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• Published Subscription 30 Mar 2019

  Radial Basis Function Neural Networks for Rainfall-Runoff Modeling

  By K. S Kasiviswanathan

  Abstract: Rainfall-runoff process is purely nonlinear and varies spatially as well as temporally. Any hydrological model requires many parameters which represent different components of the process. Availability of all the parameters is difficult for any catchment and probabilistic generation of such type of data is impossible. Under such circumstances, artificial neural networks (ANNs) have proven to be a better tool to model the rainfall-runoff process with minimum available data. The present …

  Published in Journal of Water Resource Engineering and Management · Vol. 1, Issue 2, 2014 · pp. 11–18 Read article →