| 摘要: |
| 暴露指数反映了环境在面对极端天气事件时承受灾害的潜在风险程度。研究利用遥感影像数据、数字高程数据(DEM)、海洋水深及风力数据等, 基于暴露指数模型, 以福建省东山湾为案例研究区域, 对风暴潮灾害情景下的海岸带暴露指数及其时空演变进行分析。研究结果显示: (1)近十年来, 东山湾海岸带暴露指数总体呈下降趋势, 潜在风险程度为“中”及以上区域占比由67.14%下降至59.06%, 海岸带在面对风暴潮灾害等极端天气事件时潜在的风险程度总体降低, 海湾地貌类型差异及其形态变化是影响东山湾暴露指数产生波动的主要原因; (2)基于暴露指数评价结果, 结合海岸带开发利用现状, 研究可对东山湾海岸带生态环境的敏感区域进行识别, 并制定具有针对性的开发利用与风险防范对策, 为海岸带空间规划、生态保护修复格局的科学划定提供理论支撑, 在助力海岸带陆海统筹和可持续发展上具有重要意义; (3)研究提出的一种基于时间序列的暴露指数研究技术路线和框架, 可为海岸带脆弱性评估、海岸带韧性评估、海岸带灾害监测预警等相关研究提供新的研究视角, 在基于深度学习的海岸带灾害风险预警与灾害模拟等方面也具有较为广阔的应用前景。 |
| 关键词: 暴露指数模型 风暴潮灾害 生态环境潜在风险 海岸带 东山湾 |
| DOI：10.11759/hykx20220824001 |
| 分类号: |
| 基金项目:中央级公益性科研院所(自然资源部第三海洋研究所)基本科研业务费专项(海三科2022016) |
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| Spatiotemporal evolution of the exposure index in coastal zones from the context of storm surge disaster: Dongshan Bay, Fujian province |
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WANG Chao, HUANG Fa-ming, CHEN Hua-xiang, YIN Fei-jian, SHI Rong-can, YANG Li-jing
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Third Institute of Oceanography, Ministry of Natural Resources(MNR), Fujian Provincial Key Laboratory of Marine Physical and Geological Processes, Xiamen 361005, China
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| Abstract: |
| The exposure index (EI) indicates the potential risk of possible natural disasters to an ecosystem. This study analyzes the EI and its spatiotemporal evolution based on storm surge disasters. To this end, we selected Dongshan Bay, Fujian Province, as the study area and used a combination of remote-sensing images, the digital elevation model, as well as the wind and wave data. The analysis is based on the EI evaluation model, and the following results are obtained from the study. (1) In the past decade, the EI of Dongshan Bay has been observed to decrease; the fraction of regions with “medium–high” potential risk decreased from 67.13% to 59.06%. Further, the potential risk of coastal zones decreased in the face of extreme weather conditions, such as storm surge disasters. Changes in the geomorphologic type and shoreline spatial position are primarily responsible for fluctuations in the EI in the coastal zone of Dongshan Bay. (2) Based on the degree of the potential risk and utilization status, ecologically sensitive regions in the coastal zone are identified and evaluated. This study thus proposes targeted countermeasures for the development and risk prevention to support spatial planning and scientific delineation of ecological protection and restore coastal zones. The results could considerably facilitate the overall land–sea planning and sustainable development of coastal zones. (3) Finally, this study proposes a technical route and framework for long-term EI research, providing new prospects for assessing the vulnerability and resilience of coastal zones. The proposed methodology, based on deep learning in coastal zones, is broadly applicable in the field of disaster and disaster simulation. |
| Key words: exposure index model storm surge disaster potential risk of ecological environment coastal zone Dongshan Bay |
