A generic risk assessment framework to evaluate historical and future climate-induced risk for rainfed corn and soybean yield in the U.S. Midwest

Authors: ZHOU, WANG - University Of Illinois; GUAN, KAIYU - University Of Illinois; PENG, BIN - University Of Illinois; WANG, ZHOU - University Of Illinois; FU, RONG - University Of California (UCLA); LI, BO - University Of Illinois; Ainsworth, Elizabeth - Lisa; DELUCIA, EVAN - University Of Illinois; ZHAO, LEI - University Of Illinois; CHEN, ZHANGLIANG - University Of Illinois

Submitted to: Weather and Climate Extremes
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/5/2021
Publication Date: 8/6/2021
Citation: Zhou, W., Guan, K., Peng, B., Wang, Z., Fu, R., Li, B., Ainsworth, E.A., DeLucia, E., Zhao, L., Chen, Z. 2021. A generic risk assessment framework to evaluate historical and future climate-induced risk for rainfed corn and soybean yield in the U.S. Midwest. Weather and Climate Extremes. 33. Article 100369. https://doi.org/10.1016/j.wace.2021.100369.
DOI: https://doi.org/10.1016/j.wace.2021.100369

Interpretive Summary: Global climate change is expected to increase variability in temperature and precipitation, which could increase the risk of crop yield loss in the future. Understanding how risks will change is important to the everyone in the agricultural industry, from producers to insurers to consumers. Risk analysis methods have typically used data-driven approaches with historical information, but those may not be applicable under future climate scenarios. Another approach to risk assessment is to use crop models, which require large datasets for parameterization and validation. In this study, we developed a generic risk assessment framework by combining a climate generation model with a statistical crop yield model to test how much variability in corn and soybean yield is explained by climate variability. We found that ~40% of interannual variability in corn and soybean yield can be explained by the climate, and that the risk level is greater in the southwest and northwest regions of the U.S. Corn Belt. Future climate change will likely increase crop yield risk in the future.

Technical Abstract: Fluctuations in temperature and precipitation are expected to increase with global climate change, with more frequent, more intense and longer-lasting extreme events, posing greater challenges for the security of global food production. Here we propose a generic framework to assess the impact of climate-induced crop yield risk under both current and future scenarios by combining a stochastic model for synthetic climate generation with a well-validated statistical crop yield model. The synthetic climate patterns were generated using the extended Empirical Orthogonal Function method based on PRISM dataset and future climate adjusted PRISM dataset for current and future scenarios, respectively. We applied our framework to assess the corn and soybean yield risk in the U.S. Midwest for historical and future climate conditions. We found that: (1) in the U.S. Midwest, about 45% and 40% of the interannual variability in corn and soybean yield, respectively, can be explained by the climate; (2) the risk level is higher in the southwest and northwest regions of the U.S. Midwest corresponding to 25% yield reduction for both corn and soybean; (3) the severity for the 1988 and 2012 major droughts quantified by our method represent 21-year and 30-year events for corn, and 7-year and 12-year events for soybean, respectively; (4) the crop yield risk will increase under a future climate scenario (i.e. RCP 8.5 at 2050) compared with the current climate, with averaged yield decreases and yield variability increases for both corn and soybean. The method framework and the results of this study have numerous applications for risk management policies and practices for the agriculture sectors.