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Precondition Cloud and Maximum Entropy Principle Coupling Model-Based Approach for the Comprehensive Assessment of Drought Risk

Author

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  • Xia Bai

    (State Key Laboratory Base of Eco-Hydraulic Engineering in Arid Area, Xi’an University of Technology, Xi’an 710048, China
    School of Mechanical and Vehicle Engineering, Bengbu University, Bengbu 233030, China)

  • Yimin Wang

    (State Key Laboratory Base of Eco-Hydraulic Engineering in Arid Area, Xi’an University of Technology, Xi’an 710048, China)

  • Juliang Jin

    (School of Civil Engineering, Hefei University of Technology, Hefei 230009, China)

  • Xiaoming Qi

    (School of Mechanical and Vehicle Engineering, Bengbu University, Bengbu 233030, China)

  • Chengguo Wu

    (School of Civil Engineering, Hefei University of Technology, Hefei 230009, China)

Abstract

As a frequently occurring natural disaster, drought will cause great damage to agricultural production and the sustainable development of a social economy, and it is vital to reasonably evaluate the comprehensive risk level of drought for constructing regional drought-resistant strategies. Therefore, to objectively expound the uncertainty of a drought risk system, the precondition cloud and maximum entropy principle coupling model (PCMEP) for drought risk assessment is proposed, which utilizes the principle of maximum entropy to estimate the probability distribution of cloud drops, and the two-dimensional precondition cloud algorithm to determine the certainty degree of drought risk. Moreover, the established PCMEP model is further applied in a drought risk assessment study in Kunming city covering 1956–2011, and the results indicate that (1) the probability of drought events for different levels exhibits a slight increasing trend among the 56 historical years; and (2) both the integrated certainty degree and its component of drought risk are more evident, which will be more beneficial to determine the drought risk level. In general, the proposed PCMEP model provides a new reliable idea to evaluate the comprehensive risk level of drought from a more objective and systematic perspective.

Suggested Citation

  • Xia Bai & Yimin Wang & Juliang Jin & Xiaoming Qi & Chengguo Wu, 2018. "Precondition Cloud and Maximum Entropy Principle Coupling Model-Based Approach for the Comprehensive Assessment of Drought Risk," Sustainability, MDPI, vol. 10(9), pages 1-14, September.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:9:p:3236-:d:168935
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    Cited by:

    1. Jian Liu & Kangjie Wang & Shan Lv & Xiangtao Fan & Haixia He, 2023. "Flood Risk Assessment Based on a Cloud Model in Sichuan Province, China," Sustainability, MDPI, vol. 15(20), pages 1-19, October.
    2. Feifei Jin & Lidan Pei & Huayou Chen & Reza Langari & Jinpei Liu, 2019. "A Novel Decision-Making Model with Pythagorean Fuzzy Linguistic Information Measures and Its Application to a Sustainable Blockchain Product Assessment Problem," Sustainability, MDPI, vol. 11(20), pages 1-17, October.

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