Dereje, Hailu (PhD)Tatek, Worku2018-12-162023-11-112018-12-162023-11-112015-02http://etd.aau.edu.et/handle/12345678/15147Estimates of low flow statistics are required for a variety of water resource applications. At gauged river sites, the estimation of low flow statistics requires estimation of annual n-day minimum stream flows, low flow estimates, as determined by probabilistic modeling of observed data sequences, are commonly used to describe certain stream flow characteristics. Unfortunately, reliable low-flow estimates can be difficult to come by, particularly for gauging sites with short record lengths. The shortness of records leads to uncertainties not only in the selection of a distribution for modeling purposes but also in the estimation of the parameters of a chosen model. In flood frequency analysis, the common approach to mitigate some of these problems is through the regionalization of frequency behavior. The same general approach is applied here to the case of low-flow estimation, with the general intent of not only improving low-flow estimates but also illustrating the gains that might be attained in doing so. In this study low flow regionalization has been performed using three approaches: flow duration curves, base flow index and low flow frequency analysis. Low flow frequency analysis of Dedessa river basin have been carried out using 7-day annual minimum flow series extracted from the average daily stream flows observed at 10 stream flow gauging sites across Dedessa river basin. L- Moment ratio diagrams were used for identifying and grouping of stations in to hydrological homogeneous regions and hence the underlying statistical distribution. Accordingly, the basin was delineated in to two homogeneous regions. The homogeneity of the delineated regions was tested using the Cv-based and discordance tests. The goodness of fit test (Z-statistics) and the minimum standard error of estimates have been used for assessing the suitability of the selected distribution. Consequently, the Wakebay lower boundary distribution is found to be a suitable candidate for region one and the generalized extreme value distribution for region two. The method of probability weighted moments was considered as the best parameter estimation procedure as compared with the method of moments and the maximum likelihood method. Flow duration curves of 1, 7, 10, 30 days have been derived for 10 stations. The basins flow duration curves are characterized in to two homogeneous classes based on the characteristics shown on the right tail end of the basins flow duration curves. Base flow separation has been made by the standard method called the institute of hydrology method. Accordingly the base flow index is calculated and the basin is grouped in to three classes based on their range of BFI. Regression analyses were conducted on the delineated regions to predict the index low flows (mean annual 7-day minimum flow) for ungauged catchments using catchment characteristics. The multiple coefficients of determinations R 2 was used as a measure of the ability of the regression model to describe variations in the dependent variables. The value of R was found to be 0.997 for region one and 0.84 for region two. In addition the standardized low flow frequency curves which will be used for estimating low flow quantiles at ungauged catchments have been established for the two delineated regions using the standardized flow data.en-USFlow QuantilesUngauged River CatchmentsDedessa River BasinThesis