1. PARAMETERIZATION, UNCERTAINTY – AND “REAL WORLD” MODELING
Examples of Uncertainty from Everyday Models
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2. Model Applications See www.sspa.com for more details SIMULATION
PREDICTION
PARAMETERS
CALIBRATION
PRIOR INFORMATION
Saline Intrusion
Maximum Salinity
Boundaries, flow, transport
Heads, flows, salinities
Pump tests
Contaminant transport
Contaminant source location
Heads, flows, concentrations, mass flux
Pump tests, slug tests
Maximum influent concentration
Pump tests, slug tests, domestic water use (recharge)
Water supply
Baseflow depletion, wetland levels
Boundaries, flow
Heads, flows, depletions
Recharge (DPIRSIM/Regression), Pump tests
Local flow
Surface water seepage
Heads, flows, seepage measurements
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3. Examples PROJECT UNCERTAINTY LI-1 LI-2 MI Uniondale, Long Island
MTBE plume, IRM design
Geologic setting - results presentation
Hampton Bays, Long Island
Contaminant distribution - mass
Michigan
Water supply study
Surface water impacts
Flows - problem formulation and simulation
LI-1
LI-2 MI
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4. Salient Points
Build the model with parameterization in mind right from the beginning
Construct calibration targets in the beginning and revise throughout to obtain details
Build calibration tools/programs right from the start
Construct graphical post-processing tools from beginning and throughout – graphs, maps, summary statistics
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5. PEST as Pre-Post Processor
Early steps in model construction – code selection, domain, spatial discretization – are reasonably unlikely to change
Hence - can use PEST from this point forward to control runs, vary parameters, etc
Build open-ended programs – modular, error handling
Calibration/uncertainty tool remains current as the model develops
Model testing takes place as model built
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