Typhoons cause severe monetary damage globally. Many global insurance companies and public agencies are currently developing and utilizing windstorm risk estimation models to calculate the level of risk and set up strategies for avoiding, mitigating, and relocating those economic risks. Hence, the usage and accuracy of the windstorm risk estimation model is becoming increasingly significant, and reflecting local vulnerabilities is essential for refined risk assessment. While key risk indicators have been recognized in practical studies of economic losses associated with windstorms, there remains a lack of comprehensive research addressing the relationship between economic losses of residential buildings for South Korea and vulnerability. This research investigates the real damage record of Typhoon Maemi from an insurance company in order to bridge this gap. The aim of this study is to define the damage indicators of typhoons and create a framework for typhoon damage function, using the damage caused by Typhoon Maemi as a representative paradigm. Basic building information and natural disaster indicators are adopted to develop the damage function. The results and metric of this research provide a pragmatic approach that helps create damage functions for insurance companies and contingency planners, reflecting the actual financial losses and local vulnerabilities of buildings. The framework and results of this study will provide a practical way to manage extreme cases of natural disasters, develop a damage function for insurers and public authorities, and reveal the real economic damage and local vulnerability of residential buildings in South Korea.
The purpose of this research is to identify the indicators of typhoon damage and develop a metric for typhoon vulnerability functions employing the losses associated with Typhoon Maemi. Typhoons cause significant financial damages worldwide every year. Federal and local governments, insurance companies, and construction companies strive to develop typhoon risk assessment models and use them to quantify the risks so that they can avoid, mitigate, or transfer the financial risks. Therefore, typhoon risk assessment modeling is becoming increasingly important, and in order to achieve a sophisticated evaluation, it is also important to reflect more specified and local vulnerabilities. Although several previous studies on economic loss associated with natural catastrophe have identified essential risk indicators, there has been a shortage of more specific research studies focusing on the correlation between vulnerability and economic loss caused by typhoons. In order to fill this gap, this study collected and analyzed the actual loss record of Typhoon Maemi collected and accumulated by a major insurance company in Korea. In order to create the vulnerability functions and to identify the natural hazard indicators and basic building information indicators, information from the insurance record was used in the analysis. The results and metric of this research provide a pragmatic approach that helps create vulnerability functions for abovementioned sectors and like estimating local vulnerabilities and predicting and coping with the possible damage and loss from typhoons.
Tunnel construction, a common byproduct of rapid economic growth and transportation-system development, carries inherent risks to life and various kinds of property that operations and management professionals must take into account. Due to various and complicated geological conditions, tunnel construction projects can produce unexpected collapses, landslides, avalanches, and water-related hazards. Moreover, damage from such events can be intensified by other factors, including geological hazards caused by natural disasters, such as heavy rainfall and earthquakes, resulting in huge social, economic, and environmental losses. Therefore, the present research conducted multiple linear regression analyses on financial-loss data arising from tunnel construction in Korea to develop a novel tunnel-focused method of natural-hazard risk assessment. More specifically, the total insured value and actual value of damage to 277 tunnel-construction projects were utilized to identify significant natural-disaster indicators linked to unexpected construction-budget overruns and construction-scheduling delays. Damage ratios (i.e., actual losses over total insured project value) were used as objective, quantitative indices of the extent of damage that can be usefully applied irrespective of project size. Natural-hazard impact data—specifically wind speed, rainfall, and flood occurrences—were applied as the independent variables in the regression model. In the regression model, maximum wind speed was found to be correlated with tunnel projects’ financial losses across all three of the natural-hazard indicators. The present research results can serve as important baseline references for natural disaster-related risk assessments of tunnel-construction projects, and thus serve the wider purpose of balanced and sustainable development.
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