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PROCESS‐ORIENTED ESTIMATION OF SUSPENDED SEDIMENT CONCENTRATION 1
Author(s) -
Irvine Kim Neil,
Drake John J.
Publication year - 1987
Publication title -
jawra journal of the american water resources association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.957
H-Index - 105
eISSN - 1752-1688
pISSN - 1093-474X
DOI - 10.1111/j.1752-1688.1987.tb00851.x
Subject(s) - sediment , autoregressive integrated moving average , environmental science , hydrology (agriculture) , regression analysis , regression , geology , statistics , geotechnical engineering , mathematics , time series , geomorphology
Least squares regression and ARIMA models were developed from suspended sediment data for the Ausable River, Southern Ontario, Canada. A poor correlation between discharge and suspended sediment concentration results from the dynamics of the physical system, including seasonality, antecedent conditions, and hysteresis. Regression model results were significantly improved by the division of the data set into seasons and the addition of simple. but physically meaningful variables. Misleading improvements obtained from the regression of sediment load and discharge are discussed. ARIMA models provided accurate forecasts of sediment concentration on a real‐time basis, but the rigorous data requirements limit their use in modeling suspended sediment concentrations in Canadian rivers.