Regional Flood Frequency Analysis; A case of Genale Sub-Basin, Genale Dawa River Basin, Ethiopia

Abstract

Floods are common natural hazards, and they cause great economic damage and a great loss of human life. The design of hydraulic structures requires the estimation of flood quantiles. However, the quantification of these quantiles in data-scarce regions has been a continuing challenge in hydrologic design. In many developing countries, records of flood data are rarely available. Regionalization techniques are essential to overcome the scarcity of hydrological data and provide regional flood information. The overall goal of this study is to develop a regional flood frequency analysis for the Genale Sub-Basin. The Index flood method based on the L-moment was chosen for this study. The annual maximum series of 5 gauging stations were selected to conduct regional flood frequency analysis. The collected data was evaluated and tested for data sufficiency, stationary, independence, homogeneity, randomness, and outliers. This test revealed that the data met the basic assumptions of hydrological data. The identification of homogeneous regions was performed based on flood statics. The region has shown satisfactory results in spatial homogeneity tests. Several candidate probability distributions have been applied. The parameters obtained from the Kolmogorov–Smirnov and chi-square tests using HEC-SSP helped to select the best distribution. The result shows that the Gumbel distribution was identified as a robust regional probability distribution for the study area. From the probability-probability and discharge discharge plots, the plot points tend to lie reasonably along and close to a straight line, and this provides validation of Gumbel’s distribution for accurately estimating flood flow for different return periods. The flood discharge of specific recurrence intervals was computed, and regional growth curves were developed for the regions by using the L-moment parameter estimation method. The standardize flood corresponding to return period such as 2, 2.33, 5, 10, 20, 50, 100,200,500,1000,5000 and10,000 were 0.964,1.000,1.155,1.281,1.402,1.558,1.675,1.792,1.946, 2.063, 2.333 and 2.450 respectively. Lastly, the index flood estimation model Q2.33=0.521A0.6819 was developed for the region by regression analysis with a coefficient of determination of 0.9557 for the estimation of index flood from the ungagged watershed. The parameters that affect the catchment features of the basin have to be integrated using multiple integration techniques to obtain a better estimation of the index flood of the ungauged catchment.