Gridded crop modeling to assess production shifts of maize and beans in Mexico under climate change

Using crop modeling, the project evaluates yield responses under rainfed and irrigated systems and maps hotspots where climate impacts may cause significant production losses, as well as regions—such as the highlands—where growing conditions may improve.The first step involved setting up a high-performance workstation to run the DSSAT crop model in a Linux-based parallel environment using the Mink modeling system. This system divides Mexico into equal-area grid cells (e.g., 10 × 10 km) and aggregates results to administrative units such as districts and states. Climate, soil, and environmental datasets were assembled, including baseline climate data (1990–2010) and future projections for the 2050s.Cultivar files were developed to represent maize and bean varieties grown across Mexico’s diverse agroclimatic zones. For maize, cultivars were based on CIMMYT’s six mega-environments, using physiological data from breeding trials and expert input. Bean cultivars were adapted from previous modeling work to reflect both irrigated high-input systems in northern Mexico and low-input traditional systems in the south.Management practices, including planting dates for rainfed and irrigated systems, were defined using CIMMYT’s extensive on-farm agronomic database. Baseline simulations have been completed, and model outputs are currently being validated and calibrated using national agricultural statistics. Once finalized, future climate simulations will begin.'This work was supported by the Wellcome Trust [310024/Z/24/Z]. Potential climate change effects on food security, nutrition, and health of the Mexican population. Co-design integrated policy measures. January 2024 '