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Title: Risk analysis for flood event management
Author: Wang, Miao
ISNI:       0000 0004 5924 3496
Awarding Body: Newcastle University
Current Institution: University of Newcastle upon Tyne
Date of Award: 2015
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Flood risk management seeks to reduce flood consequences and probability by considering a wide range of options that include non-structural measures such as flood event management. Quantitative flood risk analysis has provided a powerful tool to support appraisal and investment in engineered flood defence. However, analysing the risks and benefits of non-structural measures have been limited making it difficult to compare the benefits of a wide range of options on a shared assessment platform. A major challenge to understand the performance of non-structural measures during a flood event is the complexity of analysing the human responses in the system that determines the successful operation of flood event management. Here presents a risk analysis approach that couples a multi-agent simulation of individual and organizational behaviour with a hydrodynamic model. The model integrates remotely sensed information on topography, buildings and road networks with empirical survey data and information on local flood event management strategies to fit characteristics of specific communities. The model has been tested in Towyn, North Wales, and subsequently used to analyse the effectiveness of flood event management procedures, including flood warning and evacuation procedures in terms of potential loss of life , economic damages and the identification of roads susceptible to congestion. The potential loss of life increases according to the magnitude of a storm surge (e.g. 11 for 1 in 100 years surges as opposed to 94 for 1 in 1000 surges). Providing 3 hours flood warning can reduce this by 67% if individuals take appropriate action. A global sensitivity analysis shows that hydrodynamic processes are only responsible for 50% of the variance in expected loss of life because actions taken by individuals and society can greatly influence the outcome. The model can be used for emergency planners to improve flood response in a flood event.
Supervisor: Not available Sponsor: EPSRC
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available