Suspended sediment estimation using an artificial intelligence approach
[ N/A ]
Tarih
2015
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer International Publishing
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Forecasting of sediment concentration in rivers is a very important process for water resources assignment development and management. In this paper, a neural network approach is proposed to predict suspended sediment concentration from streamflow. A comparison was performed between artificial neural network, sediment rating-curve and multilinear regression models. It was based on a 5 years period of continuous streamflow, suspended sediment concentration and mean water temperature data of West Virginia, Little Coal River, Danville station operated by the United States Geological Survey. Based on comparison of the results, it is found that the artificial neural network model gives better estimates than the sediment rating-curve and multilinear regression techniques. © Springer International Publishing Switzerland 2015.
Açıklama
Anahtar Kelimeler
Forecasting, Multi-linear regression, Neural network, Sediment rating curve, Suspended sediment
Kaynak
Sediment Matters
WoS Q Değeri
Scopus Q Değeri
N/A
