Hydrologic Simulations with Artificial Neural Networks

Authors:
Qin Ju;Zhongbo Yu;Zhenchun Hao;Changjun Zhu;Dedong Liu
Affiliations:
Hohai University, China;University of Las Vegas, Nevada, USA;Hohai University, China;Hohai University, China;Hohai University, China
Venue:
ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 02
Year:
2007

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Division-based rainfall-runoff simulations with BP neural networks and Xinanjiang model

Neurocomputing

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Abstract

A back-propagation (BP) neural networks model was used for simulating daily streamflows in the upper area of Nangao Reservoir at Shanwei City, Guangdong Province, China. Approaches and techniques of applying the BP model in runoff simulation are presented in this paper. A comparison of the BP model to the Xinanjiang model was also conducted to evaluate the performance of the BP model. The simulated results indicate a satisfactory performance in the streamflow forecasting with the BP model. The study concludes that the BP model has the high practicability and good accuracy for describing complex nonlinear hydrologic processes.