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| Risk Analysis on the Impact of Typhoon Disaster to Agriculture—A Case Study of Yangjiang City |
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| DOI：10.16768/j.issn.1004-874X.2020.10.020 |
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| Abstract: |
| 【Objective】The research is to analyze the risk of the impact of super typhoon“Mangkhut”on the agriculture of Yangjiang City. Specifically, the important factors of typhoon disasters influencing the agriculture were quantitatively identified to provide references for the prevention of typhoon disasters and the work of post-disaster reconstruction.【Method】With the support of GIS, the natural disaster risk index and the weighted comprehensive evaluation method are used to establish a comprehensive risk assessment model for the impact of typhoon on agricultural production to carry out typhoon risk zoning. The model covers sensitivity, exposure and disaster resistance. In addition, the important driving factors of the impact of typhoon disasters on regional agriculture were quantitatively identified based on the geographic detector method.【Result】The areas of the highest agricultural risk area, higher risk area and medium risk area of typhoon disaster in Yangjiang City account for 0.52%, 0.06%, and 13.5% of the area of agricultural production in the study area, respectively. Totally, the areas of lower risk area and the lowest risk area account for 85.87% of the area of agricultural production. The q value of the influence of the three driving factors of sensitivity, exposure, and disaster resistance on the disaster risk index is 0.12, 0.04, and 0.07, respectively. The q value of the combined effect of sensitivity factor and disaster resilience factor on disaster risk index is 0.24.【Conclusion】The typhoon disaster risk level decreases gradually from the coast to the inland, and is closely related to the terrain. The risk index of flat cropping and fishing areas along the coast and hinterland is high and that of the northern forests is relatively lower. The sensitivity has the greatest influence on the risk index, followed by disaster and exposure. There are significant differences in the degree of influence and spatial characteristics of different driving factors on the risk index, and the combination of every two driving factors will increase the risk index. |
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