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Geospatial Methods for Monitoring a Vegetative Treatment Area Receiving Beef Feedlot Runoff

^a U.S. Meat Animal Research Center, P.O. Box 166, Clay Center, NE 68933
^b USDA-ARS, U.S. Salinity Lab., 450 W. Big Springs Rd., Riverside, CA 92507
^c USDA, P.O. Box 166, State Spur 18d, Clay Center, NE 68933. Product names are necessary to report factually on available data; however, the USDA neither guarantees nor warrants the standard of the product, and the use of the name by USDA implies no approval of the product to the exclusion of others that may also be suitable

^* Corresponding author (roger.eigenberg{at}ars.usda.gov).

Received for publication June 29, 2007. 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.

Abbreviations: EC_a, apparent soil conductivity • EMI, electromagnetic induction • ESAP, EC_e Sampling Assessment and Prediction • GPS, global positioning satellite • LR, linear regression • QQ, quantile–quantile • SRS, stratified random sampling • VTA, vegetative treatment area