Prediction of One-Day Ahead Flood-Levels of Kosi River Using Neural Networks

This paper is an attempt to predict one-day ahead flood levels of a river using Neural Networks (NNs), when only available records are flood levels of previous days. The Basua of Kosi river, India, is selected as the focus site. Several NNs are constructed and floods are forecasted. The results found that the feed forward back propagation network with input layer consisting of past two days’ flood levels and the hidden layer with four neurons to be the best performing NN model for forecasting the current flood level. The same datasets were utilized for prediction of flood levels from the five developed Autoregression models (ARs). The predicted results of flood levels by NNs are very satisfactory and acceptable as compared to ARs and seems to be a good alternative for flood forecasting