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Nationwide regression models for predicting urban runoff water quality at unmonitored sites

Water Resources Bulletin

By:
and
DOI: 10.1111/j.1752-1688.1988.tb03026.x

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Abstract

Regression models are presented that can be used to estimate mean loads for chemical oxygen demand, suspended solids, dissolved solids, total nitrogen, total ammonia plus nitrogen, total phosphorous, dissolved phosphorous, total copper, total lead, and total zinc at unmonitored sites in urban areas. Explanatory variables include drainage area, imperviousness of drainage basin to infiltration, mean annual rainfall, a land-use indicator variable, and mean minimum January temperature. Model parameters are estimated by a generalized-least-squares regression method that accounts for cross correlation and differences in reliability of sample estimates between sites. The regression models account for 20 to 65 percent of the total variation in observed loads.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Nationwide regression models for predicting urban runoff water quality at unmonitored sites
Series title:
Water Resources Bulletin
DOI:
10.1111/j.1752-1688.1988.tb03026.x
Volume
24
Issue:
5
Year Published:
1988
Language:
English
Publisher:
American Water Resources Association
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
Water Resources Bulletin
First page:
1091
Last page:
1101
Number of Pages:
11