Diatom Evidence of a Paleohurricane-Induced Coastal Flooding Event in Weeks Bay, Alabama, USA

Coastal flooding is a natural disaster that often occurs in coastal areas. Jakarta is an example of a location that is highly vulnerable to coastal flooding. Coastal flooding can result in economic and human life losses. Thus, there is a need for a coastal flooding early warning system in vulnerable locations to reduce the threat to the community and strengthen its resilience to coastal flooding disasters. This study aimed to measure the level of public acceptance toward the development of a coastal flooding early warning system of people who live in a coastal region in Jakarta. This knowledge is essential to ensure that the early warning system can be implemented successfully. A survey was conducted by distributing questionnaires to people in the coastal areas of Jakarta. The questionnaire results were analyzed using cross-tabulation and path analysis based on the variables of knowledge, perceptions, and community attitudes towards the development of a coastal flooding early warning system. The survey result shows that the level of public acceptance is excellent, as proven by the average score of the respondents’ attitude by 4.15 in agreeing with the establishment of an early warning system to manage coastal flooding. Thus, path analysis shows that knowledge and perception have a weak relationship with community attitudes when responding to the coastal flooding early warning model. The results show that only 23% of the community’s responses toward the coastal flooding early warning model can be explained by the community’s knowledge and perceptions. This research is expected to be useful in implementing a coastal flooding early warning system by considering the level of public acceptance.

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Coastal Flooding Today, Tomorrow, and the Next Ten Years in East Coast U.S. Cities

10.1002/essoar.10505392.1 ◽

2020 ◽

Author(s):

Marybeth Arcodia ◽

Emily Becker ◽

Ben Kirtman

Keyword(s):

East Coast ◽

Coastal Flooding

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Impacts of Sea Level Rise on Compound Fluvial and Coastal Flooding

10.1002/essoar.10501701.1 ◽

2020 ◽

Author(s):

Mahshid Ghanbari ◽

Mazdak Arabi

Keyword(s):

Sea Level Rise ◽

Sea Level ◽

Coastal Flooding

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Quantifying Uncertainty in Exposure to Coastal Hazards Associated with Both Climate Change and Adaptation Strategies: A U.S. Pacific Northwest Alternative Coastal Futures Analysis

Water ◽

10.3390/w13040545 ◽

2021 ◽

Vol 13 (4) ◽

pp. 545

Author(s):

Alexis K. Mills ◽

Peter Ruggiero ◽

John P. Bolte ◽

Katherine A. Serafin ◽

Eva Lipiec

Keyword(s):

Climate Change ◽

Sea Level Rise ◽

Sea Level ◽

Performance Metrics ◽

Coastal Flooding ◽

Water Levels ◽

Coastal Hazards ◽

Policy Decisions ◽

Management Decisions ◽

Quantifying Uncertainty

Coastal communities face heightened risk to coastal flooding and erosion hazards due to sea-level rise, changing storminess patterns, and evolving human development pressures. Incorporating uncertainty associated with both climate change and the range of possible adaptation measures is essential for projecting the evolving exposure to coastal flooding and erosion, as well as associated community vulnerability through time. A spatially explicit agent-based modeling platform, that provides a scenario-based framework for examining interactions between human and natural systems across a landscape, was used in Tillamook County, OR (USA) to explore strategies that may reduce exposure to coastal hazards within the context of climate change. Probabilistic simulations of extreme water levels were used to assess the impacts of variable projections of sea-level rise and storminess both as individual climate drivers and under a range of integrated climate change scenarios through the end of the century. Additionally, policy drivers, modeled both as individual management decisions and as policies integrated within adaptation scenarios, captured variability in possible human response to increased hazards risk. The relative contribution of variability and uncertainty from both climate change and policy decisions was quantified using three stakeholder relevant landscape performance metrics related to flooding, erosion, and recreational beach accessibility. In general, policy decisions introduced greater variability and uncertainty to the impacts of coastal hazards than climate change uncertainty. Quantifying uncertainty across a suite of coproduced performance metrics can help determine the relative impact of management decisions on the adaptive capacity of communities under future climate scenarios.

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Raster modelling of coastal flooding from sea‐level rise

International Journal of Geographical Information Science ◽

10.1080/13658810701371858 ◽

2008 ◽

Vol 22 (2) ◽

pp. 167-182 ◽

Cited By ~ 178

Author(s):

B. Poulter ◽

P. N. Halpin

Keyword(s):

Sea Level Rise ◽

Sea Level ◽

Coastal Flooding

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Bankruptcy filings, flooding, real estate prices and Leading Index

Property Management ◽

10.1108/pm-02-2021-0018 ◽

2021 ◽

Vol ahead-of-print (ahead-of-print) ◽

Author(s):

Billie Ann Brotman

Keyword(s):

Housing Prices ◽

The United States ◽

Flood Insurance ◽

Single Family ◽

Personal Bankruptcy ◽

Content Type ◽

Independent Variables ◽

Flooding Event ◽

Flooding Events ◽

The Impact

PurposeFlood damage to uninsured single-family homes shifts the entire burden of costly repairs onto the homeowner. Homeowners in the United States and in much of Europe can purchase flood insurance. The Netherlands and Asian countries generally do not offer flood insurance protection to homeowners. Uninsured households incur the entire cost of repairing/replacing properties damaged due to flooding. Homeowners’ policies do not cover damage caused by flooding. The paper examines the link between personal bankruptcy and the severity of flooding events, property prices and financial condition levels.Design/methodology/approachA fully modified ordinary least squares (FMOLS) regression model is developed which uses personal bankruptcy filings as its dependent variable during the years 2000 through 2018. This time-series model considers the association between personal bankruptcy court filings and costly, widespread flooding events. Independent variables were selected that potentially act as mitigating factors reducing bankruptcy filings.FindingsThe FMOLS regression results found a significant, positive association between flooding events and the total number of personal bankruptcy filings. Higher flooding costs were associated with higher bankruptcy filings. The Home Price Index is inversely related to the bankruptcy dependent variable. The R-squared results indicate that 0.65% of the movement in the dependent variable personal bankruptcy filings is explained by the severity of a flooding event and other independent variables.Research limitations/implicationsThe severity of the flooding event is measured using dollar losses incurred by the National Flood Insurance program. A macro-case study was undertaken, but the research results would have been enhanced by examining local areas and demographic factors that may have made bankruptcy filing following a flooding event more or less likely.Practical implicationsThe paper considers the impact of the natural disaster flooding on bankruptcy rates filings. The findings may have implications for multi-family properties as well as single-family housing. Purchasing flood insurance generally mitigates the likelihood of severe financial risk to the property owner.Social implicationsNatural flood insurance is underwritten by the federal government and/or by private insurers. The financial health of private property insurers that underwrite flooding and their ability to meet losses incurred needs to be carefully scrutinized by the insured.Originality/valuePrior studies analyzing the linkages existing between housing prices, natural disasters and bankruptcy used descriptive data, mostly percentages, when considering this association. The study herein posits the same questions as these prior studies but used regression analysis to analyze the linkages. The methodology enables additional independent variables to be added to the analysis.

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