Sinkhole Vulnerability Mapping Project Alan Baker, P.G. Clint - - PowerPoint PPT Presentation

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Florida Department of Environmental Protection Sinkhole Vulnerability Mapping Project Alan Baker, P.G. Clint Kromhout, P.G. Harley Means, P.G. Office of the Florida Geological Survey State Hazard Mitigation Plan Advisory Team Meeting , July

SLIDE 1

Florida Department of Environmental Protection

Alan Baker, P.G. Clint Kromhout, P.G. Harley Means, P.G. Office of the Florida Geological Survey

Sinkhole Vulnerability Mapping Project

State Hazard Mitigation Plan Advisory Team Meeting , July 16, 2013

SLIDE 2

Geologic Hazard Mapping Need

July 16, 2013 | 2

Summer of 2012 TS Debby triggered the formation of

thousands of sinkholes in Florida

This exposed the lack of a good planning tool to

mitigate large scale events or sinkhole swarms

and eventually lead to the FDEM contacting the FGS about developing a tool for evaluating the relative vulnerability of an “area” to sinkhole formation

SLIDE 3

July 16, 2013 | 3

SLIDE 4

Geologic Hazard

July 16, 2013 | 4

Sinkholes are a geologic hazard
Vulnerability depends on natural (geologic, hydrologic

and meteorological) and human (water pumping, terra-forming and ground loading)

Sinkhole hazards or risk of impact from the presence
f them increase with population
are not reported unless impact infrastructure

SLIDE 5

Underlying Geology

July 16, 2013 | 5

Major sections of Florida’s peninsula is made up of

carbonate rock and overlain by variable thicknesses of sand and clay

These carbonate rocks dissolve slowly over time due

to chemical processes and create karst terrains

Karst terrains are characterized by sinkholes, caves,

springs, disappearing/ reappearing streams and other land surface depressions

SLIDE 6

Types of Sinkholes

July 16, 2013 | 6

Two types of sinkholes
collapse – form when the roof of an underground

void can no longer support the weight of the

verburden causing a sudden collapse into voids
subsidence – form when the overburden slowly

migrates into the cracks and fissures in the underlying rock resulting in an apparent depression in land surface

SLIDE 7

Cover Collapse Sinkhole – Natural

Normal conditions
Drought
Intense rainfall

Modified from USGS

SLIDE 8

Cover Collapse Sinkhole - Induced

Modified from USGS

Pumping well

SLIDE 9

Cover Subsidence Sinkhole

Source: USGS

SLIDE 10

Triggering mechanisms

July 16, 2013 | 10

Changes in water-table elevation
Natural (TS Debby case study)
Pumping (Frost-Freeze case study)
Rainfall and soil piping
Land surface disturbance
Construction/ Excavation/ Loading
Landfills
Reservoirs
Focused infiltration: runoff, stream diversion or

retention ponds

SLIDE 11

Buried Karst and Infrastructure

Excavated retention basin Cap over solution pipe

SLIDE 12

Methodology - Weights of Evidence (WofE)

July 16, 2013| 12

Combines spatial data from diverse sources to describe and

analyze interactions and make predictive models (where will contamination likely occur?)

The magnitude of the weights depends on the measured

association between data layers and “type” occurrences (for FAVA: contaminated wells)

Uses a statistical association between contaminant
ccurrences and a data layer to estimate probability that an

area will contain a contaminated occurrence (i.e., a training point)

SLIDE 13

WofE continued..

July 16, 2013| 13

Combined evidence involves the estimation of a

response variable (probability or favorability for determining relative vulnerability) using a set of predictor variables (sinkholes)

Weights are estimated from the measured association

between known sinkhole occurrences and the values on the maps used as predictors

SLIDE 14

WofE Terminology

July 16, 2013 | 14

Evidential Theme (data layer)
Overburden thickness
Soil drainage
Predictor Theme (training points or contaminant
ccurrences)
Known sinkholes/ karst terrain
Response Theme
Model output
Relative vulnerability map

SLIDE 15

Training Points as Predictors

July 16, 2013 | 15

Point coverage of locations at which a “type” occurrence

is present

Occurrences can be sinkholes or karst features
The set of point locations is used to calculate the

weights for each data layer, one weight per class, using

verlap relationships between points and the various

classes

SLIDE 16

Response Theme

July 16, 2013 | 16

An output map that displays the probability that a unit area

contains a point

Calculated by estimating the combined weights of the data

layers

Output theme is displayed in classes of relative vulnerability