Prediction of suspended sediment in river using fuzzy logic and multilinear regression approaches
Loading...
Date
2013
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Springer
Access Rights
info:eu-repo/semantics/closedAccess
Abstract
Prediction of sediment concentration in a river is very important for many water resource projects. Conventional sediment rating curves (SRC), however, are not able to provide sufficiently accurate results. In this paper, a fuzzy logic approach is proposed to estimate suspended sediment concentration from streamflow. A comparison was performed between fuzzy logic (FL), SRC and multilinear regression models. It was based on a 5-year period of continuous streamflow, suspended sediment concentration and mean water temperature data of Sacremento Freeport Station operated by the United States Geological Survey. Based on the comparison of the results, it is found that the FL model gives better estimates than the other techniques.
Description
Keywords
Suspended sediment, Forecasting, Fuzzy logic, Sediment rating curve, Multilinear regression
Journal or Series
Neural Computing & Applications
WoS Q Value
Q2
Scopus Q Value
Q1
Volume
23
