Projected Climate Change Impacts on Phenology, Yield and Water Productivity of Wheat and Potato in Northwest Bangladesh

ABSTRACT Assessing climate change impacts on agriculture is essential for developing effective adaptation strategies, with crop simulation models providing valuable tools for evaluating future crop productivity. This study assessed climate change impacts on wheat and potato productivity in northwest Bangladesh using 27 Global Climate Models (GCMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6) under two Shared Socioeconomic Pathways (SSP245 and SSP585). The Agricultural Production Systems sIMulator (APSIM) wheat and potato models were evaluated before simulating phenology, yield and water productivity for two future periods: near future (NF: 2031–2065) and far future (FF: 2066–2100), relative to the baseline period (1988–2022). Climate projections indicated consistent increases in maximum temperature ( T max ) and minimum temperature ( T min ) during both crop‐growing seasons. During FF, mean T max ( T min ) was projected to increase by up to 1.8°C (2.0°C) under SSP245 and 3.5°C (3.8°C) under SSP585 during wheat, and 1.9°C (2.0°C) under SSP245 and 3.7°C (3.9°C) under SSP585 during potato‐growing season, with site‐specific changes in rainfall and solar radiation. Rising temperatures accelerated crop development, reducing wheat flowering time by up to 12 days and increasing potato tuber initiation time by 4 days. Despite these phenological changes, both crops demonstrated yield gains across scenarios. Wheat yield was projected to increase by up to 21.2% under SSP245, while potato yield increased by 53% under SSP585 in FF. Water productivity also improved, primarily due to increased yield under unchanged irrigation. Regression analysis indicated that T max exerted negative effect on yield, whereas T min , solar radiation, and CO 2 had positive effects. Rainfall had limited influence on potato but showed relevance to wheat. Projection uncertainty primarily originated from GCMs, and SSP scenarios used in simulations. Overall, these findings provide valuable insights for policymakers in promoting climate‐resilient crop selection under changing climate in Bangladesh.