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Forecasting of ocean state in a complex estuarine environment: the Solent-Southampton Water Estuarine System

Forecasting of ocean state in a complex estuarine environment: the Solent-Southampton Water Estuarine System
Forecasting of ocean state in a complex estuarine environment: the Solent-Southampton Water Estuarine System
Coastal flooding is a natural hazard causing devastation to many regions throughout the world, induced by the coincidence of high spring tides, large storm surges and waves. To reduce the risk posed by coastal inundation, warning systems have been developed to enable preparations to an expected threat. Although current operational predictions provide invaluable warnings, uncertainty in model formulations and input datasets, can lead to errors in forecasts. In order to provide coastal managers with the best possible information with which to make decisions, recent research has begun to focus on the movement from deterministic to probabilistic forecasting, which aims to explicitly account for uncertainty in the system.

This research described the implementation of a regional tide-surge-wave model for the Solent-Southampton Water estuarine system, a region that is likely to experience increased risk of coastal flooding in the coming century. The accuracy of the model predictions were examined relative to in-situ measurements and those obtained from independent systems. Using the model, sources of error were examined and their effects upon the model predictions quantified, with particular reference made to the spatial variability throughout the region. In light of recent research, a probabilistic modelling approach, utilising a Monte Carlo technique used to provide a forecast capable of representing the uncertainty in the system, within a suitable time-frame for real-time flood forecasting that included an hourly Kalman filter data assimilation update.

The findings presented in this thesis will be of interest to coastal modellers working in complex estuarine environments where the influences of tide-surge-wave interactions upon model predictions are uncertain. Furthermore, the application of a computationally efficient model, presented here, will provide a useful comparison with traditional physically-based systems to those wishing to quantify uncertainty in regions where computational resources are low
Quinn, Niall
7625f7b2-58ee-47c7-beea-23ff56de6c6c
Quinn, Niall
7625f7b2-58ee-47c7-beea-23ff56de6c6c
Atkinson, Peter
96e96579-56fe-424d-a21c-17b6eed13b0b
Wells, Neil
4c27167c-f972-4822-9614-d6ca8d8223b5

(2012) Forecasting of ocean state in a complex estuarine environment: the Solent-Southampton Water Estuarine System. University of Southampton, Geography, Doctoral Thesis, 228pp.

Record type: Thesis (Doctoral)

Abstract

Coastal flooding is a natural hazard causing devastation to many regions throughout the world, induced by the coincidence of high spring tides, large storm surges and waves. To reduce the risk posed by coastal inundation, warning systems have been developed to enable preparations to an expected threat. Although current operational predictions provide invaluable warnings, uncertainty in model formulations and input datasets, can lead to errors in forecasts. In order to provide coastal managers with the best possible information with which to make decisions, recent research has begun to focus on the movement from deterministic to probabilistic forecasting, which aims to explicitly account for uncertainty in the system.

This research described the implementation of a regional tide-surge-wave model for the Solent-Southampton Water estuarine system, a region that is likely to experience increased risk of coastal flooding in the coming century. The accuracy of the model predictions were examined relative to in-situ measurements and those obtained from independent systems. Using the model, sources of error were examined and their effects upon the model predictions quantified, with particular reference made to the spatial variability throughout the region. In light of recent research, a probabilistic modelling approach, utilising a Monte Carlo technique used to provide a forecast capable of representing the uncertainty in the system, within a suitable time-frame for real-time flood forecasting that included an hourly Kalman filter data assimilation update.

The findings presented in this thesis will be of interest to coastal modellers working in complex estuarine environments where the influences of tide-surge-wave interactions upon model predictions are uncertain. Furthermore, the application of a computationally efficient model, presented here, will provide a useful comparison with traditional physically-based systems to those wishing to quantify uncertainty in regions where computational resources are low

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Published date: September 2012
Organisations: University of Southampton, Geography & Environment

Identifiers

Local EPrints ID: 359671
URI: http://eprints.soton.ac.uk/id/eprint/359671
PURE UUID: c3342a49-ecac-458f-8b4b-705f8fb57835
ORCID for Peter Atkinson: ORCID iD orcid.org/0000-0002-5489-6880

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Date deposited: 17 Dec 2013 13:39
Last modified: 18 May 2019 00:38

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