Simultaneous hydrological prediction at multiple gauging stations using the NARX network for Kemaman catchment, Terengganu, Malaysia

This paper presents a neural network model capable of catchment-wide simultaneous prediction of river stages at multiple gauging stations. Thirteen meteorological parameters are considered in the input, which includes rainfall, temperature, mean relative humidity and evaporation. The NARX model is t...

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Bibliographic Details
Main Authors:	Lee, W.-K (Author), Tuan Resdi, T.A (Author)
Format:	Article
Language:	English
Published:	Taylor and Francis Ltd. 2016
Subjects:	artificial neural network backwater Backwater effects basin analysis catchment Catchments computer simulation Field observations Floods Forecasting Gauging stations Hydrological prediction hydrological regime Input and outputs Kemaman Basin Kemaman catchment Malaysia Meteorological parameters multiple gauging stations NARX network Neural network model numerical model one-step-ahead prediction prediction river flow Runoff Terengganu tidal cycle Time delay West Malaysia
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by Lee, WK, Resdi, TAT
Published 2016

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Simultaneous hydrological prediction at multiple gauging stations using the NARX network for Kemaman catchment, Terengganu, Malaysia

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