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Article

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

1
State Key Laboratory Base of Eco-Hydraulic Engineering in Arid Area, Xi’an University of Technology, Xi’an 710048, China
2
School of Mechanical and Vehicle Engineering, Bengbu University, Bengbu 233030, China
3
School of Civil Engineering, Hefei University of Technology, Hefei 230009, China
*
Author to whom correspondence should be addressed.
Sustainability 2018, 10(9), 3236; https://doi.org/10.3390/su10093236
Submission received: 8 July 2018 / Revised: 30 August 2018 / Accepted: 31 August 2018 / Published: 10 September 2018

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.
Keywords: drought risk; drought indicator; cloud model; principle of maximum entropy; certainty degree; Kunming city drought risk; drought indicator; cloud model; principle of maximum entropy; certainty degree; Kunming city

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MDPI and ACS Style

Bai, X.; Wang, Y.; Jin, J.; Qi, X.; Wu, C. Precondition Cloud and Maximum Entropy Principle Coupling Model-Based Approach for the Comprehensive Assessment of Drought Risk. Sustainability 2018, 10, 3236. https://doi.org/10.3390/su10093236

AMA Style

Bai X, Wang Y, Jin J, Qi X, Wu C. Precondition Cloud and Maximum Entropy Principle Coupling Model-Based Approach for the Comprehensive Assessment of Drought Risk. Sustainability. 2018; 10(9):3236. https://doi.org/10.3390/su10093236

Chicago/Turabian Style

Bai, Xia, Yimin Wang, Juliang Jin, Xiaoming Qi, and Chengguo Wu. 2018. "Precondition Cloud and Maximum Entropy Principle Coupling Model-Based Approach for the Comprehensive Assessment of Drought Risk" Sustainability 10, no. 9: 3236. https://doi.org/10.3390/su10093236

APA Style

Bai, X., Wang, Y., Jin, J., Qi, X., & Wu, C. (2018). Precondition Cloud and Maximum Entropy Principle Coupling Model-Based Approach for the Comprehensive Assessment of Drought Risk. Sustainability, 10(9), 3236. https://doi.org/10.3390/su10093236

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