Submitted to: Soil and Water Conservation Society
Publication Type: Abstract Only
Publication Acceptance Date: February 22, 2010
Publication Date: April 28, 2010
Citation: Baffaut, C., Mudgal, A., Anderson, S., Sadler, E.J. 2010. Identifying Critical Areas for the Management of Goodwater Creek Experimental Watershed [abstract]. SWCS Managing Agricultural Lanscapes for Environmental Quality II Achieving More Effective Conservation, April 28-30, 2010, Denver, Colorado. p.9. Technical Abstract: Identifying fields that need attention is critical to ensure conservation programs improve water quality. Targeting critical management areas (CMAs) within fields is essential to maximize cultivation area while minimizing environmental impacts. The objective of this study was to develop a physically-based index to identify CMAs in a field and critical fields in a watershed. The study was located in the 72 km2 Goodwater Creek Watershed, in northeast Missouri where most soils are characterized by a clay layer of extremely low permeability occurring within the upper 5 to 50 cm. In the first part of the study, a 32-ha research crop field was divided in 35 subareas based on slope, depth to claypan, and soil mapping units from an Order 1 soil survey. Runoff and water quality data collected at the outlet since 1991 were used to calibrate the Agricultural Policy Environmental Extender (APEX) model. Simulated output by subarea was correlated with physical parameters including depth to claypan (CD), surface saturated hydraulic conductivity (Ksat) and subarea slope (SL). Two indices were developed, CD*Ksat /SL, and CD/SL, which correlated with runoff (r = -0.77), and atrazine and sediment loads (r=-0.55), respectively. These indices captured 100 % of CMAs due to runoff and sediment yield and 75 % of CMAs due to atrazine load, as predicted by APEX; they also identified areas with lower productivity. In the second part of this study, the indices were used to identify critical fields in the watershed by overlaying a field layer, a topographic layer and the SSURGO soil map. The indices were calculated for each soil mapping unit within each field based on average slope and soil characteristics, from which critical areas were defined. Results include the fraction of cropland in the watershed classified as critical, a look at where cost-shared dollars have been directed in comparison to these critical areas, and a comparison of runoff and pollutant loadings generated from critical and non-critical fields. The identification of these critical areas is important for producers and regulators as it allows better use of cost-share dollars and greater flexibility for producers on the rest of their land.