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UNIVERSITY OF NAIROBI
DEPARTMENT OF CIVIL & CONSTRUCTION
ENGINEERING
HYDROLOGICAL STUDY OF NYANDO
BASIN
Done by: NYAMAIYERIA .E. OSUGA
F16/1305/2010
A project submitted as a partial fulfillment for the award of a Bachelor Degree in
CIVIL AND CONSTRUCTION ENGINEERING
2015
I
DEDICATION;
To my family. My mum, dad and brothers.
II
ACKNOWLEDGEMENT;
Thanks to God for enabling me pursue my academic dreams.
I deeply acknowledge my supervisor Eng. Sadrudin Charania for the keen and comprehensive
guidance that he has offered me in carrying out this project.
I immensely thank Mr. Simintei Ole Kooke from the Water Ministry for providing me with the
relevant data I required.
I also acknowledge my fellow colleagues for the motivational support and the great teamwork
displayed during the entire work from collection of data to writing reports.
III
TABLE OF CONTENTS
DEDICATION; ............................................................................................................................................ I
ACKNOWLEDGEMENT; ............................................................................................................................ II
LIST OF TABLES ....................................................................................................................................... VI
LIST OF FIGURES .................................................................................................................................... VII
ABSTRACT ............................................................................................................................................ VIII
CHAPTER ONE ......................................................................................................................................... 1
1.0 INTRODUCTION ................................................................................................................................. 1
1.1 General .......................................................................................................................................... 1
1.2 Objective ....................................................................................................................................... 3
1.3 Network of stations ....................................................................................................................... 5
CHAPTER TWO ........................................................................................................................................ 9
2.0 LITERATURE REVIEW .......................................................................................................................... 9
2.1 Introduction ................................................................................................................................... 9
2.2 Climate ........................................................................................................................................ 10
2.3 Geological setting ........................................................................................................................ 10
2.4 Previous studies on Nyando Catchment ....................................................................................... 11
2.4.1 Ecohydrological characterization of Nyando Wetland ............................................................ 11
2.4.2 Study on flooding characteristics of the Nyando River ........................................................... 12
CHAPTER THREE .................................................................................................................................... 14
3.0 METHODOLOGY ............................................................................................................................... 14
3.1 General ........................................................................................................................................ 14
3.2 Rainfall ........................................................................................................................................ 14
3.2.1 Data processing ..................................................................................................................... 14
IV
3.2.2Mean Monthly rainfalls at the stations ................................................................................... 14
3.2.3Areal rainfall .......................................................................................................................... 14
3.2.4 Rainfall pattern ..................................................................................................................... 18
3.2.5 Probability analysis of rainfall. ............................................................................................... 18
3.2.6 Moving averages curves ........................................................................................................ 18
3.3 Stream flow ................................................................................................................................. 19
3.3.1 Flow Duration ....................................................................................................................... 19
3.3.2 Flood analysis ........................................................................................................................ 19
3.3.3 Storage analysis .................................................................................................................... 19
3.3.4 Moving averages curve ......................................................................................................... 20
CHAPTER FOUR ..................................................................................................................................... 21
4.0 RESULTS AND DISCUSSION ............................................................................................................... 21
4.1 Rainfall analysis and discussion .................................................................................................... 21
4.1.1 Rainfall data summary ........................................................................................................... 21
4.1.2 Determination of seasonal rainfall patterns ........................................................................... 25
4.1.3 Determination of rainfall trend.............................................................................................. 28
4.1.4 Rainfall frequency analysis .................................................................................................... 31
4.1.5 Determination of increasing or decreasing rainfall trend ....................................................... 37
4.2 Stream flow analysis .................................................................................................................... 42
4.2.1 Summary of stream flow Data for station1GD03................................................................... 42
4.2.2 Flow duration analysis ........................................................................................................... 45
4.2.3 Flood analysis ........................................................................................................................ 46
4.2.4 Moving averages curves ........................................................................................................ 48
4.2.5 Storage analysis .................................................................................................................... 50
CHAPTER FIVE........................................................................................................................................ 52
5.0 CONCLUSION ................................................................................................................................... 52
V
RECOMMENDATION .............................................................................................................................. 53
REFERENCES .......................................................................................................................................... 54
VI
LIST OF TABLES
Table 1.1: River gauging stations in Nyando basin ......................................................................... 5
Table1.2: rainfall gauging stations in Nyando basin. ...................................................................... 7
Table3.1:Thiessen polygon method Computation table. ............................................................. 16
Table 4.1: mean monthly and total annual rainfall of station 8935001 ....................................... 22
Table 4.2: mean monthly and total annual rainfall of station 9035003 ....................................... 23
Table4.3: mean monthly and total annual rainfall of station 9034086 ........................................ 24
Table4.4: Table of the Annual Total Rainfall of station I.D.8935001 ............................................ 31
Table4.5: Table of the Annual Total Rainfall of station I.D. 9035003 ........................................... 32
Table4.6: Table of the Annual Total Rainfall of station I.D. 9034086 ........................................... 33
Table4.7:Moving Average analysis for station 8935001............................................................... 37
Table4.8: Moving Average analysis for station 9035003 .............................................................. 38
Table 4.9: Moving Average analysis for station 9034086 ............................................................. 39
Table4.10: Monthly Summary of the Flow (cumecs) of Gauging Station 1GD03 ......................... 43
Table4.11: Flow Duration Analysis Station 1GD03 ....................................................................... 44
Table4.12: Flood Analysis 1970-1997(1GD03) ............................................................................. 46
Table4.13: Moving Average analysis for station 1GD03 ............................................................... 48
Table4.14: Demand and Storage required.................................................................................... 50
VII
LIST OF FIGURES
Figure 1.1 flooding scenarios in the Nyando basin (2002) ............................................................. 3
Figure 1.2: Location map of Nyando catchment ............................................................................ 4
Figure 1.3: Network of River gauging stations in Nyando catchment ............................................ 6
Figure1.4: Network of rainfall gauging stations ............................................................................. 8
Figure 3.1 Illustration of Thiessen Polygon. .................................................................................. 16
Figure 3.2 thiessen polygon plot ................................................................................................... 17
Figure 3.3: mass curve illustration ................................................................................................ 20
Figure 4.1 : seasonal rainfall pattern of station 8935001 ............................................................. 25
Figure 4.2: seasonal rainfall pattern of station no. 9035003 ....................................................... 26
Figure 4.3: seasonal rainfall pattern of station 9034086 .............................................................. 27
Figure4.4: rainfall trend of station 8935001 ................................................................................. 28
Figure4.5: rainfall trend of station no. 9035003 .......................................................................... 29
Figure4.6: rainfall trend of station 9034086 ................................................................................. 30
Figure4.7: rainfall frequency curve for station I.D. 8935001 ........................................................ 34
Figure4.8: rainfall frequency curve for station I.D. 9035003 ........................................................ 35
Figure4.9: rainfall frequency curve for station I.D. 9034086 ........................................................ 36
Figure4.10: Moving average rainfall trend for station 8935001 .................................................. 40
Figure4.11: Moving average rainfall trend for station 9035003 .................................................. 40
Figure4.12: Moving average rainfall trends for station 9034086 ................................................. 41
Figure4.13: flow duration curve for river at 1GD03 ..................................................................... 45
Figure4.14: Flood analysis curve for station 1GD03 ..................................................................... 47
Figure4.15: moving average curve for station 1GD03 .................................................................. 49
Figure4.16: mass curve for critical period station 1GD03 ............................................................ 51
VIII
ABSTRACT
A hydrological study of Nyando basin which is located in Western Kenya was conducted. The
objective of the study was to evaluate and analyze the Nyando basin’s rainfall and stream flow.
Nyando basin was selected for study because of the frequent flooding cases that have occurred
in the region over the past years.
A systematic approach for attaining the objective was used. At first, data was visually
scrutinized. Missing data was filled through interpolation or station correlation. Areal rainfall
over Nyando basin was determined by Thiessen polygon method. Mean monthly rainfall,
rainfall trends over periods of 20-30 years and probability analyses of rainfall were carried out
as well. Flood analysis, storage analysis and frequency distributions of rainfall were determined.
The areal rainfall was obtained as 1608mm per annum and according to the moving averages
curves there was an increase in rainfall trend. The catchment experienced a bimodal seasonal
pattern of rainfall i.e. long rains in March-May and short rains in October-December or July-
September. Rainfall frequency curves were plotted to reflect rainfall at different probabilities.
Flood analysis showed that the region experiences heavy floods. The stream flow analysis
revealed an increasing trend. The flood for a 20 year return period at station 1GD03 was 595
m3/s.
1
CHAPTER ONE
1.0 INTRODUCTION
1.1 General
Nyando basin is in Western Kenya. Administratively it is located in the Rift-valley and Nyanza
provinces. It covers about 3,600 km2 of land. The basin is bounded by latitudes 00 7’ 48”N and 00
24’ 36”S and longitude 340 24’ 36”E and 350 43’ 12”E. This is between Lake Victoria to the
south, Mau escarpment to the southeast and Nandi escarpment to the North. The region has a
well outlaid network of gauging stations i.e. meteorological stations, rainfall gauging stations
and river gauging stations. Most of the river gauging stations are situated on the tributaries of
the River Nyando.
The main river on this basin is the Nyando River. The river drains parts of Nandi, Kericho and
Nyando districts with an average discharge of approximately 15m3 /s. The river has a number of
tributaries namely, Nyaidho, Awach, Namuting ,Kapchorua, Tugenon, Mbogo and the main
being Ainabng’etuny. The river meanders through the Kano plains before draining into Kano
plains then Winam Gulf of Lake Victoria. Peak flows of 29 m3 s-1 and low flows of 6 m3 s-1 or even
lower are registered in the Nyando basin during the year.
The climate varies in different parts of the basin because of the variation of topography from
the highlands to the shores next to the Lake Victoria. The area registers higher rainfall on the
highlands and lower rainfall at the lowlands with an annual average rainfall ranging from
1000mm to 1600mm. Rainfall peaks occur during the short and long rains periods that is
October to December and March to May respectively.
The elevations or altitudes of different areas in the Nyando basin vary drastically. At the lake
shores altitudes are about 1100m above sea level while on the highlands the altitudes are
about 3000m above sea level. There is reasonably vast piece of flat lands e.g. on the Kano plains
and scarps formed by the rift faults. On these flat regions is where flooding takes place.
2
Urban centres and industries in the catchment include Nandi Hills and Kericho on the highlands,
Chemilil, Muhoroni and Londiani on the middle reaches and Ahero near the river mouth.
Types of soils vary with change in land elevation. The basin consists of extrusive igneous rocks
mainly phonolites and metamorphic rocks. The region’s forestry varies similarly to the soil’s. On
the highlands soils are moderately fertile and of reasonably shallow depth while on the
lowlands and plains, the soils are less fertile and deep consisting of unstable aggregate.
Consequently, there are heavy forests on the highlands as opposed to the lowlands where most
of the trees are sparsely scattered. Most of the trees are naturally growing on the highlands
where the tributaries commence.
There have been disastrous floods which have led to damage of property and environmental
degradation in the basin over the past century with worst cases being witnessed during the
high rainfall periods. This has significantly affected the quantity of water in the region
consequently causing a variation in water use both upstream and downstream. In the past
there have been many instances of flooding in the lowlands particularly in the Kano Plains. This
is because the river has lost the ability to buffer environmental variability.
These issues have greatly disrupted the socio-economic activities of the people living in this
region and to an extent, causing poverty in the region. Large amounts of resources have been
used in trying to contain these problems with the government sparing great amounts of money
trying to cover for the displaced citizens. These floods are catastrophic and results to
destruction of property and even loss of lives. Sedimentation on the other hand disrupts the
normal use of water.
3
Figure 1.1 flooding scenarios in the Nyando basin (2002)
1.2 Objective
Figure 1.1 shows flooding scenarios at the Kano Plains that occurred in the year 2002. The
motivation behind carrying out this study is the exceptional history of disastrous floods in the
Nyando basin. The objective of this project is therefore to study Nyando catchment and hence
obtain its hydrological parameters. This is done by;
Analyzing and evaluating the precipitation of the Nyando basin.
Analyzing and evaluating stream-flow of this region.
4
Figure 1.2: Location map of Nyando catchment
5
1.3 Network of stations
In the Nyando basin there is a vast and widely spread network of river gauging and
meteorological stations. River guaging stations are located on the tributaries of the Nyando
River and the Nyando itself. Over years some of the stations have stopped recording data
while others have quite instrumental data. The network ranges from the slopes of the Nandi
to the lowlands of the Kano and Kisumu. A list of Networks is as shown below;
Table 1.1: River gauging stations in Nyando basin
Gauging station
River Type of station
Latitude Longitude Length of record
1GB03 Ainabng’etuny
Staff 0 04S 35 03E -
1GB05 Ainabng’etuny
Staff 0 01S 35 09E 1960-1985
1GC05 Masaita
Staff 0 12S 35 33E -
1GD03 Nyando
Staff 0 08S 34 59E -
1GDO7 Nyando
Staff 0 09S 35 10E -
1GC04 Tugenon Staff 0 15S 35 23E 1960-1992
6
Figure 1.3: Network of River gauging stations in Nyando catchment
7
Table1.2: rainfall gauging stations in Nyando basin.
Gauging station ID
Gauging station name Period of record
Latitude longitude Altitude (FT)
9034034 Maseno siriba training centre
1945- 0 00s 34 36E 5000
9034022 Maseno Asembo Dispensary
N/A
0 10s 34 23E 3730
9034080 Ahero Kano Irrigation Station
1943-
0 08s 34 56E 4000
9034067 Nyakwere Trading Centre
1955- 0 21s 34 47E 3800
9034086 Ahero Irrigation Research Station
1962-1988 0 09S 34 56 E 4000
9035140
Koru Mission N/A 0 12s
35 17E 5600
9035258
Lumbwa Soil Conservation N/A 0 11s
35 27E
7000
8935001
Songhor Kaabirir 1959-1988 0 02N 35 18E
6200
8935033
Nandi Hills, Savani Estate 1930- 0 03N
35 06E
6000
9035003 Kericho District Office
1959-1986 0 17s 35 17E 6500
8935148
Kapkurere Forest
1960- 0 04N
35 26E
7400
8935161
Nandi Hills, Kibwanri Tea
Estate 1959- 0 05N
35 09E 7400
9035075
Kericho, Kaisugu House N/A 0 20S
25 23E
7200
9034025
Kisumu Meterological Station
1939- 0 05S
34 45E
3770
9034060 Kisumu New Prison
N/A 0 04S 34 43E 4000
8935001 Kabagendui kibet Farm 1923- 0 02N 35 18E 6200
8
Figure1.4: Network of rainfall gauging stations
9
CHAPTER TWO
2.0 LITERATURE REVIEW
This chapter reviews the various relevant literatures, which are referred to and used in this
study.
2.1 Introduction
The hydrology of the catchment is greatly influenced by north-south movement of the Inter-
Tropical Convergence Zone and local winds (lake/land breezes), which influence the spatial and
temporal variations of hydro-meteorological parameters (Millman, 1973).
The Nyando River has its headquarters in the Mau Forest complex situated on the eastern
shoulder of the Rift Valley and pours into Lake Victoria after traversing through the Kano Plains.
Run-off accumulates in the upper Nyando River and peak discharge occurs in April or early May.
In the last 50 years, annual discharge has averaged 22.2m3/s, varying from a mean of monthly
6.26 to 29.07m3/s (Nicholas and Yin, 2001). The highest recorded peak was experienced during
the disastrous floods caused by abnormally prolonged ‘uhuru rains’ in 1961-62 periods when
the entire Kano Plains was flooded (Millman). The arrival of seasonal floods from upper
catchment through the main tributaries of Ainamutua causes a stage rise of up to 8m at Ogile
Bridge in the northern part of Kano Plains. Additionally a flood wave from the last two
tributaries of Awach Kano and Asao quickly spread out from south-eastern portion of Kano
Plains.
The sources of water for the Nyando Wetlands includes direct precipitation/ run-off from
upland areas, inflow from rivers, recharge from aquifers and backflow from lake during
flooding. In the average year, rain caused localized surface flooding during the rainy season, but
this short lived as it precipitates and infiltrates slowly into the waterlogged ground. During
periods of exceptional rain, surface flooding is widespread and may persist until the seasonal
flood arrives. Consequently, Winam Gulf experiences an occurrence of intense sediment
plumes after the flushing of the Nyando Wetlands.
10
2.2 Climate
The Nyando River basin experiences two heavy rainfall seasons with long rains beginning from
March to May and short rains beginning in September to November. The average annual
rainfall ranges from about 1100 to 1600 with a minimum and maximum mean monthly rainfall
of 72mm and 240mm respectively (JICA, 1992). The altitude and the nature or relief features of
the Nyando region immensely affect the amount of rainfall in the region. The areas on the
highlands of Nyando basin experience higher amounts of rainfall as compared to the middle
and lower areas. The mean amount of rainfall averages 1800mm per annum in the highlands.
The rainfall is orographic type of rainfall since it’s associated with the south-easterly winds
carrying warm air masses from the Indian Ocean.
The climate varies in the lowlands e.g. the Kano Plains where a semi arid climate is experienced.
The Kano Plains receive rainfall in the range of 600-1100mm per annum (FAO 1996). The area is
generally sub-humid as well. Convective currents carry moisture from the Lake Victoria hence
causing conventional rainfall on the Kano Plains and other regions located at the Lake Victoria
shore.
The lowlands and middle reaches of the Nyando basin experience a relative humidity of
between 55% and 75% in the dry and rainy seasons, respectively. The peak relative humidity is
experienced in May and July and the minimum occurring in January during the short dry season
and October, during the long dry season. The mean minimum annual temperatures are
recorded in August through September and ranges from 140C to 180C. Highest temperatures
are recorded in June and July with annual mean maximum ranging from 270C to 320C.
The monthly A-pan evaporation ranges from 1900 to 2200mm while the monthly mean
evaporation ranges from 1300 to2200mm. The monthly minimum and maximum evaporations
are recorded during June/July and March, respectively.
2.3 Geological setting
The oldest rocks are found in Nandi Escarpments (Saggerson 1947). These rocks consisted of
granites and granitized rocks. The highlands consist of volcanic material with lavas and tuffs
11
deposits located at Tinderet forest area. Lava Plateaus can be located on the Eastern edge of
Kano plains and over the Nyabondo Plateau.
Deformations and fracturing movements caused deposition of rocks in the Kano Plains
(Shackleton 1952). During the Pliocene to Pleistocene periods, the Kavirondo rift zone
deformed, followed by eruptions which led to formation of tuffs and agglomerates that cover
large areas of the Kano Plains. During the Pluvial Period, silt and clay were deposited in the Lake
Victoria and these became inter-bedded over the Kano Plains area with river and hill wash
material brought down from the surrounding highlands (Millman 1973). The most recent
geological event is the migration of the Nyando River drainage to Lake Victoria from a more
direct course to one hindered by swamps and papyrus reeds (Millman 1973).
The Kano Plains are characterized by a complex succession in the soil profiles. The northern,
southern and stern parts of the Plains are dominated by deep accumulations of hill wash that
are a result of flash floods and become mixed with lenses of alluvium. Generally, soils are fine
textured but soils in Nyakach show a broad variation. Dark coloured clays and clayey loams are
most widespread of the alluvial types; their colour varies from brown to black, which
corresponds to a variation in clay content in the sub-soil (Millman 1973).
2.4 Previous studies on Nyando Catchment
2.4.1 Ecohydrological characterization of Nyando Wetland
An eco-hydrological characterization of Nyando Wetland was conducted in 2009-2010 by The
UNESCO-IHE Institute for Water Education from Netherlands. One of the main objectives of the
research was to analyze the main hydrological factors that influenced the Nyando Wetland
evolution.
The results of the research on mean annual rainfall was that the highest mean annual rainfall
was registered as 1735mm per annum, observed at Tinderet Tea Station and Londiani Forest
station recording the lowest value at 1117mm per annum. In general, the highland Stations
(Tinderet Tea, Ainamoi’s Chief’s Camp, Nandi Hills Savani, Koru Bible) received more rainfall
12
than Stations in the Plateau (Londiani Forest and Kipkelion Water Supply) and lowlands (Ahero
Irrigation and Chemilil Sugar). Though located in the highlands close to Nandi Hills, Savani,
Kibwari Tea Station has a mean annual rainfall of only 1233 per annum.
The lowland Stations which are characterized by the Kano flood Plains and Lake Victoria
shoreline received pre-dominantly conventional rainfall. Some Plateau Stations are located on
the leeward side of the highlands and hence do not benefit from the south-easterly monsoon
winds that bring about orographic rainfall.
A visual Inspection of the long-term monthly rainfall distribution from eight selected stations in
the study area showed a bimodal seasonal pattern of rainfall variability. The long rains in
March-May and short rains varied between stations. In general, the lowland stations and some
highland stations received short rains in the October-December months, while a few highland
stations experienced short rains in the July-September months.
2.4.2 Study on flooding characteristics of the Nyando River
In 2010 Peter Ocholla of the University of Zululand conducted a study on the impact of flooding
characteristics of the Nyando Rive on the Local farming(cotton).
One of his objectives was to determine whether flooding characteristics had changed with time.
From his results he concluded that:
High variability of flow was evident throughout the period under study, namely the
flooding periods (400-521m3/s) recorded in 1977, 1978, 1988 and 1996. The same
periods also reflected higher rainfall peaks. From the 32-years of time series flow
data, 18 years of bank-full flow (200-387.9m3/s) were recorded.
The 31-year time series revealed that the lower Kano Plains had so far experienced
flooding nearly every year. While 400-521m3/s were the flood discharges computed,
13
it was argued in the study that the annual floods and inundation were the results of
bank-full flows that were unable to be contained in Nyando River low channel.
Discharges causing floods, however, had between 3 and 7 years recurrence intervals,
with an average 400m3/s discharge.
14
CHAPTER THREE
3.0 METHODOLOGY
3.1 General
This chapter describes the input data, their source and the methodology adopted to analyze
precipitation, runoff and flooding.
The input data included; rainfall and stream flow data. The data was obtained from The
Ministry of Water, JICA reports and Kenya Meteorological Department.
3.2 Rainfall
The rainfall data was obtained from JICA reports.
3.2.1 Data processing
The data obtained had to be listed appropriately for visual scrutiny of the tabulated data, filling
in the missing data by interpolation or using station correlation.
The rainfall data had a lot of fluctuations for instance features like seasonal variations or
fluctuations. Cycles or cyclic variations and even non-recurring, random variations were
observed.
3.2.2Mean Monthly rainfalls at the stations
The average rainfall in each month for the whole record of the station was obtained; monthly
normals were plotted and compared to observe variations of rainfall in each month. The rainfall
seasons were easily noted for rainfall at a station.
3.2.3Areal rainfall
Areal rainfall value was determined by thiessen polygon method. The Isohyetal method was the
most appropriate method for obtaining average rainfall in Nyando catchment due to the drastic
15
variation in topography in the region but due to lack of sufficient data, the thiessen polygon
method was used.
3.2.3.1 Thiessen polygon method
This method assumed that any point in the watershed received the same amount of rainfall as
that measured at the nearest rain gauging station. Here, rainfall recorded at a gauge could be
applied to any point at a distance halfway to the next station in any direction.
The method involved the following steps:
1. Gauge network was plotted on map of the catchment area of interest.
2. Lines joining adjacent stations were drawn.
3. Lines perpendicular to the lines drawn in step 2 were drawn.
4. The bisectors were extended and used to form the polygon around each gauge
station.
5. Rainfall value for each gauge station was multiplied by the area of each polygon.
6. All values from step 5 were summed and divided by total catchment area.
Mathematically the average rainfall is:
Where; Pi = rainfall value for each gauge station.
Ai = area of respective polygon.
A = total catchment area.
The stations used and their details are as shown in the following table:
M
i
ii
total
i
M
ii
A
AP
A
AP
P1
1
16
Figure 3.1 Illustration of Thiessen Polygon.
Table3.1:Thiessen polygon method Computation table.
Station observed rainfall(mm)
Area(km2) Ai/AT Weighted rainfall(mm)
9034086 1180 648 0.178 210.04
8935001 1854 324 O.089 165.01
9035003 1855 567 0.156 289.38
9035263 1750 445.5 0.122 213.50
9035002 1120 607.5 0.170 190.40
8935033 1587 526.5 0.167 265.03
9035148 1642 526.5 0.167 274.21
Total A=3645 =1608
17
Figure 3.2 thiessen polygon plot
18
3.2.4 Rainfall pattern
The rainfall patterns of the stations were obtained by plotting the graph of precipitation against
the stipulated period of record.
The minimum and maximum precipitations were observed on the graphs.
3.2.5 Probability analysis of rainfall.
The rainfall data was considered to be normally distributed. The solution was using appropriate
probability paper. A graph of total annual rainfall was plotted against probability.
The annual rainfall totals were obtained from the area of concern i.e. Nyando catchment for
the whole period of study. The data used for study was 25 years and above and therefore was
appropriate for statistical analysis.
The annual totals were then arranged in ascending order. The probability of occurrence
P (%) for each of the ranked observations was then calculated from the equation:
P = m/N+1
Where; P = probability in % of the observation of the rank m
m= the rank of the observation
N = total number of observations used
The ranked observations were plotted against the corresponding probabilities on a normal
probability paper. A straight line of best fit was then plotted. From this plot it is possible to
obtain the rainfall at different probabilities. Consequently, it is also possible to obtain the
magnitude of the rain corresponding to a given probability
3.2.6 Moving averages curves
In order to establish whether rainfall trend was either increasing or decreasing in the
catchment, moving average curves were plotted. A series of cumulative rainfall values were
19
calculated and averages obtained. A curve of the averages against the years was plotted and
hence the rainfall trend deduced.
3.3 Stream flow
The river flow data was obtained from the Ministry of Water Resource Kenya.
3.3.1 Flow Duration
Classes of flow data were created. Midpoints of these classes were hence obtained. The mid-
points were plotted against Cumulative Probability on Log Probability paper
The value 95% low flow was obtained using the x value of (100 – 95) % = 5%. This is the
value of flow which will be equaled or exceeded 95% of the Time or if the river used for
water supply, the supply would be available 95% of the time; there is a chance of 5% failure.
3.3.2 Flood analysis
The maximum daily flow values were arranged in ascending order; they were ranked (m),
Probabilities were assigned using plotting position, (m/N+1) where N is the Total number of
data observations. The flow data and the corresponding probabilities were plotted on Log
probability paper. Flood flows corresponding to certain return periods e.g. 20 years were then
read from the plot.
3.3.3 Storage analysis
Storage analysis was done through mass curve technique. The stream flow data was scrutinized
and a dry period selected for analysis. Monthly flows for this period were recorded. The flows
were cumulatively added. A graph of cumulative flow against the months was plotted. A
demand was assumed and the various storages located on the plot. An illustration of a mass
curve is as follows;
20
Figure 3.3: mass curve illustration
3.3.4 Moving averages curve
In order to establish whether stream flow trend was increasing or decreasing in the catchment,
a moving averages curve was plotted. A series of cumulative stream flow values were calculated
and averages obtained. A curve of the averages against the years was plotted and hence the
stream flow trend deduced.
21
CHAPTER FOUR
4.0 RESULTS AND DISCUSSION
This chapter involves the analysis of the relevant data through the methods explained in the
previous chapter.
4.1 Rainfall analysis and discussion
4.1.1 Rainfall data summary
Tables 4.1, 4.2 and 4.3 show the summary of rainfall data from stations I.D. 8935001, 9035003
and 9034086 respectively; the monthly precipitation in mm and their means(averages) over the
provided years and the total annual rainfalls for every year.
22
Table 4.1: mean monthly and total annual rainfall of station 8935001
YEAR JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC T.A.R
1959 120 20 101.6 151 207.2 77.9 99.1 149.4 117 109 211.5 24.6 1388.3
1960 131 15.2 226.7 273.7 170.5 74.5 115.5 167.9 220.6 63.1 97.7 90.2 1646.6
1961 191.2 91.8 136.6 174.9 197.3 105.3 170.9 299.7 183 103 356.4 288.5 2298.6
1962 251.4 168.4 85.4 317.3 279.6 142.6 171.7 286.5 177.1 142.4 77.3 161.5 2261.2
1963 146.7 109.3 169.7 373.9 327.6 94.1 111.1 165.1 69.5 51.6 265.8 188.4 2072.8
1964 51 80.9 115.9 327.6 123.6 93.5 154.4 180.6 145.9 106.5 10.1 36.1 1426.1
1965 37.6 13.9 51.8 260.3 102.8 46.6 137 113.7 51.5 129.7 101.7 80.3 1126.9
1966 3 191.5 128.7 273.9 159.7 103.7 94.2 157.9 74.1 61.3 58.5 29.2 1335.7
1967 2 32 124.7 162.5 303.2 52.4 127.7 155.7 95.8 87.2 117.8 53.1 1314.1
1968 62.2 123.1 144 289.5 165.2 91 171.8 259.4 42.6 157 91.8 27.4 1625
1969 122.4 134.2 89.9 29.6 161.2 100.2 113.4 173.5 71.9 200.4 57.5 7.8 1262
1970 135.5 61.5 184.4 218 110.7 120.8 77.5 151 60.1 32.2 29.6 42.2 1223.5
1971 63.3 24.9 2.6 209.2 196.1 185.9 151.5 188.5 118 24.4 52.6 83.6 1300.6
1972 11.7 146.9 38.3 100.4 265.9 189.2 90.8 85.2 79.5 173 169.1 26.9 1376.9
1973 147.6 192 5.3 68.6 164 138.9 104.1 131.3 164.3 73.9 55.3 0.5 1245.8
1974 10 32.5 180.9 135.2 116.6 197 9 73.8 157.2 70.7 16 22.4 1021.3
1975 17.9 33.7 105.6 164.2 181.6 120.6 181.2 101.6 164.4 112.7 21.9 106.1 1311.5
1976 25.7 12.3 69.9 114.5 123.4 121.3 150.6 129.4 108.1 19.1 131.8 43.7 1049.8
1977 121.5 93.7 42.8 231.3 212.1 143.8 187.1 156 51.8 124.9 170 118.1 1653.1
1978 363.9 545.8 64.2 380.6 284.7 306.9 341.3 346 401.9 378 34 120.1 3567.4
1979 106.3 280.2 85.6 511.2 62.8 108.4 255.6 22.1 219.5 43.2 154.4 29 1878.3
1980 79.8 14.5 232.8 121.9 337.4 176.2 211.8 503.6 91.9 107.3 295.2 99.1 2271.5
1981 1.1 85.5 452.9 561.1 140.7 235.5 237.7 539.2 403.2 66.3 155.4 73.3 2951.9
1982 55.6 36.2 325.4 410 814.4 320.7 464.7 387.8 239.6 309.5 640.5 154.3 4158.7
1983 110 184 63.5 302.5 760.7 379 780 492.4 389 480.7 124.5 235.2 4301.5
1984 146 3.7 12.7 113.9 1114.3 115.7 103.9 115.3 116.1 134.2 131 178.3 2285.1
1985 61.1 70.3 125.2 279.3 681 118.2 174.5 109.6 104.5 32.4 157.1 34 1947.2
1986 68.6 88.4 78.4 183.6 151.8 120.6 210.5 21.8 96.3 14.7 65.4 73.2 1173.3
1987 76.1 76.8 94.3 133.2 151.8 94.5 29.2 124.9 67.7 78.7 213.3 27.6 1168.1
1988 116.6 74 110.2 401.5 220.1 68.3 199.3 257.7 221.3 140.5 137.3 23.7 1970.5
MEAN 94.6 101.2 121.7 242.5 276.3 141.4 180.9 201.6 150.1 120.9 140.0 82.6
T.A.R-Total Annual Rainfall
23
Table 4.2: mean monthly and total annual rainfall of station 9035003
YEAR JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC T.A.R
1959 83.1 87.7 160.4 198.1 237.5 77.8 74.2 100.4 141.4 107.4 139 21.1 1428.1
1960 125.2 127.8 246.5 283.8 215.9 51.8 67.5 77 251.8 127.9 139.8 6.3 1721.3
1961 5.1 67.9 138.2 211.5 220.1 200.4 75.5 149.6 166.1 187.4 444.6 245.6 2112
1962 113.9 31 111.4 283 291.9 164.5 138.2 121.1 144.2 216.8 43.3 110.1 1769.4
1963 173.1 98.8 129.6 373.9 239.9 65.6 172.9 175 88.5 68.6 323.1 187.2 2096.2
1964 23.2 168.2 181.7 439.7 166.8 95 184.9 132.4 175.8 245.8 62.9 125.6 2002
1965 44 32 168.2 276.3 183.8 115.1 116.9 154.4 89.3 158.7 195.7 110.9 1645.3
1966 59.5 200.4 167.5 331.5 105.3 168.9 124.6 180.1 150.4 119 124.1 10.2 1741.5
1967 14.3 24.4 291.3 191.8 395.9 138.9 95 181.2 146 113 301.4 92.6 1985.8
1968 12.7 267 213.9 417.4 261 260.8 271.3 171.3 74.9 201.3 155.5 80.7 2387.8
1969 98.2 197.1 229.4 122.2 211.1 147.6 130.1 75.6 54.8 106.2 46.2 12.6 1431.1
1970 237.4 96.9 308.7 235.7 343.8 164.5 157.4 312.6 215.4 187.2 105.5 120.2 2485.3
1971 100.7 11.6 23.5 358 225.3 261 161.1 148.6 190.7 89.3 79.6 123.6 1773
1972 77.2 103.7 71.4 177.8 307.2 156.6 159.6 129.7 141.5 177.9 317.9 102.2 1922.7
1973 178.2 209.1 35.6 179.9 305.7 188.6 126.6 244.3 135.4 8.5 92 32.4 1736.3
1974 76.1 42 245.9 243.4 257.4 150.1 328.5 95.2 132.5 120.6 70.2 21.1 1783
1975 5.5 72.9 211.7 183.5 212.9 77.3 157.1 261.5 195.1 169.7 59.2 41.8 1648.2
1976 19.7 63.6 76.5 196.2 457.8 144.2 157.7 184.8 77.3 51.8 130 130.9 1690.5
1977 193.1 50.3 207.7 301.5 272.9 208.4 126.2 141 157 150.6 109.5 68.4 1986.6
1978 145 245.3 305 334.3 280.8 197.9 93 269.4 127.7 170.3 85.4 47 2301.1
1979 67.5 24 131 248.5 241.2 179.5 108.1 233.3 110.8 33.3 61.2 48.5 1486.9
1980 106.8 2.9 191.1 8.6 256.4 133.7 17.7 152.6 126.5 125.7 79.3 50 1251.3
1981 22.7 49.2 320.3 301.9 357.5 53 203.8 176.8 249.4 82.2 103 80.9 2000.7
1982 62.4 78.3 99.6 266.4 458.5 110.4 147.4 246.7 175.2 288.5 280.8 221.1 2435.3
1983 64.4 34.5 79.9 262.3 214.2 269.2 236.1 156.5 250.1 239.5 128 81.8 2016.5
1984 88.3 55.1 51.4 254 152.3 116 134.1 193.6 85.4 167.7 284.6 116.5 1699
1985 93 91.4 177.9 433.2 207.8 107.3 227.3 204.7 185 76 94.8 57.2 1955.6
1986 60.8 62 56.8 250.1 276.2 126.1 60.5 101.2 188.8 124.8 60.7 79.1 1447.1
MEAN 84.0 92.7 165.4 263.0 262.8 147.5 144.8 170.4 151.0 139.8 147.0 86.6
T.A.R-Total Annual Rainfall
24
Table4.3: mean monthly and total annual rainfall of station 9034086
YEAR JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC T.A.R
1962 121.3 20.1 150.3 222.4 92.1 58.6 95.7 46.3 62.3 43.6 114.5 73.5 1100.7
1963 89.6 89.6 165 220 85 60 30 58.4 72 34 118 73 1094.6
1964 57.8 159 135.5 224.7 99.1 57.1 161.3 34.2 52.6 53.2 111 74 1219.5
1965 36.4 140.45 117.9 231.15 114.45 69.2 114.5 38.6 57.4 62.9 116.15 98.4 1197.5
1966 15 121.9 100.3 237.6 129.8 81.3 67.7 43 62.2 72.6 121.3 122.8 1175.5
1967 24.1 41 93.7 221.4 160.4 66.7 28.3 33.7 92.6 66.8 141 119.7 1089.4
1968 5.8 202.7 106.8 253.8 109.1 95.9 39.4 52.3 31.7 78.3 101.6 125.8 1203.2
1969 114.6 112.9 140.5 174.8 113.9 86.8 63.4 45.1 38.9 40.7 108.2 59.9 1099.7
1970 221.8 101.3 160.8 198 85.6 92 79.2 127.4 35.8 35 84.2 61 1282.1
1971 59.6 6.6 34 221 167.2 147.2 55.7 71.1 50.1 46.7 134.1 67.5 1060.8
1972 33.7 96.3 60.5 202.9 128.2 62 51.7 51.4 139 102.2 152.1 72.3 1152.3
1973 153.7 132.9 41 76.1 250.5 49.2 71.1 138.4 70.1 56.7 113 95 1247.7
1974 43.2 18.5 217.4 282.9 126.6 71.9 79.3 84.3 57.6 35.5 109.3 75.7 1202.2
1975 9.7 78.1 178 97.6 117.1 59.5 101.9 233.1 64.8 61.1 95.5 78.5 1174.9
1976 112 101 43.3 144.1 97.7 82 121.8 103.9 79.3 22.1 81.7 83.9 1072.8
1977 86.1 123.9 117.3 230.7 120.7 103.9 58.8 68.2 39.9 127.2 157.4 21.9 1256
1978 125 134.9 202.3 234.1 62.1 52.4 151.3 75.6 89.2 124.9 46.6 137.7 1436.1
1979 78.7 203.3 224.8 100.6 153.9 65.3 53.7 41.8 133.8 56.6 102.7 104.7 1319.9
1980 72.8 30.9 96.6 179.1 102.5 92 50.4 45.9 92 25.3 67.5 119 974
1981 7.7 30.4 222.3 167.3 155 50.5 127.7 98.3 115.4 27.6 76 8 1086.2
1982 54.5 174.7 50.8 130.6 198.9 162.4 46.5 166.9 56.7 72.7 178 33.8 1326.5
1983 32 65.6 68.6 217.1 97.3 57.8 70.3 131.9 38.6 152.7 36.8 60.6 1029.3
1984 60.1 34.3 54.2 170.2 80.2 121.2 73 66 99 108.5 143.7 88.7 1099.1
1985 36.9 45.6 176.9 252.1 165.2 34.2 65.1 138 59.8 59.8 83.6 31 1148.2
1986 48.3 72 151.1 255.8 139.3 74.3 83.9 26.5 98.5 118.4 104.7 136.7 1309.5
1987 57.6 64.2 144.3 203.6 143.6 159.1 33.9 76.1 41.6 68 150.7 37.9 1180.6
1988 234.1 18 150.7 334.5 135.7 36.1 42.2 106.5 91.2 68.4 81.6 11.4 1310.4
MEAN 73.8 89.6 126.1 203.1 127.1 79.6 74.7 81.6 71.2 67.5 108.6 76.8
T.A.R-Total Annual Rainfall
25
4.1.2 Determination of seasonal rainfall patterns
Figure 4.1: seasonal rainfall pattern of station 8935001
94.6101.2
121.7
242.5
276.3
141.4
180.9
201.6
150.1
120.9
140.0
82.6
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
RA
INFA
LL(m
m)
MONTHS
MEAN MONTHLY RAINFALL
26
Figure 4.2: seasonal rainfall pattern of station no. 9035003
84.092.7
165.4
263.0 262.8
147.5 144.8
170.4
151.0139.8
147.0
86.6
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
RA
INFA
LL(m
m)
MONTHS
MEAN MONTHLY RAINFALL
27
Figure 4.3: seasonal rainfall pattern of station 9034086
A visual Inspection of the rainfall patterns i.e. Figures 4.1, 4.2 and 4.3 for the three selected
stations in the Nyando catchment, shows that there are two heavy rainfall seasons. The long
rains in March-May, and short rains which vary between stations. The lowland station i.e. at
Ahero Irrigation Research Station receives short rains in the October-December months, while
at Songhor Kaabirir and Kericho District Office short rains are experienced in the July-
September months.
73.8
89.6
126.1
203.1
127.1
79.674.7
81.671.2 67.5
108.6
76.8
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
RA
INFA
LL(m
m)
MONTHS
MEAN MONTHLY RAINFALL
28
4.1.3 Determination of rainfall trend
Figure4.4: rainfall trend of station 8935001
0
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
19
59
19
60
19
61
19
62
19
63
19
64
19
65
19
66
19
67
19
68
19
69
19
70
19
71
19
72
19
73
19
74
19
75
19
76
19
77
19
78
19
79
19
80
19
81
19
82
19
83
19
84
19
85
19
86
19
87
19
88
TOTA
L A
NN
UA
L R
AIN
FALL
(mm
)
YEARS
RAINFALL TREND
29
Figure4.5: Rainfall trend of station no. 9035003
0
500
1000
1500
2000
2500
3000
19
59
19
60
19
61
19
62
19
63
19
64
19
65
19
66
19
67
19
68
19
69
19
70
19
71
19
72
19
73
19
74
19
75
19
76
19
77
19
78
19
79
19
80
19
81
19
82
19
83
19
84
19
85
19
86
MEA
N
TOTA
L A
NN
UA
L R
AIN
FALL
(mm
)
YEARS
RAINFALL TREND
30
Figure4.6: Rainfall trend of station 9034086
From Figures 4.4, 4.5 and 4.6, show the variation of rainfall over long periods from station to
station with some extremes being noted. At station I.D. 8935001, the highest rainfall occurred
in the 1983 year while at station I.D 9035003 and 9034086 the years 1970 and 1977
respectively. These unusual peaks observed in the trends indicate very high rainfall which might
lead to flooding.
0
200
400
600
800
1000
1200
1400
1600
19
62
19
63
19
64
19
65
19
66
19
67
19
68
19
69
19
70
19
71
19
72
19
73
19
74
19
75
19
76
19
77
19
78
19
79
19
80
19
81
19
82
19
83
19
84
19
85
19
86
19
87
19
88
RA
INFA
LL(m
m)
YEARS
RAINFALL TREND
31
4.1.4 Rainfall frequency analysis
Table4.4: Table of the Annual Total Rainfall of station I.D.8935001
YEAR SORTED T.A.R rank m/n+1 %
1974 1021.3 1 0.032 3.23
1976 1049.8 2 0.065 6.45
1965 1126.9 3 0.097 9.68
1987 1168.1 4 0.129 12.90
1986 1173.3 5 0.161 16.13
1970 1223.5 6 0.194 19.35
1973 1245.8 7 0.226 22.58
1969 1262.0 8 0.258 25.81
1971 1300.6 9 0.290 29.03
1975 1311.5 10 0.323 32.26
1967 1314.1 11 0.355 35.48
1966 1335.7 12 0.387 38.71
1972 1376.9 13 0.419 41.94
1959 1388.3 14 0.452 45.16
1964 1426.1 15 0.484 48.39
1968 1625.0 16 0.516 51.61
1960 1646.6 17 0.548 54.84
1977 1653.1 18 0.581 58.06
1979 1878.3 19 0.613 61.29
1985 1947.2 20 0.645 64.52
1988 1970.5 21 0.677 67.74
1963 2072.8 22 0.710 70.97
1962 2261.2 23 0.742 74.19
1980 2271.5 24 0.774 77.42
1984 2285.1 25 0.806 80.65
1961 2298.6 26 0.839 83.87
1981 2951.9 27 0.871 87.10
1978 3567.4 28 0.903 90.32
1982 4158.7 29 0.935 93.55
1983 4301.5 30 0.968 96.77
T.A.R-Total Annual Rainfall
Figure 4.7 shows the probability plot of the annual total rainfall of Station 8935001.
From the graph, it is observed that for the probability of 50%, the total annual precipitation is
1500mm for the period of 1959 to 1988 whereas for 5% probability of precipitation will be
975mm.The 95% probability of precipitation will be 3250mm.
32
Table4.5: Table of the Annual Total Rainfall of station I.D. 9035003
YEAR SORTED T.A.R Rank m/n+1 Percentage
1980 1251.3 1 0.0345 3.45
1959 1428.1 2 0.0690 6.90
1969 1431.1 3 0.1034 10.34
1986 1447.1 4 0.1379 13.79
1979 1486.9 5 0.1724 17.24
1965 1645.3 6 0.2069 20.69
1975 1648.2 7 0.2414 24.14
1976 1690.5 8 0.2759 27.59
1984 1699.0 9 0.3103 31.03
1960 1721.3 10 0.3448 34.48
1973 1736.3 11 0.3793 37.93
1966 1741.5 12 0.4138 41.38
1962 1769.4 13 0.4483 44.83
1971 1773.0 14 0.4828 48.28
1974 1783.0 15 0.5172 51.72
1972 1922.7 16 0.5517 55.17
1985 1955.6 17 0.5862 58.62
1967 1985.8 18 0.6207 62.07
1977 1986.6 19 0.6552 65.52
1981 2000.7 20 0.6897 68.97
1964 2002.0 21 0.7241 72.41
1983 2016.5 22 0.7586 75.86
1963 2096.2 23 0.7931 79.31
1861 2112.0 24 0.8276 82.76
1978 2301.1 25 0.8621 86.21
1968 2387.8 26 0.8966 89.66
1982 2435.3 27 0.9310 93.10
1970 2485.3 28 0.9655 96.55
T.A.R-Total Annual Rainfall
Figure 4.8 shows the probability plot of the annual total rainfall of Station 9035003.
From the graph, it is observed that for the probability of 50%, the total annual precipitation is
1825mm for the period of 1959 to 1986 whereas for 5% probability of precipitation will be
1325mm.The 95% probability of precipitation will be 2320mm.
33
Table4.6: Table of the Annual Total Rainfall of station I.D. 9034086
YEAR SORTED T.A.R RANK M/N+1 %
1980 974.0 1 0.036 3.57
1983 1029.3 2 0.071 7.14
1971 1060.8 3 0.107 10.71
1976 1072.8 4 0.143 14.29
1981 1086.2 5 0.179 17.86
1967 1089.4 6 0.214 21.43
1963 1094.6 7 0.250 25.00
1984 1099.1 8 0.286 28.57
1969 1099.7 9 0.321 32.14
1962 1100.7 10 0.357 35.71
1985 1148.2 11 0.393 39.29
1972 1152.3 12 0.429 42.86
1975 1174.9 13 0.464 46.43
1966 1175.5 14 0.500 50.00
1987 1180.6 15 0.536 53.57
1965 1197.5 16 0.571 57.14
1974 1202.2 17 0.607 60.71
1968 1203.2 18 0.643 64.29
1964 1219.5 19 0.679 67.86
1973 1247.7 20 0.714 71.43
1977 1256.0 21 0.750 75.00
1970 1282.1 22 0.786 78.57
1986 1309.5 23 0.821 82.14
1988 1310.4 24 0.857 85.71
1979 1319.9 25 0.893 89.29
1982 1326.5 26 0.929 92.86
1978 1436.1 27 0.964 96.43
T.A.R-Total Annual Rainfall
Figure 4.9 shows the probability plot of the annual total rainfall of Station 9034086.
From the graph, it is observed that for the probability of 50%, the total annual precipitation is
1175mm for the period of 1962 to 1988 whereas for 5% probability of precipitation will be
985mm.The 95% probability of precipitation will be 1370mm.
34
Figure4.7: rainfall frequency curve for station I.D. 8935001
0.0
500.0
1000.0
1500.0
2000.0
2500.0
3000.0
3500.0
4000.0
4500.0
5000.0
0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00 90.00 100.00
AN
NU
AL
TOTA
L R
AIN
FALL
(mm
)
PROBABILITY(%)
35
Figure4.8: rainfall frequency curve for station I.D. 9035003
0
500
1000
1500
2000
2500
3000
0.00 20.00 40.00 60.00 80.00 100.00
ann
ual
to
tal r
ain
fall(
mm
)
probablilty %
36
Figure4.9: rainfall frequency curve for station I.D. 9034086
0.0
200.0
400.0
600.0
800.0
1000.0
1200.0
1400.0
1600.0
0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0
AN
NU
AL
RA
INFA
LL T
OTA
LS(m
m)
PROBABILITY(%)
37
4.1.5 Determination of increasing or decreasing rainfall trend
Table4.7:Moving Averages analysis for station 8935001
YEAR T.A.R 1ST
CUMULATIVE 2ND
CUMULATIVE AVERAGE
1959 1388.3
1960 1646.6 3034.9
1961 2298.6 3945.2 6980.1 1745.03
1962 2261.2 4559.8 8505 2126.25
1963 2072.8 4334 8893.8 2223.45
1964 1426.1 3498.9 7832.9 1958.225
1965 1126.9 2553 6051.9 1512.98
1966 1335.7 2462.6 5015.6 1253.90
1967 1314.1 2649.8 5112.4 1278.10
1968 1625 2939.1 5588.9 1397.23
1969 1262 2887 5826.1 1456.53
1970 1223.5 2485.5 5372.5 1343.13
1971 1300.6 2524.1 5009.6 1252.40
1972 1376.9 2677.5 5201.6 1300.40
1973 1245.8 2622.7 5300.2 1325.05
1974 1021.3 2267.1 4889.8 1222.45
1975 1311.5 2332.8 4599.9 1149.98
1976 1049.8 2361.3 4694.1 1173.53
1977 1653.1 2702.9 5064.2 1266.05
1978 3567.4 5220.5 7923.4 1980.85
1979 1878.3 5445.7 10666.2 2666.55
1980 2271.5 4149.8 9595.5 2398.88
1981 2951.9 5223.4 9373.2 2343.30
1982 4158.7 7110.6 12334 3083.50
1983 4301.5 8460.2 15570.8 3892.70
1984 2285.1 6586.6 15046.8 3761.70
1985 1947.2 4232.3 10818.9 2704.73
1986 1173.3 3120.5 7352.8 1838.20
1987 1168.1 2341.4 5461.9 1365.48
1988 1970.5 3138.6 5480 1370.00
T.A.R-Total Annual Rainfall
38
Table4.8: Moving Averages analysis for station 9035003
YEAR T.A.R 1ST
CUMULATIVE 2ND
CUMULATIVE AVERAGE
1959 1428.1
1960 1721.3 3149.4
1961 2112 3833.3 6982.7 1745.68
1962 1769.4 3881.4 7714.7 1928.68
1963 2096.2 3865.6 7747 1936.75
1964 2002 4098.2 7963.8 1990.95
1965 1645.3 3647.3 7745.5 1936.38
1966 1741.5 3386.8 7034.1 1758.53
1967 1985.8 3727.3 7114.1 1778.53
1968 2387.8 4373.6 8100.9 2025.23
1969 1431.1 3818.9 8192.5 2048.13
1970 2485.3 3916.4 7735.3 1933.83
1971 1773 4258.3 8174.7 2043.68
1972 1922.7 3695.7 7954 1988.50
1973 1736.3 3659 7354.7 1838.68
1974 1783 3519.3 7178.3 1794.58
1975 1648.2 3431.2 6950.5 1737.63
1976 1690.5 3338.7 6769.9 1692.48
1977 1986.6 3677.1 7015.8 1753.95
1978 2301.1 4287.7 7964.8 1991.20
1979 1486.9 3788 8075.7 2018.93
1980 1251.3 2738.2 6526.2 1631.55
1981 2000.7 3252 5990.2 1497.55
1982 2435.3 4436 7688 1922.00
1983 2016.5 4451.8 8887.8 2221.95
1984 1699 3715.5 8167.3 2041.83
1985 1955.6 3654.6 7370.1 1842.53
1986 1447.1 3402.7 7057.3 1764.33
T.A.R-Total Annual Rainfall
39
Table 4.9: Moving Average analysis for station 9034086
YEAR T.A.R 1ST
CUMULATIVE 2ND
CUMULATIVE AVERAGE(mm)
1962 1100.7
1963 1094.6 2195.3
1964 1219.5 2314.1 4509.4 1127.35
1965 1197.5 2417 4731.1 1182.78
1966 1175.5 2373 4790 1197.50
1967 1089.4 2264.9 4637.9 1159.48
1968 1203.2 2292.6 4557.5 1139.38
1969 1099.7 2302.9 4595.5 1148.88
1970 1282.1 2381.8 4684.7 1171.18
1971 1060.8 2342.9 4724.7 1181.18
1972 1152.3 2213.1 4556 1139.00
1973 1247.7 2400 4613.1 1153.28
1974 1202.2 2449.9 4849.9 1212.48
1975 1174.9 2377.1 4827 1206.75
1976 1072.8 2247.7 4624.8 1156.20
1977 1256 2328.8 4576.5 1144.13
1978 1436.1 2692.1 5020.9 1255.23
1979 1319.9 2756 5448.1 1362.03
1980 974 2293.9 5049.9 1262.48
1981 1086.2 2060.2 4354.1 1088.53
1982 1326.5 2412.7 4472.9 1118.23
1983 1029.3 2355.8 4768.5 1192.13
1984 1099.1 2128.4 4484.2 1121.05
1985 1148.2 2247.3 4375.7 1093.93
1986 1309.5 2457.7 4705 1176.25
1987 1180.6 2490.1 4947.8 1236.95
1988 1310.4 2491 4981.1 1245.28
T.A.R-Total Annual Rainfall
40
Figure4.10: Moving average rainfall trend for station 8935001
Figure4.11: Moving average rainfall trend for station 9035003
0
500
1000
1500
2000
2500
3000
3500
4000
4500
1955 1960 1965 1970 1975 1980 1985 1990
RA
INFA
LL A
VER
AG
ES(m
m)
YEARS
0
500
1000
1500
2000
2500
1955 1960 1965 1970 1975 1980 1985 1990
RA
INFA
LL A
VER
AG
ES(m
m)
YEARS
41
Figure4.12: Moving average rainfall trend for station 9034086
The moving averages curves i.e. Figures 4.10, 4.11 and 4.12 show that there has been an
increase in rainfall trend at stations I.D. 8935001 and station 9034086 while at station I.D.
9035003, rainfall is almost uniform with a very mild decreasing trend. This observation could
imply that there has been an increasing rainfall trend in certain regions of Nyando basin.
0
200
400
600
800
1000
1200
1400
1600
1960 1965 1970 1975 1980 1985 1990
AN
NU
AL
RA
INFA
LL T
OTA
LS(m
m)
YEARS
42
4.2 Stream flow analysis
River gauging station 1GD03 was selected for analysis because of its location i.e. at a point
where several tributaries combine discharges to one course and hence the analysis of this
single station suffices the need to analyze the tributaries.
4.2.1 Summary of stream flow Data for station1GD03
Table4.10 shows the summary of the stream flow data. It’s a summary of the monthly flows,
maximum monthly flows and minimum monthly flows. The missing data was filled through
interpolation and is indicated in bold.
43
Table4.10: Monthly Summary of the Flow (cumecs) of Gauging Station 1GD03
YEAR JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC MEAN MIN MAX
1970 225.3 286.3 341.2 956.0 1138.3 684.8 481.3 1301.0 982.1 465.3 223.5 157.1 603.5 157.1 1301.0
1971 155.2 78.3 69.6 521.9 745.4 657.5 876.3 1146.9 1002.2 451.1 173.3 170.3 504.0 69.6 1146.9
1972 107.9 133.6 75.9 87.9 432.1 477.1 495.7 425.9 222.7 613.0 1167.1 299.5 378.2 75.9 1167.1
1973 334.4 457.5 216.3 173.9 410.9 487.5 274.3 791.2 751.5 381.0 223.6 126.1 385.7 126.1 791.2
1974 105.9 64.1 102.4 1248.5 480.5 508.3 1307.3 570.9 529.2 317.5 163.9 96.8 458.0 64.1 1307.3
1975 70.3 55.5 155.5 380.3 309.1 459.9 756.6 1624.4 1883.2 1046.7 298.9 248.5 607.4 55.5 1883.2
1976 153.6 108.0 96.2 156.7 279.2 296.1 573.4 491.8 485.6 136.8 113.3 91.7 248.5 91.7 573.4
1977 114.9 163.1 97.7 706.8 1795.6 970.4 1215.7 1112.7 688.6 426.3 1961.0 770.6 835.3 97.7 1961.0
1978 490.2 481.4 1415.9 1203.0 1327.0 544.1 859.2 1059.3 860.4 728.7 371.8 429.8 814.2 371.8 1415.9
1979 248.2 1681.7 888.0 749.6 785.4 940.9 707.6 1211.0 483.2 269.9 255.1 169.2 699.2 169.2 1681.7
1980 177.4 101.9 105.3 547.0 890.1 494.6 541.2 346.2 268.2 120.4 115.1 85.9 316.1 85.9 890.1
1981 62.6 48.6 158.6 1401.5 997.5 232.3 542.2 1479.3 317.8 213.7 592.0 730.2 564.7 48.6 1479.3
1982 178.4 101.8 134.1 846.7 699.2 302.2 467.7 790.4 367.4 307.0 1069.0 1374.5 553.2 101.8 1374.5
1983 294.3 154.9 109.6 292.0 400.9 372.0 393.3 959.6 1057.1 1302.3 544.3 285.9 513.8 109.6 1302.3
1984 186.8 103.4 83.3 231.1 121.7 136.8 176.7 298.4 185.9 134.6 179.5 98.2 161.4 83.3 298.4
1985 45.2 60.8 97.3 1779.6 1718.8 829.7 217.7 595.5 436.5 190.1 181.4 87.9 520.0 45.2 1779.6
1986 62.5 53.1 85.3 247.5 626.0 346.2 258.6 249.0 167.8 79.6 70.2 59.8 192.1 53.1 626.0
1987 44.5 49.7 216.3 121.5 494.8 928.6 209.6 152.8 95.0 71.3 328.4 87.1 233.3 44.5 928.6
1988 367.8 70.3 154.2 2095.1 2838.5 431.5 567.8 2439.0 1198.8 1129.3 417.2 229.4 994.9 70.3 2838.5
1989 185.6 204.5 370.4 1491.3 1285.4 578.5 585.0 723.0 757.9 714.9 306.5 325.1 627.4 185.6 1491.3
1990 913.7 222.7 1334.2 2934.1 991.9 574.5 535.6 683.3 398.5 238.5 202.3 150.7 765.0 150.7 2934.1
1991 366.2 240.8 115.4 463.0 546.4 885.8 773.3 718.3 834.4 325.2 233.6 136.9 469.9 115.4 885.8
1992 102.5 91.4 70.7 200.1 325.9 607.1 693.0 1161.2 1270.2 570.7 313.6 205.9 467.7 70.7 1270.2
1993 266.7 154.5 110.2 100.4 670.7 564.2 283.0 239.3 198.9 107.2 77.6 136.4 242.4 77.6 670.7
1994 55.7 41.5 290.2 780.7 1502.7 873.9 1175.2 1227.2 868.5 307.3 1567.5 182.7 739.4 41.5 1567.5
1995 182.7 103.3 176.3 174.5 677.9 389.2 841.2 1990.3 1281.4 302.8 247.5 189.3 546.4 103.3 1990.3
1996 104.1 146.1 642.3 523.1 1101.0 1205.0 2524.0 2753.3 2199.8 265.2 223.1 184.8 989.3 104.1 2753.3
1997 164.7 216.2 109.8 1129.0 1524.0 277.0 1502.6 481.6 176.2 227.6 198.7 180.3 515.6 109.8 1524.0
MEAN 206.0 202.7 279.4 769.4 897.0 573.4 708.4 965.1 713.2 408.7 422.1 260.4
MIN 44.5 41.5 69.6 87.9 121.7 136.8 176.7 152.8 95.0 71.3 70.2 59.8
MAX 913.7 1681.7 1415.9 2934.1 2838.5 1205.0 2524.0 2753.3 2199.8 1302.3 1961.0 1374.5
44
Table4.11: Flow Duration Analysis Station 1GD03
CLASSES MIDPOINTS F CF M/N+1 TIME EXCEEDED
0-1.0 0.5 12 12 0.0013 0.9987
1.0-1.5 1.25 135 147 0.0155 0.9845
1.5-2.0 1.75 333 480 0.0507 0.9493
2.0-3.0 2.5 870 1350 0.1425 0.8575
3.0-4.0 3.5 989 2339 0.2469 0.7531
4.0-5.0 4.5 522 2861 0.3020 0.6980
5.0-10.0 7.5 1858 4719 0.4981 0.5019
10.0-20.0 15 2216 6935 0.7320 0.2680
20-30 25 1061 7996 0.8440 0.1560
30-40 35 655 8651 0.9131 0.0869
40-50 45 264 8915 0.9410 0.0590
50-60 55 157 9072 0.9576 0.0424
60-70 65 91 9163 0.9672 0.0328
70-80 75 73 9236 0.9749 0.0251
80-90 85 40 9276 0.9791 0.0209
90-100 95 31 9307 0.9824 0.0176
100-110 105 24 9331 0.9849 0.0151
110-120 115 26 9357 0.9877 0.0123
120-130 125 21 9378 0.9899 0.0101
130-150 140 27 9405 0.9927 0.0073
150-170 160 21 9426 0.9949 0.0051
170-200 185 21 9447 0.9972 0.0028
200-300 250 20 9467 0.9993 0.0007
300-400 350 6 9473 0.9999 0.0001
From the flow duration curve plotted in Figure 4.13, it can be observed that for 95% of the
time, flow equalled or exceeded 1.5 cumecs.
45
4.2.2 Flow duration analysis
Figure4.13: Flow duration curve for river at station1GD03
0
50
100
150
200
250
300
350
400
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
dai
ly f
low
(cu
me
cs)
Probabilty
0
5
10
15
20
25
30
35
40
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
dai
ly f
low
(cu
mec
s)
probablity
46
4.2.3 Flood analysis
Table4.12: Flood Analysis 1970-1997 (1GD03)
YEAR Ranking m/n+1 % MAX
1984 1 0.034 3.4 37.14
1993 2 0.069 6.9 46.09
1976 3 0.103 10.3 50.54
1971 4 0.138 13.8 84.46
1981 5 0.172 17.2 110.05
1983 6 0.207 20.7 117.97
1992 7 0.241 24.1 120.97
1986 8 0.276 27.6 123.02
1991 9 0.31 31 123.48
1987 10 0.345 34.5 124.44
1980 11 0.379 37.9 125.92
1970 12 0.414 41.4 128.76
1978 13 0.448 44.8 136.65
1995 14 0.483 48.3 144.16
1973 15 0.517 51.7 148.96
1975 16 0.552 55.2 158.61
1974 17 0.586 58.6 167.57
1979 18 0.621 62.1 192.59
1985 19 0.655 65.5 197.39
1972 20 0.69 69 198.43
1977 21 0.724 72.4 217.52
1982 22 0.759 75.9 224.73
1994 23 0.793 79.3 277.54
1990 24 0.828 82.8 285.70
1996 25 0.862 86.2 320.12
1997 26 0.897 89.7 338.24
1989 27 0.931 93.1 338.55
1988 28 0.966 96.6 359.86
M.D.F-Maximum Daily Flows
From the graph plotted in Figure 4.14 in page 47, it can be observed that for 95% flood flow,
the flow will be 595 cumecs for a 20 year return period.
47
Figure4.14: Flood analysis curve for station 1GD03
48
4.2.4 Moving averages curves
Table4.13: Moving Average analysis for station 1GD03
YEAR T.A.F 1ST CUMULATIVE 2ND CUMULATIVE AVERAGE
1970 7242.10
1971 6048.09 13290.19
1972 4538.49 10586.58 23876.77 5969.19
1973 4628.20 9166.691 19753.27 4938.32
1974 5495.41 10123.61 19290.3 4822.58
1975 7288.73 12784.14 22907.75 5726.94
1976 2982.30 10271.03 23055.16 5763.79
1977 10023.34 13005.64 23276.67 5819.17
1978 9770.58 19793.92 32799.56 8199.89
1979 8389.88 18160.46 37954.38 9488.60
1980 3793.18 12183.06 30343.52 7585.88
1981 6776.43 10569.61 22752.68 5688.17
1982 6638.61 13415.04 23984.66 5996.16
1983 6166.15 12804.76 26219.8 6554.95
1984 1936.40 8102.55 20907.31 5226.83
1985 6240.57 8176.972 16279.52 4069.88
1986 2305.59 8546.158 16723.13 4180.78
1987 2799.69 5105.274 13651.43 3412.86
1988 11938.81 14738.49 19843.77 4960.94
1989 7528.26 19467.06 34205.55 8551.39
1990 9179.95 16708.2 36175.26 9043.82
1991 5639.08 14819.03 31527.23 7881.81
1992 5612.38 11251.46 26070.49 6517.62
1993 2909.14 8521.52 19772.98 4943.24
1994 8873.07 11782.21 20303.73 5075.93
1995 6556.30 15429.37 27211.58 6802.90
1996 11871.78 18428.09 33857.46 8464.36
1997 6187.61 18059.40 36487.49 9121.87
T.A.F-Total Annual Flow
The moving averages curve i.e. Figure 4.15, in page 49 shows that discharge at station 1GD03
has an increasing trend. It is expected since the rainfall trend was increasing as well.
49
Figure4.15: Moving averages curve for station 1GD03
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
1965 1970 1975 1980 1985 1990 1995 2000
AV
ERG
E ST
REA
M F
LOW
S(C
UM
ECS)
YEARS
50
4.2.5 Storage analysis
Table4.14: Cumulative flow for station 1GD03
PERIOD FLOW(cumecs) CUMULATIVE FLOW(cumecs)
Aug-86 249 249
Sep-86 167.8 416.8
Oct-86 79.6 496.4
Nov-86 70.2 566.6
Dec-86 59.8 626.4
Jan-87 44.5 670.9
Feb-87 49.7 720.6
Mar-87 216.3 936.9
Apr-87 121.5 1058.4
May-87 494.8 1553.2
Jun-87 928.6 2481.8
Jul-87 209.6 2691.4
Aug-87 152.8 2844.2
Sep-87 95 2939.2
Oct-87 71.3 3010.5
Nov-87 328.4 3338.9
Dec-87 87.1 3426
Jan-88 367.8 3793.8
Feb-88 70.3 3864.1
Mar-88 154.2 4018.3
51
Figure4.16: mass curve for station 1GD03
Assuming a demand of 240 cumecs per month, the storage required is 1000 cumecs per month
which translates to 86,400,000m3. The time taken to empty the reservoir if the water was to be
captured in the reservoir would be 8 months while the time taken to fill it would be 2 months.
0
500
1000
1500
2000
2500
3000
3500
4000
4500
cum
ula
tive
flo
w
citical period
52
CHAPTER FIVE
5.0 CONCLUSION
The main objective of this hydrological study was to analyze rainfall and stream flow in Nyando
catchment. The objectives set for this study were achieved. The following were the conclusions
drawn from the study;
The catchment experiences two heavy rainfall seasons: the long rains in March-May and
short rains vary between stations. The lowland station i.e. at Ahero Irrigation Research
Station receives short rains in the October-December months, while at Songhor Kaabirir
and Kericho District Office short rains are experienced in the July-September months.
The average rainfall of Nyando catchment is 1608mm per annum. Orographic rainfall on
the windward side of the Rift Valley highlands and conventional rainfall on the lowlands
closer to the shores of Lake Victoria.
The statistical analysis of rainfall revealed that the 95% precipitation was found to be
3250mm for station.8935001, 2320mm for station 9035003 and 1370 for station
9034086.
The moving averages curves indicated an increasing rainfall trend and consequently an
increasing stream flow trend as well, meaning that it’s likely to flood even in the future.
The flow duration curve for station 1GD03 indicated that 95% of the time, flow equaled
or exceeded 1.5 cumecs meaning that this region experiences a considerable amount of
flood flow. Droughts whereby there is no discharge in the Nyando River are rarely
experienced.
It was established that for 95% probability, flood flow would be 595 cumecs for a return
period of 20 years meaning the Nyando basin experiences heavy floods.
If a reservoir could be built to capture water for a demand of 240 cumecs per month,
then the storage required would be 86,400,000m3 and the time taken to fill the
reservoir would be 2 months and the time taken to empty it would be 8 months.
53
RECOMMENDATION
Nyando basin experiences heavy floods which could be catastrophic. Measures should
be taken to contain the floods such as building flood control reservoirs, building dykes
and offering education to the local people on better land use practices.
The flow in the Nyando River is quite considerable and hence offers potential for
economic activities such as hydropower production and irrigation. The government
should consider such investments which could boost the region’s economy considering
that Nyando District is poverty stricken.
With better data such as updated census counts, the Nyando population can be used to
establish a more accurate demand for water consumption. The data can hence be used
to build reservoirs for water consumption.
Most of the river gauging stations and rainfall stations are currently not operational and
therefore measures should be taken to maintain the existing stations and establish new
stations so as to avoid the cases of too much missing data.
54
REFERENCES
P. S. Khisa1 ,2,3, S. Uhlenbrook2,3, A. A. van Dam2, J. Wenninger2,3, A. van Griensven2 and M.
Abira -Full Length Research Paper-Ecohydrological characterization of the Nyando wetland,
Lake Victoria, Kenya: A State of System (SoS) analysis.
Peter Omondi Ocholla-Department of Hydrology University of Zululand -The impact of flooding
characteristics of the Nyando river on cotton cultivation in lower Kano plains in Nyando district,
western Kenya.
MWRMD. 2004. Ministry of Water Resources Management and Development-Strategy for
Flood Management for Lake Victoria Basin, Kenya.
Ponce (1989). Engineering Hydrology: Principles and Practices
Chow, ven Te, Maidment, David R. and May (1988). Applied Hydrology. New York. McGraw hill.
Chow, ven Te. Handbook of Applied Hydrology.
Wilson E.M (1990) 4th Edition ,Engineering Hydrology
Tim Davie- Fundamentals of Hydrology-Second edition.