STAGE-DISCHARGE MODELING USING SUPPORT VECTOR MACHINES

Establishment of rating curves are often required by the hydrologists for flow estimates in the streams, rivers etc. Measurement of discharge in a river is a time-consuming, expensive, and difficult process, and the conventional approach of regression analysis of stage-discharge relation does not provide encouraging results especially during the floods. Present study is aimed at the application of support vector machines (SVMs) based algorithm for modelling stage-discharge relation including the hysteresis effect. A data set of two discharge-measuring stations located on two Indian rivers has been used for analysis in the present study. A back propagation neural network model was employed in order to compare the performance of the results based on support vector machines based modelling technique. The outcome of the study suggests that the support vector machines works well for both the data sets and produce promising results in comparison to the neural network technique. Finally, the results also suggest the suitability of SVMs algorithm in predicting the looped rating curve having hysteresis effect.

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