Presented at the Annual Workshop of the Hydrogeology Consortium
November 8-9, 2001, Orlando, FL
 
Topic 2: Characterization of Karst Sites (Data): Data limitations and needs, acquisition techniques and costs, and optimizing data use

Overview
Summary

Overview (morning session)

Characterization of Karst Sites
Data limitations and needs, acquisition techniques and costs, and optimizing data use
Amy Chan-Hilton, Ph.D. 
FAMU-FSU College of Engineering
abchan@eng.fsu.edu

Data, Data, Data!

  • Conceptual models based on data
  • Model predictions require good data
  • What types of data are needed?
  • How much data is sufficient?
  • Temporal data
  • Spatial data
Data Limitations and Needs
  • Direct and indirect data
  • Hydraulic heads
  • Flow rates and turbulence
  • Hydraulic conductivity
  • Geology: material and formation
  • Geochemical data
  • Pollutant concentrations
Data Limitations and Needs 2
  • Recharge and discharge points
  • Drainage basins 
  • Morphology of cave systems
  • Surface area and length
  • Size distribution of passages
  • Conduit boundaries  
  • Surface/subsurface flow routes
Data Acquisition Techniques
  • Dye tracer tests
  • Surficial Methods:
  • Direct-current electrical resistivity imaging
  • Electromagnetic conductivity
  • Ground-penetrating radar 
  • Gravity and aeromagnetic methods
  • Seismic methods
Data Acquisition Techniques 2
  • Geoprobe push technology
  • Cone penetrometer
  • Well Logging (profiling boreholes)
  • Aerial photographs 
  • Remote Sensing
  • Geographical information systems (GIS)
Optimizing Data Use
  • Characterization/sampling plan
  • Calibration: fit model to existing data, non-unique solution 
  • Inverse modeling: parameter fitting by optimization
  • Minimize error between predictions and data
  • Techniques: genetic algorithms, nonlinear programming, etc.
Optimizing Data Use 2
  • Probabilistic methods
  • Prediction: length of prediction ~ duration of data 
  • Sensitivity analysis and model verification
  • Postaudit: update model based on predictions and new data 
What are your experiences?
  • Data needs
  • Data acquisition techniques
  • Costs
  • Data use
  • Optimization and data


Summary of Break-out Session Discussion

Characterization of Karst Sites: Summary
Amy Chan-Hilton, Ph.D.
FAMU-FSU College of Engineering
abchan@eng.fsu.edu
http://www.eng.fsu.edu/~abchan

Data-The Big Picture

  • Define data objectives
    • Models-help understand system
    • Calibration
    • Verification
    • Postaudit modification
    • Monitoring
  • Then determine
    • What type of data is needed
    • How much data is sufficient
  • All this may be iterative
Existing Data
  • Document existing data
  • Consolidate existing data
  • Multiple data sets
  • Quality of existing data
  • QC/QA and standards
  • Data collected by experienced, hands-on people
Scale Issues
  • Data resolution
  • Data location
  • Data depth
  • Surface vs. subsurface data
  • Expectations based on geology?
  • Regional – Local – Borehole
Spatial Data Types
  • Direct and indirect data
  • Hydraulic heads
  • Flow rates
  • Temperature
  • Sinkholes
  • Morphology of cave systems - mapping
  • Surface area and length
  • Size distribution of passages
  • Fractures
Spatial Data Types 2
  • Land use – withdrawals
  • Hydraulic conductivity – vertical and horizontal
  • Geology - current and historical
  • Geochemical data
  • Stream flows
  • Recharge and discharge points
  • Drainage basins 
  • Surface/subsurface flow routes
Data Issues
  • May be biased spatially
  • Data may change over time
  • Confined (semi- or leaky) vs. unconfined karst
  • Politics of acquiring data – costs
Data Acquisition Techniques
  • Different methods for different scales 
  • Remote sensing methods (Regional & Local)
  • Fracture-trace tests (Regional & Local)
  • Aerial photographs (Regonal & Local)
  • Tracer tests (Regional & Local)
  • Pumping tests (Regional & Local)
Data Acquisition Techniques 2
  • Surficial Methods (Local):
    • Direct-current electrical Resistivity imaging
    • Electromagnetic conductivity
    • Ground-penetrating radar 
    • Microgravity and aeromagnetic methods
    • Seismic methods (refraction and reflection)
Data Acquisition Techniques 3
  • Borehole methods
    • Direct data logging: heads, flow, temperature, conductivity, porosity, density, natural gamma
    • Imaging: video, acoustic televiewer (360o), photo teleview (360o)
  • Geoprobe push technology
  • Cone penetrometer
Optimizing Data Acquisition
  • Limited budget!
  • Characterization/sampling plan-based on objectives
  • DOE Expedited Site Characterization (ASTM)
  • ASTM karst groundwater monitoring guidelines
  • How much data is sufficient?
    • Sensitivity analysis
    • Reduce uncertainty and risk, increase reliability
  • Optimization approaches to help guide us (genetic algorithms, etc.)
Optimizing Data Use
  • Multilayer, multiscale data compilation 
  • GIS for data analysis
  • Data interpolation 
  • Probabilistic methods
Data and Models
  • Calibration: fit model to existing data, non-unique solution 
  • Inverse modeling: parameter fitting by optimization
    • Minimize error between predictions and data
    • Techniques: genetic algorithms, nonlinear programming
  • Prediction: length of prediction ~ duration of data 
  • Sensitivity analysis
  • Model testing for applicability
  • Iteratively update model based on predictions and new data (postaudit)
Florida Database
  • Need one!
  • Data needs to be verified
  • Include metadata
  • Hydrogeology Consortium may be appropriate entity to coordinate this
  • Funding and support
  • SFWMD – hydrogeology database available in late 2002
Summary
  • Appropriate, adequate and accurate data
  • Data at multiple scales needed
  • Different methods for different scales
  • Optimize data acquisition and data use
  • Iterative process between data and models
URL http://www.eng.fsu.edu/~abchan