Modeling the impacts of agricultural best management practices on runoff, sediment, and crop yield in an agriculture-pasture intensive watershed.

Best management practices (BMPs) are commonly used to reduce sediment loadings. In this study, we modeled the Fort Cobb Reservoir watershed located in southwestern Oklahoma, USA using the Soil and Water Assessment Tool (SWAT) and evaluated the impacts of five agricultural BMP scenarios on surface runoff, sediment yield, and crop yield. The hydrological model, with 43 sub-basins and 15,217 hydrological response units, was calibrated (1991-2000) and validated (2001-2010) against the monthly observations of streamflow, sediment grab samples, and crop-yields. The coefficient of determination ( ), Nash-Sutcliffe efficiency (NS) and percentage bias (PB) were used to determine model performance with satisfactory values of (0.64 and 0.79) and NS (0.61 and 0.62) in the calibration and validation period respectively for streamflow. We found that contouring practice reduced surface runoff by more than 18% in both conservation tillage and no-till practices for all crops used in this modeling study. In addition, contour farming with either conservation tillage or no-till practice reduced sediment yield by almost half. Compared to the conservation tillage practice, no-till practice decreased sediment yield by 25.3% and 9.0% for cotton and grain sorghum, respectively. Using wheat as cover crop for grain sorghum generated the lowest runoff followed by its rotation with canola and cotton regardless of contouring. Converting all the crops in the watershed into Bermuda grass resulted in significant reduction in sediment yield (72.5-96.3%) and surface runoff (6.8-38.5%). The model can be used to provide useful information for stakeholders to prioritize ecologically sound and feasible BMPs at fields that are capable of reducing sediment yield while increasing crop yield.