Abstract:
Artificial neural network (ANN) is an efficient and useful technique and gaining popularity in hydrological modeling and forecasting. This paper presents the application of ANNs to hydrologic time series modeling, and is illustrated by an application to model the monthly reservoir inflow of Gandhi Sagar reservoir. The advantage of the ANN method is that it does not require the artificial neural network model structure to be known a priori, in contrast to most of the time series modeling techniques. The results showed that the ANN forecasted reservoir inflow series preserves the statistical properties of the original inflow series. The model also showed good performance in terms of various statistical indices. The results are highly promising.
