash50 2014
[12] E R Dahmen and M J Hall Screening of Hydrological DataTests for Stationarity and Relative Consistency Publication 49ILRI Wageningen The Netherlands 1990
[13] Q Zhang C Liu C-Y Xu Y Xu and T Jiang ldquoObserved trendsof annual maximumwater level and streamflow during past 130years in the Yangtze River basin Chinardquo Journal of Hydrologyvol 324 no 1-4 pp 255ndash265 2006
[14] H Chen S Guo C-Y Xu and V P Singh ldquoHistorical tem-poral trends of hydro-climatic variables and runoff responseto climate variability and their relevance in water resourcemanagement in the Hanjiang basinrdquo Journal of Hydrology vol344 no 3-4 pp 171ndash184 2007
[15] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 pp 245ndash259 1945
[16] M G Kendall Rank CorrelationMethods Griffin London UK1975
[17] E L Lehmann Nonparametrics Statistical Methods Based onRanks Holden-Day San Francisco Calif USA 1975
[18] R Sneyers ldquoOn the statistical analysis of series of observationsrdquoTechnical Note 143 WMO no 415 World MeteorologicalOrganization 1990
[19] A Longobardi and P Villani ldquoTrend analysis of annual andseasonal rainfall time series in the Mediterranean areardquo Inter-national Journal of Climatology vol 30 no 10 pp 1538ndash15462010
[20] Z YanmingW Jun andW Xinhua ldquoStudy on the change trendof precipitation and temperature in Kunming city based onMann-Kendall analysisrdquo in Future Computer CommunicationControl and Automation vol 119 of Advances in Intelligent andSoft Computing pp 505ndash513 Springer Berlin Germany 2011
[21] X L Yang L R Xu K K Liu C H Li J Hu and X H XialdquoTrend in temperature and precipitation in the ZhangweinanRiver Basin during the last 53 yearsrdquo Procedia EnvironmentalSciences vol 13 pp 1966ndash1974 1966
[22] Z F Yang Y Yan and Q Liu ldquoThe relationship of streamflow-precipitation-temperature in the Yellow River Basin of Chinaduring 1961ndash2000rdquo Procedia Environmental Sciences vol 13 pp2336ndash2345 2012
[23] Q-X Wang X-H Fan Z-D Qin and M-B Wang ldquoChangetrends of temperature and precipitation in the Loess PlateauRegion of China 1961ndash2010rdquo Global and Planetary Change vol92-93 pp 138ndash147 2012
[24] S Yue P Pilon and G Cavadias ldquoPower of the Mann-Kendalland Spearmanrsquos rho tests for detecting monotonic trends inhydrological seriesrdquo Journal of Hydrology vol 259 no 1ndash4 pp254ndash271 2002
[25] E Kahya and S Kalaycı ldquoTrend analysis of streamflow inTurkeyrdquo Journal of Hydrology vol 289 pp 128ndash144 2004
[26] Z L Li Z X Xu J Y Li and Z J Li ldquoShift trend and stepchanges for runoff time series in the Shiyang River BasinNorthwest Chinardquo Hydrological Processes vol 22 no 23 pp4639ndash4646 2008
[27] C Yaning X Changchun H Xingming et al ldquoFifty-yearclimate change and its effect on annual runoff in the TarimRiverBasin Chinardquo Quaternary International vol 208 no 1-2 pp53ndash61 2009
[28] M Shadmani SMarofi andMRoknian ldquoTrend analysis in ref-erence evapotranspiration usingMann-Kendall and SpearmanrsquosRho tests in arid regions of IranrdquoWater Resources Managementvol 26 no 1 pp 211ndash224 2012
[29] H Rehman and A Kamal ldquoIndus Basin River system-floodingand flood mitigationrdquo 2005 httparchiveriversymposiumcom2005indexphpelement=38
[30] Pakistan Meteorological Department (PMD) National PlanStrengthening National Capacities for Multi-hazard EarlyWarn-ing amp Response System 2006
[31] National Disaster Management Authority (NDMA) 2007National Disaster Risk Management Framework Governmentof Pakistan httpwwwndmagovpknew
[32] N H Hashimi Q T M Siddiqui A R Ghumman M AKamal and H R Mughal ldquoA critical analysis of 2010 floods inPakistanrdquo African Journal of Agricultural Research vol 7 no 7pp 1054ndash1067 2012
[33] FFC ldquoFederal Flood Commission of Pakistanrdquo Annual FloodReport-2010 2011 httpwwwffcgovpkdownloadfloodarc-hieveAnnualreport2010pdf
[34] N Gronewold and Climatewire ldquoIs the Flooding in Pakistan aClimate Change Disasterrdquo WMN 2010 httpwwwscientific-americancomarticleis-the-flooding-in-pakist
[35] H Hartmann and L Andresky ldquoFlooding in the Indus Riverbasinmdasha spatiotemporal analysis of precipitation recordsrdquoGlobal and Planetary Change vol 107 pp 25ndash35 2013
[36] S Salma S Rehman andM A Shah ldquoRainfall trends in differ-ent climate zones of Pakistanrdquo Pakistan Journal of Meteorologyvol 9 no 17 pp 37ndash47 2012
[37] M Hanif A H Khan and S Adnan ldquoLatitudinal precipitationcharacteristics and trends in Pakistanrdquo Journal ofHydrology vol492 pp 266ndash272 2013
[38] A Imran Q Zaman and M Afzal ldquoTemporal trends in thepeak monsoonal precipitation events over Northeast PakistanrdquoPakistan Journal of Meteorology vol 10 no 19 pp 19ndash30 2013
[39] S B Cheema and M Hanif ldquoSeasonal precipitation variationover Punjab provincerdquo Pakistan Journal of Meteorology vol 10no 19 pp 61ndash82 2013
[40] H Hartmann and H Buchanan ldquoTrends in extreme precipita-tion events in the indus River Basin and flooding in PakistanrdquoAtmosphere-Ocean vol 52 no 1 pp 77ndash91 2014
[41] ldquoProvincial Disaster Management Authority (PDMA 2012)Monsoon Contingency Plan-Khyber-Pakhtunkhwardquo 2012httpwwwndmagovpkDocumentsContingency Plan2012CP KPpdf
[42] Snowy Mountains Engineering Corporation Munda DamConstruction Project Detailed Design Report SMEC LahorePakistan 2014
[43] H Alexandersson ldquoA homogeneity test applied to precipitationdatardquo Journal of Climatology vol 6 no 6 pp 661ndash675 1986
[44] HAlexandersson andAMoberg ldquoHomogenization of Swedishtemperature data Part I homogeneity test for linear trendsrdquoInternational Journal of Climatology vol 17 no 1 pp 25ndash341997
[45] T A Buishand ldquoSome methods for testing the homogeneity ofrainfall recordsrdquo Journal of Hydrology vol 58 no 1-2 pp 11ndash271982
[46] M N Khaliq and T B M J Ouarda ldquoOn the critical values ofthe standard normal homogeneity test (SNHT)rdquo InternationalJournal of Climatology vol 27 no 5 pp 681ndash687 2007
[47] K H Hamed and A Ramachandra Rao ldquoA modified Mann-Kendall trend test for autocorrelated datardquo Journal of Hydrologyvol 204 no 1ndash4 pp 182ndash196 1998
[48] B Onoz and M Bayazit ldquoBlock bootstrap for Mann-Kendalltrend test of serially dependent datardquoHydrological Processes vol26 no 23 pp 3552ndash3560 2012
Advances in Meteorology 15
[49] M Yaseen H A Bhatti T Rientjes G Nabi and M LatifldquoTemporal and spatial variations in summer flows of upperIndus Basin Pakistanrdquo inProceedings of the 72ndAnnual Sessionof Pakistan Engineering Congress Paper no 747 pp 315ndash3342013
[50] G C Blain ldquoThe Mann-Kendall test the need to consider theinteraction between serial correlation and trendrdquo AgriculturalEngineering vol 35 no 4 2013
[51] M Yaseen T Rientjes G Nabi H ur-Rehman and M LatifldquoAssessment of recent temperature trends inManglawatershedrdquoJournal of Himalayan Earth Sciences vol 47 no 1 pp 107ndash1212014
[52] P K Sen ldquoEstimates of the regression coefficient based onKendallrsquos taurdquo Journal of the American Statistical Associationvol 63 no 324 pp 1379ndash1389 1968
[53] W S Cleveland ldquoRobust locally weighted regression andsmoothing scatterplotsrdquoThe Journal of the American StatisticalAssociation vol 74 no 368 pp 829ndash836 1979
[54] W S Cleveland ldquoGraphs in scientific publicationsrdquoThe Ameri-can Statistician vol 38 no 4 pp 261ndash269 1984
[55] D R Helsel and R M Hirsch ldquoStatistical methods in waterresourcesrdquo inTechniques ofWater Resources Investigations Book4 chapter A3 p 522 US Geological Survey 2002
[56] A P Dimri ldquoSurface and upper air fields during extreme winterprecipitation over the western Himalayasrdquo Pure and AppliedGeophysics vol 163 no 8 pp 1679ndash1698 2006
[57] A Ghaffar and M Javid ldquoImpact of global warming onmonsoon variability in Pakistanrdquo The Journal of Animal andPlant Sciences vol 21 no 1 pp 107ndash110 2011
[58] G Rasul ldquoClimate Data and Modelling Analysis of the IndusRegionrdquo Pakistan Meteorological Department (PMD) 2012httpwwfpakorgccappdfClimate Data Modelling20An-alysis20of20the20Indus20Ecoregionpdf
[59] A Basistha D S Arya and N K Goel ldquoAnalysis of historicalchanges in rainfall in the Indian Himalayasrdquo InternationalJournal of Climatology vol 29 no 4 pp 555ndash572 2009
[60] P G Baines ldquoThe late 1960s global climate shift and its influenceon the Southern Hemisphererdquo in Proceedings of 8 ICSHMO pp1477ndash1482 INPE Foz do Iguacu Brazil 2006
[61] K Duan and T Yao ldquoMonsoon variability in the Himalayasunder the condition of global warmingrdquo Journal of the Mete-orological Society of Japan vol 81 no 2 pp 251ndash257 2003
[62] U S Nair R O Lawton R M Welch and R A Pielke SrldquoImpact of land use on Costa Rican tropical montane cloudforests sensitivity of cumulus cloud field characteristics tolowland deforestationrdquo Journal of Geophysical Research D vol108 no 7 pp 4206ndash4219 2003
[63] R Avissar and D Werth ldquoGlobal hydroclimatological tele-connections resulting from tropical deforestationrdquo Journal ofHydrometeorology vol 6 no 2 pp 134ndash145 2005
[64] R A Pielke Sr J Adegoke A Beltran-Przekurat et al ldquoAnoverview of regional land-use and land-cover impacts onrainfallrdquo Tellus B Chemical and Physical Meteorology vol 59no 3 pp 587ndash601 2007
[65] N Ramankutty C Delire and P Snyder ldquoFeedbacks betweenagriculture and climate an illustration of the potential unin-tended consequences of human land use activitiesrdquo Global andPlanetary Change vol 54 no 1-2 pp 79ndash93 2006
[66] V Ramanathan C Chung D Kim et al ldquoAtmospheric brownclouds impacts on South Asian climate and hydrological cyclerdquoProceedings of the National Academy of Sciences of the UnitedStates of America vol 102 no 15 pp 5326ndash5333 2005
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ClimatologyJournal of
EcologyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
EarthquakesJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom
Applied ampEnvironmentalSoil Science
Volume 2014
Mining
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Hindawi Publishing Corporation httpwwwhindawicom Volume 2014
International Journal of
Geophysics
OceanographyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal ofPetroleum Engineering
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
GeochemistryHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Atmospheric SciencesInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OceanographyHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Advances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MineralogyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MeteorologyAdvances in
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Paleontology JournalHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geological ResearchJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geology Advances in
Advances in Meteorology 11
Table5MKandSR
tests
results
form
onthlyprecipitatio
ntim
eseriesinentireb
asin
andsubb
asinso
fSwatRiver
Subb
asin
Test
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
A1
MK
047
010
071
minus12
3041
349lowast
minus288lowast
minus318lowast
minus018
143
250lowast
094
SR045
006
074
minus098
047
409lowast
minus299lowast
minus363lowast
minus018
159
277lowast
094
A2
MK
107
080
016
minus093
021
201lowast
minus354lowast
minus416lowast
minus202lowast
000
187
062
SR095
072
001
minus099
013
231lowast
minus386lowast
minus486lowast
minus224lowast
011
200
063
A3
MK
250lowast
102
minus036
065
297lowast
390lowast
minus297lowast
minus255lowast
minus044
305lowast
295lowast
229lowast
SR267lowast
089
minus009
070
311lowast
479lowast
minus354lowast
minus322lowast
minus052
376lowast
365lowast
260lowast
A4
MK
237lowast
088
minus006
minus050
122
164
minus063
minus083
000
020
050
minus040
SR246lowast
084
minus001
minus059
117
182
minus059
minus090
001
045
023
minus046
AMK
185
110
013
minus062
123
369lowast
minus255lowast
minus361lowast
minus065
174
268lowast
070
SR17
010
4018
minus079
127
422lowast
minus277lowast
minus401lowast
minus070
181
299lowast
073
lowast
Sign
ificant
trend
at5
significance
leveloftwo-tailedtest
12 Advances in Meteorology
0
500
1000
1500
2000
2500
3000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Saidu Sharif station
(a)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Mardan station
(b)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Charsadda station
(c)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Thalozom station
(d)
Figure 6 Variations of annual precipitation time series in stations with significant trends during 1961ndash2011
36 Comparison of Results Results from both statistical testsMK and SR were consistent with each otherThe percentagesof statistically significant cases to total tested cases for theMK and SR tests were 32 and 30 respectively showingagreement across methods This consistency in statisticalperformance was also found in other studies [24 28]
4 Discussion
This study investigated variability in monthly seasonal andannual precipitation at 15 stations in the Swat River basinover a 51-year study period (1961ndash2011) Precipitation trendswere also analyzed for each subbasin and entire Swat Riverbasin The mean annual precipitation at different stationsshowed considerable variation with a standard deviationof 1768mm from the mean annual rainfall of 694mmThe Saidu Sharif Mardan and Charsadda stations showedsignificant positive trends (increased precipitation over time)at 5 significance level in the annual precipitation series
The maximum number of significant changes in monthlyprecipitation over time was detected at Saidu Sharif Abazaiand Khairabad stations Saidu Sharif station showed themaximum increasing slope (indicating sharpest change overtime) of 748mmyear among the selected stations in the SwatRiver basin
These study results follow the same statistical trendsreported by Hartmann and Andresky [35] for northwestparts of Pakistan Findings were consistent with results fromDimri [56] Ghaffar and Javid [57] and Rasul [58] whereinthey found statistically significant increasing trends in winterprecipitation for northwest areas of Pakistan The resultsof this analysis also support finding of Hanif et al [37]wherein they found significant variations in summer seasonprecipitation These variations in precipitation trends maylead Pakistan towards more water related disasters suchas droughts and floods in the near future Basistha et al[59] proposed possible causes of the changing precipitationtrends such as global climate shifts [60] dwindling global
Advances in Meteorology 13
Table 6 MK and SR results for seasonal and annual precipitation time series in entire basin and subbasin of Swat River
Subbasin Change (mmyear) Test Winter Spring Summer Autumn Annual
A1 minus073 MK 055 minus024 minus242lowast 305lowast minus034SR 057 001 minus227lowast 347lowast 118
A2 minus090 MK 128 minus023 minus385lowast 158 minus081SR 118 minus035 minus444lowast 164 minus090
A3 030 MK 266lowast 016 minus265lowast 375lowast 024SR 295lowast 027 minus309lowast 460lowast 040
A4 218 MK 242lowast 060 minus021 024 166SR 272lowast 054 minus037 043 173
A 048 MK 214lowast minus011 minus297lowast 307lowast 042SR 225lowast minus014 minus340lowast 336lowast 038
lowastSignificant trend at 5 significance level of two-tailed test
monsoon circulation [61] decline in forest cover [62 63] landuse changes and practices (eg irrigated agriculture) [64 65]and increasing aerosols from anthropogenic activities [66]
5 Conclusions
This paper analyzed trends in monthly seasonal and annualprecipitation in the Swat River basin over the 51-year studyperiod (1961ndash2011) A mix of positive and negative trendswas observed at various stations and subbasins The monthsof June November July and August showed the maximumnumber of significant cases at various stations in monthlyprecipitation The trends were positive in May and June andwere negative in July and August This indicates a shift inprecipitation series on monthly scale Significant positivetrends were detected in winter and autumn and annuallynegative trends were seen in spring and summer seasonsSaidu Sharif Mardan and Charsadda stations exhibitedsignificant positive trends in annual precipitation at a 95confidence level the remaining stations did not experiencea statistically significant trend
For the entire Swat River basin no significant trendswere detected in any subbasin for the annual precipitationseries Seasonally winter and autumn experienced significantpositive trends and summer experienced negative trends indifferent subbasins in the Swat River basin Most statisticallysignificant trend cases under different scenarios were positive(61)The results obtainedwith theMann-Kendall (MK) andSpearmanrsquos rho tests showed agreement in their assessmentsof monthly seasonal and annual precipitation trends Thevariability of negative and positive trends at various stationspoints to the need for more detailed studies on the climatechange of this region
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgments
The authors thank Pakistan Meteorological Department(PMD) Water and Power Development Authority
(WAPDA) Pakistan and Snowy Mountains EngineeringCorporation (SMEC) for providing cost-free data for thisstudy
References
[1] M D Rahman and M Begum ldquoApplication of non parametrictest for trend detection of rainfall in the largest Island ofBangladeshrdquo ARPN Journal of Earth Sciences vol 2 no 2 pp40ndash44 2013
[2] IPCCThePhysical Science Basis Contribution ofWorkingGroupI to the Fourth Assessment Report of the Intergovernmental Panelon Climate Change Cambridge University Press CambridgeUK 2007
[3] A B Farooq and A H Khan ldquoClimate change perspectivein Pakistanrdquo in Proceedings of the Capacity Building APNWorkshop on Global Change Research pp 39ndash46 IslamabadPakistan 2004
[4] Z Z Hu S Yang and R Wu ldquoLong-term climate variationsin China and global warming signalsrdquo Journal of GeophysicalResearch vol 108 no D19 2003
[5] P Zhai and X Pan ldquoTrends in temperature extremes during1951ndash1999 in Chinardquo Geophysical Research Letters vol 30 no17 p 1913 2003
[6] D Duhan and A Pandey ldquoStatistical analysis of long termspatial and temporal trends of precipitation during 1901ndash2002at Madhya Pradesh Indiardquo Atmospheric Research vol 122 pp136ndash149 2013
[7] B J Peterson RM Holmes JWMcClelland et al ldquoIncreasingriver discharge to the Arctic oceanrdquo Science vol 298 no 5601pp 2171ndash2173 2002
[8] N I Savelieva I P Semiletov L N Vasilevskaya and S PPugach ldquoA climate shift in seasonal values of meteorologicaland hydrological parameters for Northeastern Asiardquo Progress inOceanography vol 47 no 2ndash4 pp 279ndash297 2000
[9] Y F Shi Y P Shen and R J Hu ldquoPreliminary study on signalimpact and foreground of climatic shift from warm-dry towarm-humid in Northwest Chinardquo Journal of Glaciology andGeocryology vol 24 pp 219ndash226 2002 (Chinese)
[10] S Farhana and M M Rahman ldquoCharacterizing rainfall trendin Bangladesh by temporal statistics analysisrdquo in Proceedings ofthe 4th Annual Paper Meet and 1st Civil Engineering CongressDhaka Bangladesh 2011
[11] R H Rimi S H Rahman S Karmakar and S G HussainldquoTrend analysis of climate change and investigation on its
14 Advances in Meteorology
probable impacts on rice production at Satkhira BangladeshrdquoPakistan Journal of Meteorology vol 6 no 11 pp 37ndash50 2014
[12] E R Dahmen and M J Hall Screening of Hydrological DataTests for Stationarity and Relative Consistency Publication 49ILRI Wageningen The Netherlands 1990
[13] Q Zhang C Liu C-Y Xu Y Xu and T Jiang ldquoObserved trendsof annual maximumwater level and streamflow during past 130years in the Yangtze River basin Chinardquo Journal of Hydrologyvol 324 no 1-4 pp 255ndash265 2006
[14] H Chen S Guo C-Y Xu and V P Singh ldquoHistorical tem-poral trends of hydro-climatic variables and runoff responseto climate variability and their relevance in water resourcemanagement in the Hanjiang basinrdquo Journal of Hydrology vol344 no 3-4 pp 171ndash184 2007
[15] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 pp 245ndash259 1945
[16] M G Kendall Rank CorrelationMethods Griffin London UK1975
[17] E L Lehmann Nonparametrics Statistical Methods Based onRanks Holden-Day San Francisco Calif USA 1975
[18] R Sneyers ldquoOn the statistical analysis of series of observationsrdquoTechnical Note 143 WMO no 415 World MeteorologicalOrganization 1990
[19] A Longobardi and P Villani ldquoTrend analysis of annual andseasonal rainfall time series in the Mediterranean areardquo Inter-national Journal of Climatology vol 30 no 10 pp 1538ndash15462010
[20] Z YanmingW Jun andW Xinhua ldquoStudy on the change trendof precipitation and temperature in Kunming city based onMann-Kendall analysisrdquo in Future Computer CommunicationControl and Automation vol 119 of Advances in Intelligent andSoft Computing pp 505ndash513 Springer Berlin Germany 2011
[21] X L Yang L R Xu K K Liu C H Li J Hu and X H XialdquoTrend in temperature and precipitation in the ZhangweinanRiver Basin during the last 53 yearsrdquo Procedia EnvironmentalSciences vol 13 pp 1966ndash1974 1966
[22] Z F Yang Y Yan and Q Liu ldquoThe relationship of streamflow-precipitation-temperature in the Yellow River Basin of Chinaduring 1961ndash2000rdquo Procedia Environmental Sciences vol 13 pp2336ndash2345 2012
[23] Q-X Wang X-H Fan Z-D Qin and M-B Wang ldquoChangetrends of temperature and precipitation in the Loess PlateauRegion of China 1961ndash2010rdquo Global and Planetary Change vol92-93 pp 138ndash147 2012
[24] S Yue P Pilon and G Cavadias ldquoPower of the Mann-Kendalland Spearmanrsquos rho tests for detecting monotonic trends inhydrological seriesrdquo Journal of Hydrology vol 259 no 1ndash4 pp254ndash271 2002
[25] E Kahya and S Kalaycı ldquoTrend analysis of streamflow inTurkeyrdquo Journal of Hydrology vol 289 pp 128ndash144 2004
[26] Z L Li Z X Xu J Y Li and Z J Li ldquoShift trend and stepchanges for runoff time series in the Shiyang River BasinNorthwest Chinardquo Hydrological Processes vol 22 no 23 pp4639ndash4646 2008
[27] C Yaning X Changchun H Xingming et al ldquoFifty-yearclimate change and its effect on annual runoff in the TarimRiverBasin Chinardquo Quaternary International vol 208 no 1-2 pp53ndash61 2009
[28] M Shadmani SMarofi andMRoknian ldquoTrend analysis in ref-erence evapotranspiration usingMann-Kendall and SpearmanrsquosRho tests in arid regions of IranrdquoWater Resources Managementvol 26 no 1 pp 211ndash224 2012
[29] H Rehman and A Kamal ldquoIndus Basin River system-floodingand flood mitigationrdquo 2005 httparchiveriversymposiumcom2005indexphpelement=38
[30] Pakistan Meteorological Department (PMD) National PlanStrengthening National Capacities for Multi-hazard EarlyWarn-ing amp Response System 2006
[31] National Disaster Management Authority (NDMA) 2007National Disaster Risk Management Framework Governmentof Pakistan httpwwwndmagovpknew
[32] N H Hashimi Q T M Siddiqui A R Ghumman M AKamal and H R Mughal ldquoA critical analysis of 2010 floods inPakistanrdquo African Journal of Agricultural Research vol 7 no 7pp 1054ndash1067 2012
[33] FFC ldquoFederal Flood Commission of Pakistanrdquo Annual FloodReport-2010 2011 httpwwwffcgovpkdownloadfloodarc-hieveAnnualreport2010pdf
[34] N Gronewold and Climatewire ldquoIs the Flooding in Pakistan aClimate Change Disasterrdquo WMN 2010 httpwwwscientific-americancomarticleis-the-flooding-in-pakist
[35] H Hartmann and L Andresky ldquoFlooding in the Indus Riverbasinmdasha spatiotemporal analysis of precipitation recordsrdquoGlobal and Planetary Change vol 107 pp 25ndash35 2013
[36] S Salma S Rehman andM A Shah ldquoRainfall trends in differ-ent climate zones of Pakistanrdquo Pakistan Journal of Meteorologyvol 9 no 17 pp 37ndash47 2012
[37] M Hanif A H Khan and S Adnan ldquoLatitudinal precipitationcharacteristics and trends in Pakistanrdquo Journal ofHydrology vol492 pp 266ndash272 2013
[38] A Imran Q Zaman and M Afzal ldquoTemporal trends in thepeak monsoonal precipitation events over Northeast PakistanrdquoPakistan Journal of Meteorology vol 10 no 19 pp 19ndash30 2013
[39] S B Cheema and M Hanif ldquoSeasonal precipitation variationover Punjab provincerdquo Pakistan Journal of Meteorology vol 10no 19 pp 61ndash82 2013
[40] H Hartmann and H Buchanan ldquoTrends in extreme precipita-tion events in the indus River Basin and flooding in PakistanrdquoAtmosphere-Ocean vol 52 no 1 pp 77ndash91 2014
[41] ldquoProvincial Disaster Management Authority (PDMA 2012)Monsoon Contingency Plan-Khyber-Pakhtunkhwardquo 2012httpwwwndmagovpkDocumentsContingency Plan2012CP KPpdf
[42] Snowy Mountains Engineering Corporation Munda DamConstruction Project Detailed Design Report SMEC LahorePakistan 2014
[43] H Alexandersson ldquoA homogeneity test applied to precipitationdatardquo Journal of Climatology vol 6 no 6 pp 661ndash675 1986
[44] HAlexandersson andAMoberg ldquoHomogenization of Swedishtemperature data Part I homogeneity test for linear trendsrdquoInternational Journal of Climatology vol 17 no 1 pp 25ndash341997
[45] T A Buishand ldquoSome methods for testing the homogeneity ofrainfall recordsrdquo Journal of Hydrology vol 58 no 1-2 pp 11ndash271982
[46] M N Khaliq and T B M J Ouarda ldquoOn the critical values ofthe standard normal homogeneity test (SNHT)rdquo InternationalJournal of Climatology vol 27 no 5 pp 681ndash687 2007
[47] K H Hamed and A Ramachandra Rao ldquoA modified Mann-Kendall trend test for autocorrelated datardquo Journal of Hydrologyvol 204 no 1ndash4 pp 182ndash196 1998
[48] B Onoz and M Bayazit ldquoBlock bootstrap for Mann-Kendalltrend test of serially dependent datardquoHydrological Processes vol26 no 23 pp 3552ndash3560 2012
Advances in Meteorology 15
[49] M Yaseen H A Bhatti T Rientjes G Nabi and M LatifldquoTemporal and spatial variations in summer flows of upperIndus Basin Pakistanrdquo inProceedings of the 72ndAnnual Sessionof Pakistan Engineering Congress Paper no 747 pp 315ndash3342013
[50] G C Blain ldquoThe Mann-Kendall test the need to consider theinteraction between serial correlation and trendrdquo AgriculturalEngineering vol 35 no 4 2013
[51] M Yaseen T Rientjes G Nabi H ur-Rehman and M LatifldquoAssessment of recent temperature trends inManglawatershedrdquoJournal of Himalayan Earth Sciences vol 47 no 1 pp 107ndash1212014
[52] P K Sen ldquoEstimates of the regression coefficient based onKendallrsquos taurdquo Journal of the American Statistical Associationvol 63 no 324 pp 1379ndash1389 1968
[53] W S Cleveland ldquoRobust locally weighted regression andsmoothing scatterplotsrdquoThe Journal of the American StatisticalAssociation vol 74 no 368 pp 829ndash836 1979
[54] W S Cleveland ldquoGraphs in scientific publicationsrdquoThe Ameri-can Statistician vol 38 no 4 pp 261ndash269 1984
[55] D R Helsel and R M Hirsch ldquoStatistical methods in waterresourcesrdquo inTechniques ofWater Resources Investigations Book4 chapter A3 p 522 US Geological Survey 2002
[56] A P Dimri ldquoSurface and upper air fields during extreme winterprecipitation over the western Himalayasrdquo Pure and AppliedGeophysics vol 163 no 8 pp 1679ndash1698 2006
[57] A Ghaffar and M Javid ldquoImpact of global warming onmonsoon variability in Pakistanrdquo The Journal of Animal andPlant Sciences vol 21 no 1 pp 107ndash110 2011
[58] G Rasul ldquoClimate Data and Modelling Analysis of the IndusRegionrdquo Pakistan Meteorological Department (PMD) 2012httpwwfpakorgccappdfClimate Data Modelling20An-alysis20of20the20Indus20Ecoregionpdf
[59] A Basistha D S Arya and N K Goel ldquoAnalysis of historicalchanges in rainfall in the Indian Himalayasrdquo InternationalJournal of Climatology vol 29 no 4 pp 555ndash572 2009
[60] P G Baines ldquoThe late 1960s global climate shift and its influenceon the Southern Hemisphererdquo in Proceedings of 8 ICSHMO pp1477ndash1482 INPE Foz do Iguacu Brazil 2006
[61] K Duan and T Yao ldquoMonsoon variability in the Himalayasunder the condition of global warmingrdquo Journal of the Mete-orological Society of Japan vol 81 no 2 pp 251ndash257 2003
[62] U S Nair R O Lawton R M Welch and R A Pielke SrldquoImpact of land use on Costa Rican tropical montane cloudforests sensitivity of cumulus cloud field characteristics tolowland deforestationrdquo Journal of Geophysical Research D vol108 no 7 pp 4206ndash4219 2003
[63] R Avissar and D Werth ldquoGlobal hydroclimatological tele-connections resulting from tropical deforestationrdquo Journal ofHydrometeorology vol 6 no 2 pp 134ndash145 2005
[64] R A Pielke Sr J Adegoke A Beltran-Przekurat et al ldquoAnoverview of regional land-use and land-cover impacts onrainfallrdquo Tellus B Chemical and Physical Meteorology vol 59no 3 pp 587ndash601 2007
[65] N Ramankutty C Delire and P Snyder ldquoFeedbacks betweenagriculture and climate an illustration of the potential unin-tended consequences of human land use activitiesrdquo Global andPlanetary Change vol 54 no 1-2 pp 79ndash93 2006
[66] V Ramanathan C Chung D Kim et al ldquoAtmospheric brownclouds impacts on South Asian climate and hydrological cyclerdquoProceedings of the National Academy of Sciences of the UnitedStates of America vol 102 no 15 pp 5326ndash5333 2005
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ClimatologyJournal of
EcologyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
EarthquakesJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom
Applied ampEnvironmentalSoil Science
Volume 2014
Mining
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Hindawi Publishing Corporation httpwwwhindawicom Volume 2014
International Journal of
Geophysics
OceanographyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal ofPetroleum Engineering
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
GeochemistryHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Atmospheric SciencesInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OceanographyHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Advances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MineralogyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MeteorologyAdvances in
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Paleontology JournalHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geological ResearchJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geology Advances in
12 Advances in Meteorology
0
500
1000
1500
2000
2500
3000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Saidu Sharif station
(a)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Mardan station
(b)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Charsadda station
(c)
0
500
1000
1500
2000
1960 1970 1980 1990 2000 2010
Prec
ipita
tion
(mm
yea
r)
Year
Thalozom station
(d)
Figure 6 Variations of annual precipitation time series in stations with significant trends during 1961ndash2011
36 Comparison of Results Results from both statistical testsMK and SR were consistent with each otherThe percentagesof statistically significant cases to total tested cases for theMK and SR tests were 32 and 30 respectively showingagreement across methods This consistency in statisticalperformance was also found in other studies [24 28]
4 Discussion
This study investigated variability in monthly seasonal andannual precipitation at 15 stations in the Swat River basinover a 51-year study period (1961ndash2011) Precipitation trendswere also analyzed for each subbasin and entire Swat Riverbasin The mean annual precipitation at different stationsshowed considerable variation with a standard deviationof 1768mm from the mean annual rainfall of 694mmThe Saidu Sharif Mardan and Charsadda stations showedsignificant positive trends (increased precipitation over time)at 5 significance level in the annual precipitation series
The maximum number of significant changes in monthlyprecipitation over time was detected at Saidu Sharif Abazaiand Khairabad stations Saidu Sharif station showed themaximum increasing slope (indicating sharpest change overtime) of 748mmyear among the selected stations in the SwatRiver basin
These study results follow the same statistical trendsreported by Hartmann and Andresky [35] for northwestparts of Pakistan Findings were consistent with results fromDimri [56] Ghaffar and Javid [57] and Rasul [58] whereinthey found statistically significant increasing trends in winterprecipitation for northwest areas of Pakistan The resultsof this analysis also support finding of Hanif et al [37]wherein they found significant variations in summer seasonprecipitation These variations in precipitation trends maylead Pakistan towards more water related disasters suchas droughts and floods in the near future Basistha et al[59] proposed possible causes of the changing precipitationtrends such as global climate shifts [60] dwindling global
Advances in Meteorology 13
Table 6 MK and SR results for seasonal and annual precipitation time series in entire basin and subbasin of Swat River
Subbasin Change (mmyear) Test Winter Spring Summer Autumn Annual
A1 minus073 MK 055 minus024 minus242lowast 305lowast minus034SR 057 001 minus227lowast 347lowast 118
A2 minus090 MK 128 minus023 minus385lowast 158 minus081SR 118 minus035 minus444lowast 164 minus090
A3 030 MK 266lowast 016 minus265lowast 375lowast 024SR 295lowast 027 minus309lowast 460lowast 040
A4 218 MK 242lowast 060 minus021 024 166SR 272lowast 054 minus037 043 173
A 048 MK 214lowast minus011 minus297lowast 307lowast 042SR 225lowast minus014 minus340lowast 336lowast 038
lowastSignificant trend at 5 significance level of two-tailed test
monsoon circulation [61] decline in forest cover [62 63] landuse changes and practices (eg irrigated agriculture) [64 65]and increasing aerosols from anthropogenic activities [66]
5 Conclusions
This paper analyzed trends in monthly seasonal and annualprecipitation in the Swat River basin over the 51-year studyperiod (1961ndash2011) A mix of positive and negative trendswas observed at various stations and subbasins The monthsof June November July and August showed the maximumnumber of significant cases at various stations in monthlyprecipitation The trends were positive in May and June andwere negative in July and August This indicates a shift inprecipitation series on monthly scale Significant positivetrends were detected in winter and autumn and annuallynegative trends were seen in spring and summer seasonsSaidu Sharif Mardan and Charsadda stations exhibitedsignificant positive trends in annual precipitation at a 95confidence level the remaining stations did not experiencea statistically significant trend
For the entire Swat River basin no significant trendswere detected in any subbasin for the annual precipitationseries Seasonally winter and autumn experienced significantpositive trends and summer experienced negative trends indifferent subbasins in the Swat River basin Most statisticallysignificant trend cases under different scenarios were positive(61)The results obtainedwith theMann-Kendall (MK) andSpearmanrsquos rho tests showed agreement in their assessmentsof monthly seasonal and annual precipitation trends Thevariability of negative and positive trends at various stationspoints to the need for more detailed studies on the climatechange of this region
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgments
The authors thank Pakistan Meteorological Department(PMD) Water and Power Development Authority
(WAPDA) Pakistan and Snowy Mountains EngineeringCorporation (SMEC) for providing cost-free data for thisstudy
References
[1] M D Rahman and M Begum ldquoApplication of non parametrictest for trend detection of rainfall in the largest Island ofBangladeshrdquo ARPN Journal of Earth Sciences vol 2 no 2 pp40ndash44 2013
[2] IPCCThePhysical Science Basis Contribution ofWorkingGroupI to the Fourth Assessment Report of the Intergovernmental Panelon Climate Change Cambridge University Press CambridgeUK 2007
[3] A B Farooq and A H Khan ldquoClimate change perspectivein Pakistanrdquo in Proceedings of the Capacity Building APNWorkshop on Global Change Research pp 39ndash46 IslamabadPakistan 2004
[4] Z Z Hu S Yang and R Wu ldquoLong-term climate variationsin China and global warming signalsrdquo Journal of GeophysicalResearch vol 108 no D19 2003
[5] P Zhai and X Pan ldquoTrends in temperature extremes during1951ndash1999 in Chinardquo Geophysical Research Letters vol 30 no17 p 1913 2003
[6] D Duhan and A Pandey ldquoStatistical analysis of long termspatial and temporal trends of precipitation during 1901ndash2002at Madhya Pradesh Indiardquo Atmospheric Research vol 122 pp136ndash149 2013
[7] B J Peterson RM Holmes JWMcClelland et al ldquoIncreasingriver discharge to the Arctic oceanrdquo Science vol 298 no 5601pp 2171ndash2173 2002
[8] N I Savelieva I P Semiletov L N Vasilevskaya and S PPugach ldquoA climate shift in seasonal values of meteorologicaland hydrological parameters for Northeastern Asiardquo Progress inOceanography vol 47 no 2ndash4 pp 279ndash297 2000
[9] Y F Shi Y P Shen and R J Hu ldquoPreliminary study on signalimpact and foreground of climatic shift from warm-dry towarm-humid in Northwest Chinardquo Journal of Glaciology andGeocryology vol 24 pp 219ndash226 2002 (Chinese)
[10] S Farhana and M M Rahman ldquoCharacterizing rainfall trendin Bangladesh by temporal statistics analysisrdquo in Proceedings ofthe 4th Annual Paper Meet and 1st Civil Engineering CongressDhaka Bangladesh 2011
[11] R H Rimi S H Rahman S Karmakar and S G HussainldquoTrend analysis of climate change and investigation on its
14 Advances in Meteorology
probable impacts on rice production at Satkhira BangladeshrdquoPakistan Journal of Meteorology vol 6 no 11 pp 37ndash50 2014
[12] E R Dahmen and M J Hall Screening of Hydrological DataTests for Stationarity and Relative Consistency Publication 49ILRI Wageningen The Netherlands 1990
[13] Q Zhang C Liu C-Y Xu Y Xu and T Jiang ldquoObserved trendsof annual maximumwater level and streamflow during past 130years in the Yangtze River basin Chinardquo Journal of Hydrologyvol 324 no 1-4 pp 255ndash265 2006
[14] H Chen S Guo C-Y Xu and V P Singh ldquoHistorical tem-poral trends of hydro-climatic variables and runoff responseto climate variability and their relevance in water resourcemanagement in the Hanjiang basinrdquo Journal of Hydrology vol344 no 3-4 pp 171ndash184 2007
[15] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 pp 245ndash259 1945
[16] M G Kendall Rank CorrelationMethods Griffin London UK1975
[17] E L Lehmann Nonparametrics Statistical Methods Based onRanks Holden-Day San Francisco Calif USA 1975
[18] R Sneyers ldquoOn the statistical analysis of series of observationsrdquoTechnical Note 143 WMO no 415 World MeteorologicalOrganization 1990
[19] A Longobardi and P Villani ldquoTrend analysis of annual andseasonal rainfall time series in the Mediterranean areardquo Inter-national Journal of Climatology vol 30 no 10 pp 1538ndash15462010
[20] Z YanmingW Jun andW Xinhua ldquoStudy on the change trendof precipitation and temperature in Kunming city based onMann-Kendall analysisrdquo in Future Computer CommunicationControl and Automation vol 119 of Advances in Intelligent andSoft Computing pp 505ndash513 Springer Berlin Germany 2011
[21] X L Yang L R Xu K K Liu C H Li J Hu and X H XialdquoTrend in temperature and precipitation in the ZhangweinanRiver Basin during the last 53 yearsrdquo Procedia EnvironmentalSciences vol 13 pp 1966ndash1974 1966
[22] Z F Yang Y Yan and Q Liu ldquoThe relationship of streamflow-precipitation-temperature in the Yellow River Basin of Chinaduring 1961ndash2000rdquo Procedia Environmental Sciences vol 13 pp2336ndash2345 2012
[23] Q-X Wang X-H Fan Z-D Qin and M-B Wang ldquoChangetrends of temperature and precipitation in the Loess PlateauRegion of China 1961ndash2010rdquo Global and Planetary Change vol92-93 pp 138ndash147 2012
[24] S Yue P Pilon and G Cavadias ldquoPower of the Mann-Kendalland Spearmanrsquos rho tests for detecting monotonic trends inhydrological seriesrdquo Journal of Hydrology vol 259 no 1ndash4 pp254ndash271 2002
[25] E Kahya and S Kalaycı ldquoTrend analysis of streamflow inTurkeyrdquo Journal of Hydrology vol 289 pp 128ndash144 2004
[26] Z L Li Z X Xu J Y Li and Z J Li ldquoShift trend and stepchanges for runoff time series in the Shiyang River BasinNorthwest Chinardquo Hydrological Processes vol 22 no 23 pp4639ndash4646 2008
[27] C Yaning X Changchun H Xingming et al ldquoFifty-yearclimate change and its effect on annual runoff in the TarimRiverBasin Chinardquo Quaternary International vol 208 no 1-2 pp53ndash61 2009
[28] M Shadmani SMarofi andMRoknian ldquoTrend analysis in ref-erence evapotranspiration usingMann-Kendall and SpearmanrsquosRho tests in arid regions of IranrdquoWater Resources Managementvol 26 no 1 pp 211ndash224 2012
[29] H Rehman and A Kamal ldquoIndus Basin River system-floodingand flood mitigationrdquo 2005 httparchiveriversymposiumcom2005indexphpelement=38
[30] Pakistan Meteorological Department (PMD) National PlanStrengthening National Capacities for Multi-hazard EarlyWarn-ing amp Response System 2006
[31] National Disaster Management Authority (NDMA) 2007National Disaster Risk Management Framework Governmentof Pakistan httpwwwndmagovpknew
[32] N H Hashimi Q T M Siddiqui A R Ghumman M AKamal and H R Mughal ldquoA critical analysis of 2010 floods inPakistanrdquo African Journal of Agricultural Research vol 7 no 7pp 1054ndash1067 2012
[33] FFC ldquoFederal Flood Commission of Pakistanrdquo Annual FloodReport-2010 2011 httpwwwffcgovpkdownloadfloodarc-hieveAnnualreport2010pdf
[34] N Gronewold and Climatewire ldquoIs the Flooding in Pakistan aClimate Change Disasterrdquo WMN 2010 httpwwwscientific-americancomarticleis-the-flooding-in-pakist
[35] H Hartmann and L Andresky ldquoFlooding in the Indus Riverbasinmdasha spatiotemporal analysis of precipitation recordsrdquoGlobal and Planetary Change vol 107 pp 25ndash35 2013
[36] S Salma S Rehman andM A Shah ldquoRainfall trends in differ-ent climate zones of Pakistanrdquo Pakistan Journal of Meteorologyvol 9 no 17 pp 37ndash47 2012
[37] M Hanif A H Khan and S Adnan ldquoLatitudinal precipitationcharacteristics and trends in Pakistanrdquo Journal ofHydrology vol492 pp 266ndash272 2013
[38] A Imran Q Zaman and M Afzal ldquoTemporal trends in thepeak monsoonal precipitation events over Northeast PakistanrdquoPakistan Journal of Meteorology vol 10 no 19 pp 19ndash30 2013
[39] S B Cheema and M Hanif ldquoSeasonal precipitation variationover Punjab provincerdquo Pakistan Journal of Meteorology vol 10no 19 pp 61ndash82 2013
[40] H Hartmann and H Buchanan ldquoTrends in extreme precipita-tion events in the indus River Basin and flooding in PakistanrdquoAtmosphere-Ocean vol 52 no 1 pp 77ndash91 2014
[41] ldquoProvincial Disaster Management Authority (PDMA 2012)Monsoon Contingency Plan-Khyber-Pakhtunkhwardquo 2012httpwwwndmagovpkDocumentsContingency Plan2012CP KPpdf
[42] Snowy Mountains Engineering Corporation Munda DamConstruction Project Detailed Design Report SMEC LahorePakistan 2014
[43] H Alexandersson ldquoA homogeneity test applied to precipitationdatardquo Journal of Climatology vol 6 no 6 pp 661ndash675 1986
[44] HAlexandersson andAMoberg ldquoHomogenization of Swedishtemperature data Part I homogeneity test for linear trendsrdquoInternational Journal of Climatology vol 17 no 1 pp 25ndash341997
[45] T A Buishand ldquoSome methods for testing the homogeneity ofrainfall recordsrdquo Journal of Hydrology vol 58 no 1-2 pp 11ndash271982
[46] M N Khaliq and T B M J Ouarda ldquoOn the critical values ofthe standard normal homogeneity test (SNHT)rdquo InternationalJournal of Climatology vol 27 no 5 pp 681ndash687 2007
[47] K H Hamed and A Ramachandra Rao ldquoA modified Mann-Kendall trend test for autocorrelated datardquo Journal of Hydrologyvol 204 no 1ndash4 pp 182ndash196 1998
[48] B Onoz and M Bayazit ldquoBlock bootstrap for Mann-Kendalltrend test of serially dependent datardquoHydrological Processes vol26 no 23 pp 3552ndash3560 2012
Advances in Meteorology 15
[49] M Yaseen H A Bhatti T Rientjes G Nabi and M LatifldquoTemporal and spatial variations in summer flows of upperIndus Basin Pakistanrdquo inProceedings of the 72ndAnnual Sessionof Pakistan Engineering Congress Paper no 747 pp 315ndash3342013
[50] G C Blain ldquoThe Mann-Kendall test the need to consider theinteraction between serial correlation and trendrdquo AgriculturalEngineering vol 35 no 4 2013
[51] M Yaseen T Rientjes G Nabi H ur-Rehman and M LatifldquoAssessment of recent temperature trends inManglawatershedrdquoJournal of Himalayan Earth Sciences vol 47 no 1 pp 107ndash1212014
[52] P K Sen ldquoEstimates of the regression coefficient based onKendallrsquos taurdquo Journal of the American Statistical Associationvol 63 no 324 pp 1379ndash1389 1968
[53] W S Cleveland ldquoRobust locally weighted regression andsmoothing scatterplotsrdquoThe Journal of the American StatisticalAssociation vol 74 no 368 pp 829ndash836 1979
[54] W S Cleveland ldquoGraphs in scientific publicationsrdquoThe Ameri-can Statistician vol 38 no 4 pp 261ndash269 1984
[55] D R Helsel and R M Hirsch ldquoStatistical methods in waterresourcesrdquo inTechniques ofWater Resources Investigations Book4 chapter A3 p 522 US Geological Survey 2002
[56] A P Dimri ldquoSurface and upper air fields during extreme winterprecipitation over the western Himalayasrdquo Pure and AppliedGeophysics vol 163 no 8 pp 1679ndash1698 2006
[57] A Ghaffar and M Javid ldquoImpact of global warming onmonsoon variability in Pakistanrdquo The Journal of Animal andPlant Sciences vol 21 no 1 pp 107ndash110 2011
[58] G Rasul ldquoClimate Data and Modelling Analysis of the IndusRegionrdquo Pakistan Meteorological Department (PMD) 2012httpwwfpakorgccappdfClimate Data Modelling20An-alysis20of20the20Indus20Ecoregionpdf
[59] A Basistha D S Arya and N K Goel ldquoAnalysis of historicalchanges in rainfall in the Indian Himalayasrdquo InternationalJournal of Climatology vol 29 no 4 pp 555ndash572 2009
[60] P G Baines ldquoThe late 1960s global climate shift and its influenceon the Southern Hemisphererdquo in Proceedings of 8 ICSHMO pp1477ndash1482 INPE Foz do Iguacu Brazil 2006
[61] K Duan and T Yao ldquoMonsoon variability in the Himalayasunder the condition of global warmingrdquo Journal of the Mete-orological Society of Japan vol 81 no 2 pp 251ndash257 2003
[62] U S Nair R O Lawton R M Welch and R A Pielke SrldquoImpact of land use on Costa Rican tropical montane cloudforests sensitivity of cumulus cloud field characteristics tolowland deforestationrdquo Journal of Geophysical Research D vol108 no 7 pp 4206ndash4219 2003
[63] R Avissar and D Werth ldquoGlobal hydroclimatological tele-connections resulting from tropical deforestationrdquo Journal ofHydrometeorology vol 6 no 2 pp 134ndash145 2005
[64] R A Pielke Sr J Adegoke A Beltran-Przekurat et al ldquoAnoverview of regional land-use and land-cover impacts onrainfallrdquo Tellus B Chemical and Physical Meteorology vol 59no 3 pp 587ndash601 2007
[65] N Ramankutty C Delire and P Snyder ldquoFeedbacks betweenagriculture and climate an illustration of the potential unin-tended consequences of human land use activitiesrdquo Global andPlanetary Change vol 54 no 1-2 pp 79ndash93 2006
[66] V Ramanathan C Chung D Kim et al ldquoAtmospheric brownclouds impacts on South Asian climate and hydrological cyclerdquoProceedings of the National Academy of Sciences of the UnitedStates of America vol 102 no 15 pp 5326ndash5333 2005
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ClimatologyJournal of
EcologyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
EarthquakesJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom
Applied ampEnvironmentalSoil Science
Volume 2014
Mining
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Hindawi Publishing Corporation httpwwwhindawicom Volume 2014
International Journal of
Geophysics
OceanographyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal ofPetroleum Engineering
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
GeochemistryHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Atmospheric SciencesInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OceanographyHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Advances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MineralogyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MeteorologyAdvances in
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Paleontology JournalHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geological ResearchJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geology Advances in
Advances in Meteorology 13
Table 6 MK and SR results for seasonal and annual precipitation time series in entire basin and subbasin of Swat River
Subbasin Change (mmyear) Test Winter Spring Summer Autumn Annual
A1 minus073 MK 055 minus024 minus242lowast 305lowast minus034SR 057 001 minus227lowast 347lowast 118
A2 minus090 MK 128 minus023 minus385lowast 158 minus081SR 118 minus035 minus444lowast 164 minus090
A3 030 MK 266lowast 016 minus265lowast 375lowast 024SR 295lowast 027 minus309lowast 460lowast 040
A4 218 MK 242lowast 060 minus021 024 166SR 272lowast 054 minus037 043 173
A 048 MK 214lowast minus011 minus297lowast 307lowast 042SR 225lowast minus014 minus340lowast 336lowast 038
lowastSignificant trend at 5 significance level of two-tailed test
monsoon circulation [61] decline in forest cover [62 63] landuse changes and practices (eg irrigated agriculture) [64 65]and increasing aerosols from anthropogenic activities [66]
5 Conclusions
This paper analyzed trends in monthly seasonal and annualprecipitation in the Swat River basin over the 51-year studyperiod (1961ndash2011) A mix of positive and negative trendswas observed at various stations and subbasins The monthsof June November July and August showed the maximumnumber of significant cases at various stations in monthlyprecipitation The trends were positive in May and June andwere negative in July and August This indicates a shift inprecipitation series on monthly scale Significant positivetrends were detected in winter and autumn and annuallynegative trends were seen in spring and summer seasonsSaidu Sharif Mardan and Charsadda stations exhibitedsignificant positive trends in annual precipitation at a 95confidence level the remaining stations did not experiencea statistically significant trend
For the entire Swat River basin no significant trendswere detected in any subbasin for the annual precipitationseries Seasonally winter and autumn experienced significantpositive trends and summer experienced negative trends indifferent subbasins in the Swat River basin Most statisticallysignificant trend cases under different scenarios were positive(61)The results obtainedwith theMann-Kendall (MK) andSpearmanrsquos rho tests showed agreement in their assessmentsof monthly seasonal and annual precipitation trends Thevariability of negative and positive trends at various stationspoints to the need for more detailed studies on the climatechange of this region
Conflict of Interests
The authors declare that there is no conflict of interestsregarding the publication of this paper
Acknowledgments
The authors thank Pakistan Meteorological Department(PMD) Water and Power Development Authority
(WAPDA) Pakistan and Snowy Mountains EngineeringCorporation (SMEC) for providing cost-free data for thisstudy
References
[1] M D Rahman and M Begum ldquoApplication of non parametrictest for trend detection of rainfall in the largest Island ofBangladeshrdquo ARPN Journal of Earth Sciences vol 2 no 2 pp40ndash44 2013
[2] IPCCThePhysical Science Basis Contribution ofWorkingGroupI to the Fourth Assessment Report of the Intergovernmental Panelon Climate Change Cambridge University Press CambridgeUK 2007
[3] A B Farooq and A H Khan ldquoClimate change perspectivein Pakistanrdquo in Proceedings of the Capacity Building APNWorkshop on Global Change Research pp 39ndash46 IslamabadPakistan 2004
[4] Z Z Hu S Yang and R Wu ldquoLong-term climate variationsin China and global warming signalsrdquo Journal of GeophysicalResearch vol 108 no D19 2003
[5] P Zhai and X Pan ldquoTrends in temperature extremes during1951ndash1999 in Chinardquo Geophysical Research Letters vol 30 no17 p 1913 2003
[6] D Duhan and A Pandey ldquoStatistical analysis of long termspatial and temporal trends of precipitation during 1901ndash2002at Madhya Pradesh Indiardquo Atmospheric Research vol 122 pp136ndash149 2013
[7] B J Peterson RM Holmes JWMcClelland et al ldquoIncreasingriver discharge to the Arctic oceanrdquo Science vol 298 no 5601pp 2171ndash2173 2002
[8] N I Savelieva I P Semiletov L N Vasilevskaya and S PPugach ldquoA climate shift in seasonal values of meteorologicaland hydrological parameters for Northeastern Asiardquo Progress inOceanography vol 47 no 2ndash4 pp 279ndash297 2000
[9] Y F Shi Y P Shen and R J Hu ldquoPreliminary study on signalimpact and foreground of climatic shift from warm-dry towarm-humid in Northwest Chinardquo Journal of Glaciology andGeocryology vol 24 pp 219ndash226 2002 (Chinese)
[10] S Farhana and M M Rahman ldquoCharacterizing rainfall trendin Bangladesh by temporal statistics analysisrdquo in Proceedings ofthe 4th Annual Paper Meet and 1st Civil Engineering CongressDhaka Bangladesh 2011
[11] R H Rimi S H Rahman S Karmakar and S G HussainldquoTrend analysis of climate change and investigation on its
14 Advances in Meteorology
probable impacts on rice production at Satkhira BangladeshrdquoPakistan Journal of Meteorology vol 6 no 11 pp 37ndash50 2014
[12] E R Dahmen and M J Hall Screening of Hydrological DataTests for Stationarity and Relative Consistency Publication 49ILRI Wageningen The Netherlands 1990
[13] Q Zhang C Liu C-Y Xu Y Xu and T Jiang ldquoObserved trendsof annual maximumwater level and streamflow during past 130years in the Yangtze River basin Chinardquo Journal of Hydrologyvol 324 no 1-4 pp 255ndash265 2006
[14] H Chen S Guo C-Y Xu and V P Singh ldquoHistorical tem-poral trends of hydro-climatic variables and runoff responseto climate variability and their relevance in water resourcemanagement in the Hanjiang basinrdquo Journal of Hydrology vol344 no 3-4 pp 171ndash184 2007
[15] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 pp 245ndash259 1945
[16] M G Kendall Rank CorrelationMethods Griffin London UK1975
[17] E L Lehmann Nonparametrics Statistical Methods Based onRanks Holden-Day San Francisco Calif USA 1975
[18] R Sneyers ldquoOn the statistical analysis of series of observationsrdquoTechnical Note 143 WMO no 415 World MeteorologicalOrganization 1990
[19] A Longobardi and P Villani ldquoTrend analysis of annual andseasonal rainfall time series in the Mediterranean areardquo Inter-national Journal of Climatology vol 30 no 10 pp 1538ndash15462010
[20] Z YanmingW Jun andW Xinhua ldquoStudy on the change trendof precipitation and temperature in Kunming city based onMann-Kendall analysisrdquo in Future Computer CommunicationControl and Automation vol 119 of Advances in Intelligent andSoft Computing pp 505ndash513 Springer Berlin Germany 2011
[21] X L Yang L R Xu K K Liu C H Li J Hu and X H XialdquoTrend in temperature and precipitation in the ZhangweinanRiver Basin during the last 53 yearsrdquo Procedia EnvironmentalSciences vol 13 pp 1966ndash1974 1966
[22] Z F Yang Y Yan and Q Liu ldquoThe relationship of streamflow-precipitation-temperature in the Yellow River Basin of Chinaduring 1961ndash2000rdquo Procedia Environmental Sciences vol 13 pp2336ndash2345 2012
[23] Q-X Wang X-H Fan Z-D Qin and M-B Wang ldquoChangetrends of temperature and precipitation in the Loess PlateauRegion of China 1961ndash2010rdquo Global and Planetary Change vol92-93 pp 138ndash147 2012
[24] S Yue P Pilon and G Cavadias ldquoPower of the Mann-Kendalland Spearmanrsquos rho tests for detecting monotonic trends inhydrological seriesrdquo Journal of Hydrology vol 259 no 1ndash4 pp254ndash271 2002
[25] E Kahya and S Kalaycı ldquoTrend analysis of streamflow inTurkeyrdquo Journal of Hydrology vol 289 pp 128ndash144 2004
[26] Z L Li Z X Xu J Y Li and Z J Li ldquoShift trend and stepchanges for runoff time series in the Shiyang River BasinNorthwest Chinardquo Hydrological Processes vol 22 no 23 pp4639ndash4646 2008
[27] C Yaning X Changchun H Xingming et al ldquoFifty-yearclimate change and its effect on annual runoff in the TarimRiverBasin Chinardquo Quaternary International vol 208 no 1-2 pp53ndash61 2009
[28] M Shadmani SMarofi andMRoknian ldquoTrend analysis in ref-erence evapotranspiration usingMann-Kendall and SpearmanrsquosRho tests in arid regions of IranrdquoWater Resources Managementvol 26 no 1 pp 211ndash224 2012
[29] H Rehman and A Kamal ldquoIndus Basin River system-floodingand flood mitigationrdquo 2005 httparchiveriversymposiumcom2005indexphpelement=38
[30] Pakistan Meteorological Department (PMD) National PlanStrengthening National Capacities for Multi-hazard EarlyWarn-ing amp Response System 2006
[31] National Disaster Management Authority (NDMA) 2007National Disaster Risk Management Framework Governmentof Pakistan httpwwwndmagovpknew
[32] N H Hashimi Q T M Siddiqui A R Ghumman M AKamal and H R Mughal ldquoA critical analysis of 2010 floods inPakistanrdquo African Journal of Agricultural Research vol 7 no 7pp 1054ndash1067 2012
[33] FFC ldquoFederal Flood Commission of Pakistanrdquo Annual FloodReport-2010 2011 httpwwwffcgovpkdownloadfloodarc-hieveAnnualreport2010pdf
[34] N Gronewold and Climatewire ldquoIs the Flooding in Pakistan aClimate Change Disasterrdquo WMN 2010 httpwwwscientific-americancomarticleis-the-flooding-in-pakist
[35] H Hartmann and L Andresky ldquoFlooding in the Indus Riverbasinmdasha spatiotemporal analysis of precipitation recordsrdquoGlobal and Planetary Change vol 107 pp 25ndash35 2013
[36] S Salma S Rehman andM A Shah ldquoRainfall trends in differ-ent climate zones of Pakistanrdquo Pakistan Journal of Meteorologyvol 9 no 17 pp 37ndash47 2012
[37] M Hanif A H Khan and S Adnan ldquoLatitudinal precipitationcharacteristics and trends in Pakistanrdquo Journal ofHydrology vol492 pp 266ndash272 2013
[38] A Imran Q Zaman and M Afzal ldquoTemporal trends in thepeak monsoonal precipitation events over Northeast PakistanrdquoPakistan Journal of Meteorology vol 10 no 19 pp 19ndash30 2013
[39] S B Cheema and M Hanif ldquoSeasonal precipitation variationover Punjab provincerdquo Pakistan Journal of Meteorology vol 10no 19 pp 61ndash82 2013
[40] H Hartmann and H Buchanan ldquoTrends in extreme precipita-tion events in the indus River Basin and flooding in PakistanrdquoAtmosphere-Ocean vol 52 no 1 pp 77ndash91 2014
[41] ldquoProvincial Disaster Management Authority (PDMA 2012)Monsoon Contingency Plan-Khyber-Pakhtunkhwardquo 2012httpwwwndmagovpkDocumentsContingency Plan2012CP KPpdf
[42] Snowy Mountains Engineering Corporation Munda DamConstruction Project Detailed Design Report SMEC LahorePakistan 2014
[43] H Alexandersson ldquoA homogeneity test applied to precipitationdatardquo Journal of Climatology vol 6 no 6 pp 661ndash675 1986
[44] HAlexandersson andAMoberg ldquoHomogenization of Swedishtemperature data Part I homogeneity test for linear trendsrdquoInternational Journal of Climatology vol 17 no 1 pp 25ndash341997
[45] T A Buishand ldquoSome methods for testing the homogeneity ofrainfall recordsrdquo Journal of Hydrology vol 58 no 1-2 pp 11ndash271982
[46] M N Khaliq and T B M J Ouarda ldquoOn the critical values ofthe standard normal homogeneity test (SNHT)rdquo InternationalJournal of Climatology vol 27 no 5 pp 681ndash687 2007
[47] K H Hamed and A Ramachandra Rao ldquoA modified Mann-Kendall trend test for autocorrelated datardquo Journal of Hydrologyvol 204 no 1ndash4 pp 182ndash196 1998
[48] B Onoz and M Bayazit ldquoBlock bootstrap for Mann-Kendalltrend test of serially dependent datardquoHydrological Processes vol26 no 23 pp 3552ndash3560 2012
Advances in Meteorology 15
[49] M Yaseen H A Bhatti T Rientjes G Nabi and M LatifldquoTemporal and spatial variations in summer flows of upperIndus Basin Pakistanrdquo inProceedings of the 72ndAnnual Sessionof Pakistan Engineering Congress Paper no 747 pp 315ndash3342013
[50] G C Blain ldquoThe Mann-Kendall test the need to consider theinteraction between serial correlation and trendrdquo AgriculturalEngineering vol 35 no 4 2013
[51] M Yaseen T Rientjes G Nabi H ur-Rehman and M LatifldquoAssessment of recent temperature trends inManglawatershedrdquoJournal of Himalayan Earth Sciences vol 47 no 1 pp 107ndash1212014
[52] P K Sen ldquoEstimates of the regression coefficient based onKendallrsquos taurdquo Journal of the American Statistical Associationvol 63 no 324 pp 1379ndash1389 1968
[53] W S Cleveland ldquoRobust locally weighted regression andsmoothing scatterplotsrdquoThe Journal of the American StatisticalAssociation vol 74 no 368 pp 829ndash836 1979
[54] W S Cleveland ldquoGraphs in scientific publicationsrdquoThe Ameri-can Statistician vol 38 no 4 pp 261ndash269 1984
[55] D R Helsel and R M Hirsch ldquoStatistical methods in waterresourcesrdquo inTechniques ofWater Resources Investigations Book4 chapter A3 p 522 US Geological Survey 2002
[56] A P Dimri ldquoSurface and upper air fields during extreme winterprecipitation over the western Himalayasrdquo Pure and AppliedGeophysics vol 163 no 8 pp 1679ndash1698 2006
[57] A Ghaffar and M Javid ldquoImpact of global warming onmonsoon variability in Pakistanrdquo The Journal of Animal andPlant Sciences vol 21 no 1 pp 107ndash110 2011
[58] G Rasul ldquoClimate Data and Modelling Analysis of the IndusRegionrdquo Pakistan Meteorological Department (PMD) 2012httpwwfpakorgccappdfClimate Data Modelling20An-alysis20of20the20Indus20Ecoregionpdf
[59] A Basistha D S Arya and N K Goel ldquoAnalysis of historicalchanges in rainfall in the Indian Himalayasrdquo InternationalJournal of Climatology vol 29 no 4 pp 555ndash572 2009
[60] P G Baines ldquoThe late 1960s global climate shift and its influenceon the Southern Hemisphererdquo in Proceedings of 8 ICSHMO pp1477ndash1482 INPE Foz do Iguacu Brazil 2006
[61] K Duan and T Yao ldquoMonsoon variability in the Himalayasunder the condition of global warmingrdquo Journal of the Mete-orological Society of Japan vol 81 no 2 pp 251ndash257 2003
[62] U S Nair R O Lawton R M Welch and R A Pielke SrldquoImpact of land use on Costa Rican tropical montane cloudforests sensitivity of cumulus cloud field characteristics tolowland deforestationrdquo Journal of Geophysical Research D vol108 no 7 pp 4206ndash4219 2003
[63] R Avissar and D Werth ldquoGlobal hydroclimatological tele-connections resulting from tropical deforestationrdquo Journal ofHydrometeorology vol 6 no 2 pp 134ndash145 2005
[64] R A Pielke Sr J Adegoke A Beltran-Przekurat et al ldquoAnoverview of regional land-use and land-cover impacts onrainfallrdquo Tellus B Chemical and Physical Meteorology vol 59no 3 pp 587ndash601 2007
[65] N Ramankutty C Delire and P Snyder ldquoFeedbacks betweenagriculture and climate an illustration of the potential unin-tended consequences of human land use activitiesrdquo Global andPlanetary Change vol 54 no 1-2 pp 79ndash93 2006
[66] V Ramanathan C Chung D Kim et al ldquoAtmospheric brownclouds impacts on South Asian climate and hydrological cyclerdquoProceedings of the National Academy of Sciences of the UnitedStates of America vol 102 no 15 pp 5326ndash5333 2005
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ClimatologyJournal of
EcologyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
EarthquakesJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom
Applied ampEnvironmentalSoil Science
Volume 2014
Mining
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Hindawi Publishing Corporation httpwwwhindawicom Volume 2014
International Journal of
Geophysics
OceanographyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal ofPetroleum Engineering
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
GeochemistryHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Atmospheric SciencesInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OceanographyHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Advances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MineralogyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MeteorologyAdvances in
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Paleontology JournalHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geological ResearchJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geology Advances in
14 Advances in Meteorology
probable impacts on rice production at Satkhira BangladeshrdquoPakistan Journal of Meteorology vol 6 no 11 pp 37ndash50 2014
[12] E R Dahmen and M J Hall Screening of Hydrological DataTests for Stationarity and Relative Consistency Publication 49ILRI Wageningen The Netherlands 1990
[13] Q Zhang C Liu C-Y Xu Y Xu and T Jiang ldquoObserved trendsof annual maximumwater level and streamflow during past 130years in the Yangtze River basin Chinardquo Journal of Hydrologyvol 324 no 1-4 pp 255ndash265 2006
[14] H Chen S Guo C-Y Xu and V P Singh ldquoHistorical tem-poral trends of hydro-climatic variables and runoff responseto climate variability and their relevance in water resourcemanagement in the Hanjiang basinrdquo Journal of Hydrology vol344 no 3-4 pp 171ndash184 2007
[15] H BMann ldquoNonparametric tests against trendrdquo Econometricavol 13 pp 245ndash259 1945
[16] M G Kendall Rank CorrelationMethods Griffin London UK1975
[17] E L Lehmann Nonparametrics Statistical Methods Based onRanks Holden-Day San Francisco Calif USA 1975
[18] R Sneyers ldquoOn the statistical analysis of series of observationsrdquoTechnical Note 143 WMO no 415 World MeteorologicalOrganization 1990
[19] A Longobardi and P Villani ldquoTrend analysis of annual andseasonal rainfall time series in the Mediterranean areardquo Inter-national Journal of Climatology vol 30 no 10 pp 1538ndash15462010
[20] Z YanmingW Jun andW Xinhua ldquoStudy on the change trendof precipitation and temperature in Kunming city based onMann-Kendall analysisrdquo in Future Computer CommunicationControl and Automation vol 119 of Advances in Intelligent andSoft Computing pp 505ndash513 Springer Berlin Germany 2011
[21] X L Yang L R Xu K K Liu C H Li J Hu and X H XialdquoTrend in temperature and precipitation in the ZhangweinanRiver Basin during the last 53 yearsrdquo Procedia EnvironmentalSciences vol 13 pp 1966ndash1974 1966
[22] Z F Yang Y Yan and Q Liu ldquoThe relationship of streamflow-precipitation-temperature in the Yellow River Basin of Chinaduring 1961ndash2000rdquo Procedia Environmental Sciences vol 13 pp2336ndash2345 2012
[23] Q-X Wang X-H Fan Z-D Qin and M-B Wang ldquoChangetrends of temperature and precipitation in the Loess PlateauRegion of China 1961ndash2010rdquo Global and Planetary Change vol92-93 pp 138ndash147 2012
[24] S Yue P Pilon and G Cavadias ldquoPower of the Mann-Kendalland Spearmanrsquos rho tests for detecting monotonic trends inhydrological seriesrdquo Journal of Hydrology vol 259 no 1ndash4 pp254ndash271 2002
[25] E Kahya and S Kalaycı ldquoTrend analysis of streamflow inTurkeyrdquo Journal of Hydrology vol 289 pp 128ndash144 2004
[26] Z L Li Z X Xu J Y Li and Z J Li ldquoShift trend and stepchanges for runoff time series in the Shiyang River BasinNorthwest Chinardquo Hydrological Processes vol 22 no 23 pp4639ndash4646 2008
[27] C Yaning X Changchun H Xingming et al ldquoFifty-yearclimate change and its effect on annual runoff in the TarimRiverBasin Chinardquo Quaternary International vol 208 no 1-2 pp53ndash61 2009
[28] M Shadmani SMarofi andMRoknian ldquoTrend analysis in ref-erence evapotranspiration usingMann-Kendall and SpearmanrsquosRho tests in arid regions of IranrdquoWater Resources Managementvol 26 no 1 pp 211ndash224 2012
[29] H Rehman and A Kamal ldquoIndus Basin River system-floodingand flood mitigationrdquo 2005 httparchiveriversymposiumcom2005indexphpelement=38
[30] Pakistan Meteorological Department (PMD) National PlanStrengthening National Capacities for Multi-hazard EarlyWarn-ing amp Response System 2006
[31] National Disaster Management Authority (NDMA) 2007National Disaster Risk Management Framework Governmentof Pakistan httpwwwndmagovpknew
[32] N H Hashimi Q T M Siddiqui A R Ghumman M AKamal and H R Mughal ldquoA critical analysis of 2010 floods inPakistanrdquo African Journal of Agricultural Research vol 7 no 7pp 1054ndash1067 2012
[33] FFC ldquoFederal Flood Commission of Pakistanrdquo Annual FloodReport-2010 2011 httpwwwffcgovpkdownloadfloodarc-hieveAnnualreport2010pdf
[34] N Gronewold and Climatewire ldquoIs the Flooding in Pakistan aClimate Change Disasterrdquo WMN 2010 httpwwwscientific-americancomarticleis-the-flooding-in-pakist
[35] H Hartmann and L Andresky ldquoFlooding in the Indus Riverbasinmdasha spatiotemporal analysis of precipitation recordsrdquoGlobal and Planetary Change vol 107 pp 25ndash35 2013
[36] S Salma S Rehman andM A Shah ldquoRainfall trends in differ-ent climate zones of Pakistanrdquo Pakistan Journal of Meteorologyvol 9 no 17 pp 37ndash47 2012
[37] M Hanif A H Khan and S Adnan ldquoLatitudinal precipitationcharacteristics and trends in Pakistanrdquo Journal ofHydrology vol492 pp 266ndash272 2013
[38] A Imran Q Zaman and M Afzal ldquoTemporal trends in thepeak monsoonal precipitation events over Northeast PakistanrdquoPakistan Journal of Meteorology vol 10 no 19 pp 19ndash30 2013
[39] S B Cheema and M Hanif ldquoSeasonal precipitation variationover Punjab provincerdquo Pakistan Journal of Meteorology vol 10no 19 pp 61ndash82 2013
[40] H Hartmann and H Buchanan ldquoTrends in extreme precipita-tion events in the indus River Basin and flooding in PakistanrdquoAtmosphere-Ocean vol 52 no 1 pp 77ndash91 2014
[41] ldquoProvincial Disaster Management Authority (PDMA 2012)Monsoon Contingency Plan-Khyber-Pakhtunkhwardquo 2012httpwwwndmagovpkDocumentsContingency Plan2012CP KPpdf
[42] Snowy Mountains Engineering Corporation Munda DamConstruction Project Detailed Design Report SMEC LahorePakistan 2014
[43] H Alexandersson ldquoA homogeneity test applied to precipitationdatardquo Journal of Climatology vol 6 no 6 pp 661ndash675 1986
[44] HAlexandersson andAMoberg ldquoHomogenization of Swedishtemperature data Part I homogeneity test for linear trendsrdquoInternational Journal of Climatology vol 17 no 1 pp 25ndash341997
[45] T A Buishand ldquoSome methods for testing the homogeneity ofrainfall recordsrdquo Journal of Hydrology vol 58 no 1-2 pp 11ndash271982
[46] M N Khaliq and T B M J Ouarda ldquoOn the critical values ofthe standard normal homogeneity test (SNHT)rdquo InternationalJournal of Climatology vol 27 no 5 pp 681ndash687 2007
[47] K H Hamed and A Ramachandra Rao ldquoA modified Mann-Kendall trend test for autocorrelated datardquo Journal of Hydrologyvol 204 no 1ndash4 pp 182ndash196 1998
[48] B Onoz and M Bayazit ldquoBlock bootstrap for Mann-Kendalltrend test of serially dependent datardquoHydrological Processes vol26 no 23 pp 3552ndash3560 2012
Advances in Meteorology 15
[49] M Yaseen H A Bhatti T Rientjes G Nabi and M LatifldquoTemporal and spatial variations in summer flows of upperIndus Basin Pakistanrdquo inProceedings of the 72ndAnnual Sessionof Pakistan Engineering Congress Paper no 747 pp 315ndash3342013
[50] G C Blain ldquoThe Mann-Kendall test the need to consider theinteraction between serial correlation and trendrdquo AgriculturalEngineering vol 35 no 4 2013
[51] M Yaseen T Rientjes G Nabi H ur-Rehman and M LatifldquoAssessment of recent temperature trends inManglawatershedrdquoJournal of Himalayan Earth Sciences vol 47 no 1 pp 107ndash1212014
[52] P K Sen ldquoEstimates of the regression coefficient based onKendallrsquos taurdquo Journal of the American Statistical Associationvol 63 no 324 pp 1379ndash1389 1968
[53] W S Cleveland ldquoRobust locally weighted regression andsmoothing scatterplotsrdquoThe Journal of the American StatisticalAssociation vol 74 no 368 pp 829ndash836 1979
[54] W S Cleveland ldquoGraphs in scientific publicationsrdquoThe Ameri-can Statistician vol 38 no 4 pp 261ndash269 1984
[55] D R Helsel and R M Hirsch ldquoStatistical methods in waterresourcesrdquo inTechniques ofWater Resources Investigations Book4 chapter A3 p 522 US Geological Survey 2002
[56] A P Dimri ldquoSurface and upper air fields during extreme winterprecipitation over the western Himalayasrdquo Pure and AppliedGeophysics vol 163 no 8 pp 1679ndash1698 2006
[57] A Ghaffar and M Javid ldquoImpact of global warming onmonsoon variability in Pakistanrdquo The Journal of Animal andPlant Sciences vol 21 no 1 pp 107ndash110 2011
[58] G Rasul ldquoClimate Data and Modelling Analysis of the IndusRegionrdquo Pakistan Meteorological Department (PMD) 2012httpwwfpakorgccappdfClimate Data Modelling20An-alysis20of20the20Indus20Ecoregionpdf
[59] A Basistha D S Arya and N K Goel ldquoAnalysis of historicalchanges in rainfall in the Indian Himalayasrdquo InternationalJournal of Climatology vol 29 no 4 pp 555ndash572 2009
[60] P G Baines ldquoThe late 1960s global climate shift and its influenceon the Southern Hemisphererdquo in Proceedings of 8 ICSHMO pp1477ndash1482 INPE Foz do Iguacu Brazil 2006
[61] K Duan and T Yao ldquoMonsoon variability in the Himalayasunder the condition of global warmingrdquo Journal of the Mete-orological Society of Japan vol 81 no 2 pp 251ndash257 2003
[62] U S Nair R O Lawton R M Welch and R A Pielke SrldquoImpact of land use on Costa Rican tropical montane cloudforests sensitivity of cumulus cloud field characteristics tolowland deforestationrdquo Journal of Geophysical Research D vol108 no 7 pp 4206ndash4219 2003
[63] R Avissar and D Werth ldquoGlobal hydroclimatological tele-connections resulting from tropical deforestationrdquo Journal ofHydrometeorology vol 6 no 2 pp 134ndash145 2005
[64] R A Pielke Sr J Adegoke A Beltran-Przekurat et al ldquoAnoverview of regional land-use and land-cover impacts onrainfallrdquo Tellus B Chemical and Physical Meteorology vol 59no 3 pp 587ndash601 2007
[65] N Ramankutty C Delire and P Snyder ldquoFeedbacks betweenagriculture and climate an illustration of the potential unin-tended consequences of human land use activitiesrdquo Global andPlanetary Change vol 54 no 1-2 pp 79ndash93 2006
[66] V Ramanathan C Chung D Kim et al ldquoAtmospheric brownclouds impacts on South Asian climate and hydrological cyclerdquoProceedings of the National Academy of Sciences of the UnitedStates of America vol 102 no 15 pp 5326ndash5333 2005
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ClimatologyJournal of
EcologyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
EarthquakesJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom
Applied ampEnvironmentalSoil Science
Volume 2014
Mining
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Hindawi Publishing Corporation httpwwwhindawicom Volume 2014
International Journal of
Geophysics
OceanographyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal ofPetroleum Engineering
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
GeochemistryHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Atmospheric SciencesInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OceanographyHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Advances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MineralogyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MeteorologyAdvances in
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Paleontology JournalHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geological ResearchJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geology Advances in
Advances in Meteorology 15
[49] M Yaseen H A Bhatti T Rientjes G Nabi and M LatifldquoTemporal and spatial variations in summer flows of upperIndus Basin Pakistanrdquo inProceedings of the 72ndAnnual Sessionof Pakistan Engineering Congress Paper no 747 pp 315ndash3342013
[50] G C Blain ldquoThe Mann-Kendall test the need to consider theinteraction between serial correlation and trendrdquo AgriculturalEngineering vol 35 no 4 2013
[51] M Yaseen T Rientjes G Nabi H ur-Rehman and M LatifldquoAssessment of recent temperature trends inManglawatershedrdquoJournal of Himalayan Earth Sciences vol 47 no 1 pp 107ndash1212014
[52] P K Sen ldquoEstimates of the regression coefficient based onKendallrsquos taurdquo Journal of the American Statistical Associationvol 63 no 324 pp 1379ndash1389 1968
[53] W S Cleveland ldquoRobust locally weighted regression andsmoothing scatterplotsrdquoThe Journal of the American StatisticalAssociation vol 74 no 368 pp 829ndash836 1979
[54] W S Cleveland ldquoGraphs in scientific publicationsrdquoThe Ameri-can Statistician vol 38 no 4 pp 261ndash269 1984
[55] D R Helsel and R M Hirsch ldquoStatistical methods in waterresourcesrdquo inTechniques ofWater Resources Investigations Book4 chapter A3 p 522 US Geological Survey 2002
[56] A P Dimri ldquoSurface and upper air fields during extreme winterprecipitation over the western Himalayasrdquo Pure and AppliedGeophysics vol 163 no 8 pp 1679ndash1698 2006
[57] A Ghaffar and M Javid ldquoImpact of global warming onmonsoon variability in Pakistanrdquo The Journal of Animal andPlant Sciences vol 21 no 1 pp 107ndash110 2011
[58] G Rasul ldquoClimate Data and Modelling Analysis of the IndusRegionrdquo Pakistan Meteorological Department (PMD) 2012httpwwfpakorgccappdfClimate Data Modelling20An-alysis20of20the20Indus20Ecoregionpdf
[59] A Basistha D S Arya and N K Goel ldquoAnalysis of historicalchanges in rainfall in the Indian Himalayasrdquo InternationalJournal of Climatology vol 29 no 4 pp 555ndash572 2009
[60] P G Baines ldquoThe late 1960s global climate shift and its influenceon the Southern Hemisphererdquo in Proceedings of 8 ICSHMO pp1477ndash1482 INPE Foz do Iguacu Brazil 2006
[61] K Duan and T Yao ldquoMonsoon variability in the Himalayasunder the condition of global warmingrdquo Journal of the Mete-orological Society of Japan vol 81 no 2 pp 251ndash257 2003
[62] U S Nair R O Lawton R M Welch and R A Pielke SrldquoImpact of land use on Costa Rican tropical montane cloudforests sensitivity of cumulus cloud field characteristics tolowland deforestationrdquo Journal of Geophysical Research D vol108 no 7 pp 4206ndash4219 2003
[63] R Avissar and D Werth ldquoGlobal hydroclimatological tele-connections resulting from tropical deforestationrdquo Journal ofHydrometeorology vol 6 no 2 pp 134ndash145 2005
[64] R A Pielke Sr J Adegoke A Beltran-Przekurat et al ldquoAnoverview of regional land-use and land-cover impacts onrainfallrdquo Tellus B Chemical and Physical Meteorology vol 59no 3 pp 587ndash601 2007
[65] N Ramankutty C Delire and P Snyder ldquoFeedbacks betweenagriculture and climate an illustration of the potential unin-tended consequences of human land use activitiesrdquo Global andPlanetary Change vol 54 no 1-2 pp 79ndash93 2006
[66] V Ramanathan C Chung D Kim et al ldquoAtmospheric brownclouds impacts on South Asian climate and hydrological cyclerdquoProceedings of the National Academy of Sciences of the UnitedStates of America vol 102 no 15 pp 5326ndash5333 2005
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ClimatologyJournal of
EcologyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
EarthquakesJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom
Applied ampEnvironmentalSoil Science
Volume 2014
Mining
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Hindawi Publishing Corporation httpwwwhindawicom Volume 2014
International Journal of
Geophysics
OceanographyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal ofPetroleum Engineering
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
GeochemistryHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Atmospheric SciencesInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OceanographyHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Advances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MineralogyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MeteorologyAdvances in
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Paleontology JournalHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geological ResearchJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geology Advances in
Submit your manuscripts athttpwwwhindawicom
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ClimatologyJournal of
EcologyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
EarthquakesJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom
Applied ampEnvironmentalSoil Science
Volume 2014
Mining
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Hindawi Publishing Corporation httpwwwhindawicom Volume 2014
International Journal of
Geophysics
OceanographyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal ofPetroleum Engineering
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
GeochemistryHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Journal of
Atmospheric SciencesInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
OceanographyHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Advances in
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MineralogyInternational Journal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
MeteorologyAdvances in
The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014
Paleontology JournalHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geological ResearchJournal of
Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014
Geology Advances in