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2015 | OriginalPaper | Chapter

Suspended Sediment Estimation Using an Artificial Intelligence Approach

Authors : Mustafa Demirci, Fatih Üneş, Sebahattin Saydemir

Published in: Sediment Matters

Publisher: Springer International Publishing

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Abstract

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.

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Title: Suspended Sediment Estimation Using an Artificial Intelligence Approach
Authors: Mustafa Demirci
Fatih Üneş
Sebahattin Saydemir
Publisher: Springer International Publishing
Book: Sediment Matters
Print ISBN: 978-3-319-14695-9

Electronic ISBN: 978-3-319-14696-6

Copyright Year: 2015
DOI: https://doi.org/10.1007/978-3-319-14696-6_6