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Simulation von Variablen der Fließgewässerqualität mittels Mehrfachregressionen

Simulation von Variablen der Fließgewässerqualität mittels Mehrfachregressionen There are investigated the variables O2, BOD5, seston, NO3‐N, NH4‐N and o‐PO4 from at least five‐year series of five stations along a river section of 50 km. After exclusion of a linear trend and substraction of the individual monthly mean values from the monthly mean of many years in order to eliminate the effect of the annual variation as well as testing for normal distribution, first the correlation coefficients of the variables to the flow rate Q and the temperatures of air and water are determined, which show directional changes just in the longitudinal profile of the river. The same holds for the correlation of the variables between the measuring points. From this the model structure is derived, according to which the concentration at one measuring station can be simulated by multiple regression to Q and T at the same level as well as the concentration at the upper level. The results are discussed in detail and evaluated with respect to their inclusion in longterm management models of water quantity management. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Acta hydrochimica et hydrobiologica Wiley

Simulation von Variablen der Fließgewässerqualität mittels Mehrfachregressionen

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References (5)

Publisher
Wiley
Copyright
Copyright © 1991 Wiley Subscription Services, Inc., A Wiley Company
ISSN
0323-4320
eISSN
1521-401X
DOI
10.1002/aheh.19910190110
Publisher site
See Article on Publisher Site

Abstract

There are investigated the variables O2, BOD5, seston, NO3‐N, NH4‐N and o‐PO4 from at least five‐year series of five stations along a river section of 50 km. After exclusion of a linear trend and substraction of the individual monthly mean values from the monthly mean of many years in order to eliminate the effect of the annual variation as well as testing for normal distribution, first the correlation coefficients of the variables to the flow rate Q and the temperatures of air and water are determined, which show directional changes just in the longitudinal profile of the river. The same holds for the correlation of the variables between the measuring points. From this the model structure is derived, according to which the concentration at one measuring station can be simulated by multiple regression to Q and T at the same level as well as the concentration at the upper level. The results are discussed in detail and evaluated with respect to their inclusion in longterm management models of water quantity management.

Journal

Acta hydrochimica et hydrobiologica – Wiley

Published: Jan 1, 1991

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