Publication Date

8-2023

Advisor(s) - Committee Chair

Jason Polk, Jun Yan, Nick Lawhon, James Shelley, Pat Kambesis

Degree Program

Department of Earth, Environmental, and Atmospheric Sciences

Degree Type

Master of Science

Abstract

Urban karst environments are often plagued by groundwater flooding, which occurs when water rises from the subsurface to the surface through the underlying caves and other karst features. The heterogeneity and interconnectedness of karst systems often makes them very unpredictable, especially during intense storm events; urbanization exacerbates the problem with the addition of many impervious surfaces. Residents in such areas are frequently disturbed and financially burdened by the effects of karst groundwater flooding. The Federal Emergency Management Agency (FEMA) offers limited protection to citizens living near flood-prone areas as they primarily focus on the areas near surface bodies of water. The City of Bowling Green, Kentucky is one of the largest cities in the United States built entirely upon karst and experiences frequent, unpredictable groundwater flooding making it the ideal study area for this project. This research attempted to aid the flooding problem in Bowling Green, by laying the framework for the creation of a predictive flood model in the Lost River Karst Aquifer, in Bowling Green, KY. The model was created primarily by analyzing relationships between precipitation and antecedent moisture conditions of the aquifer using effective precipitation and antecedent water levels as a proxy. High-resolution, spatiotemporal data monitoring of several hydrometeorological parameters to ensure accuracy of the model. The results from this study provide a stable and validated methodology to create a predictive flood model for karst environments that could potentially allow residents to better prepare for rain events and offers additional information on the storage and response times of a large karst aquifer.

Disciplines

Earth Sciences | Geology | Hydrology | Physical Sciences and Mathematics

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