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.
