Hydrological Models for Cidanau Watershed

Abstract

Hydrological models are necessary in assessing water resources and valuable tool for water resources management. This paper describes applications of Tank model, storage function model and artificial neural networks (ANN) for Cidanau watershed in Indonesia. The Tank model consists of a series of 4 tanks and 5 outflows with 12 independent parameters. Storage function model has 3 parameters. Genetic algorithm (GA) was used for finding the optimum parameters of the tank model and the storage function model. Back-propagation was used in the learning rule of ANN. A series of daily rainfall, evapotranspiration and discharge data for 6 years (1996-2001) from Cidanau watershed was used. The accuracy is evaluated by statistical performance index, the shape of hydrographs and the flood peaks. The results show that tank model, storage function model and ANN are successful in predicting watershed discharge in Cidanau watershed. Comparison of the accuracy of ANN, Tank model and storage function model show that ANN is better than the other models. These hydrological models have been developed in form of application program under Windows and applicable to use in other watershed.