Damage caused by natural disasters has been increasing throughout the world due to climate change. As part of adaptation strategies, concept of vulnerability to climate change is introduced abroad to identify flood hotspots and to establish improvement measures. However, there has been very few research on vulnerability domestically. In addition, vulnerability studies conducted at a country level was also reported to be unsuitable for sub-country level. In this study, we conduct vulnerability assessment using entropy method for the Nakdong River Basin as part of domestic application. Vulnerability for present condition are first determined, and then changes in vulnerability due to climate change and large-scale river restoration project to identify their impacts. To achieve this, proxy variables that make up the vulnerability index were selected based on literature survey and data availability. Using data collected for this area, weights for proxy variables were then determined by entropy method. Finally, vulnerability was calculated and mapped for the basin. Reviewing the vulnerability maps showed that vulnerability hotspots were consistent with historical flooded areas for present condition. This suggests that the methodology employed is reasonable. The results for future scenario also showed that there were areas where vulnerability is mitigated by the large-scale river restoration project but also increased by climate change. However, the effect of the project in the future is found to be minimal because the decrease in water level by the project is offset by the increase in runoff due to climate change. The methodology presented in this study is thought to be useful in establishing the disaster prevention plan and climate-change adaptation policy by identifying hotspots.
The main objective of this paper is to develop the model for flooding area decision including location, slope, elevation and depth of the flooding area and runoff drainage system thorough SWMM simulation DB and for the display model of the flooding areas. This model also provides the searching service to the historical flooding areas. ArcObject GIS engine and Oracle DBMS is used to model development, and the prototype system programmed with C# is applied to verify the model. The result of the model application analyzes flooding hazard areas of 143.47m2 with flooding depth of 0.08m. The six drainage systems is required improvement for discharge capacity. This research can be used the element technology of the disaster historical system for areas prone to floods.
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