Improved flood modelling for the built environment and infrastructure - Achieving urban flood resilience through hydrodynamic models

Abstract

This thesis explores and develops methods for the simulation and analysis of flood risk for urban environments, using an advanced hydrodynamic model (CityCAT). Focused on bolstering urban flood resilience, the research is aimed at the need for better representation of urban features and blue green adaptations within hydrodynamic models. A number of aspects of urban flood modelling, exposure analysis and adaptation are addressed using novel methods and detailed applications to city casestudies in Newcastle-upon-Tyne, Greater London (both UK) and Thessaloniki (Greece). Accurately representing buildings is addressed by critically comparing the ‘Building Hole’ method with the prevalent ‘Stubby Building’ approach, demonstrating superior performance using a detailed flood validation dataset. Efficient flood risk management in urban areas necessitates interventions that modify surface flow pathways and introduce storage, so a novel cost-benefit ‘source-receptor’ framework is developed to identify flood sources, vulnerable receptors, and optimal locations for implementing Blue-Green Infrastructure (BGI). The framework integrates economic considerations, surpassing conventional hydraulic analyses. High-resolution flood risk and property-level exposure modelling for whole megacities has previously not been achievable, so here a case study of London is carried out, showcasing cloud-based flood modelling as a transformative tool for insurance and flood resilience strategies worldwide. In addition to extending the scale and accuracy of flood risk and exposure modelling practice, a number of conclusions are drawn and advice presented on practical aspects, such as : assessment of the superiority of the “Building Hole” method, alongside advice on improving the alternative “Stubby Building” method; firm guidelines for minimum DEM resolution and building representation in the model domain, considering both cases where high quality datasets are available and absent; an improved benefit-cost method for optimising placement of blue-green infrastructure, alongside proposals for further development through automation