Precondition cloud algorithm and Copula coupling model-based approach for drought hazard comprehensive assessment

Wu, Chengguo; Zhou, Liyang; Zhang, Libing; Jin, Juliang; Zhou, Yuliang

doi:10.1016/j.ijdrr.2019.101220

Cited by 13 publications

(2 citation statements)

References 13 publications

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“…(3) Comprehensive assessment of drought: in order to objectively elaborate the uncertainty of a drought risk system, Bai et al (2018) proposed the precondition cloud and maximum entropy principle coupling model (PCMEP), which can provide a new and reliable way to evaluate the comprehensive risk grade of drought; Wu et al (2019) put forward a precondition cloud algorithm and Copula coupling model, which can be further applied in drought hazard identification and assessment field; by using distributed hydrological modeling, Xu and Pan (2014) introduced a drought model to simulate the drought developing processes. Taking the severe drought events in the upper reaches of the Yangtze River in 2006 as an example, the application case study was carried out.…”

Section: Literature Review 21 Drought Risk Assessmentmentioning

confidence: 99%

Two-stage grey cloud clustering model for drought risk assessment

Luo

Zhang

2019

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Purpose The purpose of this paper is to establish a two-stage grey cloud clustering model to assess the drought risk level of 18 prefecture-level cities in Henan Province. Design/methodology/approach The clustering process is divided into two stages. In the first stage, grey cloud clustering coefficient vectors are obtained by grey cloud clustering. In the second stage, with the help of the weight kernel clustering function, the general representation of the weight vector group of kernel clustering is given. And a new coefficient vector of kernel clustering that integrates the support factors of the adjacent components was obtained in this stage. The entropy resolution coefficient of grey cloud clustering coefficient vector is set as the demarcation line of the two stages, and a two-stage grey cloud clustering model, which combines grey and randomness, is proposed. Findings This paper demonstrates that 18 cities in Henan Province are divided into five categories, which are in accordance with five drought hazard levels. And the rationality and validity of this model is illustrated by comparing with other methods. Practical implications This paper provides a practical and effective new method for drought risk assessment and, then, provides theoretical support for the government and production departments to master drought information and formulate disaster prevention and mitigation measures. Originality/value The model in this paper not only solves the problem that the result and the rule of individual subjective judgment are always inconsistent owing to not fully considering the randomness of the possibility function, but also solves the problem that it’s difficult to ascertain the attribution of decision objects, when several components of grey clustering coefficient vector tend to be balanced. It provides a new idea for the development of the grey clustering model. The rationality and validity of the model are illustrated by taking 18 cities in Henan Province as examples.

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Section: Literature Review 21 Drought Risk Assessmentmentioning

confidence: 99%

Two-stage grey cloud clustering model for drought risk assessment

Luo

Zhang

2019

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“…Many droughts vulnerability studies [18][19][20] have been done at agriculture aspects, with extensive discussions on framework building [21], methodology [22], and index selection [23]. Various drought indexes have been developed to estimate drought vulnerability.…”

Section: Introductionmentioning

confidence: 99%

Drought Vulnerability Assessment and Cluster Analysis of Island Areas Taking Korean Island Areas at Eup (Town) and Myeon (Subcounty) Levels as Study Targets

Shim¹,

Kim²,

Hong³

et al. 2021

Water

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The purpose of this study is to conduct drought vulnerability assessment and cluster analysis of Korean island areas at eup (town) myeon (subcounty) level. Drought vulnerability assessment was conducted using factor analysis and entropy method, and cluster analysis was analyzed using K-means, a nonhierarchical cluster analysis method. Vulnerability consisted of climate exposure, sensitivity, and adaptive capacity. Twenty-two indicators were used to evaluate and analyze vulnerability of drought in small island areas. The results of entropy method showed that winter rainfall, no rainfall days, agricultural population rate, cultivation area rate, water supply rate and groundwater capacity have a substantial impact on drought assessment. The overall assessment of vulnerability indicated that Seodo-myeon Ganghwa-gun, Seolcheon-myeon Namhae-gun, and Samsan-myeon Ganghwa-gun were most vulnerable to drought. The cluster analysis was evaluated by categorizing the regions into three clusters, and policy support and planning are needed to suit the characteristics of each cluster was observed.

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