07/04/22 CJM 1 Modeling Introduction
Mar 22, 2016
04/24/23 CJM 1
Modeling Introduction
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What is a “model”? Any “device” that represents approximation
to field system Physical Models Mathematical Models
Analytical Numerical
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Modeling Protocol Establish the Purpose of the Model Develop Conceptual Model of the
System Select Governing Equations and
Computer Code Model Design Calibration
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Modeling Protocol Calibration Sensitivity Analysis Model Verification Prediction Predictive Sensitivity Analysis Presentation of Modeling Design and
Results Post Audit Model Redesign
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Purpose - What questions do you want the model to answer?
Prediction; System Interpretation; Generic Modeling
What do you want to learn from the model? Is a modeling exercise the best way to
answer the question? Historical data? Can an analytical model provide the answer?
System Interpretation: Inverse Modeling: Sensitivity Analysis
Generic: Response to Tidal Influences
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Model “Overkill”? Is the vast labor of characterizing the system,
combined with the vast labor of analyzing it, disproportionate to the benefits that follow?
EXAMPLE: Siting study for a residential community….one of the potential sites has some pre-existing contamination. You could complete a full-blown model of the site ($1 Mill) to learn that it is an unlikely candidate.
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ETHICS There may be a cheaper, more effective
approach Warn of limitations
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Conceptual Model“Everything should be made as simple as possible, but not simpler.” Albert Einstein
Pictoral representation of the groundwater flow system
Will set the dimensions of the model and the design of the grid
“Parsimony”….conceptual model has been simplified as much as possible yet retains enough complexity so that it adequately reproduces system behavior.
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Select Governing Equation
Select Computer Model Code Verification
Comparison to Analytical Solutions; Other Numerical Models
Model Design Design of Grid, selecting time steps,
boundary and initial conditions, parameter data set
Steady/Unsteady..1, 2, or 3-D; …Heterogeneous/Isotropic…..Instantaneous/Continuous
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Calibration Show that Model can reproduce field-
measured heads and flow (concentrations if cont. transport)
Results in parameter data set that best represents field-measured conditions.
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Calibration Sensitivity Analysis Uncertainty in Input Conditions Determine Effect of Uncertainty on
Calibrated Model
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Model Verification Use Model to Reproduce a Second Set of Field
Data
Prediction Desired Set of Conditions Sensitivity Analysis
Effect of uncertainty in parameter values and future stresses on the predicted solution
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Presentation of Modeling Design and Results
Effective Communication of Modeling Effort Graphs, Tables, Text, Physical
Models, Analogies
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Postaudit
New field data collected to determine if prediction was correct
Site-specific data needed to validate model for specific site application
Model Redesign Include new insights into system
behavior
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ASTM D 540 - 93
Standard Guide For Comparing Ground Water Flow Model Simulations to Site – Specific Information
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SCOPE Techniques for comparing ground
water flow model simulations to measured field data (CALIBRATION)
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Definitions Application Verification… approximate acceptably a second
set of field data Calibration… desired degree of correspondence
between model stimulations and observations
Censored Data
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Definitions Conceptual Models Residual
Xcomputed – Xobserved
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Quantitative Comparisons
Calculation of Head Residuals Correlation among Residuals Calculation of Flow Residuals
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Qualitative Comparisons General Flow Features Calibration Considerations
- Number of Distinct Conditions
- Reasonableness of Calibrated Data Set
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Use of Comparison Identify potentially beneficial
directions for further calibration efforts
Afford Confidence in Model
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Techniques Head Residuals
[ Point Heads, Not Contours][ same time, space]
r I = h i – H I
computed measured
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Techniques Residual Statistics
- maximum … largest positive- minimum … negative
one w/ max & min residuals closest to Ø has better correspondence… (this criterion)
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Techniques – Mean Value
nr
R ii
n
1
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Techniques – Standard Deviation
5.0
2
1
1
nRr
S i
n
i
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Techniques - mean value, R
One w/ R closest to Ø …(assuming there is no correlation among residuals) Never consider R alone
- standard deviation, SS
Smaller values of S, greater correspondence
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Correlations among Residuals
Spatial or Temporal Correlation Lesser correlation greater correspondence - Listings - Scattergrams - Spatial Correlation plot in plan or section - Temporal Correlation
BROWNFIELD REDEVELOPMENT
What is a Brownfield? Abandoned, idled or underused Industrial /
commercial facility where expansion or redevelopment is complicated by real or perceived environmental contamination.
A property which has been impacted by contaminants, including but not limited to hazardous substances and petroleum products.
Brownfield Redevelopment
Environmental and Financial Regulations:
– Site Evaluation Processes– Testing– Uncertainty in Environmental
Liability.– Expensive (Can’t Afford )
No One Wants to Play with Fire !
What is Being Done ? Federal, State, and Local Governments:
Change Regulations
Voluntary Remediation Programs
Establish Financial and/or Environmental Incentives.
Statistics By some estimates there are close to one million brownfield sites in the
United States.
As of June 20, 2002 Governor Engler stated during a press release :
In Michigan 30 brownfield properties are being redeveloped through the new brownfield regulations.
They are expected to generate more than $3 billion in private investment in Michigan’s core communities.
Brownfields Close to Home
City Project Investment (million)
Detroit Federal Office and Processing Center $90
American Axle World Headquarters $44
Compuware Headquarters $350
Monroe Mason Run $86
Marteq Project $24
Towns on Front Street $13
Cleanup of Contaminated Sites1. Site Assessment
2. Site Investigation
3. Assess Cleanup Options
4. Design and Implement Remedy
Site Investigation and RemediationModeling
Select Model: Track and Predict Impacts.
Furnish Input Parameters: Field/Laboratory Testing Published Values
Model sensitivity: Different Models Different
Results
Contaminant Transport Advection
Diffusion
Dispersion Sorption
Biodegradation
How Clean is Clean?The Tiered approach : Tiers are used to:
Evaluate/ develop cleanup objectives Evaluate Contaminant Transport Models
Multiple levels of complexity “tiers”: Tier 1 ….the most restrictive. Tier 2…..less restrictive than 1. Tier 3…..less restrictive than 2.
"Tiered" Risk-Based Cleanup
Concerns: Uncertainty Questionable Effectiveness and Reliability
Reasons for Concerns: Engineering Controls Cumulative Risk :
Multiple Contaminants The Ecosystem
Uncertainty in Fate/Transport Models.
Streamlining Brownfield Redevelopment
Alleviate the burdens associated with brownfield redevelopment.
Attract more developers to adopt contaminated sites for new construction.
Reduce the number of idled sites .
While maintaining enough confidence that results would not adversely affect the environment.
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