An Assessment Of predictive Accuracy For Regional flood frequancy distribution Estimation Methods On Awash River Basins

Abstract

The most important face of flood from water resources improvement and management part is its returning interfering with interventions and actions made by people. The loss of life and damage can be pictured in terms of economic dead and risk to human life. The main concern is here to significantly analyze the occurrence and amount of the flooding intervention. The main objectives of this study includes screening of time series data, derivation of frequency curve, identifying the best-fit statistical distributions to the data of each gauges, finding a suitable parameter estimation method for each stations, identification homogeneous region and establishing of regional frequency curves for homogeneous regions of Awash river basin. An assessment of predictive accuracy for regional flood frequency distributions and analysis estimation methods has been the backbone of water resources project planning, design of any structures and the economic analysis of flood control projects. The l-moment and easy fit software was employed for selection of best-fit distributions and methods of parameters estimation for a station. Goodness-of-Fit tests such as Chi-square, Anderson-Darling and Kolmogorov–Smirnov are applied for checking the satisfactoriness of fitting of probability distributions to the recorded data. Kolmogorov–Smirnov test is used for the choice of a suitable distribution for estimation of maximum flood discharge. The performance of regional General Extreme value, General Pareto and Uniform distributions are found to be highly satisfactory and widely applied in this paper, however this paper reveals that the General Extreme Value distribution is better appropriate amongst seven distributions used in the estimation of maximum flood discharge at Awash River basins. In GEV most quantile estimation offer almost balanced estimates of the percentile of interest, but the uniform distribution gets its name from the fact that the probabilities for all outcomes are the same. The basin was delineated in to five homogeneous regions; more attention is given to at-site homogeneity test to group stations in the Awash basin in to five regions after checking them for the consistency and independency testes and estimation of standard error. All regions have shown satisfactory results for homogeneity tests. Consequently, a flood frequency curve was developed at 5% and 95% of confidence limit with different return period for each region