RAINFALL-RUNOFF MODEL FOR SUNGAI BEDUP BASIN USING ARTIFICIAL NEURAL NETWORK - Mah, Yau Seng (Universiti Malaysia Sarawak, (UNIMAS), 2003)
A relatively new tool, artificial neural network (ANN), was applied to simulate the runoff at a river section. A catchment, Sungai Bedup basin of Samarahan division, Sarawak with a drainage area of about 47.77 km2 was considered in the study. The rainfall and river flow data of 2 years (1995 and 1998) were used as the input and target to train the neural networks. The trained model was used to predict the flow of the year 1999. Different combinations of variables and parameters have been investigated to find the best forecasting model. Results from both training and testing simulation showed a high degree of agreement between the simulated and the measured river flow. A good fit, regression analysis coefficient, R2, over 0.9 and 0.8 were obtained from the training and testing simulations, respectively.