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

Journal Article · Sat Oct 01 04:00:00 EDT 1988 · Water Resources Bulletin; (USA)

DOI:https://doi.org/10.1111/j.1752-1688.1988.tb03026.x· OSTI ID:7027785

Tasker, G D ^[1]; Driver, N E ^[2]

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1. Geological Survey, Reston, VA (USA)
2. Geological Survey, Lakewood, CO (USA)

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 phosphorus, dissolved phosphorus, 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.

• OSTI ID: 7027785
• Journal Information: Water Resources Bulletin; (USA), Journal Name: Water Resources Bulletin; (USA) Vol. 24:5; ISSN WARBA; ISSN 0043-1370
• Country of Publication: United States
• Language: English

Related Subjects

54 ENVIRONMENTAL SCIENCES
540320* -- Environment
Aquatic-- Chemicals Monitoring & Transport-- (1990-)
COPPER
ELEMENTS
ENVIRONMENTAL QUALITY
ENVIRONMENTAL TRANSPORT
LEAD
MASS TRANSFER
MATHEMATICAL MODELS
MATHEMATICS
METALS
NONMETALS
PHOSPHORUS
REGRESSION ANALYSIS
RUNOFF
STATISTICS
TRANSITION ELEMENTS
URBAN AREAS
WATER QUALITY
ZINC