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Modeling Pollutant Release from a Surface Source during Rainfall Runoff
Author(s) -
Walter M. Todd,
Parlange J.Y.,
Walter M. F.,
Xin X.,
Scott C. A.
Publication year - 2001
Publication title -
journal of environmental quality
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.888
H-Index - 171
eISSN - 1537-2537
pISSN - 0047-2425
DOI - 10.2134/jeq2001.301151x
Subject(s) - surface runoff , pollutant , flume , nonpoint source pollution , environmental science , pollution , hydrology (agriculture) , manure , watershed , environmental engineering , environmental chemistry , soil science , chemistry , flow (mathematics) , ecology , geotechnical engineering , geology , geometry , mathematics , organic chemistry , machine learning , computer science , biology
Though runoff from manure spread fields is recognized as an important mode of nonpoint‐source pollution, there are no models that mechanistically describe transport from a field‐spread manure–type source. A mechanistic, physically based model for pollutant release from a surface source, such as field‐spread manure, was hypothesized, laboratory tested, and field‐applied. The primary objective of this study was to demonstrate the potential applicability of a mechanistic model to pollutant release from surface sources. The laboratory investigation used stable sources and a conservative “pollutant” (KCl) so that the dynamic effects of source dissolution and chemical transformations could be ignored and transport processes isolated. The field investigation used runoff and soluble reactive phosphorus (SP) data collected from a dairy‐manure‐spread field in the Cannonsville watershed in the Catskills region of New York State. The model predictions corroborated well with observations of runoff and pollutant delivery in both the laboratory and the field. “Pollutant” release from surface sources was generally predicted within 11% of laboratory KCl measurements and field SP observations. Laboratory flume runoff predictions with 15 and 26% errors for 25 and 15 mm h −1 simulated rainfall intensity experiments, respectively, represented root mean square errors of less than 0.2 mL s −1 A 26% error was calculated for overland flow predictions in the field, which translated into approximately a 39 mL s −1 error. Results suggest that the hypothesized model satisfactorily represents the primary mechanisms in pollutant release from surface sources.