Regional Flood Frequency Analysis: A Case Study on Genale-Dawa River Basin, Ethiopia

Abstract

Determining the magnitude and frequency of floods for any hydrologically analogous region affords vigorous information in planning, designing, economic evaluation of flood protection and management of various types of water resources projects. The necessity of using this regional information arises from the need to improve estimates. It is due to the fact floods represent the most disastrous natural event causing several damages to enormous economic and life losses in the study area. However, the estimation of flood values with high return periods for a site of interest poses a great challenge due to the paucity of data. To analyze this event, future information on the hydrology of water resources and its impact has to be significantly studied. Thus, the main objective of this study was to perform appropriate regional flood frequency analysis on Genale-Dawa River Basin of Ethiopia. To achieve this, based on data from 16 stream gauged sites, three hydrological homogeneous subregions were defined and delineated based on L-moment homogeneity tests, namely Region-A, Region-B and Region-C. A delineation of homogeneous regions was accomplished using ArcGIS10.4.1. The delineated regions were covered 32.708, 48.328 and 18.963% of Region-A, Region-B and Region-C respectively. Discordancy of regional data of the L-moment statistics was identified using Matlab2017a. All regions have shown satisfactory results for discordance measures and homogeneity tests. For the regions, best-fit distributions were selected. L-moment ratio diagrams and goodness of fit tests with the help of Easy Fit Statistical Software were used to select best-fit probability distributions. The performances of the distributions were evaluated using Kolmogorov Smirnov, Anderson-Darling and Chi-Squared goodness-of-tests. After three goodness of fit tests were carried out and results compared, generalized extreme value and generalized Pareto distributions were identified as suitable distributions for modeling accurate annual maximum flows in the basin. Based on best-fit distributions for the three regions, regional flood frequency curves were constructed and peak flood discharge predicted for the return periods of 2-10,000 years. The derived flood frequency curves at a given confidence limit of 95% and 5%, suggested that how important engineering decisions and actions such as design and operation of the water resources project have to be undertaken. As a result of this, statistical analysis of gauged sites was revealed an acceptable method of regionalization. Henceforth, the study can be further extended into flood hazard, risk and inundation mapping of identified regions of the study area