Browsing by Author "Williams, Lauren Lyn"

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    Developing a spatial risk profile: assessing building vulnerability to extreme coastal inundation hazard
    (Stellenbosch : Stellenbosch University, 2020-12) Williams, Lauren Lyn; Luck-Vogel, Melanie; Pharoah, Robyn; Stellenbosch University. Faculty of Arts and Social Sciences. Dept. of Geography and Environmental Studies.
    ENGLISH ABSTRACT: Coastal zones are dynamic spaces where human activities and infrastructure interface directly with natural forces, particularly extreme weather events such as storm surges. Coastal inundation is regarded as one of the most dangerous and destructive natural hazards, and while there are many studies to analyse these events, few provide assessment techniques relevant to the local context. This research aimed at developing a spatial risk profile for building vulnerability to coastal inundation hazard. GIS was determined to be the most appropriate technology as more sophisticated technologies such as hydrodynamic modelling were found to be limited to specialists,‘data-hungry’ and computationally expensive. An improved GIS based enhanced Bathtub Model (eBTM)was thus developed, which is more appropriate to the local coastal inundation context than the widely used simple Bathtub Model (sBTM). The advantage of the eBTM is that incorporates beach slope and surface roughness and that it instils hydrological connectivity to the coast through embedded cost-distance models. The use of such models thus allows for simplistic hydrodynamic processes such as the water distribution through urban infrastructure to be simulated, the output of which also includes the potential water depth relative to the input elevation model. The model was packaged into a user-friendly Graphical User Interface (GUI) tool and the modelled outputs were further tested and validated against observed data, which supported its applicability. Strand and Fish Hoek (Cape Town, South Africa )were selected as the study sites for which the inundation levels for three independent scenarios were determined by combining the xtreme sea level for a 1-in-100 year storm and two sea level rise scenarios. The risk assessment component used the eBTM to generate inundation hazard maps for the three defined scenarios and to identify affected buildings. Both the hazard and hazard exposure scores were directly dependent on the eBTM outputs in terms of the inundation limits and water depths respectively. The physical building vulnerability indicators were developed through stakeholder engagements. The assessment was undertaken through the use of desktop technologies and on site building inspections. Weighted indicators were used to determine the vulnerability scores for each individual building. Determining the spatial risk profile was based on the scores from the preceding work to determine the risk status of each individual building in each study site. Again, weightings were applied to highlight the importance of components and to reduce the weight of less robust input factors. Overall, in Fish Hoek, one building was found to be at high risk of experiencing coastal inundation based on the given scenarios and three are at low risk. In Strand the spatial risk profile showed that 71 buildings are at low risk, 86 at moderate risk and 35 at high risk. The identified high risk buildings can thus be further assessed in terms of methods to reduce their vulnerability and/or hazard exposure.This study departs from existing regional risk assessment approaches and presents an assessment mechanism that allows the risk components (i.e. hazard, hazard exposure and vulnerability) to be assessed individually, at a locally relevant scale and through their individual assessment frameworks.The eBTM tool and assessment techniques were developed to be transferable to other areas. Furthermore, the eBTM tool enhances the accessibility of GIS based techniques for undertaking localised coastal risk assessments. The maps produced for the individual risk components can thus be used for knowledge transfer, while the final risk maps can be used to inform the management response required relevant to the local context.