Flooding poses a growing threat to global food security in a warming climate, yet a critical gap remains in quantifying flood-induced agricultural losses, hindering the design of effective adaptations to potential food crises. Here, we present a methodological framework for projecting crop losses from flooding, using a flooding stress algorithm to refine yield simulations from existing crop models. This approach ensures that simulated yield reductions for maize, soybean, and wheat align with observations in the United States and demonstrates strong agreement between estimated and reported flood-induced crop losses both in the United States and globally. Future flood-induced losses, which were substantially underestimated in the original simulations, are projected to be comparable to or even exceed drought-induced losses in many regions and exhibit distinct spatial and temporal patterns. Mitigation of greenhouse gas emissions helps reduce these risks. This framework provides a robust basis for assessing agricultural vulnerability to flood shocks and guiding strategies to safeguard food supplies under climate change.
Zhang et al. (Wed,) studied this question.