Date of Award

Summer 7-16-2021

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Civil and Environmental Engineering

Advisor(s)

Kelleher, Christa

Keywords

blue spots, fast inundation model, FEMA, high-resolution DEM, land cover, pluvial flooding

Subject Categories

Civil and Environmental Engineering | Engineering

Abstract

Although there have been many advances in regulations to assess flood risk in urban environments, the majority of these investigations to date have focused on fluvial or coastal flooding. However, in urban systems, pluvial flooding continues to be a pressing issue in need of attention. Due to the limited research on pluvial flooding in Syracuse, NY, its population and assets are exposed to the risks imposed by this type of flooding, as their primary metric for delineating flood risk is the traditional riverine flood zones designated by the Federal Emergency Management Agency (FEMA). To address this issue, this research implemented an existing 1D rainfall-runoff model to screen for pluvial flooding risk in Syracuse using a 1 m resolution DEM with simulations generated for a 100-year 1-hour storm size. The analysis was executed for five different boundaries, including the City of Syracuse municipal boundary and four watersheds that terminate within the city. To ascertain the accuracy of the approach, I compared model predictions of flood locations – called blue spots – to locations of flooding from news reports of large storms (n = 16) as well as areas of reported street flooding from a municipal database (n = 65). While 87.5% of locations obtained from news reports corresponded with the blue spots with various depths, only about a third of municipal database reports matched the blue spots. Across all boundaries, I compared blue spot depths within five depth categories (from nuisance to very high risk) to high resolution land cover and with the FEMA floodplain. I found that the majority of blue spots, including the deepest areas, were located in pervious areas, which may be related to some limitations and assumptions of the approach. However, some areas predicted to flood using the blue spot method were within critical areas, such as roads, commercial and residential areas. Information about these critical areas may be useful for providing mitigation and adaptation strategies (e.g., frequently maintenance of the drainage systems; locations where investments are needed to improve the drainage networks). Finally, I found that most blue spots indicative of areas at risk from pluvial flooding were concentrated outside of the FEMA floodplain. Overall, my study emphasizes the need to analyze different types of flooding together to improve flood risk assessment in urban environments.

Access

Open Access

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