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The use of joint probability analysis to predict flood frequency in estuaries and tidal rivers

The use of joint probability analysis to predict flood frequency in estuaries and tidal rivers
The use of joint probability analysis to predict flood frequency in estuaries and tidal rivers
This thesis investigates the combined influence of river flow, tide and surge on the frequency of extreme water levels in tidal rivers and estuaries. The estimation of flood risk may depend on extreme combinations of these variables rather than individual extreme events, but these relationships are complex and difficult to quantify. A probabilistic approach traditionally involves an assumption of independence between these primary hydrological variables, which can lead to the underestimation of the level of risk where river flow and tidal surge are often linked to the same low pressure weather system. This research develops a new methodology which combines traditional flood risk modelling techniques with statistical dependence to define the relationship between the hydrological variables. Dependence between river flow, tide and surge is assessed for a case study area of Lewes, East Sussex, UK, a town which is prone to both tidal and fluvial flooding. Bivariate and trivariate daily and extreme joint exceedance methods are developed and used in conjunction with a one-dimensional hydraulic model to analyse the interaction of river flow, tide and surge to predict the joint probability of potential flood events occurring in Lewes. The approach is validated using existing historical water levels observed in Lewes. The results demonstrate that the joint exceedance approach can be successfully employed to model the frequency of flood events caused by tide and river flow. The incorporation of a third variable of surge refines the approach further, and identifies the zone where the interaction of the variables has the greatest impact on resultant flood water levels.
White, Christopher John
9105a57a-bb57-4983-bde6-762edb2d9083
White, Christopher John
9105a57a-bb57-4983-bde6-762edb2d9083
Tanton, Trevor
0f6a361e-394f-4cfc-94a6-5311442ae366

White, Christopher John (2007) The use of joint probability analysis to predict flood frequency in estuaries and tidal rivers. University of Southampton, School of Civil Engineering and the Environment, Doctoral Thesis, 357pp.

Record type: Thesis (Doctoral)

Abstract

This thesis investigates the combined influence of river flow, tide and surge on the frequency of extreme water levels in tidal rivers and estuaries. The estimation of flood risk may depend on extreme combinations of these variables rather than individual extreme events, but these relationships are complex and difficult to quantify. A probabilistic approach traditionally involves an assumption of independence between these primary hydrological variables, which can lead to the underestimation of the level of risk where river flow and tidal surge are often linked to the same low pressure weather system. This research develops a new methodology which combines traditional flood risk modelling techniques with statistical dependence to define the relationship between the hydrological variables. Dependence between river flow, tide and surge is assessed for a case study area of Lewes, East Sussex, UK, a town which is prone to both tidal and fluvial flooding. Bivariate and trivariate daily and extreme joint exceedance methods are developed and used in conjunction with a one-dimensional hydraulic model to analyse the interaction of river flow, tide and surge to predict the joint probability of potential flood events occurring in Lewes. The approach is validated using existing historical water levels observed in Lewes. The results demonstrate that the joint exceedance approach can be successfully employed to model the frequency of flood events caused by tide and river flow. The incorporation of a third variable of surge refines the approach further, and identifies the zone where the interaction of the variables has the greatest impact on resultant flood water levels.

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Published date: November 2007
Organisations: University of Southampton

Identifiers

Local EPrints ID: 63847
URI: http://eprints.soton.ac.uk/id/eprint/63847
PURE UUID: 9e11c76e-1be3-4bfd-8678-7f355cba7e1b

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Date deposited: 10 Nov 2008
Last modified: 13 Mar 2019 20:23

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Contributors

Author: Christopher John White
Thesis advisor: Trevor Tanton

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