Tocchi, Gabriella (2023) Multi-risk assessment for disaster risk reduction: a framework for integrating physical, social and multi-hazard dimensions. [Tesi di dottorato]

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Abstract

Prioritizing risks originating from different hazards in a region of interest is crucial to enable decisions on appropriate and cost-effective mitigation or preparedness measures. However, the performing of multi-risk assessment is a difficult task, mostly due to different methodologies and spatial/temporal resolutions adopted in the quantification of single risks. Moreover, evidence indicates that people in vulnerable situation may be disproportionately affected. Poverty and inequality have been officially recognized as risk drivers and the interest of governments and local stakeholders in understanding the influence of socio-economic factors on vulnerability to hazards notably increased during last years. However, conventional risk assessments typically fail to account for social vulnerability. This study proposes a framework for integrating both socio-economic and physical factors in multi-risk analysis for overcoming the above limitations. A Risk Index (RI) was developed based on the combination of individual standardized indicators for hazard, physical and social vulnerability and exposure inputs. As a matter of fact, index-based approaches are the most suitable ones for measuring multidimensional concepts which cannot be captured by a single indicator. Indicators selected are combined defining suitable weights that may explicitly reflect stakeholder priorities in policymaking. This approach allows to rank regions exposed to multiple hazards and to identify multi-risk hotspots that more needs disaster risk reduction strategies, also accounting for socio-economic aspects. Hence, it may be a useful support for prioritizing area at risk in decision-making process, that is one the main challenges in Disaster Risk Reduction. The use of the proposed multi-risk index for earthquake and flood risk is demonstrated across the entire country of Italy, selecting the municipality as scale of analysis and residential buildings and population as assets at risk. This index-based approach allows to compare and rank those hazards in the country, leading to the identification of the regions where earthquakes/floods impacts are likely to be very high, due to high hazard level, poor performance of asset exposed to such hazard as well as weak capacity of people to adapt and respond to a natural disaster. Exploiting the aforementioned index, a risk map of the Italian territory is obtained and the hotspots that should be prioritized in disaster risk reduction policies are identified. The application will also show that the involvement of social aspects in risk analysis may play a crucial role in the identification of such hotspots, underlying how ignoring social aspects in risk assessment may affect the effectiveness of disaster risk reduction plans. Sensitivity analyses are also performed in order to understand how multi-risk hotspots can change as a function of the relative importance given to a single RI component, i.e., how stakeholder priorities can affect the results. For a proper quantification of expected economic losses, that are crucial for preparedness purposes, a quantitative risk assessment is also performed. The RI allows to identify the municipalities with highest risk score in a country. On the other hand, a detailed risk analysis is required to compare perils in terms of economic losses at municipal and sub-municipal scales. Through such analysis it is possible to identify the district with higher risk, both in terms of economic losses and social vulnerability, and to disaggregate losses on several social groups. For instance, low-income people may tend to experience the largest losses. Through detailed risk analysis the effectiveness of some mitigation strategies can also be estimated. The quantification of loss reduction associated to such strategies allows the definition of the most suitable mitigation options, also accounting for different social groups. Thus, for example, some mitigation policies may be particularly notable for the lowest income population class. To demonstrate the usefulness of such detailed assessment, among Italian municipality, the one with highest risk score is selected for performing a quantitative risk assessment at sub-municipal scale. The analysis show that low-income people tend to experience the largest expected annual losses per square meter both for earthquake and flood events. For the specific case study, risk assessment is repeated twice with some modelling modifications to evaluate the effectiveness of reducing expected losses through some disaster risk reduction strategies and related policies. The results show that the reduction of the expected losses thanks to the adoption such policies is particularly notable for the lowest income class. These types of analyses are likely to represent a helpful tool for decision-makers, enabling them to select appropriate, cost-effective mitigation or preparedness measures that directly target those most in need.

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