GSA Connects 2022 meeting in Denver, Colorado

Paper No. 248-4
Presentation Time: 2:20 PM

WATER TABLE FLOODING EVENTS: MIAMI-DADE COUNTY FLORIDA JUNE 2022 CASE STUDY


SUKOP, Michael, Sea Level Solutions Center, Florida International University, University Park, MIAMI, FL 33199, ROGERS, Martina, Department of Earth and Environment, Florida International University, Miami, FL 33199 and OBEYSEKERA, Jayantha, Institute of Environment/Sea Level Solutions Center, Florida International University, University Park, MIAMI, FL 33199

Increasing precipitation intensity coupled with highly responsive groundwater tables appears to be responsible for flooding events in some cases. Areas of near-surface water tables, including many low-lying coastal areas, are likely to be particularly susceptible to such water table flooding. It is common for news media to note the ‘saturated’ or ‘swollen’ condition of the ground in many reports of flooding. But the precise meaning of this and its importance in predicting flooding remain unclear.

The 25- to 50-year return-period storms that impacted Miami-Dade County Florida in June 2022 can serve as a case study. Rapid increases in the water table elevation in response to the storms led to water tables approaching and exceeding the surface elevation in some areas and subsequently to widespread flooding. Due to typically low regional gradients in the region (~4 x 10-5 ) extrapolation of maximum measured water table elevations at wells to approximately one mile is generally expected to result in only small errors on the order of 0.2 feet.

Flooded areas estimated on the basis of this extrapolated maximum water table elevation approach are consistent with reports to the County Department of Emergency Management. A higher-density well network would enable enhanced estimation of flooded areas.

This approach might be exploited to provide early predictive estimation of flooding potential based on machine learning models trained to estimate the response of the water table to different intensity and duration rainfall events in the context of different antecedent conditions. Water table and precipitation monitoring data would ideally be co-located and available in real-time to enable near real-time estimation of what areas might be flooded. Such estimates of areas likely to be flooded could assist emergency responders in the allocation of their resources and guide potential evacuations.