Role of Climate Change in Vulnerability Assessments

Vulnerability assessment protocols, such as RAMCAP, estimate a system risk by adding the risks of all meaningful hazards of each individual critical component. Whenever a system includes several distributed critical components, like in the case of water systems, the estimates for risks can include a large number of terms whose significance can be hard to prioritize. Whenever the potential effects of climate change induced hazards are included in an assessment, the prioritization of risks then become even harder.

In these cases, alternate approaches to risk analysis can be developed whenever the scope of the vulnerability assessments are triggered by communities' needs for coping with change in severe weather patterns. In fact, in the case of natural hazards, it is possible to distinguish between probability estimates obtained from statistical distribution of historical data and estimates obtained combining climate model projections with statistical considerations. The different natures of the two types of estimates and the inadequate availability of direct statistics on the performance of climate models prevent direct comparisons of the separate types of risk measurements.

Probability distributions of historical data provide estimates of exceedances whose validity is under scrutiny since current changes in severe weather patterns may invalidate the stationarity hypothesis on which they are based. However, alternative methods for computing natural hazards from a climate model with proven ability to reproduce past environmental changes are still under evaluation and their validity still needs to be verified.

During recent research efforts, an ontological model, named the Vulnerability Upper Model (VUM), was developed with the aim to support a better understanding of how risks estimation and vulnerability assessments of water systems can be conceptually interconnected to facilitate the comparisons of different methodologies in risk analysis. Since the VUM enables its users to differentiate between viewpoints of stakeholders with different areas of interest and technical backgrounds, a method is proposed where different visualizations are used to present both exceedances and climate model projections within their correct scientific context.