Flooding is the most frequent natural disaster that causes significant, societal, economic, and
environmental damage. The processes involved in flooding are shaped by spatial and
temporal factors including weather patterns, topography and geomorphology. In urban
setting, where landscapers are dynamic, land cover, green spaces, and drainage play a crucial
role. Recognising flood source areas (FSAs) is pivotal for strategic flood risk management
(FRM). Although FSA identification is not novel concept, recent advancements in flood
modelling research, driven by technology and methodology improvements have extended
beyond traditional methods. Emerging modelling approaches in FRM propose innovative
methodologies for flood risk mitigation focusing on understanding and addressing flooding at
its source.
This thesis offers a review of current modelling approaches used to identify FSAs,
specifically the Unit Flood Response (UFR) approach. The approach is a spatial prioritisation
method for flood defences and mitigation. Traditionally, reliant on hydrological modelling and
streamflow routing, this these instead uses rain-on-grid models (TUFLOW and HEC-RAS 2D)
to assess the importance of model choice for the UFR approach for a catchment in the UK.
The thesis further developed the UFR methodology by using a Hazard Index (HI) and Building
Exposure Index (BEI) to show the significant differences between the model outputs, as well
as emphasising on the computational costs associated with these methodologies.
Additionally, recognising the important role of drainage systems in urban
infrastructure, this thesis addresses the limited body of work available on drainage
representation in flood models by introducing the Capacity Assessment Framework (CAF) to
be used for drainage representation. By applying the CAF to assess and represent the drainage
system in Leeds, the thesis draws a direct link between spatial prioritisation of flood defences
and drainage system performance. The thesis introduces the application of the CAF outputs
in flood models, demonstrating a more explicit representation of spatially varied drinage
capacity. By comparing the national average removal rate (NARR) of 12 mm/hr with CAFderived rates, the significant of realistic drainage representation in flood models is
highlighted.
Lastly, the UFR approach coupled with 2D rain-on-grid modelling is used to investigate
the impact of climate change and drainage representation in the Lin Dyke catchment. This
approach considers three scenarios (Baseline, Baseline+Climate Change, and
Baseline+Climate Change+Drainage) to establish hazard and building exposure indices.
Results highlight the importance of incorporating climate change projections and drainage
representation in the UFR methodology for a thorough urban flood risk assessment.
In synthesis, this thesis investigates the multiple factors of flood risk management,
offering insights and innovations across various dimensions. The Unit Flood Response (UFR)
emerges as promising tools for identifying flood source areas (FSAs), emphasising the need
for adaptive decision-making in flood risk management (FRM). Our investigation extends
beyond affected areas, focusing on understanding, and addressing flooding at its source.
Moreover, the introduction of the Capacity Assessment Framework (CAF) provides a novel
methodology for representing drainage systems in flood models based on their realistic
performance in urban environments. By incorporating realistic representations of spatially
varied drainage capacities in flood models, this thesis highlightsthe importance of considering
multiple factors in the assessment for effective urban flood risk management. As climate
change and urban development exert increasing pressures, the findings in this thesis
underscore the importance of integrating these factors into flood risk models to ensure
resilience and relevance in the face of evolving challenges
