Nonstationary flood risk assessment in coastal regions under climate change

2021 Spring. Includes bibliographical references. Coastal cities are exposed to multiple flood drivers including high tide, storm surge, extreme rainfall, and high river flows. The occurrence of these flood drivers, either in isolation or in combination, can cause significant risk to property and hu...

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Main Author: Ghanbari, Mahshid
Other Authors: Arabi, Mazdak, Ettema, Robert, Schumacher, Russ, Bhaskar, Aditi
Format: Text
Language:English
Published: Colorado State University. Libraries 2021
Subjects:
Online Access:https://hdl.handle.net/10217/232588
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spelling ftcolostateunidc:oai:mountainscholar.org:10217/232588 2023-06-11T04:15:17+02:00 Nonstationary flood risk assessment in coastal regions under climate change Ghanbari, Mahshid Arabi, Mazdak Ettema, Robert Schumacher, Russ Bhaskar, Aditi 2021-06-07T10:21:02Z born digital doctoral dissertations application/pdf https://hdl.handle.net/10217/232588 English eng eng Colorado State University. Libraries 2020- CSU Theses and Dissertations Ghanbari_colostate_0053A_16473.pdf https://hdl.handle.net/10217/232588 Copyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright. extreme value analysis mixture probability model stormwater management flood risk analysis compound flood risk sea level rise Text 2021 ftcolostateunidc 2023-05-04T17:40:22Z 2021 Spring. Includes bibliographical references. Coastal cities are exposed to multiple flood drivers including high tide, storm surge, extreme rainfall, and high river flows. The occurrence of these flood drivers, either in isolation or in combination, can cause significant risk to property and human life. Climate change is placing greater pressure on coastal communities by increasing frequency and intensity of flood events through sea level rise (SLR) and more extreme rainfall and storm events. Therefore, effective adaptation strategies are essential to reduce future flood risk in exposed communities. The planning and implementation of effective adaptation strategies require a comprehensive understanding of future flood hazards and risks under future climate conditions and adaptation options. The overarching goal of this dissertation is to improve the capacity to understand, estimate and mitigate future flood hazards and risks in coastal areas under uncertain climate change. To achieve this goal, first, a nonstationary mixture probability model was developed that enables simultaneous characterization of minor and major flood events under future sea level conditions. The probability model was used to estimate minor and major flooding frequency at 68 locations along the coasts of the Contiguous United States (CONUS). The results showed a significant increase in frequency of both minor and major flood events under future sea level conditions. However, the frequency amplification of minor and major flooding varied by coastal regions. While regions in the Pacific and southeast Atlantic coast are likely to be exposed to higher frequency amplification in major flooding, the Gulf and northeast Atlantic coastal regions should expect the highest minor flood frequency amplification. Second, the proposed mixture probability model was employed in a flood risk assessment framework to enable assessing future acute and chronic coastal flood risks under different SLR and adaptation levels. The HAZUS-MH flood loss ... Text Northeast Atlantic Digital Collections of Colorado (Colorado State University) Pacific
institution Open Polar
collection Digital Collections of Colorado (Colorado State University)
op_collection_id ftcolostateunidc
language English
topic extreme value analysis
mixture probability model
stormwater management
flood risk analysis
compound flood risk
sea level rise
spellingShingle extreme value analysis
mixture probability model
stormwater management
flood risk analysis
compound flood risk
sea level rise
Ghanbari, Mahshid
Nonstationary flood risk assessment in coastal regions under climate change
topic_facet extreme value analysis
mixture probability model
stormwater management
flood risk analysis
compound flood risk
sea level rise
description 2021 Spring. Includes bibliographical references. Coastal cities are exposed to multiple flood drivers including high tide, storm surge, extreme rainfall, and high river flows. The occurrence of these flood drivers, either in isolation or in combination, can cause significant risk to property and human life. Climate change is placing greater pressure on coastal communities by increasing frequency and intensity of flood events through sea level rise (SLR) and more extreme rainfall and storm events. Therefore, effective adaptation strategies are essential to reduce future flood risk in exposed communities. The planning and implementation of effective adaptation strategies require a comprehensive understanding of future flood hazards and risks under future climate conditions and adaptation options. The overarching goal of this dissertation is to improve the capacity to understand, estimate and mitigate future flood hazards and risks in coastal areas under uncertain climate change. To achieve this goal, first, a nonstationary mixture probability model was developed that enables simultaneous characterization of minor and major flood events under future sea level conditions. The probability model was used to estimate minor and major flooding frequency at 68 locations along the coasts of the Contiguous United States (CONUS). The results showed a significant increase in frequency of both minor and major flood events under future sea level conditions. However, the frequency amplification of minor and major flooding varied by coastal regions. While regions in the Pacific and southeast Atlantic coast are likely to be exposed to higher frequency amplification in major flooding, the Gulf and northeast Atlantic coastal regions should expect the highest minor flood frequency amplification. Second, the proposed mixture probability model was employed in a flood risk assessment framework to enable assessing future acute and chronic coastal flood risks under different SLR and adaptation levels. The HAZUS-MH flood loss ...
author2 Arabi, Mazdak
Ettema, Robert
Schumacher, Russ
Bhaskar, Aditi
format Text
author Ghanbari, Mahshid
author_facet Ghanbari, Mahshid
author_sort Ghanbari, Mahshid
title Nonstationary flood risk assessment in coastal regions under climate change
title_short Nonstationary flood risk assessment in coastal regions under climate change
title_full Nonstationary flood risk assessment in coastal regions under climate change
title_fullStr Nonstationary flood risk assessment in coastal regions under climate change
title_full_unstemmed Nonstationary flood risk assessment in coastal regions under climate change
title_sort nonstationary flood risk assessment in coastal regions under climate change
publisher Colorado State University. Libraries
publishDate 2021
url https://hdl.handle.net/10217/232588
geographic Pacific
geographic_facet Pacific
genre Northeast Atlantic
genre_facet Northeast Atlantic
op_relation 2020- CSU Theses and Dissertations
Ghanbari_colostate_0053A_16473.pdf
https://hdl.handle.net/10217/232588
op_rights Copyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
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