Daily Rainfall-Runoff Modelling of Upper Awash Sub Basin Using Conceptual Rainfall Run off Models
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Date
2010-12
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Addis Ababa
Abstract
Hydro-meteorological data are very indispensable for the assessment and development of water resource. Upper Awash (UA), part of Awash River Basin, is densely populated and large population growth as well as the expansion of development activities and large farms such as flower farms in the region is expected to put further pressure on the water and associated resources of the area. Moreover, every hydrological process in the upper Awash has effect on the development activities in the downstream of the basin which calls for huge water resource planning and management activities. In this study, a daily rainfall- runoff modeling which is very helpful to further strengthen assessment, planning and management of water resource in the basin was conducted for selected three catchments of Upper Awash Sub Basin using two models namely AWBM and SMAR models among five lumped conceptual models nested in rainfall-Runoff library.
Automatic calibration and verification of the models were performed using Genetic Algorithm optimization method together with Nash Sutcliffe criteria and runoff difference as primary and secondary objectives respectively. In connection with this, flow generation, model parameter determination, a comparison of observed and simulated flow as well as comparison of performance of the two models were conducted. The quality of fit between the observed and simulated flow is judged by reviewing plots of the hydrographs. Comparison of the observed and computed flows reveals that except for the extreme peak flows the medium flow and low flows are generally modeled quite satisfactorily. Further more, performance of the models is assessed by using Nash Sutcliffe criteria and comparing the annual total flow volume and the maximum peak flows. Both AWBM and SMAR models predict the flows fairly well with overall Nash Sutcliffe criteria of 0.6 to 0.85 for both calibration and verification periods except for Mojo catchment. As far as the performance of the two models concerned, AWBM gives better results as compared to SMAR model for selected catchments. In addition, Model sensitivity analysis was undertaken to analyze the sensitivity of a particular model parameter with regard to a selected objective function and subsequently the most sensitive parameters for the two models were determined.
Finally, based on the results obtained the necessary conclusion and Recommendation were drawn. Generally, conceptual models have given encouraging results in this sub basin but further detail work is required verify the performance of the models under strict quality data situation.
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Hydro-meteorological data