Bernhofen, Mark Viktor ORCID: https://orcid.org/0000-0002-4919-0111 (2022) Global flood model assessment and flood risk evaluation. PhD thesis, University of Leeds.
Abstract
Floods are the most frequent and damaging natural hazard globally. To adequately prepare for floods it is essential to know where they will occur and what their impacts will be. This can be done by developing a flood model. Traditionally, these models have been local in scale, limited to areas with the necessary expertise and data to develop a flood model. However, the last decade has seen the proliferation of several global flood models, which use global datasets and automated approaches to map flood hazard globally. When combined with global datasets of exposure and vulnerability, they can be used to assess global flood risk. The development of these global flood risk datasets marks a potential paradigm shift in flood risk analysis from the traditional “ad hoc” approach to global datasets which can be used to assess flood risk anywhere in the world. Despite this, these global flood risk datasets still need significant evaluation to understand the limits of their effective application.
This thesis furthers the evaluation and explores the potential applications of global flood risk datasets. The current state of global flood risk modelling is reviewed, highlighting the different models, their history, structure, and application. The models are then collectively validated for the first time against observed flood events, demonstrating the skill of some models and identifying model characteristics which influence performance. The impact of river size thresholds, a key difference identified between the models, are quantified by calculating flood exposure to different sized rivers globally. Both the chosen river size thresholds and the global population maps used to calculate exposure are found to have a significant impact on flood exposure estimates. The use of global flood risk data is then explored nationally as global datasets of hazard, exposure, and vulnerability are evaluated for flood risk management in five countries. While some global datasets are found to be of potential use, there is still significant uncertainty in their national flood risk estimates and potential issues are identified related to the capacity there is to use them nationally.
Metadata
Supervisors: | Trigg, Mark and Sleigh, Andrew |
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Related URLs: | |
Keywords: | Global Flood Models, Flooding, Rivers, Flood Risk, Exposure, Vulnerability |
Awarding institution: | University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering (Leeds) > School of Civil Engineering (Leeds) |
Identification Number/EthosID: | uk.bl.ethos.870985 |
Depositing User: | Dr. Mark Viktor Bernhofen |
Date Deposited: | 03 Feb 2023 09:36 |
Last Modified: | 11 Feb 2023 10:55 |
Open Archives Initiative ID (OAI ID): | oai:etheses.whiterose.ac.uk:30476 |
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