Coastal flooding, caused by sea level rise (SLR), storm surge, and tropical cyclones, is a growing threat. Previous studies have documented mortality associated with historical coastal flooding and developed predictions of mortality risk based on SLR and human development. This study updates those estimates and provides a new model by including new mortality data from events between 2010 and 2020 and an updated method for estimating the population exposed to coastal flooding events. Primary data sources include the Emergency Events Database (EM-DAT) and the Sea Level Impacts Input Dataset by Elevation, Region, and Scenario (SLIIDERS) model. We first characterize trends in exposed populations and mortality associated with coastal flooding between 1990 and 2020. A mixed effect regression model estimates mortality associated with coastal flooding and investigates the influence of variables including Human Development Index (HDI), country population, and event frequency. The frequency of coastal flooding events between 1990 and 2020 has increased, while there was an overall decrease in recorded deaths associated with coastal flooding events. The association between mortality and coastal flood exposure is reduced in countries with higher populations. This result suggests countries with larger populations may buffer risks in exposed regions. Results showed significant reduction in mortality risk, by approximately 34% (95% CI, 17-47%), associated with an increase of approximately 61 million in country-level population. Additionally, a 7% increase (95% CI, 3-11%) in mortality risk with each additional occurrence of coastal flooding events was observed. By leveraging this knowledge, decision-makers can develop targeted policies and interventions to enhance community preparedness, reduce vulnerability, and ultimately save lives in the face of increasing coastal flooding risks. / Master of Science / This study aims to explore the association between coastal flooding deaths and socio-economic variables globally. Additionally, it seeks to analyze trends in coastal flooding mortality, exposed populations, and flooding frequency across global regions, as well as income regions differentiated by the World Bank, from 1990 to 2020. Coastal flooding mortality data for every coastal flooding event were sourced from EM-DAT, a widely utilized disaster database. We utilized a climate model to retrieve the population exposed to coastal flooding for every event. Human Development Index (HDI) data and country population from 1990 to 2020 were taken from United Nations Development Programme (UNDP) and World Bank databases, respectively. A statistical model was used to estimate mortality risk associated with coastal flooding events and to investigate the influence of variables including Human Development Index (HDI), population, and event frequency. The frequency of coastal flooding events between 1990 and 2020 has increased, while there was an overall decrease in recorded deaths associated with coastal flooding events. The association between mortality and coastal flood exposure is reduced in countries with higher populations. This result suggests countries with larger populations may buffer risks in exposed regions. Results showed significant reduction in mortality risk, by approximately 34% (95% CI, 17-47%), associated with an increase of approximately 61 million in country population. Additionally, a 7% increase (95% CI, 3-11%) in mortality risk with each additional occurrence of a coastal flooding event was observed.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/119459 |
| Date | 14 June 2024 |
| Creators | Timilsina, Saurav |
| Contributors | Environmental Science and Engineering, Gohlke, Julia M., Marr, Linsey C., Foroutan, Hosein |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
Page generated in 0.0022 seconds