基于气候变化情景应用的未来滑坡易感区对比分析

Jun Woo Kim, Huicheul Jung, Ho Gul Kim
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引用次数: 0

摘要

背景与目的:多年来,山体滑坡对人类生命和财产造成了重大损害,造成了巨大的社会经济成本和环境退化。随着气候变化的到来,降雨的增加和加剧加剧了山体滑坡的风险。考虑到这种情况,了解滑坡应对的优先事项变得至关重要。本研究的目的是比较未来滑坡易发区域的预测方法,探索准确的预测技术,确定城市层面的滑坡应对重点。研究方法:(1)收集和开发滑坡清查图和滑坡调节因子。(2)利用滑坡盘存图和条件因子构建滑坡敏感性模型(LSM)。(3)将B期和C期的降水数据投影到a期的LSM上。(4)对各情景和年份的滑坡易发地区进行比较和分析。(5)根据B期和c期雨季滑坡易发区最频繁的情景确定滑坡易发区。结果:通过LSM确定A期滑坡易发区为31,902平方公里。在滑坡易发区,所有供给侧平台(SSP)情景均呈现增加趋势,其中SSP5-8.5情景增加最为显著。考虑到这一点,确定了应对滑坡的优先顺序,庆尚南道高城郡以88.4%的LSA比率排名第一。这表明该地区应优先考虑未来的滑坡风险缓解。结论:该研究为未来考虑环境变化的滑坡应对策略提供了基础模型。本研究的局限性在于,在分析未来滑坡易感性时,需要考虑降雨以外的滑坡调节因素。未来的研究将旨在通过更高分辨率的分析和损害规模预测提供更可靠的信息,并辨别反应优先级。
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Comparative Analysis of Future Landslide Susceptible Areas Based on Climate Change Scenario Applications
Background and objective: Landslides have inflicted significant damage to human lives and property for many years, leading to substantial socio-economic costs and environmental degradation. With the advent of climate change, the increase and intensification of rainfall exacerbate the risk of landslides. Considering this scenario, understanding the priorities in landslide response becomes crucial. This study aims to compare methods of predicting future landslide-prone areas, explore accurate forecasting techniques, and determine the landslide response priorities at the municipal level in the study Methods: (1) Collection and development of the landslide inventory map and landslide conditioning factors. (2) Constructing the landslide susceptibility model (LSM) using the landslide inventory map and conditioning factors. (3) Projecting rainfall data from periods B and C onto the LSM of past period A. (4) Comparing and analyzing landslide-prone areas for each scenario and year. (5) Identifying areas vulnerable to landslides based on the scenario with the most frequent occurrence of landslide-prone areas during the rainy seasons in periods B and C.Results: From the LSM, the landslide susceptible area (LSA) for period A was identified as 31,902 ㎢. All Supply-side platform(SSP) scenarios displayed an increasing trend in landslide-prone areas, with the SSP5-8.5 scenario displaying the most significant increase. Taking this into consideration, landslide response priorities were established, with Goseong County in South Gyeongsang ranking first with an LSA ratio of 88.4%. This suggests that this area should be prioritized for future landslide risk mitigation.Conclusion: The study provides a foundational model for future landslide response strategies which consider environmental changes. limitations of the study were challenges in considering landslide conditioning factors other than rainfall when analyzing future landslide susceptibility. Future studies will aim to provide more reliable information through higher resolution analysis and damage scale predictions and to discern response priorities.
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来源期刊
Journal of People, Plants, and Environment
Journal of People, Plants, and Environment Social Sciences-Urban Studies
CiteScore
1.10
自引率
0.00%
发文量
42
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