An EPIC model-based vulnerability assessment of wheat subject to drought

• Published in: Natural hazards (Dordrecht) Vol. 78; no. 3; pp. 1629 - 1652
• Main Authors: Yue, Yaojie, Li, Jian, Ye, Xinyue, Wang, Zhiqiang, Zhu, A-Xing, Wang, Jing-ai
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.09.2015; Springer Nature B.V
• Subjects: Agricultural production; Assessments; Cereal crops; Civil Engineering; Crop calendars; Crop production; Crop yield; Drought; Droughts; Earth and Environmental Science; Earth Sciences; Environmental conditions; Environmental Management; Environmental policy; Farming; Farming systems; Farms; Genetics; Geophysics/Geodesy; Geotechnical Engineering & Applied Earth Sciences; Hazards; Hydrogeology; Natural Hazards; Original Paper; Risk assessment; Statistical analysis; Weather hazards; Wheat; EPIC model; Drought; Wheat; China; Regionalized vulnerability curves
• ISSN: 0921-030X; 1573-0840
• DOI: 10.1007/s11069-015-1793-8

This paper presents a regionalized vulnerability curve-building approach to vulnerability and risk assessment of wheat subjected to drought that uses the Environmental Policy Integrated Climate (EPIC) model and statistical analysis. We defined wheat vulnerability as the degree to which a wheat production system is likely to experience yield loss due to a perturbation or drought hazard. Wheat vulnerability in a given region is thus the yield loss divided by the drought hazard index (DHI). By simulating a variety of wheat yield losses and associated DHIs, wheat drought vulnerability curves can be developed. We propose that agricultural systems be considered uniform within each wheat-planting region and different in different regions, according to territorial differentiation, when regionalized vulnerability curves are built. Based on this principle, a detailed regional crop calendar was improved, and optimized wheat varieties were refined that can differentiate agricultural systems within wheat-planting regions. The crop calendar was improved based on the assumption that local farmers have perfect knowledge in selecting sowing and harvesting dates. The wheat varieties were optimized by adjusting the genetic parameters of wheat in the EPIC model using the Shuffled Complex Evolution algorithm–University of Arizona (SCE-UA) method. Based on these improvements and innovations, the precision of most vulnerability curves was improved, and the curves were compared favorably to those observed in previous studies related to differences in the genetic character of wheat, the crop calendar, environmental conditions, and other relevant factors. Differences within each region were smaller than differences between regions. More detailed wheat vulnerability curves allow for the assessment of expected wheat yield loss and also allow for a high level of precision in an evaluation, at a variety of scales, of risk of wheat subject to drought. The proposed approach to building regionalized vulnerability curves has the potential to be the basis for crop drought vulnerability curves in different geographical areas at multiple scales.