Assessment of Vulnerability to Climate Change Using Indicators: Methodological Challenges

Abstract

Climate change vulnerability assessment (CCVA) can help policy makers incorporate climate futures in planning. We discuss some of the most important methodological challenges facing CCVA, including geographical and temporal scales, aggregation, and nonlinearity. CCVA literature is large and multidisciplinary and appears to stem from a number of different paradigms (risk assessment, natural disaster management, urban planning, etc.). It is therefore difficult to elicit major directions, findings, and methodologies from this body of work. We study a sample of peer-reviewed CCVA publications and investigate the extent to which the CCVA literature is foregrounding and engaging with these methodological problems. We find that: 1. Critical scrutiny of prevalent assessment methodologies and development of new ones remain limited since only 10 % of the studies focus on such issues. This is despite the fact that many scholars have raised questions about the methodological aspects of vulnerability assessment. 2. Among the studies that aggregate indicators and consider both the biophysical and socioeconomic processes generating vulnerability, 59 % use methods based on multiple attribute utility theory (MAUT) such as arithmetic mean, geometric mean, or GIS-based MAUT, approaches that have strict theoretical requirements which are hardly met in the context of CCVA. 3. Although a number of theoretical papers have argued that indicator-based vulnerability assessment is likely to be most valid at smaller rather than larger geographical scales, only 17 % of studies are conducted at local scale.