Downstream flow top width prediction in a river system

Abstract

ANFIS, ARIMA and Hybrid Multiple Inflows Muskingum models (HMIM) were applied to simulate and forecast downstream discharge and flow top widths in a river system. The ANFIS model works on a set of linguistic rules while the ARIMA model uses a set of past values to predict the next value in a time series. The HMIM model assumes a powerlaw relationship between water discharge and flow top width at a section. The models were used to simulate and forecast discharge and flow top width at a downstream section in the Barak River system in India. Flow top widths corresponding to different flow depths at the downstream section were estimated using a digital elevation model (DEM). The parameters in the hybrid model were estimated by applying Non-dominated Sorting Genetic Algorithm II (NSGA-II). The study shows that the power-law relationship involving section characteristics can describe the top width versus discharge relationship for a section. The models allow direct estimation of the downstream flow top width on the basis of upstream flow variables.

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