1. Summary of Results & Conclusions
Final Project
Summary of Results
&
Conclusions

2. 2008 Project“ TRUTH” Hydraulic Conductivity Layer 1
PW2 discharge reduced
To 0.90E8 ft3/year

3. Layer 2

4. Layer 3
All these complicated details may not matter.
What matters is to capture the essential features
of the system for the purposes of predicting
the response to pumping and the movement
of the contaminant particles.

5. Recharge rates
Extinction depths = 10, 30 ft
Leakance = 4 ft/yr

6. PW2. Dry cell.
Reduce pumping rate from
-0.99E8 ft3/year
to -0.90E8 ft3/year

7. PW1 doesn’t capture
any particles.

8. PW1
No cone of depression.
PW1 doesn’t look like a sink
and doesn’t capture particles.

9. Particles by-pass PW1 and
exit in PW2.
PW 2
All the particles exit in wells;
none end up in the playa.

10. All of the particles that enter in layer 1,
stay in layer 1.

11. Predicted ARM > Calibrated ARM
Calibration
Prediction
Group
ARM h
ARM ET (x10e7)
(at targets) 1
0.72
0.58
8.51 2
0.97
1.19
10.37 3
0.93
0.74
6.12 4*
2.76
6.84
*Dry cells. PW2 went dry.
Predicted ARM > Calibrated ARM

12. Calibration
Prediction
Group
ARM h
ARM ET (x10e7)
(at targets)
(at pumping wells)** 1
0.72
0.58
8.51
26.64 2
0.97
1.19
10.37
18.72 3
0.93
0.74
6.12
3.57 4*
2.76
6.84
6.50
*Dry cells. PW2 went dry.
** Doesn’t include PW2
since it is also a target.
1. Predicted ARM > Calibrated ARM
Generally predicted ARM at non-target cells > predicted ARM at target cells

13. 724 Project Results ? A “good” calibration does not guarantee
Includes results from
2006 and 4 other years ?
A “good” calibration
does not guarantee
an accurate prediction.

14. Calibrated ARM of around 1.0 is a good calibration.
2006
Project Results
Calibration
Prediction
Group
ARM h
ARM ET (x10e7)
(at targets)
(at pumping wells)* 1
1.16
0.20
2.87
5.02 2
0.80
0.52
1.81
2.27 3
1.18
0.47
2.73
12.77 4
2.39
0.784
0.76 5
2.07
1.13
1.61
2.61 6
0.96
0.45
2.13
2.90 7
0.92
0.956 8
0.50
0.604
3.70
2.71 9
0.054
0.0049
3.54
5.52
1. Predicted ARM > Calibrated ARM
Predicted ARM at pumping wells > predicted ARM at targets
*Does not include PW2 since it is also a target.

15. Calibrated ARM of around 1.0 is a good calibration.
Prediction
Group
ARM h
ARM ET (x10e7)
(at targets)
(at pumping wells)* 1
1.16
0.20
2.87
5.02 2
0.80
0.52
1.81
2.27 3
1.18
0.47
2.73
12.77 4
2.39
0.784
0.76 5
2.07
1.13
1.61
2.61 6
0.96
0.45
2.13
2.90 7
0.92 8
0.50
0.60
3.70
2.71 9
0.054
0.0049
3.54
5.52
1. Predicted ARM > Calibrated ARM
Predicted ARM at pumping wells > predicted ARM at targets
Predicted ARM at targets >
predicted ARM at pumping wells

16. 2006 Project Results Despite the relatively poor calibration, groups
Prediction
Group
ARM h
ARM ET (x10e7)
(at targets)
(at pumping wells)* 1
1.16
0.20
2.87
5.02 2
0.8
0.52
1.81
2.27 3
1.18
0.47
2.73
12.77 4
2.39
0.78
0.80
0.76 5
2.07
1.10
1.61
2.61 6
0.96
0.48
2.13
2.90 7
0.92 8
0.50
0.60
3.70
2.71 9
0.054
0.0049
3.54
5.52
Despite the relatively
poor calibration, groups
4 and 5 managed to
capture the essential
features of the system
for the purpose of
the prediction.

17. 2008 Results
Calibration
Prediction
Group
ARM h
ARM ET (x10e7)
(at targets)
(at pumping wells)** 1
0.72
0.58
8.51
26.64 2
0.97
1.19
10.37
18.72 3
0.93
0.74
6.12
3.57 4*
2.76
6.84
6.50
*Dry cells. PW2 went dry.
** Doesn’t include PW2
since it is also a target.

18. 2008 Particle Tracking

19. 2008 Results Particle Tracking Results    
travel time (yr) & exit location    
Group P1 P2 P3 P4 P5 P6 P7 1
4507
PW2
2100
461,423
220 PW4
3956
playa
24,923
1395 2
719
253
2192 86
PW4
5874
540
2424 3
87,800
114,000
646,000
PW3
21,000PW4
200,000
PW5
147,000
595,000 4*
2810
(Playa*)
1870
5270
172 PW4
1111
2490
8750
Truth
20,940 PW2
18,887 PW2
15,366 PW3
217 PW4
651 PW4
20,187 PW2
574
6 hits
or Luck?
*PW2 went dry.
PEST?
Low porosity gives high velocity
which yields short travel times.

20. 2006 Project Results Despite the relatively poor calibration, groups
Prediction
Group
ARM h
ARM ET (x10e7)
(at targets)
(at pumping wells)* 1
1.16
0.20
2.87
5.02 2
0.8
0.52
1.81
2.27 3
1.18
0.47
2.73
12.77 4
2.39
0.78
0.80
0.76 5
2.07
1.10
1.61
2.61 6
0.96
0.48
2.13
2.90 7
0.92 8
0.50
0.60
3.70
2.71 9
0.054
0.0049
3.54
5.52
Despite the relatively
poor calibration, groups
4 and 5 managed to
capture the essential
features of the system
for the purpose of
the prediction.

21. Particle Tracking Results
2006
Project Results
Particle Tracking Results
travel time (yr) & exit location    
Group P1 P2 P3 P4 P5 P6 P7 1
5450 playa
2561 PW2
5060 playa
1098 PW4
401 PW4
1465 playa
1220 PW2 2
2120 PW2
606 PW2
709 playa
474 PW4
595 PW4
608 playa
310 PW3 3
5247 PW2
1088 PW2
1599 playa
361 PW4
510 PW4
2317 PW1
2243 playa 4
6601 playa
1226 PW2
592 playa
623 PW4
846 PW4
968 playa
1194 PW2 5
4548 playa
1660 PW2
1513 playa
1412 PW4
744 PW4
817 PW1
4410 playa 6
1.20E5 PW5
820 PW2
1.82 E4 PW5
587 PW4
576 PW4
1.19 E5 PW5
9990 PW5 7
4083 playa
1039 PW2
618 playa
647 PW4
629 PW4
908 playa
2484 PW2 8
2810 PW2
986 PW2
752 playa
659 PW4
577 PW4
359 PW1
502 PW3 9
546 PW1
534 PW2
1156 playa
402 PW4
1121 playa
91 PW1
1170 PW2
Truth
672 PW1
549 PW2
1.25 E5 playa
359 PW4
650 PW4
238 PW1
1712 playa
6 hits
5 hits

22. 2008 Results 3 0.93 6.12 3.57 6 hits or Luck? PEST? 0.74 20,940 PW2
Calibration
Prediction
Group
ARM h
ARM ET (x10e7)
(at targets)
(at pumping wells)** 3
0.93
0.74
6.12
3.57
Group P1 P2 P3 P4 P5 P6 P7 1
4507
PW2
2100
461,423
220 PW4
3956
playa
24,923
1395 2
719
253
2192 86
PW4
5874
540
2424 3
87,800
114,000
646,000
PW3
21,000PW4
200,000
PW5
147,000
595,000 4
2810
(Playa)
1870
5270
172 PW4
1111
2490
8750
Truth
20,940 PW2
18,887 PW2
15,366 PW3
217 PW4
651 PW4
20,187 PW2
574
6 hits
or Luck?
PEST?
2008 Results
Group 3 managed to capture the essential
features of the system for the best pumping
prediction and the best prediction of particle
exit points, but not travel times.

23. Observations Generally predicted ARM at targets > Calibrated ARM
Generally, predicted ARM at pumping wells >
Predicted ARM at nodes with targets
Head predictions are more robust (consistent among different calibrated models) than transport (particle tracking) predictions.

24. To use conventional inverse models/parameter estimation
models in calibration, you need to have a pretty good idea of
zonation (of K, for example).
(New version of PEST with pilot points does not need zonation as it works with continuous distribution of parameter values.)
Also need to identify reasonable ranges for the
calibration parameters.

25. Calibration to Fluxes
When recharge rate (R) is a calibration parameter, calibrating to fluxes can help in estimating K and/or R.
R was not a calibration parameter in our problem.

26. In this example, flux information helps calibrate K.
q = KI
K = ? H1 H2

27. or discharge information helps calibrate R.

28. In our example, total recharge is known/assumed to be 7
In our example, total recharge is known/assumed to be 7.14E08 ft3/year and discharge = recharge.
All water discharges to the playa.
Calibration to ET merely fine tunes
the discharge rates within the playa
area. Calibration to ET does not
help calibrate the heads and K values
except in the immediate vicinity
of the playa.

29. Conclusions Calibrations are non-unique.
A good calibration (even if ARM = 0)
does not ensure that the model will make
good predictions.
Field data are essential in constraining the model
so that the model can capture the essential
features of the system.
Modelers need to maintain a healthy skepticism
about their results.
Need for an uncertainty analysis to accompany
calibration results and predictions.