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Snow vulnerability analysis was implemented using 400 years of controlled RCP 2.6, 4.5, 6.0, and 8.5 scenarios in the following divided periods: the former period (2011-2040), middle period (2041-2070), and later period (2071-2100). Data from a total of 74 meteorological stations were used and the Thiessen polygon method was applied in the areas without stations. The indicators were classified into the Pressure-State-Response (PSR) structure, and the weight for vulnerability analysis was calculated using the entropy method. As snow vulnerability analysis was implemented for the future scenarios, it was difficult to determine social and economic factors as indicators; thus, only predicted weather data and population trends were considered. As a result, the rankings for snow vulnerable areas were determined for each period and scenario. Overall, snow vulnerability would decrease due to the decrease in long-term heavy snowfall in climate change scenarios. However, increased snow vulnerability is also expected in Sejong-si and the western coastal area due to a rise in population and snow depth in the future. Based on this, disaster prevention projects considering the characteristics of the region in the future could be implemented.

Snow Vulnerability Analysis in the Korean Peninsula using RCP Climate Change Scenarios