Daily rainfall forecast of Patna gauge station by using wavelet neural network

Abstract

Rainfall is one of the most significant parameters in a hydrological model, several models have been developed to analyze and predict the rainfall forecast. In recent years, wavelet techniques have been widely applied to various water resources research because of their time-frequency representation. In this paper an attempt has been made to find an alternative method for rainfall prediction by combining the wavelet technique with Artificial Neural Network (ANN). The wavelet and ANN models have been applied to daily rainfall data series of IMD Patna rain gauge station. The calibration and validation performance of the models is evaluated with appropriate statistical methods. The results of daily rainfall series modeling indicate that the performances of wavelet models are more effective than the ANN models.