Collaborative Research: Detection and mechanics of sinkhole activity in Central Florida Grant

Collaborative Research: Detection and mechanics of sinkhole activity in Central Florida .

abstract

  • Sinkhole activity in central Florida is a major natural hazard. Over the past several years, two events in particular attracted media attention. In March 2013, a sinkhole collapsed beneath a house in Seffner and "swallowed" a person from his bedroom. In August 2013 a sinkhole collapse destroyed a resort complex near Disney World. These dramatic events, however, are just extreme examples that stand out from a steady stream of about $200 million per year in property damage claims, which spike at times of anthropogenic groundwater withdrawals. Detecting incipient sinkhole activity is a challenging task, because most of the activity occurs in the subsurface. However, in some cases sinkhole activities also induce surface subsidence, which can be detected by space-based Interferometric Synthetic Aperture Radar (InSAR) observations. This project is a follow up of a proof-of-concept project funded by NSF, in which the researchers demonstrated that InSAR observations can detect localized patterns of surface changes in central Florida. However, the detection of slow subsidence using more advanced InSAR time series techniques requires longer span of acquisitions than obtained during the limited duration of the initial project. In this renewal project, we propose to continue the InSAR-based detection of sinkhole activity in central Florida by extending the observation period for two additional years. The longer time series will allow us to reduce the effect of measurement noise and detect localized slow subsidence induced by sinkhole activity. The proposed project also includes geophysical surveys to map sinkhole structure and soil sampling at selected field sites. In addition, a mechanical modeling effort will examine whether, at the field sites, InSAR-detected subsidence is compatible with measured properties of cohesive soils, field data, and simple models for sinkhole subsidence. This modeling method could be used to assess whether observed subsidence represents a likely precursor to collapse.

date/time interval

  • September 15, 2016 - August 31, 2020

sponsor award ID

  • EAR-1620617

local award ID

  • AWD000000007007

contributor