A comparison of various artificial intelligence approaches performance for estimating suspended sediment load of river systems: a case study in United States

Environmental Monitoring and Assessment
Ehsan OlyaieAssefa M Melesse

Abstract

Accurate and reliable suspended sediment load (SSL) prediction models are necessary for planning and management of water resource structures. More recently, soft computing techniques have been used in hydrological and environmental modeling. The present paper compared the accuracy of three different soft computing methods, namely, artificial neural networks (ANNs), adaptive neuro-fuzzy inference system (ANFIS), coupled wavelet and neural network (WANN), and conventional sediment rating curve (SRC) approaches for estimating the daily SSL in two gauging stations in the USA. The performances of these models were measured by the coefficient of correlation (R), Nash-Sutcliffe efficiency coefficient (CE), root-mean-square error (RMSE), and mean absolute percentage error (MAPE) to choose the best fit model. Obtained results demonstrated that applied soft computing models were in good agreement with the observed SSL values, while they depicted better results than the conventional SRC method. The comparison of estimation accuracies of various models illustrated that the WANN was the most accurate model in SSL estimation in comparison to other models. For example, in Flathead River station, the determination coefficient was 0.91 for the ...Continue Reading

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Citations

Jun 26, 2018·International Journal of Environmental Research and Public Health·Sangmok Lee, Donghyun Lee
Feb 16, 2019·Water Science and Technology : a Journal of the International Association on Water Pollution Research·Avat GhasemiFereshteh Motiee
May 20, 2019·Environmental Monitoring and Assessment·Mohammad Najafzadeh, Alireza Ghaemi
May 17, 2019·Environmental Science and Pollution Research International·Lei LiHui Wu
Jun 7, 2019·Environmental Science and Pollution Research International·Anurag MalikJalal Shiri
Nov 21, 2019·Environmental Science and Pollution Research International·Lian SunTao Tao
Oct 16, 2015·Environmental Monitoring and Assessment·Muhammad HassanAnwar Khitab
Jul 10, 2018·Environmental Science and Pollution Research International·Xiaoliang Ji, Jun Lu
Nov 14, 2018·Environmental Science and Pollution Research International·Hai TaoShamsuddin Shahid
Sep 27, 2018·International Journal of Environmental Research and Public Health·Hye-Suk YiKeun-Chang Kwak
May 3, 2018·Environmental Monitoring and Assessment·Edson Marcelino AlvesEutimio Gustavo Fernández Núñez
Jun 20, 2018·The Science of the Total Environment·M J AscottB W J Surridge
Jun 24, 2021·Environmental Monitoring and Assessment·Yong Jie WongNik Meriam Nik Sulaiman

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