Evaluating Sensitivities of Economic Factors through Coupled Economics‐ALMANAC Model System

Abstract

Core Ideas A linked Economics land‐use model with the ALMANAC model has been constructed for crop simulation.The linked crop and economics modeling system can be used for estimating dynamic crop acreages.The impacts of policy and market changes on crop simulations can be studied with the linked system. 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.

Albedo Impacts of Changing Agricultural Practices in the United States through Space-Borne Analysis

“…The database includes the mean, standard deviation, and pixel counts for matching crop, location, and time conditions for both white-and black-sky albedo allowing for a broad use of the data across multiple types of study. For example, linking the resulting albedo parameters to modeling of crop acreage changes driven by economic forces could allow estimation of currently unquantified surface albedo and regional climate effects of US agricultural and trade policies that affect farmers' choice of crops via the price mechanism (i.e., Starr et al [33]). The database is attached as a supplement to this paper for potential remote-sensing, weather, and climate applications that require accurate quantification of lower boundary conditions.…”