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

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

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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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