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Dynamic drought risk assessment for maize based on crop simulation model and multi-source drought indices

Zhang, Feng, Chen, Yanan, Zhang, Jiquan, Guo, Enliang, Wang, Rui, Li, Danjun
Journal of cleaner production 2019 v.233 pp. 100-114
Crop Environment Resource Synthesis models, Zea mays, corn, developmental stages, drought, evapotranspiration, field experimentation, rainfed farming, risk, risk assessment, simulation models, soil water, spatial data, vegetation, China
Agricultural drought is a globally impacted natural disaster for the rain-fed agriculture region. The aim of this study is to construct a dynamic drought risk assessment (DDRA) model of maize for different growth periods based on risk assessment theory. In this model, optimal drought hazard indices for maize of the four growth stages were selected among 11 time scales daily Standardized Precipitation Evapotranspiration Index, Precipitation Condition Index, Soil Moisture Condition Index, Vegetation Condition Index, and Optimized Vegetation Drought Index. Secondly, the CERES-Maize model was used to fit the physical vulnerability curves with their corresponding drought hazards indices. DDRA model of maize in Jilin Province, China during 1981–2014 was conducted based on in situ data, remote sensing data, and field experiments data. The maize drought risk series maps were drawn and the results showed that the risk value under same hazard level presented an increasing trend at emergence-jointing and jointing-heading stage, and had a slight decreasing trend at heading-milky and milky-mature stage. For spatial dimension, the high drought risk value was distributed in the west and middle region. During the last three growth periods, the high risk value areas increased gradually from northwest to southeast region. The results indicated that the DDRA model provides more accurate evaluation in both the time and spatial scale and has significant guidance value for improving the adaptability of agricultural drought risk.