Climate change, combined with the rapid and often unplanned urbanisation trends, is associated with a rising trend in the frequency and severity of disasters triggered by natural hazards. In order to face the impacts of such threats, it is necessary to have an appropriate Disaster Risk Assessment (DRA). Traditional DRA approaches for disaster risk reduction (DRR) have focused mainly on the hazard component of risk, with little attention to the vulnerability and the exposure components. To address this issue, this dissertation’s main objective is to develop and test a disaster risk modelling framework that incorporates socioeconomic vulnerability and the adaptive nature of exposure associated with human behaviour in extreme hydro-meteorological events in the context of SIDS. To achieve the objective, an Adaptive Disaster Risk Assessment (ADRA) framework is proposed. ADRA uses an index-based approach (PeVI) to assess the socioeconomic vulnerability using three components: susceptibility, lack of coping capacities, and lack of adaptation. Furthermore, ADRA explicitly incorporates the exposure component using two approaches; first, a logistic regression model was built using the actual evacuation rates observed during Hurricane Irma, and second, an Agent-based model is used to simulate how households change their exposure levels in relation to different sources of information
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Neiler Medina is a PhD researcher in Urban Water Systems at IHE Delft Institute for Water Education, Delft, The Netherlands. Neiler obtained his BSc, in Sanitary Engineering, a post-graduate certificate as a specialist in Geographic Information Systems (GIS), and his MSc in Water Science and Engineering, specialization Hydroinformatics from UNESCO-IHE. Mr Medina is an experienced water engineer with an extensive background in modelling water systems, focus on urban drainage and sewerage networks. His expertise also includes disaster risk assessment/management for hydro-meteorological hazards such as floods and hurricanes, including hazard modelling, socioeconomic vulnerability and exposure assessment and mapping.
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