Chae Yeon Park (Korea, Republic of) 1; Dong Kun Lee (Korea, Republic of) 1; Jiyeon Kim (Korea, Republic of) 1
1 - Seoul National University
Climate change adaptation (CCA) in local government is very important since it can develop the adaptation that fit their local condition. However, there are many barriers for local government to develop adaptation plans: lack of awareness, lack of fund, an indifferent attitude. EU (2013) recommended researchers to provide information and methodology about the climate change adaptation using portal or toolkit. Also, they highlighted that central government should support local funding using multi-level government framework. However the last barrier has not been referred before. When the damage from climate change is not extreme, local governments, who have lower ability to deal with climate change adaptation, are easy to assume an indifferent attitude toward the adaptation. For this reason, we suggest the new concept of the decision support tool that provide easy-to-use steps for creating priority of adaptation options to the local governments who don’t have enough ability to build the CCA plan. Instead of relieving their burden, the experts’ opinions are systemically reflected in the tool in advance.
The purpose of this study is suggesting the framework of the support tool and case study in the water management sector. In the framework, we proposed how to prioritize adaptation options. We used ‘assembly form’ as a broker who gathers experts’ opinion through meetings and survey. Firstly we set up the items of questionnaire such as the adaptation options’ list and scoring criteria. Secondly, we did multi-criteria analysis using the result of expert survey. As the result of case study, 21 options were categorized with 3 policies (flood, drought, and water quality) and they scored with 7 criteria. And finally, expansion of sewage reuse, safety system at land development, and Ecological river and wetland composition came up with first option in the flood, drought, and water quality policies, respectively. This result could differ depending on the local government by changing the score of feasibility (one of the criteria) and the weight of criteria. Thus, we confirmed how the results change according to the feasibility and weight. We expect that this system can support local government to develop their own adaptation plans with reliable data.