Development of stage-discharge rating curve using ANN
by Barkha Chaplot; Prashant Birbal
International Journal of Hydrology Science and Technology (IJHST), Vol. 14, No. 1, 2022

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.

Online publication date: Thu, 30-Jun-2022

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Hydrology Science and Technology (IJHST):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com