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Statistical simulation of flood variables: incorporating short-term sequencing / Y Cai, B Gouldby, P Hawkes, P Dunning, Yuzhi Cai

Journal of Flood Risk Management, Volume: 1, Issue: 1, Pages: 3 - 10

Swansea University Author: Yuzhi Cai

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Abstract

The pluvial and fluvial flooding in the United Kingdom over the summer of 2007arose as a result of anomalous climatic conditions that persisted for over a month.Gaining an understanding of the sequencing of storm events and representing theircharacteristics within flood risk analysis is therefore of...

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Published in: Journal of Flood Risk Management
ISSN: 1753-318X
Published: 2008
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URI: https://cronfa.swan.ac.uk/Record/cronfa11979
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first_indexed 2013-07-23T12:06:39Z
last_indexed 2018-02-09T04:41:55Z
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spelling 2016-05-01T15:35:23.9218600 v2 11979 2012-07-12 Statistical simulation of flood variables: incorporating short-term sequencing eff7b8626ab4cc6428eef52516fda7d6 0000-0003-3509-9787 Yuzhi Cai Yuzhi Cai true false 2012-07-12 BAF The pluvial and fluvial flooding in the United Kingdom over the summer of 2007arose as a result of anomalous climatic conditions that persisted for over a month.Gaining an understanding of the sequencing of storm events and representing theircharacteristics within flood risk analysis is therefore of importance. This paperprovides a general method for simulating univariate time series data, with a givenmarginal extreme value distribution and required autocorrelation structure,together with a demonstration of the method with synthetic data. The method isthen extended to the multivariate case, where cross-variable correlations are alsorepresented. The multivariate method is shown to work well for a two-variablesimulation of wave heights and sea surges at Lerwick. This work was prompted byan engineering need for long time series data for use in continuous simulationstudies where gradual deterioration is a contributory factor to flood risk andpotential structural failure. Journal Article Journal of Flood Risk Management 1 1 3 10 1753-318X Autocorrelation; correlation structure;flood risk; marginal extremes; simulation; time series; waves; surges. 31 12 2008 2008-12-31 10.1111/j.1753-318X.2008.00002.x COLLEGE NANME Accounting and Finance COLLEGE CODE BAF Swansea University 2016-05-01T15:35:23.9218600 2012-07-12T14:20:19.2321586 School of Management Accounting and Finance Y Cai 1 B Gouldby 2 P Hawkes 3 P Dunning 4 Yuzhi Cai 0000-0003-3509-9787 5
title Statistical simulation of flood variables: incorporating short-term sequencing
spellingShingle Statistical simulation of flood variables: incorporating short-term sequencing
Yuzhi, Cai
title_short Statistical simulation of flood variables: incorporating short-term sequencing
title_full Statistical simulation of flood variables: incorporating short-term sequencing
title_fullStr Statistical simulation of flood variables: incorporating short-term sequencing
title_full_unstemmed Statistical simulation of flood variables: incorporating short-term sequencing
title_sort Statistical simulation of flood variables: incorporating short-term sequencing
author_id_str_mv eff7b8626ab4cc6428eef52516fda7d6
author_id_fullname_str_mv eff7b8626ab4cc6428eef52516fda7d6_***_Yuzhi, Cai
author Yuzhi, Cai
author2 Y Cai
B Gouldby
P Hawkes
P Dunning
Yuzhi Cai
format Journal article
container_title Journal of Flood Risk Management
container_volume 1
container_issue 1
container_start_page 3
publishDate 2008
institution Swansea University
issn 1753-318X
doi_str_mv 10.1111/j.1753-318X.2008.00002.x
college_str School of Management
hierarchytype
hierarchy_top_id schoolofmanagement
hierarchy_top_title School of Management
hierarchy_parent_id schoolofmanagement
hierarchy_parent_title School of Management
department_str Accounting and Finance{{{_:::_}}}School of Management{{{_:::_}}}Accounting and Finance
document_store_str 0
active_str 0
description The pluvial and fluvial flooding in the United Kingdom over the summer of 2007arose as a result of anomalous climatic conditions that persisted for over a month.Gaining an understanding of the sequencing of storm events and representing theircharacteristics within flood risk analysis is therefore of importance. This paperprovides a general method for simulating univariate time series data, with a givenmarginal extreme value distribution and required autocorrelation structure,together with a demonstration of the method with synthetic data. The method isthen extended to the multivariate case, where cross-variable correlations are alsorepresented. The multivariate method is shown to work well for a two-variablesimulation of wave heights and sea surges at Lerwick. This work was prompted byan engineering need for long time series data for use in continuous simulationstudies where gradual deterioration is a contributory factor to flood risk andpotential structural failure.
published_date 2008-12-31T03:24:29Z
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