Classification of risk levels for snow damage estimation considering socioeconomic factors in South Korea

IF 5.7 3区 环境科学与生态学 Q1 WATER RESOURCES Applied Water Science Pub Date : 2024-10-25 DOI:10.1007/s13201-024-02297-x
Hyeongjoo Lee, Donghyun Kim, Gunhui Chung
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Abstract

In South Korea, the snowy season spans from October to April, and the annual average snowfall varies significantly depending on specific regions, latitudes, and elevations, ranging from 0 to 260 cm. The average annual snowfall in South Korea is 25.1 cm. Despite of the relatively shallow snowfall depth, over the past decade, South Korea has experienced approximately 120 million dollars in damages attributed to snow-related incidents. In this study, the DPSIR (Driver-Pressure-State-Impact-Response) framework was employed to consider the meteorological and socioeconomic factors to calculate the snow damage vulnerability. A total of 17 indicators were taken into account to comprehend meteorological conditions, socioeconomic factors, and historical damage records from 1994 to 2020. However, due to the limited availability of meteorological observatories and changes in greenhouse design standards, accurately estimating the snow damage amount poses challenges. Therefore, based on the vulnerability, the risk levels were classified into four categories and estimated snow damage generated by the categorized models was compared with those of the model constructed using the entire dataset. The categorized models offer improved estimation results, as the meteorological and socioeconomic characteristics within each category differ and should be addressed separately in modeling. Among the categorized models, the Green zone exhibited the best results, primarily because it did not include outlier snow damage incidents. The developed model in this study could be utilized to mitigate the impact of heavy snowfall and prioritize snow removal regions.

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考虑韩国社会经济因素的雪灾估算风险等级划分
韩国的雪季从 10 月持续到次年 4 月,年平均降雪量因地区、纬度和海拔高度的不同而有很大差异,从 0 厘米到 260 厘米不等。韩国的年平均降雪量为 25.1 厘米。尽管降雪深度相对较浅,但在过去十年中,韩国因降雪相关事故造成的损失约为 1.2 亿美元。本研究采用 DPSIR(动因-压力-状态-影响-反应)框架,考虑气象和社会经济因素来计算雪灾脆弱性。共考虑了 17 项指标,包括气象条件、社会经济因素以及 1994 年至 2020 年的历史雪灾记录。然而,由于气象观测站的有限性和温室设计标准的变化,准确估算雪灾损失量面临挑战。因此,根据脆弱性将风险等级分为四类,并将分类模型生成的雪灾损失估计与使用整个数据集构建的模型进行比较。分类模型提供了更好的估算结果,因为每个类别中的气象和社会经济特征各不相同,在建模时应分别处理。在分类模型中,绿色区域的结果最好,主要是因为它不包括异常雪灾事件。本研究开发的模型可用于减轻强降雪的影响,并确定除雪区域的优先次序。
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来源期刊
Applied Water Science
Applied Water Science WATER RESOURCES-
CiteScore
9.90
自引率
3.60%
发文量
268
审稿时长
13 weeks
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