OJMH  Vol.3 No.1 , January 2013
Streamflow Decomposition Based Integrated ANN Model

The prediction of riverflows requires the understanding of rainfall-runoff process which is highly nonlinear, dynamic and complex in nature. In this research streamflow decomposition based integrated ANN (SD-ANN) model is developed to improve the efficacy rather than using a single ANN model for the flow hydrograph. The streamflows are decomposed into two states namely 1) the rise state and 2) the fall state. The rainfall-runoff data obtained from the Kolar River basin is used to test the efficacy of the proposed model when compared to feed-forward ANN model (FF-ANN). The results obtained in this study indicate that the proposed SD-ANN model outperforms the single ANN model in terms of both the statistical indices and the prediction of high flows.

Cite this paper
N. Bhatia, L. Sharma, S. Srivastava, N. Katyal and R. Srivastav, "Streamflow Decomposition Based Integrated ANN Model," Open Journal of Modern Hydrology, Vol. 3 No. 1, 2013, pp. 15-19. doi: 10.4236/ojmh.2013.31003.

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