2020
DOI: 10.1029/2020ef001614
|View full text |Cite
|
Sign up to set email alerts
|

Flood Risks in Sinking Delta Cities: Time for a Reevaluation?

Abstract: Sea level rise (SLR) and subsidence are expected to increase the risk of flooding and reliance on flood defenses for cities built on deltas. Here, we combine reliability analysis with hydrodynamic modeling to quantify the effect of projected relative SLR on dike failures and flood hazards for Shanghai, one of the most exposed delta cities. We find that flood inundation is likely to occur in low‐lying and poorly protected periurban/rural areas of the city even under the present‐day sea level. However, without a… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4
1

Citation Types

1
41
0

Year Published

2021
2021
2024
2024

Publication Types

Select...
6
2

Relationship

3
5

Authors

Journals

citations
Cited by 48 publications
(42 citation statements)
references
References 68 publications
1
41
0
Order By: Relevance
“…[2017]) do not adequately take into account local features that affect flooding. Numerous large‐scale modeling studies have highlighted the need for flood adaptation databases (Sampson et al., 2015; Scussolini et al., 2016; Yin et al., 2020), although those currently available have significant limitations. For example, flood defenses in the Wing et al.…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…[2017]) do not adequately take into account local features that affect flooding. Numerous large‐scale modeling studies have highlighted the need for flood adaptation databases (Sampson et al., 2015; Scussolini et al., 2016; Yin et al., 2020), although those currently available have significant limitations. For example, flood defenses in the Wing et al.…”
Section: Introductionmentioning
confidence: 99%
“…Third, even the most highly resolved large-scale flood models (e.g., the 30 m resolution US model of Wing et al [2017]) do not adequately take into account local features that affect flooding. Numerous large-scale modeling studies have highlighted the need for flood adaptation databases (Sampson et al, 2015;Scussolini et al, 2016;Yin et al, 2020), although those currently available have significant limitations. For example, flood defenses in the Wing et al (2017) model taken from the US Army Corps of Engineers National Levee Database which is thought to be only ∼30% complete (American Society of Civil Engineers, 2017).…”
Section: Introductionmentioning
confidence: 99%
“…CC BY 4.0 License. protection standard) compared to the high floodwall (1000-year period flood protection standard) along the mid-and downstream urban regions of the Huangpu River (Yin et al, 2020). Furthermore, because the region has a northern subtropical monsoon climate, pluvial flood events caused by extreme rainfall, typically associated with typhoons, are frequently recorded during the flood season (June to September) (Yin & Zhang, 2015).…”
Section: Study Areamentioning
confidence: 99%
“…Cannata et al (2011) used a GIS-based approach to simplify a 2D dam break simulation. Yin et al (2020) predicted dike failures and flood inundations in Shanghai, China, under various emission scenarios using an interdisciplinary process-based approach.…”
Section: Introductionmentioning
confidence: 99%
“…Recently, such studies have focused on the wetland systems in the Mekong River delta, Vietnam (Nguyen et al, 2016(Nguyen et al, , 2017Binh et al, 2020), on the low-lying Jiangsu coast, China (Bao et al, 2019a;2019b), and the Yangtze River delta (Ma et al, 2018). For the megacity of Shanghai, which is situated at the Yangtze River mouth, scholars have identified high flood risk in the near future as a key concern (Yin et al, 2020), and evaluated the functioning of the coastal wetlands in flood hazard mitigation (Du et al, 2020). However, the balance between coastal wetland utilization and climate change adaptation needs further consideration, as is particularly the case for China.…”
Section: Introductionmentioning
confidence: 99%