Crop Economics, Production, and Management
Using crop models to simulate crop growth and productivity at a regional scale is a complex process designed to represent the observed impact of individual farmer decision-making on the agricultural landscape. Typically, during agricultural simulation efforts, the planting acreages have largely been based on a set of predetermined, static scenarios. In this study, we developed a system to dynamically enhance the Agricultural Land Management Alternative with Numerical Assessment Criteria (ALMANAC) crop simulation model through a two-way linkage with an economics land-use model. This coupled model approach integrated farmers’ land-use choices based on relative economic returns and produced dynamic land-use probabilities for ALMANAC simulations through a feedback loop. The coupled model approach was intercompared with static crop modeling through a historic acreage approach, and comparable accuracies were found from both modeling efforts for the 2014 growing season. Furthermore, as a proof-of-concept effort, the method was applied to evaluate the impact of two scenarios on crop simulations: major crops (maize, soybean, and wheat) intensification through price increases (e.g., market change) and incentivized grassland conservation (e.g., policy change). The results of this sensitivity study suggest that the coupled system has the capability to integrate economic factors into traditional crop simulation, allowing for insight into the impacts of changes in markets and policies on agricultural landscapes and crop yields.
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Jon Starr, Haochi Zheng, Jianglong Zhang, et al.. "Evaluating Sensitivities of Economic Factors through Coupled Economics-ALMANAC Model System" (2019). Earth System Science and Policy Faculty Publications. 13.