Homogeneity Testing for Peak Discharge in Catchments in the Equatorial Nile Basins

Journal of Kenya Meteorological Society


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Volume 3:2

Homogeneity Testing for Peak Discharge in Catchments in the Equatorial Nile Basins

Opere, A.O.*, Mkhandi, S.**, Willems, P.***

* Department of Meteorology, University of Nairobi, Kenya, ** Department of water resources Engineering, University of Dar-Es-Salaam, Tanzania, ***Hydraulics Laboratory, University of Leuven, Belgium


Alfred Opere,

University of Nairobi,

P.O. Box 30197—00100 GPO, Nairobi

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(Manuscript received 12 March 2008, in final form 21 April 2009)


Regional flood frequency analysis deals with the identification of homogeneous regions of which the distribution of peak flows from sites from in such a region are similar. Once a homogenous region is identified, standardized data from different sites within the region can be pooled together and a single frequency curve applicable to the region can be derived. The data used in this study includes Annual Maximum Annual Flood (MAF) series of daily discharges from 28 river gauging stations located in the Nile Equatorial Basin. These data were quality controlled using single mass analysis, and time series plots to check any inconsistencies before the MAF series were extracted. The regional homogeneity testing was done independently for stations in Kenya and Tanzania because of the large variations in the length of records. The methods used for regional homogeneity testing are the heterogeneity measure statistics, the use of L-moments diagrams and at-site regional analysis. L-moments are defined as linear combinations of probability weighted moments (PWM). L-moment ratio diagrams are based on simple measure of the dispersion of the sample L-moments such as linear combination of; the coefficient of variation (L-CV), the skewness (L-CS) and kurtosis (L-CK). In this case the method of assessing heterogeneity is based on visual assessment of the dispersion of the atsite L-moments of the observed and simulated region. Heterogeneity statistics are also computed on the basis of L-moment ratios. The regional analysis approach, used with Tanzanian data, is based on the empirical distributions determined for all the sites within the region. The average of the empirical distributions is determined to represent the frequency curve for the region. Based on the Quantile-Quantile (Q-Q) plots, Extreme Value Type I(EV1) was the selected theoretical distribution used to derive the regional frequency curve for the Tanzania data using the method of PWM to estimate the parameters. The regional frequency curve in this case is derived by regional averaging of dimensionless at-site order statistics. The results of the study indicated that the stations in the Kenyan part of the basin can be considered to be moderately heterogeneous and cannot entirely be represented by a single distribution in regional analysis. The L-moment ratio diagrams for the observed and simulated data show some dissimilarity while the absolute value of the heterogeneity measure statistics is 1.25. The result of regional analysis based on empirical distributions grouped together the Tanzanian stations into relatively homogeneous region.

Keywords: L-moment ratios, homogeneity grouping, discordancy measure, heterogeneity measure, Quantile-Quantile (Q-Q) plots

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