Low Flow Analysis of Regionalization Abaya –Chamo Sub Basin, Ethiopia
MelakuSisayAbebe,HongShengQiu
School of transportation, Wuhan University of Technology, 430063, Wuhan Hubei China
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Abstract
Ethiopia, is located in horn of theAfrica. The Abaya-Chamo basin mainly comprises the Rift valley floor islocated insouthern region of the country.Regional low flow frequency analysis has been studied in Abaya-Chamo sub basin in detail. L-moment ratio diagram has been plotted for theoreticalfrequency distribution using L moments Statistical value Kurtosis (T3) and Skeweness (T4). Standardized sample data statistical values kurtosis (T3) and Skeweness (T4) for each stations plotted on the same paper view. Those points which fall in nearby to theoretical frequency distribution function has preliminary grouped as homogeneous sub basin region. The homogeneous region of L-moment ratio values which fall at nearby the theortical frequency distribution leads to obtain the regional candidate frequency distributions. The best fitted frequency distributions have been selected through employing goodness of fit measure and standard error. Those best fitted distribution of the four region are GLL,GPa,GEVand,Wakeby.FORTRAN Program employed to calculate regionallow flow quintile which is called the growth curve. Finally the regional low frequency curve has been plotted by regional growth curve versus return period. Low flow quintile of project sites and catchment has been calculated from low flow frequency curves and low flow index.
Keywords: Homogeneous, L-moment ratio, Growth curve, and FORTRAN program.
1. Introduction
In early days of application of hydrology numerical techniques in the field of hydrology, low river flow stream were basically carried out to analyze its ability to supply a particular water demand. The main categories of water demand were including domestic agriculture and industrial. If it was found that the low flow of the river or stream was insufficient to supply a demand, further analysis were carried out to ascertain how much quantity of water to be stored in order to meet the demand.Even in the present context, low flow studies remain paramount important for the supplying of such direct demands, either directly or by a suitable storage.
Low flow frequency analysis is used to evaluate the ability of stream or river to meet specified flow requirement at particular location in basin and sub basin. The frequency analysis can be providing an indication of adequacy natural flow to meet a given demand with stated probability experiencing shortage. Additional frequency analysis can indicate the amount of storage that would be required to meet a given demand, again with stated probability of being deficient. The planning and designof hydroelectric power plants, determination of minimum flow requirement for water quality and/or fish and wild life and design of water storage project can benefit from low frequency analysis.
Regional low flow frequency analysis is one of the practical means providing low flow information at sites with little or no local data. In the regional approach, available low flow data series from hydrological homogenous region are pooled in dimensionless form and a frequency distribution is fitted to combined data. However, the main problem of in low frequency analysis is the determination of probability distribution that can provide a curve that defines the regional average relation between standardized flow magnitudes (QT) and return period (T)).A homogenous region is hydrology unit which has site having a similar low flow characteristics and therefore have the same standardized frequency distribution and parameters. Low flow frequency analysis is used toestimate low flow quintile (Q) at the interest of site or project location. The low flow event being estimated is expressed by its return period (T).The estimation of flow regimes at un-gauged sites can be achieved by transfer of statistics derived from homogeneous gauged catchments using regionalization procedures. The term regionalization in hydrology refers to grouping catchments in to homogenous regions.
2. Background and Literature Review
Methods based on L-moments have been recommended for hydrologic regional frequency analysis (Hosking, Wallis, 1993).L-moment ratio (Lcv,Lsk,Lkr) analogous for conventional moment ratio
(coefficient of variation, skewness, and kurtosis) were used to test for frequency distribution homogeneity of Hutchinson’s region and to test other group of catchment based on catchment characteristics best region or group dimensionless frequency curves were then estimated for each group of catchments.(C.P.pearson,1995).In General there is no more information and studies in low flow frequency analysis.
3. Problem Statement
Due to increased high population pressure and food insecurity in the country, it is envisaged that there would be huge demand for water resources by the farmers, investors and as the matter of policy priority by the government at all level. This will undoubtedly create huge demand on the water resources particularly during lean season. This extra demand on the river may create undesirable environmental as well as upstream downstream conflict
Low flow estimates are vital for planning water supplies, water quality management issuing and renewing of waste disposal permits, hydropower, and the impact prolonged drought on aquatic ecosystems. Similarly estimation of low flow is also important for small scale irrigation projects that contribute significantly to poverty alleviation by means of increased crop production and generation of rural employment. So analysis of low flows would provide an accurate understanding of the demand that may safely be placed on a stream flow. (V.T Maidment, 1988)
Abaya- Chamo river sub basin have a good potential in water resources development including hydropower, small scale irrigation, water supply, aquatic ecosystem and etc. But nothing have been done in the low flow characteristics of the Abaya- Chamo river sub basin so far since little . Also the volume and duration of dependable base flow is not quantified. Most of all the availability and quality of information is not adequate, so further development of any water resource project within the region is difficult and unreliable unless and otherwise the low flow characteristics is well known. Therefore the objective of this study is to analyze and characterize the low flow in Abaya-Chamo sub basin to provide the necessary information about the low flow of the sub basin.
4. Research Methodology
Ethiopiais a water fall which is located in theHorn of Africa .The Abaya-Chamo sub basin mainly comprises the Rift valley floor within the drainage basin is located southern region of the country.
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Fig.1. Study area
Monthly rain fall of eleven stations which are located within Abaya Chamo sub basin have been collected from The National Meteorological and daily flow data have been collected with varying length of record periods of 17 operational gauging stations from Ministry of Water Resource. Annual daily minimum flow have been used for regionalization of low flows.
First of this all collected data has been checking of adequacy consistency, independency, and randomness of the data of the sample to make shure the accuracy available sample data L-moment ratio diagram has been plotted for parent frequency distribution using L moments Statistical value Kurtosis (T3) and Skeweness (T4). Standardized sample data statistical values kurtosis (T3) and Skewedness (T4) for each stations plotted on the same paper view. Those points L-moment ratio diagram of the standardized sample data which fall in nearby parent frequency distribution function have preliminary grouped as homogeneous sub-catchment or sub basin region. Similarly regional frequency distributions have been identified form the homogenous region standardized sample data by drawing L moments Statistical value Kurtosis (T3) and Skewedness (T4).The homogeneous L-moment ratio values which fall at nearby the parent frequency distribution leads to obtain the regional candidate frequency distributions. The best fitted frequency distribution has been selected through employing goodness of fit measure and standard error. Numerical low flow quintile equations have been formulated based on regional frequency distribution function to estimate the regional low flow quintiles. The numerical low flow quintile equation and standardized annual low flow from each homogeneous region use as input in the FORTRAN Program to calculate regional low flow quintile with different period of exceedance is called the growth curve. Finally the regional low frequency curve has been plotted by regional growth curve versus a return period. Low flow quintile of project sites and catchment have been calculated from low flow frequency curves and low flow index. Low flow regression model have also employed to calculate low flow quintiles for ungagged site or little information.
5. Research Result and Discussion
5.1 Identification of Homogeneous region.
During this study a combination of site statistics using L-moments ratio and site Characteristics including drainage catchments area, Climate, topography, land use/ land cover and soil have been considered.L-moment ratio diagram has been plotted for all parent frequency distribution using L moments Statistical value Kurtosis (T3) and Skeweness (T4) and standardized sample data statistical values kurtosis (T3) and Skewedness (T4). Stations which fall in the same distribution function havepreliminary grouped as homogeneous sub-catchment or sub basin region.Based on the regionalization studies, the Abaya-Chamo homogeneous regions have been established using the Arc-GIS as show in the figure 2b.
Fig.2a Loment ratio Diagram of theoretical frequency Distribution and gaging stations
Fig.2b. Homogeneous Region
5.2Choice of Regional Frequency Distribution
After testing Homogeneity of the stations, Candidate distributions have been selected for each region using L- moment Ratio diagram and Catchments characteristics. The L moment ratio diagrams are based on relationship between the L moment ratios. A diagram based on T3 verses T4, can be used to identify appropriate distributions. The best parent distribution is the one that the average value of the point (T3, T4) of all stations with in the region gets close to one of the plotted LMRD of the parent distribution. The result obtained is as shown on the fig below.
Fig.3.L-Moment ratio Diagram
Table1.Regional Frequency Distribution
Region name / DistributionOne / GLL(Generalized logistic)
Two / GPa(generalized pareto)
Three / GEV(generalized extreme Value)
Four / Wakeby
5.3Regional Low Flow Growth Curve
Regional frequency distribution has been determined which is the best fit for the specific homogeneous region so far. Numerical low flow quintile has been formulated based on regional frequency distribution function to estimate the regional low flow quintiles. Like example using frequency distribution function use to develop estimating low flow quintile for different period of exceedance.
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Similarly the low flow regional quintile numerical equation has been developed through formulating from regional frequency distribution function for each homogeneous regiona. Since the analysis is very long and complex to calculate regional flow quintile for each homogeneous region, FORTRAN program has been written to obtain the result of regional low flow quintile for different period of exceedance. Standardized annual low flow for each gauge station inside the homogeneous region and modified low flow quintile numerical equation have been employed in FORTRAN Program to calculate regional low flow quintile for different period of exceedance. Therefore regional low flow quintile for each best fitted regional frequency distribution has been computed for each homogeneous region which is equal to the growth curve. Finally the regional low frequency curve has been plot by regional growth curve (standardized flow) versus a return period T as show in the figure 4.
Fig 4. Regional low flow frequency growth curve.
5.4Estimation of Low Flow Index for Ungauged Sites
It is suggested that the low flow frequency has been used by engineers and hydrologist during planning and pre-feasibility studies in areas where data are scarce (C. Cunnane, 1996).Using Index flow Procedure, regional growth curve (a dimensionless quintile function), which is identical for homogeneous region a. Each homogeneous region has own fitted regional frequency distribution. Based on fitted regional frequency distribution low flow Quintile for each homogeneous region has been computed to obtain the regional growth curve which help to develop the low flow frequency curve. This regional low flow quintile value employed to the following equation to compute the specific project sites low flow quintile for different period of exceedance.
Qij=
Where uij mean of regional frequency distribution
qij = Regional growth curve
Qij = Quintile function.
Conclusion and Recommendation.
Missed data and extension records have been filled by developing correlation between the station with missed data and any of nearby station which ever gives good correlation for common data period.The output have been employed base flow separation but for regional frequency analysis not missed recorded year data have been used to reduce disturbance of L moment ratio. Daily annual minimum data have been employed for regional low flow analysis. Before conducting regional frequency analysis, stationary and independence of data has been analyzed using Wald-Wolfowitz (W-W) test.
Four homogeneous regions have been delineated through Loments ratio for those stations falls on the same parent frequency distribution. Regional frequency distribution has been selected for the homogeneous region using L-moment ratio and then goodness of fit has been computed to check robustness. GLL(Generalized logistic), GPa( Generalized Pareto), GEV( Generalized Extrem Value), and Wake by have been selected regional fitted distribution for Region One, Region Two , Region Three and Region four respectively. PWM has smallest error for parameter estimation for all regions. Finally the regional frequency curve has been drawn for each region using regional growth curve versus return period .Regional growth curve is very important in planning, pre-feasibility studies and design water resources project. Besides Predicative regression model has been developed for each homogeneous region based on rational analysis of the problem and catchments characteristics to estimate low flow for ungagged catchments and those comprises limited gauging stations.
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