Submitted to: Agriculture, Ecosystems and Environment
Publication Type: Peer reviewed journal
Publication Acceptance Date: 4/17/2007
Publication Date: 1/4/2008
Citation: Farahbakhshazad, N., Dinnes, D.L., Li, C., Jaynes, D.B., Salas, W. 2008. Modeling Biochemical Impacts of Alternative Management Practices for a Row-Crop Field in Iowa. Agriculture, Ecosystems and Environment. 123(1-3):30-48. Interpretive Summary: Land use and farm management practices can greatly affect water outflow, sediment, nutrient, and pesticide losses from agricultural watersheds. There is an increasing demand by decision makers and planners for information regarding the magnitude of these effects and how water quality parameters may change due to adoption of various agricultural practices. Because of the complexity of watershed systems and the large number of possible management practices to be considered, computer simulation models are best suited for this task. We used the DNDC model that we had previously modified and successfully tested for a Midwest corn and soybean rotation to evaluate a number of management options for maintaining high crop yields while providing additional ecosystem services. The ecosystem services we focused on were reducing nitrate leaching to surface waters, reducing the emissions of the greenhouse gas nitrous oxide, and the sequestration of soil organic carbon. Options tested included switch from chisel plow to no-till; variations in nitrogen fertilizer application rate, placement, and timing; and incorporating leguminous and non-leguminous cover crops into the rotation. We also examined the effects of changes in annual precipitation and mean temperature that could result from possible future climate changes on crop yield and ecosystem services. We found that a number of management changes could positively affect one or more of the environmental services screened for. Overall, we found that the best combination of practices for the maximum improvement in environmental services with the least impact on crop yields was a no-till system with nitrogen fertilizer injected 15 cm below the surface three times during the corn growing season and planting a non-leguminous cover crop after corn and soybean harvest every fall. The approach used here will be of interest to agronomists interested in optimizing farming systems for farmer profit and ecosystem services.
Technical Abstract: The management of contemporary agriculture is rapidly shifting from single-goal to multi-goal strategies. The bottleneck of implementing the strategies is the capacity of predicting the simultaneous impacts of change in management practices on agricultural production, soil, and water resources and environmental safety. Process-based models provide an opportunity to quantify the impacts of farm management options on various pools and fluxes of carbon and nitrogen (N) in agroecosystems. The denitifications-decomposition or DNDC model was recently modified for simulating N cycling for the U.S. Midwestern agricultural systems. This paper reports a continuous effort on applying the model for estimating the impacts of alternative management practices (e.g., no-till, cover crop, change in fertilizer rate, or timing) on agro-ecosystems in the midwestern U.S. A typical row-crop field in Iowa was selected for the sensitivity tests. The modeled results were assessed with a focus on four major indicators of agro-ecosystems, namely drop yield, soil organic carbon (SOC) sequestration, nitrate-N leaching loss, and nitrous oxide (N2O) emissions. The results indicated that no-till practice significantly increased SOC storage and reduced nitrate-N leachng rate, but slightly decreased crop yield and increased N3O emissions. By modifying the methods of fertilizer application in conjunction with the no-till practice, the disadvantages of no-till could be overcome. For example, increasing the fertilizing depth and using a nitrification inhibitor could substantially reduce N2O emissions and increase crop yield under the no-till conditions. This study revealed the complexity of impacts of the alternative farming management practices across different climate conditions, soil properties and management regimes. Process-based models can play an impportant role in quantifying the comprehensive effects of management alternatives on agricultural production and the environment.