AnnAGNPS Model Application for Nitrogen Loading Assessment for the Future Midwest Landscape Study

摘要

The Future Midwest Landscape (FML) project is part of the US Environmental Protection Agency (EPA)’s new Ecosystem Services Research Program, undertaken to examine the variety of ways in which landscapes that include crop lands, conservation areas, wetlands, lakes, and streams affect human well-being. The goal of the FML project is to quantify current and future ecosystem services across the region and to examine changes expected to occur as a result of the growing demand for biofuels. This study is one of several pilots taking place under the umbrella of the FML research project. In this study, the USDA Annualized Agricultural Non-Point Source Pollution (AnnAGNPS) model was applied to the East Fork Kaskaskia River watershed (289.3 km2) located in the Kaskaskia River Basin within the Upper Mississippi River Basin in Illinois. The effect of different spatial resolutions on model performance was investigated by comparing the observed runoff with the AnnAGNPS simulated results. Alternative future scenarios such as meeting future biofuel target were also simulated and analyzed. All delineations of the study area (coarser to finer) produced satisfactory results in simulating monthly and annual runoff. However, the size of the delineation does impact the simulation results. Finer delineations better represented the actual landscape and captured small critical areas that would be homogenized in coarser delineation. Those small critical areas are important to target to achieve maximum environment benefit. Simulations of alternative future scenarios showed that as corn production increases to meet future biofuel needs, total nitrogen loss increases. For this watershed, total N loss would be more than doubled if converting all corn/soybean rotation (15,871.2 ha) to continuous corn comparing with the base year total N loss which is 11.2 kg/ha. Conservation practices are needed to reduce total nitrogen loss from the watershed. This study provides an important foundation for the larger FML region modeling effort by addressing challenging FML landscape modeling issues such as model selection, need for further model development, and spatial resolution.