Regional Low Flow Frequency Analysis based on Cluster Analysis and the GLS regression modeling for Ungauged Sites (The Case of Omo-Gibe River Basin, Ethiopia)

Abstract

Water resource development planning is usually referred as the process to define how to utilize the available water resource to meet the desired objectives. In order to compensate for the scarcity of data for the available water resource, regionalization is found to be one of the best methods of transferring information from the gauged station to ungauged sites. This study analyses regional low flow frequency for Omo-Gibe River Basin. Rapid water resources development and population growth in this basin have caused serious concerns over the adequacy of the quantity and quality of water withdrawn from the Rivers. Information on the magnitude and frequency of low flows in the basin is needed for planning of water resources at present and in the near future. Hydrological homogeneous low flow regions are formed by the cluster analysis of site characteristics, using the hierarchical clustering and Ward's method. Statistical tests for regional homogeneity are utilized, by Discordancy and Heterogeneity measure tests. In compliance with results of the tests, the area of the Omo-Gibe River Basin has been divided into four homogeneous regions. The findings are supported by Monte Carlo simulations proposed to evaluate stability of the test results and the uncertainty of estimates. The L-moment and LL-moment method is used to analyses the regional frequency of low flows, since recent studies have shown that both methods are superior to other methods that have been used previously. In this study, frequency analysis of low flows using 7-day minimum low flow series is conducted using six distributions: Generalized logistic (GLOG), Generalized extreme value (GEY), Pearson type III (P-III), Generalized Pareto (GPAR), Weibull (WEI) and Power (PR) distributions. Flow model, providing a simple and effective method for estimation of low flows of desired return periods for ungauged catchments. Generally, Physiographic and drainage characteristics are related to low flow characteristics of watersheds to identify and delineate homogeneous pools and to derive best regression models for ungauged sites.