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Uncertainty and Non-uniqueness

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Presentation on theme: "Uncertainty and Non-uniqueness"— Presentation transcript:

1 Uncertainty and Non-uniqueness
The calibrated model is always non-unique..

2 Traditional approach Two types of uncertainty analysis
Uncertainty in the calibration. This is usually called a sensitivity analysis Uncertainty in the prediction. This is usually called an uncertainty analysis.

3 Steps in Transport Modeling
Traditional approach Adjust parameter values Calibration sensitivity analysis Prediction (Zheng and Bennett)

4 Perform sensitivity analysis during calibration
New Paradigm Perform sensitivity analysis during calibration to help find the “best” solution. Sensitivity coefficients Assess uncertainty in the prediction during calibration.

5 New Paradigm Multi-model Analysis (MMA) Predictions and sensitivity
analysis are now inside the calibration loop From Hill and Tiedeman 2007

6 Case Study: Woburn, Massachusetts
Several equally plausible simulations of TCE transport were developed based on estimates of source locations, source concentrations, release times, and retardation. It cannot be determined which, if any, of the plausible scenarios actually represents what occurred in the groundwater flow system during this period, even though each of the plausible scenarios closely reproduced measured values of TCE.

7 An example from John Doherty
Cattle Ck.

8 Cattle Creek Catchment

9 Soils and current land use

10 New Development CANE EXPANSION CURRENT

11 Model grid; fixed head and drainage cells shown coloured

12 Calibrated transmissivities

13 Modelled and observed water levels after model calibration.
14 different versions of the conceptual model all showed high water levels in the area of interest.

14 Monte Carlo Analysis Z&B

15 PDF CDF Z&B Fig. 13.1

16 PDF CDF Z&B Fig. 13.2

17 Hydraulic conductivity
Initial concentrations (plume configuration) Both Z&B Fig. 13.5

18 With inverse flow modeling
Reducing Uncertainty Hypothetical example truth Hard data only Soft and hard data With inverse flow modeling Z&B Fig. 13.6

19 “Truth lies at the bottom of a bottomless pit.”
J. Facher, attorney for Beatrice, Woburn Trial “…knowledge competes with resolution…” L.N. Hughes, Federal Judge “One more run…”

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