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Agricultural Drought Risk Evaluation Based on an Optimized Comprehensive Index System

Author

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  • Menghua Deng

    (Institute of Management Science, Hohai University, Nanjing 210098, China)

  • Junfei Chen

    (Institute of Management Science, Hohai University, Nanjing 210098, China
    State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China)

  • Jing Huang

    (Institute of Management Science, Hohai University, Nanjing 210098, China
    State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China)

  • Wenjuan Niu

    (Institute of Management Science, Hohai University, Nanjing 210098, China
    State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China)

Abstract

In this study, a new optimized comprehensive drought index system (OCDIS) was developed based on pressure-state-response (PSR) and random forest (RF). Then the pressure, state, response, and integrated agricultural drought risk were evaluated according to the synthetic-weight variable fuzzy set (SW-VFS) model. Finally, the countermeasures in terms of pressure, state, and response were discussed. The proposed index has been implemented in Qujing, Yunnan Province, China. The results showed that of the 10 indices included in the OCDIS, the four most important indices for agricultural drought risk management are reservoir storage capacity, precipitation anomaly percentage, soil moisture, and per capita annual income. The pressure risk and response risk of Malong are relatively higher than other counties. The integrated results indicated that most counties of Quijng have moderate drought risk. The assessment results are consistent with the actual situation of Qujing. The proposed model provides a scientific and objective way to develop the risk index system of agricultural drought. This study can potentially assist government agencies with information on the most important drought impacts and provide the basis for science-informed decision-making.

Suggested Citation

  • Menghua Deng & Junfei Chen & Jing Huang & Wenjuan Niu, 2018. "Agricultural Drought Risk Evaluation Based on an Optimized Comprehensive Index System," Sustainability, MDPI, vol. 10(10), pages 1-22, September.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:10:p:3465-:d:172566
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    References listed on IDEAS

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    1. George Tsakiris, 2017. "Drought Risk Assessment and Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(10), pages 3083-3095, August.
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    Cited by:

    1. Yuangang Li & Maohua Sun & Guanghui Yuan & Qi Zhou & Jinyue Liu, 2019. "Study on Development Sustainability of Atmospheric Environment in Northeast China by Rough Set and Entropy Weight Method," Sustainability, MDPI, vol. 11(14), pages 1-22, July.
    2. Xinyue Ke & Ni Wang & Long Yu & Zihan Guo & Tianming He, 2023. "Spatial Distribution of Water Risk Based on Atlas Compilation in the Shaanxi Section of the Qinling Mountains, China," Sustainability, MDPI, vol. 15(12), pages 1-21, June.

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