Snow Disaster Risk Index in the Ulsan Metropolitan City

Park, Heeseong; Lee, Seung Joon; Yu, Insang; Jeong, Sangman; Chung, Gunhui

doi:10.9798/kosham.2014.14.2.97

Cited by 14 publications

(5 citation statements)

References 4 publications

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“…전 세계적인 인류의 발전은 우리의 삶을 양적으로 질적으 로 풍요롭고 윤택하게 해주었다. 그러나 인류의 발전은 양날 의 검과도 같이 지구온난화, 기후변화, 생태계 파괴 등과 같은 다양한 형태로 우리에게 위협을 가해왔다 (Yu, 2017 (Kim et al, 2012;Park, 2012;Song, 2012;KEI, 2014 ;Park et al, 2014;Cho, 2015;Han et al, 2015;Hwang, 2015;Nam, 2015 (Son et al, 2013). 이와 같이 위험도뿐 만 아니라 기후변화의 취약성 평가에 대한 연구는 최근 들어 국내외적으로 활발하게 진행되고 있다 (IPCC, 2001;Kelly and Adger, 2000;Moss et al, 2001;Brooks et al, 2005;Eriksen and Kelly, 2007 (Lee and Chang, 2014;Shin et al, 2014;Choi et al, 2015;Oh et al, 2015;Jeong et al, 2016;Park et al, 2016;Shin, 2016 Fig.…”

Section: 서 론unclassified

Grid-Based Flood Risk Mapping Considering Indices of Regional Characteristics

Yu¹,

Kim²,

Jeong³

2018

J. Korean Soc. Hazard Mitig

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This study developed a grid-based flood risk map with indices considering the regional characteristics of Daegu City, Ulsan City, Gyeongsangbuk-do, and Gangwon-do. Indices for mapping flood risk such as flood depth, population density, population ratio vulnerable to disaster, and rainwater storage capacity consist of hazard, exposure, vulnerability, and disaster coping and adaptive capacity. These four indices have a variety of sub-indices. Weights of indices and sub-indices were determined through analytic hierarchy process, and then values for the indices and sub-indices were standardized using z-score method. The flood risk was estimated by performing arithmetic operations on the four indices that were calculated through standardized values of sub-indices using the computed weight. The results show that the central and northern areas of Gangwon-do, namely Wonju City, Hoengseong-gun, Hongcheon-gun, Gangneung City, and so on were classified to be more than "high risk" throughout the area. Jung-gu and Nam-gu of Ulsan City located downtown near Taehwa river, Dalseong-gun and Dalseo-gu of Daegu City located in low-lying area near Nakdong river, and some lowlands near Hyeongsan river of Gyeongju City and Pohang City were determined to have "very high risk." The flood risk map developed in this study is expected to support decision makers in establishing countermeasures to mitigate flood disasters for grid-based small areas.

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Section: 서 론unclassified

Grid-Based Flood Risk Mapping Considering Indices of Regional Characteristics

Yu¹,

Kim²,

Jeong³

2018

J. Korean Soc. Hazard Mitig

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“…Park et al utilized the PSR method to analyze their proposed snow disaster risk indices. They applied a hierarchical analysis and the entropy weight method in determining indicator weights to identify the area vulnerable to snow disasters [6]. Yu et al utilized nearly a century of observed data from weather stations in Korea to analyze snowfall frequencies.…”

Section: Introductionmentioning

confidence: 99%

Snow Disaster Risk Assessment Based on Long-Term Remote Sensing Data: A Case Study of the Qinghai–Tibet Plateau Region in Xizang

Sun,

Miao,

Feng

et al. 2024

Remote Sensing

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The risk analysis and assessment of snow disasters are essential foundational tasks in natural disaster management and profoundly impact the scientific and precise formulation of disaster prevention, preparedness, and mitigation strategies. Employing the theory and methodology of snow disaster assessment, this research focuses on historical and potential snow disasters in the Qinghai–Tibetan Plateau (QTP) Region. Utilizing a long-time-series snow depth remote sensing dataset, we extracted six assessment indicators for historical snow disaster risk factors and potential snow disaster risk factors. We determined the weights of these six assessment indicators using the entropy weight method. Subsequently, we established a snow disaster assessment model to evaluate the grade distribution of snow disasters in the study area. This method can effectively solve the problem of the sparse data distribution of meteorological stations and reflect degrees of snow disaster risk on a large spatial scale. The findings reveal that areas with a relatively high snow disaster risk are primarily concentrated in the western part of the Ali Region, the central part of Chamdo, and near the border in Southern Xizang. Additionally, regions with a high frequency of snow disasters are predominantly located at the junction of Nagchu, Chamdo, and Nyingchi in the eastern part of Xizang. These results contribute valuable insights into the risk assessment of snow disasters and facilitate the development of effective strategies for disaster management in the region.

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“…To effectively mitigate regional disaster risk, it is crucial to identify the spatial patterns of snow disaster hazards and assess them through analysis of disaster factors and environmental conditions. Previous studies have used semi-quantitative methods, such as the analytic hierarchy process (AHP), fuzzy integrated evaluation, and Delphi method, to assess snow disaster hazards by selecting multiple causal factors [22][23][24][25]. However, these methods can only qualitatively reflect snow hazards and disaster magnitude.…”

Section: Introductionmentioning

confidence: 99%

Snow Disaster Hazard Assessment on the Tibetan Plateau Based on Copula Function

Xu,

Huang,

Mou

et al. 2023

Sustainability

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In the context of global climate change, the Tibetan Plateau is particularly susceptible to meteorological disasters, including snow disasters. This study utilized daily temperature and precipitation data from 44 meteorological stations on the Tibetan Plateau spanning from 1960 to 2018 to construct a snow event dataset. Optimal marginal distribution and the copula function were chosen to calculate the joint return period and joint probability, which effectively assess the hazard of snow disasters in the region. Additionally, the study analyzed the comprehensive risk of snow disasters under various return periods by integrating social and economic data. The results indicate the following: (1) Based on the five different Archimedean copula functions, the joint return period of an error rate of each station was calculated to be less than 36%, which is significantly lower than the recurrence interval of univariate analysis; (2) High-hazard areas are predominantly concentrated in the northwest region of the Tanggula Mountains and the eastern foothills of the Bayankara Mountains. As the return period increases, the spatial distribution of snow disaster hazard probability shifts gradually from “double-core” to continuous distribution; and (3) the northwestern Karakorum Mountains and Bayankara Mountains are two distinct high-risk areas for snow disasters. The range of high-risk areas in the region expands with an increase in the return period.

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Snow Disaster Risk Index in the Ulsan Metropolitan City

Cited by 14 publications

References 4 publications

Grid-Based Flood Risk Mapping Considering Indices of Regional Characteristics

Grid-Based Flood Risk Mapping Considering Indices of Regional Characteristics

Snow Disaster Risk Assessment Based on Long-Term Remote Sensing Data: A Case Study of the Qinghai–Tibet Plateau Region in Xizang

Snow Disaster Hazard Assessment on the Tibetan Plateau Based on Copula Function

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