modeling introduction

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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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