Development of stage-discharge rating curve using ANN

被引:6
|
作者
Chaplot, Barkha [1 ]
Birbal, Prashant [2 ]
机构
[1] Babasaheb Bhimrao Ambedkar Bihar Univ, MJK Coll, Dept Geog, Bettiah, Muzaffarpur, India
[2] Univ West Indies, Dept Civil & Environm Engn, St Augustine, Trinidad Tobago
关键词
stage-discharge; neural networks; rating curve; regression; modelling; NEURAL-NETWORKS; RIVER; TREES; FUZZY; MODEL;
D O I
10.1504/IJHST.2022.123643
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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.
引用
收藏
页码:75 / 95
页数:21
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