Probabilistic Assessment of Crop Yield Loss Under Drought and Global Warming in the Canadian Prairies

This study assessed the vulnerability of canola, spring wheat, and barley yields in the Canadian Prairies to drought stress under future climate scenarios, integrating DSSAT crop models with NEX-GDDP CMIP6 projections and probabilistic copula analysis. The DSSAT simulations reproduced historical yields with high accuracy (d > 0.7, nRMSE < 15–20%), confirming its applicability for Prairie agroecosystems. Results indicate distinct crop-specific sensitivities to warming: barley showed relative resilience with modest yield gains (~10%) at 1.5–2 °C of global warming (GW), wheat exhibited heterogeneous responses with early minor gains (~1%) followed by declines (~8%) beyond 3 °C of GW, and canola displayed consistent and substantial losses (20–37%) even under moderate warming. Spatial analysis highlighted relatively stable regions in northern Alberta, central Saskatchewan, and southern Manitoba (Gray and Black soil zones), while the southern and southwestern Prairie areas (Brown and Black-Brown zones) showed the greatest yield declines. Copula-based analysis further revealed that canola is most vulnerable to dry conditions, with yield exceedance probabilities falling from 62% (wet years) to ~25–28% (dry years) under GW. These findings underscore that Prairie crop production faces increasingly heterogeneous risks, with canola emerging as the most climate-sensitive crop. Targeted adaptation strategies such as stress-tolerant cultivars, shifting cropping zones, and improved water management will be essential to mitigate projected drought impacts and sustain Prairie agricultural productivity.