Risk evaluation of agricultural drought disaster using a grey cloud clustering model in Henan province, China
| Autor: | Lili Ye, Dang Luo, Decai Sun |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
021110 strategic
defence & security studies 010504 meteorology & atmospheric sciences business.industry 0211 other engineering and technologies Geology Cloud computing 02 engineering and technology Building and Construction Geotechnical Engineering and Engineering Geology 01 natural sciences Hazard Agriculture Scale (social sciences) Environmental science business China Risk assessment Water resource management Safety Research Risk management 0105 earth and related environmental sciences Panel data |
| Zdroj: | International Journal of Disaster Risk Reduction. 49:101759 |
| ISSN: | 2212-4209 |
| DOI: | 10.1016/j.ijdrr.2020.101759 |
| Popis: | Frequent drought is a critical limiting factor for regional agriculture development. Accurately evaluating regional agricultural drought risk contributes to raising disaster risk management and reducing drought disaster losses. This paper proposes a grey cloud clustering model based on panel data to assess the agricultural drought disaster risk of Henan province. The new model includes two parts. One component is indicator and time weights determination which uses the grey incidence analysis methods, the maximum deviation and maximum entropy principle, respectively. The other part is the construction of grey cloud possibility function which calculates the drought disaster risk grade. Then, the proposed model is applied for assessing the agricultural drought disaster risk of Henan Province at the regional scale, and the time scale selected is from 2012 to 2016. The agricultural drought disaster presents different spatial distribution in drought hazard, exposure, damage sensitivity and drought resistance capacity. The comprehensive risk evaluation results indicate that the drought risk in the most northern and southern regions of Henan Province is lower, while the western, mid-western and eastern regions have a higher risk. Compared with the traditional assessment models for disaster risk, the proposed model can recognize the random, fuzzy and grey uncertainties of the agricultural drought disaster system. Thus, it is a beneficial tool for drought disaster risk assessment and can help to make some suggestions for drought disaster mitigation. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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