Assessing climate change vulnerability with group multi-criteria decision making approaches

This study developed an approach to assess the vulnerability to climate change and variability using various group multi-criteria decision-making (MCDM) methods and identified the sources of uncertainty in assessments. MCDM methods include the weighted sum method, one of the most common MCDM methods, the technique for order preference by similarity to ideal solution (TOPSIS), fuzzy-based TOPSIS, TOPSIS in a group-decision environment, and TOPSIS combined with the voting methods (Borda count and Copeland’s methods). The approach was applied to a water-resource system in South Korea, and the assessment was performed at the province level by categorizing water resources into water supply and conservation, flood control and water-quality sectors according to their management objectives. Key indicators for each category were profiled with the Delphi surveys, a series of questionnaires interspersed with controlled opinion feedback. The sectoral vulnerability scores were further aggregated into one composite score for water-resource vulnerability. Rankings among different MCDM methods varied in different degrees, but noticeable differences in the rankings from the fuzzy- and non-fuzzy-based methods suggested that the uncertainty with crisp data, rather widely used, should be acknowledged in vulnerability assessment. Also rankings from the voting-based methods did not differ much from those from non-voting-based (i.e., average-based) methods. Vulnerability rankings varied significantly among the different sectors of the water-resource systems, highlighting the need to assess the vulnerability of water-resource systems according to objectives, even though one composite index is often used for simplicity.

[1]  Mohamed A. Hamouda,et al.  Vulnerability Assessment of Water Resources Systems in the Eastern Nile Basin , 2009 .

[2]  Richard Bellman,et al.  Decision-making in fuzzy environment , 2012 .

[3]  J. Seager,et al.  Perspectives and limitations of indicators in water management , 2001 .

[4]  Richard J. T. Klein,et al.  Climate Change Vulnerability Assessments: An Evolution of Conceptual Thinking , 2006 .

[5]  J. Palutikof,et al.  Climate change 2007 : impacts, adaptation and vulnerability , 2001 .

[6]  Guangtao Fu,et al.  A fuzzy optimization method for multicriteria decision making: An application to reservoir flood control operation , 2008, Expert Syst. Appl..

[7]  Donald G. Saari,et al.  Mathematical Complexity of Simple Economics , 1996 .

[8]  E. Stanley Lee,et al.  An extension of TOPSIS for group decision making , 2007, Math. Comput. Model..

[9]  Yang Qing,et al.  A multi-objective fuzzy pattern recognition model for assessing groundwater vulnerability based on the DRASTIC system , 1999 .

[10]  Ta-Chung Chu,et al.  Facility Location Selection Using Fuzzy TOPSIS Under Group Decisions , 2002, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[11]  Eun-Sung Chung,et al.  Integrated multi-criteria flood vulnerability approach using fuzzy TOPSIS and Delphi technique , 2013 .

[12]  Nils Brunsson My own book review : The Irrational Organization , 2014 .

[13]  Eun-Sung Chung,et al.  Identification of Spatial Ranking of Hydrological Vulnerability Using Multi-Criteria Decision Making Techniques: Case Study of Korea , 2009 .

[14]  Eun-Sung Chung,et al.  A fuzzy multi-criteria approach to flood risk vulnerability in South Korea by considering climate change impacts , 2013, Expert Syst. Appl..

[15]  Chih-Hung Wang,et al.  A multiattribute GDSS for aiding problem-solving , 2004 .

[16]  Ching-Lai Hwang,et al.  Multiple Attribute Decision Making: Methods and Applications - A State-of-the-Art Survey , 1981, Lecture Notes in Economics and Mathematical Systems.

[17]  S. Eriksen,et al.  Developing Credible Vulnerability Indicators for Climate Adaptation Policy Assessment , 2007 .

[18]  Eun-Sung Chung,et al.  Development of spatial water resources vulnerability index considering climate change impacts. , 2011, The Science of the total environment.

[19]  Lynn P. Nygaard,et al.  Mapping vulnerability to multiple stressors: climate change and globalization in India , 2004 .

[20]  Matti Eronen Global climatic changes , 2008 .

[21]  Eun-Sung Chung,et al.  Fuzzy VIKOR approach for assessing the vulnerability of the water supply to climate change and variability in South Korea , 2013 .

[22]  Elizabeth L. Malone,et al.  VULNERABILITY TO CLIMATE CHANGE A Quantitative Approach , 2001 .

[23]  W. Adger,et al.  The determinants of vulnerability and adaptive capacity at the national level and the implications f , 2005 .