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Changes in seasonal compound floods in Vietnam revealed by a time-varying dependence structure of extreme rainfall and high surge

Han Wang, Yunqing Xuan Orcid Logo, Thi Van Thu Tran, Anaïs Couasnon, Paolo Scussolini, Linh Nhat Luu, Hong Quan Nguyen, Dominic Reeve Orcid Logo

Coastal Engineering, Volume: 183, Start page: 104330

Swansea University Authors: Han Wang, Yunqing Xuan Orcid Logo, Dominic Reeve Orcid Logo

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DOI (Published version): 10.1016/j.coastaleng.2023.104330

Abstract

Compound floods due to intense rainfall and storm surges in coastal areas have shown an increasing trend in some parts of the world and many studies suggested a strong link with climate change. Yet, such link has not been fully explored and quantitively accounted for. In this paper, we demonstrate t...

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Published in: Coastal Engineering
ISSN: 0378-3839
Published: Elsevier BV 2023
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URI: https://cronfa.swan.ac.uk/Record/cronfa63367
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In addition, the results reveal that the dry season (represented by March) is expected to receive more floods triggered by the increased intensity and frequency of rainfall extremes, with the magnitude reaching a similar level to that of the wet season (represented by October). This is in line with the climate projections under RCP4.5 and 8.5 scenarios although the duration of dry spells is expected to increase and the total annual rainfall to decrease in Vietnam. 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spelling v2 63367 2023-05-08 Changes in seasonal compound floods in Vietnam revealed by a time-varying dependence structure of extreme rainfall and high surge a718b31e3f1749890106d990af40fb3c Han Wang Han Wang true false 3ece84458da360ff84fa95aa1c0c912b 0000-0003-2736-8625 Yunqing Xuan Yunqing Xuan true false 3e76fcc2bb3cde4ddee2c8edfd2f0082 0000-0003-1293-4743 Dominic Reeve Dominic Reeve true false 2023-05-08 FGSEN Compound floods due to intense rainfall and storm surges in coastal areas have shown an increasing trend in some parts of the world and many studies suggested a strong link with climate change. Yet, such link has not been fully explored and quantitively accounted for. In this paper, we demonstrate the development and application of a nonstationary framework to determining different compound scenarios where individual drivers and their interactions have altered under climate change. The framework has been applied to one of the most flood-prone areas, the Ho Chi Minh City of Vietnam, to help analyze the present and future compound flood risks in both the dry and wet seasons driven by the joint effect from heavy inland rainfall and high skew surge. Over the period of 1980–2017, the two drivers are found to be significantly correlated in March and April, corresponding to the transition from dry-to-wet seasons. We also find that the commonly-used traditional multivariate statistical models underestimate the flood magnitudes for the current (represented by 2020) and future (represented by 2050) scenarios, compared with the results produced by the nonstationary methods. In addition, the results reveal that the dry season (represented by March) is expected to receive more floods triggered by the increased intensity and frequency of rainfall extremes, with the magnitude reaching a similar level to that of the wet season (represented by October). This is in line with the climate projections under RCP4.5 and 8.5 scenarios although the duration of dry spells is expected to increase and the total annual rainfall to decrease in Vietnam. The simulated flood inundations indicate remarkable increases in flood magnitude and extension, especially at the locations identified as low risk by the stationary models. Journal Article Coastal Engineering 183 104330 Elsevier BV 0378-3839 Coastal compound flood, Climate change, Quantification framework, Rainfall extremes, Storm surge 1 5 2023 2023-05-01 10.1016/j.coastaleng.2023.104330 http://dx.doi.org/10.1016/j.coastaleng.2023.104330 COLLEGE NANME Science and Engineering - Faculty COLLEGE CODE FGSEN Swansea University Not Required Academy of Medical Sciences Grant, Dutch Research Council GCRFNGR4_1165, 016.161.324, ALWOP.164 2023-06-29T15:54:32.8927594 2023-05-08T13:30:33.4517139 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering Han Wang 1 Yunqing Xuan 0000-0003-2736-8625 2 Thi Van Thu Tran 3 Anaïs Couasnon 4 Paolo Scussolini 5 Linh Nhat Luu 6 Hong Quan Nguyen 7 Dominic Reeve 0000-0003-1293-4743 8 63367__27781__4b70629a6a1941e193c597b65c17b3f7.pdf 63367.pdf 2023-06-09T13:37:07.4619589 Output 10796252 application/pdf Version of Record true © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). true eng http://creativecommons.org/licenses/by/4.0/
title Changes in seasonal compound floods in Vietnam revealed by a time-varying dependence structure of extreme rainfall and high surge
spellingShingle Changes in seasonal compound floods in Vietnam revealed by a time-varying dependence structure of extreme rainfall and high surge
Han Wang
Yunqing Xuan
Dominic Reeve
title_short Changes in seasonal compound floods in Vietnam revealed by a time-varying dependence structure of extreme rainfall and high surge
title_full Changes in seasonal compound floods in Vietnam revealed by a time-varying dependence structure of extreme rainfall and high surge
title_fullStr Changes in seasonal compound floods in Vietnam revealed by a time-varying dependence structure of extreme rainfall and high surge
title_full_unstemmed Changes in seasonal compound floods in Vietnam revealed by a time-varying dependence structure of extreme rainfall and high surge
title_sort Changes in seasonal compound floods in Vietnam revealed by a time-varying dependence structure of extreme rainfall and high surge
author_id_str_mv a718b31e3f1749890106d990af40fb3c
3ece84458da360ff84fa95aa1c0c912b
3e76fcc2bb3cde4ddee2c8edfd2f0082
author_id_fullname_str_mv a718b31e3f1749890106d990af40fb3c_***_Han Wang
3ece84458da360ff84fa95aa1c0c912b_***_Yunqing Xuan
3e76fcc2bb3cde4ddee2c8edfd2f0082_***_Dominic Reeve
author Han Wang
Yunqing Xuan
Dominic Reeve
author2 Han Wang
Yunqing Xuan
Thi Van Thu Tran
Anaïs Couasnon
Paolo Scussolini
Linh Nhat Luu
Hong Quan Nguyen
Dominic Reeve
format Journal article
container_title Coastal Engineering
container_volume 183
container_start_page 104330
publishDate 2023
institution Swansea University
issn 0378-3839
doi_str_mv 10.1016/j.coastaleng.2023.104330
publisher Elsevier BV
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Civil Engineering
url http://dx.doi.org/10.1016/j.coastaleng.2023.104330
document_store_str 1
active_str 0
description Compound floods due to intense rainfall and storm surges in coastal areas have shown an increasing trend in some parts of the world and many studies suggested a strong link with climate change. Yet, such link has not been fully explored and quantitively accounted for. In this paper, we demonstrate the development and application of a nonstationary framework to determining different compound scenarios where individual drivers and their interactions have altered under climate change. The framework has been applied to one of the most flood-prone areas, the Ho Chi Minh City of Vietnam, to help analyze the present and future compound flood risks in both the dry and wet seasons driven by the joint effect from heavy inland rainfall and high skew surge. Over the period of 1980–2017, the two drivers are found to be significantly correlated in March and April, corresponding to the transition from dry-to-wet seasons. We also find that the commonly-used traditional multivariate statistical models underestimate the flood magnitudes for the current (represented by 2020) and future (represented by 2050) scenarios, compared with the results produced by the nonstationary methods. In addition, the results reveal that the dry season (represented by March) is expected to receive more floods triggered by the increased intensity and frequency of rainfall extremes, with the magnitude reaching a similar level to that of the wet season (represented by October). This is in line with the climate projections under RCP4.5 and 8.5 scenarios although the duration of dry spells is expected to increase and the total annual rainfall to decrease in Vietnam. The simulated flood inundations indicate remarkable increases in flood magnitude and extension, especially at the locations identified as low risk by the stationary models.
published_date 2023-05-01T15:54:28Z
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