Published Article / Early indication of possible drought can help in developing suitable drought mitigation strategies and measures in advance. Therefore, drought forecasting plays an important role in the planning and management of water resource in such circumstances. In this study, a non-linear streamflow forecasting model was developed using Artificial Neural Network (ANN) modeling technique at the Melka Sedi stream gauging station, Ethiopia, with adequate lead times. The available data was divided into two independent sets using a split sampling tool of the neural network software. The first data set was used for training and the second data set, which is normally about one fourth of the total available data, was used for testing the model. A one year data was set aside for validating the ANN model. The streamflow predicted using the model on weekly time step compared favorably with the measured streamflow data (R2 = 75%) during the validation period. Application of the model in assessing appropriate agricultural water management strategies for a large-scale irrigation scheme in the Awash River Basin, Ethiopia, has already been considered for publication in a referred journal.

The growing pressure on the world‘s fresh water resources is enforced by population growth that leads to conflicts between demands for different purposes. A main concern on water use is the conflict between the environment and other purposes like hydropower, irrigation for agriculture and domestic and industry water supply, where total flows are diverted without releasing water for ecological conservation. As a consequence, some of the common problems related to water faced by many countries are shortage, quality deterioration and flood impacts. Hence, utilization of integrated water resources management in a single system, which is built up by river basin, is an optimum way to handle the question of water. However, in many areas, when planning for balancing water demands major gaps exist on baseline knowledge of water resources. In order to bridge these gaps, hydro-logical models are among the available tools used to acquire adequate understanding of the characteristics of the river basin. Apart from forecasting and predicting the quantity and quality of water for decision makers, some models could also help in predicting the impacts of natural and anthropogenic changes on water resources and also in quantifying the spatial and temporal availability of the resources. However, main challenges lie in choosing and utilizing these models for a specific basin and managerial plan. In this study, an analysis of the different types of models and application of a selected model to characterize the Awash River basin, located in Ethiopia, is presented. The results from the modeling procedure and the performance of the model are discussed. The different possible sources of uncertainties in the modeling process are also discussed. The results indicate dissimilar predictions in using different methods; hence proper care must be taken in selecting and employing available methods for a specific watershed prior to presenting the results to decision makers. / QC 20110516