In its efforts to tackle climate change Bhutan has undertaken several climate related hazard assessments. The Climate change vulnerability analyses (CCVA) and mapping complements such assessments with analyses and mapping of vulnerability at District level, with a focus on socio-economic and non-climatic, development data with view of enhancing the understanding of the scale of impact of climate change. It also provides actionable information about the social and economic impacts of climate change to inform adaptation planning.
Data Collection Methodology
Step 1: Development of impact chains and Selection of Indicators; Impact chains help understand the factors that drive vulnerability in a system and their cause-and-effect relationship. These were developed based on the key functions of Risk, Hazard, and Vulnerability
Step 2: Descriptive statistics: After the collection of data, the team prepared a descriptive statistics table that described the basic features of the data
Step 3: Normalization of data: The data was normalized (N) by removing the units and converting all the values into dimensionless units that are expressed as values between 0 and 1.
Step 4: Major component: After normalization, the indicators (sub-components) were averaged using the formula of simple arithmetic mean to get the value of average index (AI) for each major component
Step 5: IPCC Contributing factors: The major components as described in the earlier step were multiplied with a balanced weighted method allocated to get the values of IPCC contributing factors (Hazard, Exposure, Sensitivity and Adaptive capacity).
Step 6: Vulnerability Index: The values of sensitivity and adaptive capacity were aggregated to obtain the vulnerability index (VI) value for all the Dzongkhags of Bhutan
Step 7: Risk Index: The values of IPCC contributing factors were aggregated to obtain the risk index value for all the Dzongkhags of Bhutan.
Step 8: Vulnerability and Risk Mapping: The value for risk/vulnerability index ranges from 0 to 1, with higher values reflecting higher degree of risk/vulnerability. The entire range was divided into five categories and assigned a qualitative indicator of risk (from very low to very high) (Žurovec et al., 2017).