Simulation models are increasingly used to analyze the impact of agricultural management at the watershed-scale. In this study, the Agricultural Policy/Environmental eXtender (APEX) model was tested using long-term (1976-1995) data from two watersheds (W2 and W3) at the USDA Deep Loess Research Station near Treynor, Iowa. The two watersheds were cropped with continuous corn (Zea mays L.) and managed with conventional-tillage at W2 (34.4 ha) and ridge-till at W3 (43.3 ha). The monthly runoff and sediment yield were calibrated for the two watersheds during 1976-1987 by adjusting the curve numbers, curve number index coefficient, RUSLE C factor exponential residue and height coefficients, and erosion control practice factor for grassed waterways. Soil organic carbon values in the top 0.15 m soil layer were calibrated for the two watersheds in 1984 by adjusting the microbial decay rate coefficient. Model validation was conducted from 1988 to 1995. The calibrated model was able to reasonably replicate the monthly and yearly surface runoff and sediment yield for both watersheds for the validation period, with Nash-Sutcliffe efficiencies (EF) larger than 0.62 except for the EF of 0.41 for monthly sediment yield comparison at W3. The errors between the predicted and observed means were all within ±6% for runoff and sediment yield; predicted soil organic carbon in the 0.15 m soils in 1994 were within 10% of the observed values for both watersheds. The percentage error between the predicted and observed average corn grain yields was -5.3% at W2 and -2.7% at W3 during the 20-year simulation period. Scenario analyses were also conducted to assess the benefits of ridge-till over conventional-tillage. Over the 20 years, the predicted benefit of ridge-till versus conventional-tillage on surface runoff reduction was 36% in W2 and 39% in W3, and about 82-86% sediment yield reduction in both watersheds. The cumulative soil organic carbon losses from sediment were reduced about 63-67%. The long-term benefit of ridge-till over conventional-tillage was also quantified as a minimum corn grain yield increase of 3.8%. The results of this study indicate that APEX has the ability to predict differences between the two tillage systems. The modeling approach can be extended to other watersheds to examine the impacts of different tillage systems.
All Science Journal Classification (ASJC) codes
- Agronomy and Crop Science
- Soil Science
- Earth-Surface Processes