Modeling Introduction

1. Modeling Introduction CJM

2. What is a “model”? • Any “device” that represents approximation to field system • Physical Models • Mathematical Models • Analytical • Numerical CJM

3. Modeling Protocol • Establish the Purpose of the Model • Develop Conceptual Model of the System • Select Governing Equations and Computer Code • Model Design • Calibration CJM

4. Modeling Protocol • Calibration Sensitivity Analysis • Model Verification • Prediction • Predictive Sensitivity Analysis • Presentation of Modeling Design and Results • Post Audit • Model Redesign CJM

5. 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 CJM

6. 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. CJM

7. ETHICS • There may be a cheaper, more effective approach • Warn of limitations CJM

8. 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. CJM

9. Select Governing Equation Steady/Unsteady..1, 2, or 3-D; …Heterogeneous/Isotropic…..Instantaneous/Continuous • 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 CJM

10. 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. CJM

11. Calibration Sensitivity Analysis • Uncertainty in Input Conditions • Determine Effect of Uncertainty on Calibrated Model CJM

12. 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 CJM

13. Presentation of Modeling Design and Results • Effective Communication of Modeling Effort • Graphs, Tables, Text, Physical Models, Analogies CJM

14. 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 CJM

15. ASTM D 540 - 93 Standard Guide For Comparing Ground Water Flow Model Simulations to Site – Specific Information CJM

16. SCOPE • Techniques for comparing ground water flow model simulations to measured field data (CALIBRATION) CJM

17. Definitions • Application Verification … approximate acceptably a second set of field data • Calibration … desired degree of correspondence between model stimulations and observations • Censored Data CJM

18. Definitions • Conceptual Models • Residual Xcomputed – Xobserved CJM

19. Quantitative Comparisons • Calculation of Head Residuals • Correlation among Residuals • Calculation of Flow Residuals CJM

20. Qualitative Comparisons • General Flow Features • Calibration Considerations - Number of Distinct Conditions - Reasonableness of Calibrated Data Set CJM

21. Use of Comparison • Identify potentially beneficial directions for further calibration efforts • Afford Confidence in Model CJM

22. Techniques • Head Residuals [ Point Heads, Not Contours] [ same time, space] r I = h i – H I computed measured CJM

23. Techniques • Residual Statistics - maximum … largest positive - minimum … negative one w/ max & min residuals closest to Ø has better correspondence… (this criterion) CJM

24. Techniques – Mean Value CJM

25. Techniques – Standard Deviation CJM

26. Techniques - mean value, R One w/ R closest to Ø …(assuming there is no correlation among residuals) Never consider R alone - standard deviation, S Smaller values of S, greater correspondence CJM

27. Correlations among Residuals • Spatial or Temporal Correlation Lesser correlation greater correspondence - Listings - Scattergrams - Spatial Correlation plot in plan or section - Temporal Correlation CJM

28. BROWNFIELD REDEVELOPMENT

29. 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.

30. 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 !

31. What is Being Done ? • Federal, State, and Local Governments: • Change Regulations • Voluntary Remediation Programs • Establish Financial and/or Environmental Incentives.

32. 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.

33. Brownfields Close to Home

34. Cleanup of Contaminated Sites • Site Assessment • Site Investigation • Assess Cleanup Options • Design and Implement Remedy

35. Site Investigation and Remediation Modeling • Select Model: • Track and Predict Impacts. • Furnish Input Parameters: • Field/Laboratory Testing • Published Values • Model sensitivity: • Different Models Different Results

36. Contaminant Transport • Dispersion • Sorption • Advection • Diffusion • Biodegradation

37. 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.

38. "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. The Future

39. 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.

40. CJM