A case study of temperature and rainfall trends using Mann ... · A case study of temperature and rainfall trends using Mann-Kendall test in ... (Beena Shah 2010). In

INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCES Volume 6, No 6, 2016

© Copyright by the authors - Licensee IPA- Under Creative Commons license 3.0

Research article ISSN 0976 – 4402

Received on January 2016 Published on May 2016 954

A case study of temperature and rainfall trends using Mann-Kendall test in

Saurashtra Region (Junagadh) of Gujaart, India Chinchorkar S.S1, Bhavin Ram D.M2, Paradava3 and Trivedi M.M4

1- Assistant Professor, Anand Agricultural University, Dahod,

2- Assistant Professor, Anand Agricultural University, Anand.

3- Research Associate, Anand Agricultural University,Dahod.

4- Associate Professor, Anand Agricultural University, Dahod.

[email protected]

doi: 10.6088/ijes.6090

ABSTRACT

The long–term change in temperature and rainfall has been assessed by linear trend analysis.

It is evident from above Figures that monthly mean of maximum (MMAX) temperatures

have increased significantly for all the months except the month of October for which a very

weak decrease in MMAX temperature is observed. This implies that in Junagadh, the highest

increase in MMAX temperature occurs in November by (0.021C) during last 32 years. The

annual mean of monthly mean of maximum temperatures observed a decreasing trend having

an annual increase of 0.041C per year. The monthly mean of TMRF have increased

significantly for the months February, March, April May, July, August, September, whereas

it shows decreasing trend in January, June, October, November, and December. The highest

increase in TMRF occurs in August by 1.463 mm during the last 32 years. The highest

decrease in TMRF occurs in November and decreased by 0.1.60 mm. the annual mean of

monthly mean of total mean rainfall observed an increasing trend having an increase of 0.482

mm per year. In winter total mean rainfall observed a deceasing trend of 1.291 mm per day

where as in summer increasing trend by 0.64 mm and in monsoon slightly increase trend by

1.12 mm per year in Junagadh station. Annual MMAX temperature shows increasing trend

which is statistically significant at 5% level of significance whereas annual TMRF shows

increasing trend which is statistically insignificant at 5% level of significance.

Keywords: Rainfall, maximum temperature, trend analysis, Mann-Kendall test, rainfall

pattern, global warming

1. Introduction

Climate change has brought in unexpected changes not only in India but all over the regions

across the world. Emergence of global warming due to climate change is the new and most

talked subject of today’s world as it being the most threatening issue for very existence of life

on the earth. One of the consequences of climate change is the alteration of rainfall patterns

and increase in temperature. According to Intergovernmental Panel on Climate Change

(IPCC,2007) reports, the surface temperature of the earth has risen by 0.6+ 0.20C over the

20th century. Also in the last 50 years, the rise in temperature has been 0.13 + 0.070C per

decade. As the warming depends on emissions of GHGs in the atmosphere, the IPCC has

projected a warming of about 0.20C per decade.

Further, surface air temperature could rise by between 1.10C to 6.40C over 21st century. In

case of India, the climate change expected to adversely affect its natural resources, forestry,

A case study of temperature and rainfall trends using Mann-Kendall test in Saurashtra Region (Junagadh) of

Gujaart, India

Chinchorkar S. S et al., International Journal of Environmental Sciences Volume 6 No.6 2016

955

agriculture, and change in precipitation, temperature, monsoon timing and extreme events (M.

H. Fulekar, R.K. Kale, 2010). Due to global warming, precipitation amount, type and timing

are changing or are expected to change because of increased evaporation, especially in the

tropics (Ritter, 2006). The pattern and amount of rainfall are among the most important

factors that affects agricultural production. Agriculture is vital to India’s economy and the

livelihood of its people. Agriculture is contributing 21% to the country’s GDP, accounting for

115 of total export, employing 56.4% of the total workforce, and supporting 600 million

people directly and indirectly (Beena Shah, 2010). The analysis of rainfall records for long

periods provides information about rainfall patterns and variability (Lazaro et. al., 2001). The

main objective of this paper is to analyze the 1980 to 2011 rainfall and temperature records

obtained from Junagadh Agricultural University Junagadh, Gujarat as a basis on

sustainability of crop production.

2. Climate Change

Several studies relating to changing pattern of rainfall over India observed that there is no

clear trend of increase or decrease in average rainfall over the country (Mooley and

Parthasarathy, 1984; Thapliyal and Kulshrestha, 1991; Lal, 2001; Kumar et al., 2010).

Although long-term trends in monsoon rainfall have not been observed on an all-India scale,

several studies have found significant trends in rainfall on a regional scale (Koteswaram and

Alvi, 1969; Jagannathan and Parthasarathy, 1973; Raghavendra, 1974; Chaudhary and

Abhyankar, 1979; Kumar et al., 2005; Dash et al., 2007; Kumar and Jain, 2010). In India, the

climate change is expected to adversely cause changes in precipitation, temperature, monsoon

timing and extreme events (Fulekar and Kale 2010). Due to global warming, precipitation

amount, type and timing are changing or are expected to change because of increased

evaporation, especially in the tropics (Ritter, 2006). The pattern and amount of the rainfall are

among the most important factors that affect agriculture production. Agriculture is vital to

India’s economy and livelihood of its people.

Agriculture is contributing 21% to the country’s GDP, employing 56.4% of the total

workforce and supporting 600 million people directly and indirectly (Beena Shah 2010). In

India despite recent progress in industrlization, the soundness of economy is significantly

dependent upon the gross production of agricultural commodities and agriculture is the

mainstay of millions of teeming population with crops pre-dominantly dependent upon

natural rainfall. Excepting the south-eastern part of the peninsula and Jammu and Kashmir,

the south west monsoon (June – Sept.) is the principle source of rain in the entire country.

During monsoonal period more than 75% of annual rainfall is received over a major portion

of the country. India’s economy has traditionally been agricultural in nature and excess

climate anomalies, deficient and flooded rainfall years have a dramatic impact on the

economy as well as on the living conditions of the inhabitants of the affected regions

(Parthasarthy et al. 1988). The green revolution on technology has increased the rice and

other food grain production and productivity substantially.

3. Study Area

The Junagadh city is located between latitudes 21º 31’N and 70º 49’ E in Figure 1. The city is

a gate way to famous Gir Forest which is the natural habitat for the last existing population of

Asiatic Lion in the wild. Apart from Gir, there is Girnar Ranges, Barda Hills and extensive

grasslands known as Vidis, which also support a variety of wildlife especially avifauna.

Junagadh has a tropical wet and dry climate, with three distinct seasons observed, a mild


Gujaart, India


956

winter from November to February, a hot summer from March to June, and a monsoon from

July to October. Junagadh faces adverse climatic conditions in the summer months with the

temperature ranging from 28° Celsius to 38° Celsius. In the winter months, the temperature

ranges from 10° Celsius to 25° Celsius. Various factors such as its close proximity to the sea

influence the weather of Junagadh. The latent winds from the sea affect the climatic

conditions in the region.

Figure 1: Location map of study area

4. Data and Methodology

The data used in this paper are the monthly averages of total mean rainfall, minimum and

maximum atmospheric temperatures during 1980-2011 (32 years). The time series is made up

of four components known as seasonal, trend, cyclical and irregular (Patterson, [11]). Trend

is defined as the general movement of a series over an extended period of time or it is the

long term change in the dependent variable over a long period of time (Webber and Hawkins,

[18]). Trend is determined by the relationship between the two variables as temperature and

time, rainfall and time. The statistical methods such as regression analysis and coefficient of

determination R2 (Murray R. Spiegel, Larry J. Stephens, [10]) are used. The magnitudes of

the trends of increasing or decreasing maximum temperatures and total mean rainfall were

derived and tested by the Mann-Kendall (M-K),[9] trend test and slope of the regression line

using the least squares method.

The coefficient of variation for MMAX temperature is highest in the month of January and it

is observed as 6.294% whereas it is lowest in the month April and it is 2.957 % for the

Junagadh station. This means that maximum temperature is most stable in the month of April

and least stable in the month of January for the Junagadh station given in Table 1.

Table 1: Statistical summary of monthly mean of MMAX temperatures.

Month Mean SD CV (%)

January 29.70 1.869 6.294

February 31.85 1.930 6.060

March 36.10 1.431 3.964

April 39.13 1.157 2.957

May 38.81 1.181 3.043

June 35.62 1.147 3.222

July 31.71 1.213 3.826

August 30.48 1.099 3.604


Gujaart, India


957

September 32.72 1.249 3.819

October 35.77 1.415 3.955

November 34.10 1.144 3.355

December 31.15 1.214 3.897

4.1 Trend Analysis of Monthly Mean of Maximum Temperature (MMAX)

The trends of monthly mean of maximum temperatures over different years were obtained

using linear regression best fit lines. The linear regression trends with their linear regression

equations and coefficient of determinations for all the months from January to December are

represented in Figure1 and summarized in Table2 below. It is evident from above Figures

that monthly mean of maximum (MMAX) temperatures have increased significantly for all

the months except the month of October for which a very weak decrease in MMAX

temperature is observed. This implies that in Junagadh, the highest increase in MMAX

temperature occurs in November by (0.021C) during last 31 years.

y = 0.0088x + 12.21

R2 = 0.0019

0

10

20

30

40

1975 1980 1985 1990 1995 2000 2005 2010 2015

Year

JA

N-M

MA

X

y = 0.0043x + 23.23

R2 = 0.0004

0

10

20

30

40

50

1975 1980 1985 1990 1995 2000 2005 2010 2015

Year

FE

B-M

MA

X

y = 0.035x - 33.795

R2 = 0.0527

0

10

20

30

40

50

1975 1980 1985 1990 1995 2000 2005 2010 2015

Year

MA

R-M

MA

X


Gujaart, India


958

y = 0.0375x - 35.665

R2 = 0.0923

0

10

20

30

40

50

1975 1980 1985 1990 1995 2000 2005 2010 2015

Year

AP

R-M

MA

X

y = -0.034x + 106.75

R2 = 0.0731

0

10

20

30

40

50

1975 1980 1985 1990 1995 2000 2005 2010 2015

Year

MA

Y-M

MA

X

y = 0.01x + 15.61

R2 = 0.0067

0

10

20

30

40

50

1975 1980 1985 1990 1995 2000 2005 2010 2015

Year

JUN

-MM

AX

y = -0.0239x + 79.386

R2 = 0.0341

0

10

20

30

40

50

1975 1980 1985 1990 1995 2000 2005 2010 2015

Year

JUL

-MM

AX


Gujaart, India


959

y = -0.0259x + 87.441

R2 = 0.0295

0

10

20

30

40

50

1975 1980 1985 1990 1995 2000 2005 2010 2015

Year

OC

T-M

MA

X

y = 0.0212x - 8.2167

R2 = 0.0302

0

10

20

30

40

50

1975 1980 1985 1990 1995 2000 2005 2010 2015

Year

NO

V-M

MA

X

y = -0.0216x + 74.218

R2 = 0.0278

0

10

20

30

40

1975 1980 1985 1990 1995 2000 2005 2010 2015

Year

DE

C-M

MA

X

Figure 1: Linear regression trends of monthly mean of maximum temperatures.


Gujaart, India


960

Table 2: Linear regression equations of MMAX temperatures for all the months.

Month Regression Line R2

January Y=0.0088x+12.21 0.0019

February Y= 0.0043x+23.23 0.0004

March Y=0.035x-33.795 0.0527

April Y=0.0375x-35.66 0.0923

May Y=-0.0239x+79.38 0.0341

June Y= 0.01x+15.61 0.0067

July Y=-0.0239x+79.386 0.00341

August Y= -0.0152x+60.721 0.0167

September Y= -0.0455x+123.42 0.1165

October Y=-0.0259x+87.441 0.0295

November Y=0.0212x-8.2167 0.0302

December Y=-0.0216x+74.218 0.0278

4.2 Trend analysis of annual mean of monthly maximum temperature (MMAX)

The annual mean of monthly mean of maximum temperatures observed a decreasing trend

having an annual increase of 0.041C per year, as represented in Figure 2 during the last 31

years.

y = -0.0036x + 41.283

R2 = 0.0034

0

15

30

45

1975 1980 1985 1990 1995 2000 2005 2010 2015

Year

MM

AX

Figure 2: Trend of annual mean of monthly maximum temperature

The coefficient of variation for TMRF observed highest in the month of April and it is

520.79% whereas coefficient of variation is minimum for the month of July and it is 62.97%

for the Junagadh Station. This shows that rainfall is more stable in the month of July and is

more variable in the month of April for the Junagadh district and summarized in Table 3.

Table 3: Statistical summary of monthly mean of total mean rainfall (TMRF)

Month Mean SD CV (%)

January 0.11 0.53 459.11

February 0.34 1.54 451.01

March 0.07 0.26 387.45

April 0.21 1.09 520.79

May 1.95 3.66 187.84

June 50.41 73.60 146.00


Gujaart, India


961

July 85.48 53.82 62.97

August 47.78 36.13 75.60

September 33.55 33.36 99.44

October 7.82 11.91 152.25

November 3.03 9.22 304.02

December 0.12 0.47 410.77

Annual 975.50 477.32 48.93

Winter 34.38 65.29 189.91

Summer 66.60 78.79 118.31

Monsoon 874.52 473.97 54.20

The trends of monthly mean of total mean rainfall over different years were obtained using

linear regression best fit lines. The linear regression trends with their linear regression

equations and coefficient of determinations for all the months from January to December are

represented in Figure 3 and summarized in Table 4 below. It is evident from above Figures

that monthly mean of TMRF have increased significantly for the months February, March,

April May, July, August, September, whereas it shows decreasing trend in January, June,

October, November, and December for the Junagadh district. This implies that in Junagadh

district the highest increase in TMRF occurs in August by 1.463 mm during the last 31 years.

The highest decrease in TMRF occurs in November and decreased by 0.1.60 mm.

y = 0.0003x - 0.4246

R2 = 2E-05

0

1

2

3

4

1975 1980 1985 1990 1995 2000 2005 2010 2015

Year

JA

N-T

MR

F

y = 0.0205x - 40.623

R2 = 0.0152

0

2

4

6

8

10

1975 1980 1985 1990 1995 2000 2005 2010 2015

Year

FE

B-T

MR

F


Gujaart, India


962

y = 0.0072x - 14.35

R2 = 0.0639

0

1

2

3

4

1975 1980 1985 1990 1995 2000 2005 2010 2015

Year

MA

R-T

MR

F

y = 0.0294x - 58.502

R2 = 0.0625

0

2

4

6

8

1975 1980 1985 1990 1995 2000 2005 2010 2015

Year

AP

R-T

MR

F

y = 0.1047x - 206.88

R2 = 0.0695

0

2

4

6

8

10

12

14

1975 1980 1985 1990 1995 2000 2005 2010 2015

Year

MA

Y-T

MR

F

y = -2.1528x + 4346.4

R2 = 0.0729

0

100

200

300

400

1975 1980 1985 1990 1995 2000 2005 2010 2015

Year

JU

N-T

MR

F


Gujaart, India


963

y = -0.465x + 1013.4

R2 = 0.0064

0

50

100

150

200

250

1975 1980 1985 1990 1995 2000 2005 2010 2015

Year

JU

L-T

MR

F

y = 1.463x - 2871.5

R2 = 0.1398

0

20

40

60

80

100

120

140

160

1975 1980 1985 1990 1995 2000 2005 2010 2015

Year

AU

G-T

MR

F

y = 1.0665x - 2094.7

R2 = 0.0871

0

50

100

150

1975 1980 1985 1990 1995 2000 2005 2010 2015

Year

SE

P-T

MR

F

y = -0.1516x + 310.33

R2 = 0.0138

0

20

40

60

1975 1980 1985 1990 1995 2000 2005 2010 2015

Year

OC

T-T

MR

F


Gujaart, India


964

y = -0.1609x + 324.15

R2 = 0.026

0

20

40

60

1975 1980 1985 1990 1995 2000 2005 2010 2015

Year

NO

V-T

MR

F

y = -0.0102x + 20.433

R2 = 0.0392

0

20

40

60

1975 1980 1985 1990 1995 2000 2005 2010 2015

Year

DE

C-T

MR

F

Figure 3: Linear regression trends of monthly mean of total mean rainfall

Table 4: Linear regression equations of TMRF for all the months

Month Regression equations R2

January y = 0.0003x - 0.4246 2E-05

February y = 0.0205x - 40.623 0.0152

March y = 0.0072x - 14.35 0.0639

April y = 0.0294x - 58.502 0.0625

May y = 0.1047x - 206.88 0.0695

June y = -2.1528x + 4346.4 0.0729

July y = -0.465x + 1013.4 0.0064

August y = 1.463x - 2871.5 0.1398

September y = 1.0665x - 2094.7 0.0871

October y = -0.1516x + 310.33 0.0138

November y = -0.1609x + 324.15 0.026

December y = -0.0102x + 20.433 0.0392

Annual y = 0.4826x + 12.553 9E-05

Winter y = -1.2916x + 2611.7 0.0334

Summer y = 0.6446x - 1219.6 0.0057

Monsoon y = 1.1295x - 1379.5 0.0005


Gujaart, India


965

4.4 Trend Analysis of annual, winter, summer, monsoon mean of total mean rainfall

(TMRF)

y = 0.4826x + 12.553

R2 = 9E-05

0

500

1000

1500

2000

2500

3000

1975 1980 1985 1990 1995 2000 2005 2010 2015

Year

AN

NU

AL

-TM

RF

y = -1.2916x + 2611.7

R2 = 0.0334

0

50

100

150

200

250

300

350

1975 1980 1985 1990 1995 2000 2005 2010 2015

Year

WIN

TE

R-T

MR

F

y = 0.6446x - 1219.6

R2 = 0.0057

0

50

100

150

200

250

300

350

1975 1980 1985 1990 1995 2000 2005 2010 2015

Year

SU

MM

ER

-TM

RF


Gujaart, India


966

y = 1.1295x - 1379.5

R2 = 0.0005

0

500

1000

1500

2000

2500

3000

1975 1980 1985 1990 1995 2000 2005 2010 2015

Year

MO

NS

OO

N-T

MR

F

Figure 4: Trend of annual, winter, summer, monsoon mean of monthly

total mean rainfall.

From the figure 4, the annual mean of monthly mean of total mean rainfall observed an

increasing trend having an increase of 0.482 mm per year. In winter total mean rainfall

observed a deceasing trend of 1.291 mm per day where as in summer increasing trend by 0.64

mm and in monsoon slightly increase trend by 1.12 mm per year.

The MANN-Kendall Test for trend

The Mann-Kendall test is a nonparametric test for identifying trends in time series data. The

test was suggested by Mann (1945) and has been extensively used with environmental time

series (Hipel and McLeod, 2005). The test compares the relative magnitudes of sample data

rather than the data values them. One benefit of this test is that the data need not confirm to

any particular distribution. Let X1, X2………. Xn represents n data points where Xj

represents the data point at time j. Then the Mann-Kendall statistic (S) is given by

A very high positive value of S is an indicator of an increasing trend, and a very low negative

value indicates a decreasing trend. However, it is necessary to compute the probability

associated with S and the sample size, n, to statistically quantify the significance of the trend.

For a sample size >10, a normal approximation to the Mann-Kendall test may be used. For

this, variance of S is obtained as,


Gujaart, India


967

The presence of a statistically significant trend is evaluated using Z value.

5. Conclusions

It is observed that the long–term change in temperature and rainfall has been assessed by

linear trend analysis. It is evident from above figures that monthly mean of maximum

(MMAX) temperatures have increased significantly for all the months except the month of

October for which a very weak decrease in MMAX temperature is observed. This implies

that in Junagadh, the highest increase in MMAX temperature occurs in November by

(0.021C) during last 32 years. The annual mean of monthly mean of maximum temperatures

observed an decreasing trend having an annual increase of 0.041C per year. The monthly

mean of TMRF have increased significantly for the months February, March, April May, July,

August, September, whereas it shows decreasing trend in January, June, October, November,

and December.The highest increase in TMRF occurs in August by 1.463 mm during the last

32 years. The highest decrease in TMRF occurs in November and decreased by 0.1.60 mm.

the annual mean of monthly mean of total mean rainfall observed an increasing trend having

an increase of 0.482 mm per year. In winter total mean rainfall observed an deceasing trend

of 1.291 mm per day where as in summer increasing trend by 0.64 mm and in monsoon

slightly increase trend by 1.12 mm per year in Junagadh station. Annual MMAX temperature

shows increasing trend which is statistically significant at 5% level of significance whereas

annual TMRF shows increasing trend which is statistically insignificant at 5% level of

significance.

6. References

1. Beena Shah, (2010), Global and National Concerns on Climate Change,‖ University

News, 48(24), pp 15-23.

2. Chaudhary A, Abhyankar VP., (1979), Does precipitation pattern foretell Gujarat

climate becoming arid. Mausam 30, pp 85–90.

3. Dash SK, Jenamani RK, Kalsi SR, Panda SK., (2007), Some evidence of climate

change in twentieth-century India, Climatic Change 85, pp 299–321.

4. Deshmukh, D. T., Lunge, H. S., (2013), A Study of Temperature and Rainfall Trends

In. Buldana District of Vidarbha, India. International Journal of Scientific &

Technology Research, 2(2).

5. Fulekar, M.H., Kale, R.K., (2010), Impact of Climate Change: Indian Scenario,

University News, 48(24), pp 15-23.

6. IPCC, Climate Change-A Synthesis Report of the IPCC, Technical Report, Inter

governmental Panel on Climate Change (2007).

7. Jagannathan P, Parthasarathy B, (1973), Trends and periodicities of rainfall over India,

Monthly Weather Review, 101, pp 371–375.


Gujaart, India


968

8. Jestinos Mzezewa, Titus Misi and Leon D van Rensburg, (2009), Characterization of

rainfall at a semi-arid ecotope in the Limpopo Province (South Africa) and its

implications for sustainable crop production.

9. Julious M. Huho, Josephine K.W. Ngaira, Harun O.Ogindo and Nelly Masayi, (2012),

The changing rainfall pattern and the associated impacts on subsistence agriculture in

Laikipia East District, Kenya,‖ Journal of Geography and Regional Planning, 5(7), pp

198-206.

10. Koteswaram P, Alvi SMA, (1969), Secular trends and periodicities in rainfall at west

coast stations in India, Current Science 38, pp 229–231.

11. Kumar V, Singh P, Jain SK, (2005), Rainfall trends over Himachal Pradesh, Western

Himalaya, India. In: Development of Hydro Power Projects – A Prospective

Challenge. Conference, Shimla, pp 20–22.

12. Kumar V, Jain SK, Singh Y, (2010), Analysis of long-term rainfall trends in India,

Hydrological Sciences Journal 55(4), pp 484–496

13. Lal M, (2001), Climatic change – implications for India’s water resources. Journal of

Indian Water Resource Society 21, pp 101–119.

14. Lazaro R, Rodrigo FS, Gutierrez L, (2001), Domingo Fand Puigdefafregas J

―Analysis of a 30-year rainfall record (1967-1997) in semi-arid SE Spain for

implications on vegetation, J. Arid Environ. 48, pp 373-395.

15. Mooley DA, Parthasarthy B, (1984), Fluctuations of all India summer monsoon

rainfall during 1871–1978. Climatic Change 6, pp 287–301.

16. Murray R. Spigel, Larry J. Stephens, Schaum’s outlines Statistics, third edition,

TATA Mcgraw-Hill Edition, (2000).

17. Mann, H.B., (1945), Nonparametric tests against trend, Econometrica, 13, pp 245-259.

18. Parthasarthy, B. A.A. Munot and D.R. Kothawale, (1988), Regression model for

estimation of India’s food grain production from summer monsoon rainfall.

Agricultural and Forest Meteorology 42, pp 167-182.

19. Patterson, P.E. ―Statistical Methods‖, Richard D. Irwin INC, Homewood, IL, (1987).

20. Raghavendra VK, (1974), Trends and periodicities of rainfall in subdivisions of

Maharashtra state. Indian Journal of Meteorology and Geophysics 25, pp 197–210.

21. Ritter ME ―The physical environment: an introduction to physical Geography.

22. Del Rio S, R.Fraile, L. Herrero and A.Penas, ―Analysis of Recent Trends in Mean

Maximum and Minimum Temperatures in a Region of the NW of Spain (Castillay

Leon), Theorotical and Applied Climatology, 90(1-2), pp 1-12.


Gujaart, India


969

23. Thapliyal V, Kulshrestha SM, (1991), Decadal changes and trends over India,

Mausam, 42, pp 333–338.

24. Webber, J. and Hawkins, C. Statistical Analysis Application to Business and

Economics, Harper and Row, New York,(1980).

Documents

A case study of temperature and rainfall trends using Mann ... · A case study of temperature and rainfall trends using Mann-Kendall test in ... (Beena Shah 2010). In