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Adaptive Disaster Risk Assessment
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Adaptive Disaster Risk Assessment : Combining Multi-Hazards with Socioeconomic Vulnerability and Dynamic Exposure

Book Details

Format Paperback / Softback
ISBN-10 103211617X
ISBN-13 9781032116174
Publisher Taylor & Francis Ltd
Imprint CRC Press
Country of Manufacture GB
Country of Publication GB
Publication Date Oct 9th, 2021
Print length 312 Pages
Weight 453 grams
Ksh 18,900.00
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This dissertation developed an Adaptive Disaster Risk Assessment (ADRA) framework for weather-related disasters in the context of SIDS. The adaptivity of the framework comes from the explicit assessment of the exposure component and from the modular and flexibility of an index-based approach used to assess the socioeconomic vulnerability.

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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