Prediction of Economic Damage Caused by Heavy Snowfall Considering Climate Change

Ha， Ji Hye; Kang， Jung Eun

doi:10.15793/kspr.2020.104..010

This study developed prediction models of economic damage caused by heavy snowfall disasters as a starting point for the preparation of the measures of heavy snow, and examined the changes of future damage by reflecting future climate change scenarios. We employed panel tobit analyses for developing two facility-specific damage models (structure/agriculture and forestry/fisheries facilities). The results showed that significant increases in average new snowfall, maximum new snowfall and new snowfall days over 20cm influenced the economic damage increase. Furthermore, local governments with more sum snowfall and larger urban areas had less damage. Applying a climate change scenario to the forecast models, the predicted damages caused by snowfall disasters in the future(2030 and 2050) were ranged from 5.18 trillion won to 6.17 trillion won. Thus, we need to prepare for economic damage although it is difficult to conclude that the future damage will increase unconditionally compared to the present. Quantitative analysis of property damage based on the information currently available and climate change scenario can play a critical role in making decisions and prioritizing policies.

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