Stream Flow Simulation by Hydrological and Meteorological Parameters using Neural Network (RBF): Babolrud Basin-Iran

It is of great economic prominence to estimate the flow rate of stream due to itsinfluence on water resource management. There are several ways to calculate theoutput runoff of a basin, each of which has its own advantages and disadvantages.Recently, Artificial Neural Network (ANN) has attracted scientists’ interest as oneof the methods of dynamic systems analysis in a variety of hydrology engineeringfields. The present study uses MATLAB software package for analysis in whichthe model is fed with the hydrometrical data and monthly temperature of Babolrudbasin in gauging stations, namely, Qrantalaar and Koshtargah, and flow rate ofhydrometric station on the Babolrud River within a statistical period of 33 years,9128-8295 .The results of this modeling showed that the ANN would accuratelyestimate the flow rate of the Babolrud River.

Keywords:

Artificial Neural Network , Meteorological Parameters , RBF