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Geospatial Methods for Monitoring a Vegetative Treatment Area Receiving Beef Feedlot Runoff
Author(s) -
Eigenberg Roger A.,
Lesch Scott M.,
Woodbury Bryan,
Nienaber John A.
Publication year - 2008
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/jeq2007.0347
Subject(s) - feedlot , environmental science , surface runoff , sampling (signal processing) , hydrology (agriculture) , soil water , soil salinity , environmental engineering , soil science , engineering , ecology , geography , forestry , electrical engineering , geotechnical engineering , filter (signal processing) , biology
A vegetative treatment area (VTA) offers alternative solutions to traditional feedlot runoff holding ponds, but the distribution of nutrients is not easily defined. Methods for monitoring salt accumulations in soils have been demonstrated at the United States Salinity Laboratory, Riverside, CA. This study was conducted to determine if methods developed to inventory saline soils can be used to inventory a VTA designed to control feedlot runoff. A soil conductivity map was generated at a VTA site using electromagnetic induction equipment (Dualem‐1S) and global positioning satellite. The ESAP software package, developed by the United States Salinity Laboratory at Riverside, CA, was used to determine a representative set of ( n = 20) soil sampling locations for estimating the chloride distribution in the VTA (Cl − : selected as an indicator ion to track feedlot runoff). An additional set of ( n = 20) stratified random sampling (SRS) locations were selected for comparison. The ESAP‐generated, prediction‐based sampling plan exhibited better design optimality criteria than the SRS plan. Statistical validation tests confirmed that the regression model estimated from the ESAP‐generated sample data was capable of producing accurate and unbiased predictions of the natural log (Cl − ) levels at the independently chosen SRS sites. The combination of geo‐referenced soil conductivity, directed soil sample data, and regression modeling provides a cost‐effective tool to observe and manage liquid flow patterns in a VTA.