4.7 Article

Rice drought risk assessment under climate change: Based on physical vulnerability a quantitative assessment method

期刊

SCIENCE OF THE TOTAL ENVIRONMENT
卷 751, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.scitotenv.2020.141481

关键词

Global rice drought risk; EPIC; Yield loss rate; Physical vulnerability curves; RCPs

资金

  1. National Natural Science Foundation [41671501]
  2. National Key Research and Development Program [2016YFA0602402]

向作者/读者索取更多资源

This study used the EPIC model to simulate the future risk of rice yield due to drought, finding that high-risk areas are mainly located north of 30 degrees latitude. The expected increase in shortwave radiation is associated with a loss in rice yield.
Drought is the most serious natural disaster causing severe damage to agriculture. Drought impacts on rice (Oryza sativa) production present a major threat to future global food security. In this paper, the Environmental Policy Integrated Climate (EPIC) model was used to simulate the growth of rice, in different periods (short-term (2019-2039), medium-term (2040-2069), long-term (2070-2099)), based on multiple Representative Concentration Pathways (RCP) scenarios. Drought intensity and rice physical vulnerability curves were assessed, based on the output parameters of EPIC, to evaluate global rice yield risk, due to drought. The results show that the average expected loss rate of global rice yield may reach 13.1% (+/- 0.4%) in the future. The high-risk area of rice drought ismainly located in the north of 30 degrees N. The fluctuation of rice drought risk and the proportion of increased risk areaswill increase significantly. About 77.6% of the changes in rice drought risk are explained by variations in shortwave radiation (r= 0.88). Projections showthat the average value of daily shortwave radiation increases by 1W/m(2) during the rice growth period, accompanied by an expected rice yield loss rate of about 12.7%. The rice drought riskmethods presented in this paper provide plausible estimates of forecasting future drought risk under climate change, and address challenges of sparse data; we believe thesemethods can be applied to decisions for reducing drought-related crop losses and ensuring global food security. (C) 2020 Elsevier B.V. All rights reserved.

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