Integrated Risk Assessment of Water-Related Disasters

This chapter updates the conceptual KULTURisk Framework and its implementation methods (SERRA or Socio-Economic Regional Risk Assessment) for integrated (physical and economical) risk assessment and evaluation of risk prevention benefits in the field of water-related processes. The framework (i.e. named after the European project within which it originated) and the SERRA approach were developed upon pre-existing methods, with three main innovation aims: (1) to include the social capacities of reducing vulnerability and risk, (2) to operationalize the assessment of exposed assets, and the benefits of risk reduction measures, by including a monetary estimation of costs and benefits, (3) to estimate intangible and indirect costs, (4) to improve the ability to track uncertainty in estimated values. We build on the well-established Hazard-Vulnerability-Exposure framework but vulnerability is expanded to consider the interactions between physical (territorial) characteristics, susceptibility, and capacities of socio-economic systems to adapt and cope with specific hazards, and it is here formulated as a nondimensional index ranging between 0 and 1. Exposure is instead assessed in monetary terms, and thus the multiplicative combination of two indices ranging between 0 and 1 (hazard and vulnerability) with a third one (exposure) expressed in monetary terms produces a monetary quantification of risk, which can be used for supporting decisions via cost-benefit analysis. Operational solutions are proposed to evaluate four possible socio-economic costs deriving from the adverse consequences of floods, namely direct/indirect and tangible/intangible costs. The proposed methodology aims to be comprehensive concerning the set of receptors usually considered in the literature of regional risk assessment. The sets of receptors considered are people, economic activities, categorized as (1) buildings; (2) infrastructures; and (3) agriculture and cultural heritage and ecosystems. By applying the framework to the Eastern part of Dhaka city, Bangladesh, we illustrate how SERRA can be implemented to support decision-makers identifying robust risk management solutions in a highly uncertain context, by simulating key climate and socio-economic variables and their uncertainty, and by utilizing data-mining to extract useful information for decision-makers. Results are summarized and communicated using decision trees that describe a categorized view of the vulnerabilities of the proposed risk reduction measures, by identifying the states and combinations of key variables that could determine considerable failures