No Cover Image

Journal article 1145 views

Statistical simulation of flood variables: incorporating short-term sequencing

Y Cai, B Gouldby, P Hawkes, P Dunning, Yuzhi Cai Orcid Logo

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

Swansea University Author: Yuzhi Cai Orcid Logo

Full text not available from this repository: check for access using links below.

Check full text

DOI (Published version): 10.1111/j.1753-318X.2008.00002.x

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...

Full description

Published in: Journal of Flood Risk Management
ISSN: 1753-318X
Published: 2008
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa11979
Tags: Add Tag
No Tags, Be the first to tag this record!
first_indexed 2013-07-23T12:06:39Z
last_indexed 2018-02-09T04:41:55Z
id cronfa11979
recordtype SURis
fullrecord <?xml version="1.0"?><rfc1807><datestamp>2016-05-01T15:35:23.9218600</datestamp><bib-version>v2</bib-version><id>11979</id><entry>2012-07-12</entry><title>Statistical simulation of flood variables: incorporating short-term sequencing</title><swanseaauthors><author><sid>eff7b8626ab4cc6428eef52516fda7d6</sid><ORCID>0000-0003-3509-9787</ORCID><firstname>Yuzhi</firstname><surname>Cai</surname><name>Yuzhi Cai</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2012-07-12</date><deptcode>BAF</deptcode><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 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.</abstract><type>Journal Article</type><journal>Journal of Flood Risk Management</journal><volume>1</volume><journalNumber>1</journalNumber><paginationStart>3</paginationStart><paginationEnd>10</paginationEnd><publisher/><issnPrint>1753-318X</issnPrint><issnElectronic/><keywords>Autocorrelation; correlation structure;flood risk; marginal extremes; simulation; time series; waves; surges.</keywords><publishedDay>31</publishedDay><publishedMonth>12</publishedMonth><publishedYear>2008</publishedYear><publishedDate>2008-12-31</publishedDate><doi>10.1111/j.1753-318X.2008.00002.x</doi><url/><notes/><college>COLLEGE NANME</college><department>Accounting and Finance</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>BAF</DepartmentCode><institution>Swansea University</institution><apcterm/><lastEdited>2016-05-01T15:35:23.9218600</lastEdited><Created>2012-07-12T14:20:19.2321586</Created><path><level id="1">Faculty of Humanities and Social Sciences</level><level id="2">School of Management - Accounting and Finance</level></path><authors><author><firstname>Y</firstname><surname>Cai</surname><order>1</order></author><author><firstname>B</firstname><surname>Gouldby</surname><order>2</order></author><author><firstname>P</firstname><surname>Hawkes</surname><order>3</order></author><author><firstname>P</firstname><surname>Dunning</surname><order>4</order></author><author><firstname>Yuzhi</firstname><surname>Cai</surname><orcid>0000-0003-3509-9787</orcid><order>5</order></author></authors><documents/><OutputDurs/></rfc1807>
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 Faculty of Humanities and Social Sciences 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 Faculty of Humanities and Social Sciences
hierarchytype
hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str School of Management - Accounting and Finance{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}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 2008-12-31T03:13:53Z
_version_ 1763750165163802624
score 10.997866

Similar Items