4.7 Article

GEPIC-V-R model: A GIS-based tool for regional crop drought risk assessment

Journal

AGRICULTURAL WATER MANAGEMENT
Volume 144, Issue -, Pages 107-119

Publisher

ELSEVIER
DOI: 10.1016/j.agwat.2014.05.017

Keywords

Large scale risk assessment model (GEPIC-VR model); Global; Vulnerability curves; Drought risk; Maize

Funding

  1. State Key Scientific Program of China (973 Project): Global Change, Environmental Risk and Its Adaptation Paradigms [2012CB955403]
  2. National Natural Science Foundation of China: Research of Regional Agricultural Drought Adaptability Evaluation Model and Risk Prevention Paradigms [41171402]
  3. Foundation for Innovative Research Groups of the National Natural Science Foundation of China [41321001]

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In recent years, food losses caused by drought accounted for approximately 60% of the total world food loss, seriously threatening the world's food security and sustainable development. Against the background of frequent extreme climate events and local warming and drying, frequency and potential risks of global drought have tended to increase. As the scientific basis for disaster prevention and mitigation, disaster risk assessment has drawn widespread attention in the scientific community. Using the commonly used EPIC crop model, this study constructed a crop drought risk assessment model GEPIC-V-R model suitable for large regional scale, with functions to fit vulnerability curves and calculate risk. Additionally, global maize drought risk was assessed. From a global perspective, South Africa, Chile, Western and Central Europe, Russia and southeastern regions have elevated risks of maize drought; Chinese maize drought risk distribution is characterized by low risk in southern regions and high risk in northern regions. For once in 10- and 30-years, Pearson values between converted maize loss rate (CMLR) or Harikishan Jayanthi's loss rate and loss rate are greater than 0.7, with a S.D. of 0.01. Rank correlation analyses of 28 provinces in China and seven countries in Africa generated Pearson, Kendall and Spearman values greater than 0.48, with a S.D. of 0.05. There was a close correlation between the results and statistical predictions or existing results. Therefore, the simulation results,supply the theoretical support for acting based on local conditions to manage drought and drought risk. (C) 2014 Elsevier B.V. All rights reserved.

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