Authors: Barkha Chaplot; Prashant Birbal
Addresses: Department of Geography, M.J.K. College, Bettiah, Babasaheb Bhimrao Ambedkar Bihar University, Muzaffarpur, India ' Department of Civil and Environmental Engineering, University of the West Indies, Trinidad and Tobago
Abstract: Accurate forecasting of river discharge is essential for the efficient operation of water resources systems. Therefore, researchers are consistently developing and improving various techniques to predict river discharge with relative ease and high accuracy, although traditional methods are available. This paper presents mainly three data-driven modelling techniques, namely the stage rating curve (SRC), generalised reduced gradient (GRG) solver, and an artificial neural network (ANN) to accurately model the stage-discharge relationship for local rivers in Trinidad and Tobago using only low flow data. The model that produced the overall superior results was the ANN.
Keywords: stage-discharge; neural networks; rating curve; regression; modelling.
International Journal of Hydrology Science and Technology, 2022 Vol.14 No.1, pp.75 - 95
Received: 01 Sep 2020
Accepted: 08 Oct 2020
Published online: 30 Jun 2022 *