JEQ Journal of Natural Resources and Life Sciences Education
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Journal of Environmental Quality 30:112-120 (2001)
© 2001 American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America

TECHNICAL REPORT
LANDSCAPE AND WATERSHED PROCESSES

Predicting Physical and Chemical Water Properties from Relationships with Watershed Soil Characteristics

Mostafa A. Shirazia, Larry Boersmab, Colleen Burch Johnsonc and Patricia K. Haggertyc

a Western Ecology Division, NHEERL, U.S. Environmental Protection Agency, 200 S.W. 35th Street, Corvallis, OR 97333
b Dep. of Crop and Soil Science, ALS 3017, Oregon State Univ., Corvallis, OR 97331-7306
c OAO Corporation, 200 S.W. 35th Street, Corvallis, OR 97333

Corresponding author (safa{at}mail.cor.epa.gov)

Received for publication February 22, 2000. The Surface Waters component of the Environmental Monitoring and Assessment Program (EMAPSW) was developed by the USEPA to evaluate the extent and condition of lakes and streams over national and regional scales. Realistically, chemical or physical water properties (WPs) such as acidity or turbidity can be field-sampled for only a small portion of all lakes and streams. However, soil characteristics (SCs) affect WPs and broad-scale soil survey data have become available in the State Soil Geographic Data Base (STATSGO). We developed models relating observed WPs to SCs to extrapolate the sampled WPs to a region, potentially reducing extensive monitoring needs. Our study region consisted of 13 northeastern and Mid-Atlantic states and contained 882 STATSGO soil map units. We used map units as the spatial component of WP analysis. The WPs were sampled in 721 randomly selected EMAPSW study sites. The watersheds of these sites represent 7.1% of the region's total area and spatially intersect 400 of its soil map units. Each intersected map unit was assigned the weighted average WPs from the corresponding watersheds. Conditional expectation models were used to extrapolate sampled WPs to 882 map units. The relative standard errors ranged from low for pH (0.8%), intermediate for total P (12.1%), and very high for chloride (54.8%). The high extrapolation errors indicate outlier conditions from natural, non-soil, or anthropogenic sources.

Abbreviations: ANC, acid neutralizing capacity • {sigma}g, geometric particle standard deviation • cr, coarse-textured soils • cstdv, conditional standard deviation • dg, geometric mean particle diameter • DOC, dissolved organic carbon • EMAPSW, Environmental Monitoring and Assessment Program of Surface Waters • fn, fine-textured soils • ir, index of relationship for a soil characteristic of a map unit • mecr, medium coarse-textured soils • mocr, moderately coarse-textured soils • mofn, moderately fine-textured soils • MUG, map unit group • PSD, particle size distribution • SC, soil characteristic • STATSGO, State Soil Geographic Data Base • stdv, standard deviation • USDA12, conventional USDA texture classes • USDA5, aggregated USDA texture classes • WP, physical and chemical water property




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The SCI Journals Agronomy Journal Crop Science
Journal of Natural Resources
and Life Sciences Education
Vadose Zone Journal
Soil Science Society of America Journal Journal of Plant Registrations The Plant Genome
Copyright © 2001 by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America.