Streamflow Forecasting Using Neuro-Fuzzy Inference System

Abstract

This paper presents combined approaches of neural network analysis and fuzzy inference techniques to the problem of streamflow forecasting. In the present study, one step ahead forecasts are made for ten-daily flows, which are mostly required for short term operational planning of multipurpose reservoirs. A Neuro-Fuzzy model is developed to forecast ten-daily flows into the Hirakud reservoir on River Mahanadi in the state of Orissa. The input variables influencing the flows into the reservoir are identified using correlation analysis. The performance of the model is evaluated using various performance indicators and the results are presented. The results indicate that the Neuro-Fuzzy modeling technique is able to model the streamflow process with reasonable accuracy and can be used for real time forecasting of streamflows.