Improving Estimation of Inter-basin Groundwater Flowinto Northern Yucca Flat, Nevada National Security Site,

Using Multi-models and Multi-kinds of Observations

Ming Ye1, Liying Wang1, and Karl F. Pohlmann2

1Department of Scientific Computing, Florida State University

2Division of Hydrologic Sciences, Desert Research Institute

Supported by DOE contract DE-AC52-06NA26383

andNSF Grant NSF-EAR 0911074

Nevada National Security Site and Yucca Flat

Nevada National Security Site• Located 65 miles north of Las Vegas• 928 nuclear tests from 1951 to 1992

Yucca Flat• Located at NNSS northeast corner• 739 nuclear tests were conducted

Photo courtesy of National Nuclear Security Administration / Nevada Site Office

As part of the Corrective Action Investigation, models of groundwater flow and radionuclide transport are being developed.

This study arises from DOE’senvironmental restoration program on the NNSS, specifically for Yucca Flat.

Inter-basin Groundwater Flow (Qy) from Northern Yucca Flat (Climax Mine) to Yucca Flat

• The Climax Mine area is located at the northern end of the Yucca Flat-Climax Mine CAU.

• Three tests were conducted in the very different hydrogeologic setting of the Climax Mine granite stock.

• Modeling objective: Provide simulated inter-basin groundwater flows (Qy) from the northern Yucca Flat with consideration of model uncertainty.

Estimates of Inter-basin Groundwater FlowPrevious studies show different estimates:• 1,180 m3/d (Winograd and Thordarson, 1975), but too small according to

Farnham et al. (2006)• 25,3000 m3/d (IT Corporation, 1996)• 40,829 m3/d (Belcher et al., 2004), consistent with the isotope study of

Carroll et al. (2008)• 44,407 ~ 106,622 m3/d (Pohlmann et al., 2007; Ye et al., 2010)

Estimates are inherently uncertain due to• uncertainty in the estimation methods (e.g., mass balance, isotopes, and

modeling), • uncertainty between different models, and• uncertainty in model parameters.

• Choose the estimate of 25,000 m3/d as the likely target.• Improve the estimate using multi-models and multi-kinds of

observations.

Numerical Modeling of the Death Valley Regional Flow System (DVRFS)

• U.S. Geological Survey (Belcher et al., 2004)

• MODFLOW 2000• Provides the framework

for sensitivity analysis and model calibration

• The entire DVRFS model is calibrated, as calibration data in northern Yucca Flat are limited.

• Convert from transient state to steady state

DVRFSmodelboundary

NorthernYucca Flat

Modified from Figure F-10, Belcher (2004)

Six Alternative Groundwater Flow Models• Pohlmann et al. (2007) and Ye et

al. (2010) considered a total of 25 models.

• The six most plausible ones are considered in this study.

• Two recharge models (R2 and R5)• Three geological models (G1 – G3)• Developed based on the DVRFS

framework

R2: Net infiltration model (NIM1) R5: Chloride mass balance model (CMB2)

Six Alternative Groundwater Flow Models• Pohlmann et al. (2007) and Ye et

al. (2010) considered a total of 25 models.

• The six most plausible ones are considered in this study.

• Two recharge models (R2 and R5)• Three geological models (G1 – G3)• Developed based on the DVRFS

framework

G2: Base Model G3: CP Thrust Alternative

Sensitivity Analysis and Model Calibration

• Select about 50 parameters to calibrate for each model.

• Calibrate all the six models using MODFLOW 2000.• Estimated inter-basin flow is significantly larger than

the target of 25,000 m3/day.

11,37510,76710,14010,88610,3849,883SSWR

39,50957,25227,57960,15250,44550,289Qy (m3/d)

495849584951Number of calibrated parametersG3R5G3R2G2R5G2R2G1R5G1R2Model

Reduction of Inter-basin Flow

• Small change in hydraulic conductivity may result in large change in Qy (red).

• SSWR (sum of squared weighted residual, blue) is quadratic about hydraulic conductivity.

• Reducing Qy estimate is possible by varying model parameters, but at (tolerable) sacrifice of model goodness-of-fit.K11_ICU

Qy

(m3 /d

)

SS

WR

0.002 0.004 0.006 0.00840000

45000

50000

55000

60000

65000

70000

10000

11000

12000

13000

14000

15000

(b)

Centered parameter study (implemented in DAKOTA) shows that

Modeling Procedure• Calibrate each model. • Conduct Morris runs for each model to determine the

critical parameters to which the Qy estimate is most sensitive.

• Conduct MC simulations for the critical parameters to evaluate uncertainty in Qy and SSWR.

• For each model, select the optimum Qy (close to 25,000 m3/d) having a reasonable SSWR value.

The method is general when the target Qy changes.

11,37510,76710,14010,88610,3849,883SSWR

39,50957,25227,57960,15250,44550,289Qy (m3/d)

495849584951Number of calibrated parameters

G3R5G3R2G2R5G2R2G1R5G1R2Model

Morris AnalysisSelect 9 out of 58 parameters for model G3R2, marked in red and green

0 20000 400000

10000

20000

30000

40000

50000(a)

The method selects the parameters:

• Adjacent to northern Yucca Flat

• Upgradient and downgradient of the area

Uncertainty in Qy Estimates

• For individual models, the Qy estimate is uncertain due to parametric uncertainty.

• Different models give significantly different Qy estimates, indicative of model uncertainty.

• Examining the multimodels provides an opportunity to improving the estimate of inter-basin groundwater flow.

Smoothed histogram of Qy estimate for the individual models

Optimum Qy Estimate Select the realization with• Qy close to 25,000 m3/d and• Smallest SSWR

Original Qy and SSWR from Model Calibration39,50957,25227,57960,15250,44550,289Qy (m3/d)

11,17011,45510,67811,56012,38012,491SSWR

G3R5G3R2G2R5G2R2G1R5G1R2Model

Selected Qy and Corresponding SSWR

11,37510,76710,14010,88610,3849,883SSWR

21,74722,98819,17322,67225,74324,444Qy (m3/d)

Qy (m3/d)

SS

WR

10000 20000 30000 40000 50000 60000 70000

10000

12000

14000

16000

18000

20000(b)

0

Model G3R2

Measures of Goodness-of-FitThree kinds of observations• Head• Discharge• Constant-head

boundary flow

Simulated hydraulic head

Obs

erve

dhy

drau

liche

ad

0 200 400 600 800 1000 1200 1400 16000

200

400

600

800

1000

1200

1400

1600(a)

Simulated boundary flow and discharge

Obs

erve

dbo

unda

ryflo

wan

ddi

scha

rge

-20 -10 0 10-20

-15

-10

-5

0

5

10(b)

3.88-2.152.3611,455760Total

1.57-1.290.953715Constant-head boundary flow

3.51-2.653.4955445Discharge

3.94-2.112.3610,864700Hydraulic head

[SSWR/NOBs]1/2

Average negative weighted residual

Average positive weighted residualSSWRNumber of

observationsType of

observations

Sources of Reduction• Inflow is reduced at the northern boundary of

the northern Yucca Flat area.• This is caused by reduction of flow through

several segments along the constant-head boundary.

-34,26422,98857,252Qy at cross section J=101 (m3/d)

-33,92725,63559,562Qy at cross section J=137

65834769Qx at cross section I=216

-33,86226,46960,331Total outflow (m3/d)

-33,49719,75053,247Qy at cross section J=63

-2893,9914,280Qx at cross section I=90

03,4923,492Recharge

-33,78627,23361,019Total inflow (m3/d)

DifferenceRealization 1768Calibrated model

The estimates of constant-head boundary flow are subject to large uncertainty.

Why Not Choose Model G2R5?

11,17011,45510,67811,56012,38012,491SSWR

G3R5G3R2G2R5G2R2G1R5G1R2Model Selected Qy and Corresponding SSWR

21,74722,98819,17322,67225,74324,444Qy (m3/d)

Model G2R5 has the smallest Qy estimate and best goodness-of-fit (SSWR).

• ds

42.12

82

4,474

23,289

938

1,381

72,061

645

-7,245

-14

2,299

4,221

-5,113

-22,419

-2,281

-2,165

G2R2

37.19205.78SSWR

343-2,400500C_SILU0100

4,5592,9411,682C_OWLS1203

23,7716,90615,000C_PANA1100

49116,41315,100C_EURS0900

1,639-4,275667C_CLAY0800

64,116-17,03912,476C_STNC0700

653-9,0642,334C_GRDN0603

-7,149-13,393-2,521C_PAHR0505

-341-999-2,346C_PAHR0502

2,0475,4401,827C_PAHR0501

3,63214,2255,927C_SHPR0404

-4,665-11,459-4,959C_SHPR0403

-20,134-42,755-15,305C_SHPR0402

-2,001-3,709-4,410C_SHPR0401

-2,081-7,319-3,633C_LASV0303

G3R2G2R5ObservationObservation

• For model G2R5, simulated boundary flows have opposite directionsfrom the observed.

• This also happens for model G3R5, but not for any other models.

Conclusions• Estimates of inter-basin groundwater flow are

inherently uncertain due to variation between estimation methods and parametric and model uncertainty in numerical estimation.

• Using multiple models provides an opportunity to better improving the estimates.

• Our approach combining Morris (screening) sensitivity analysis and Monte Carlo simulation is general, and the results can be used together with any target estimate of inter-basin flow.

• The best model cannot be selected simply based on the overall SSWR, but on examination of different kinds of observations.

Hydrostratigraphic Models 1 and 2

Legend

2. Yucca Flat-Climax Mine Base

1. DVRFS Hydrogeologic Model

• North-south cross-section west of the Climax stock outcrop.• The Cenozoic volcanic units tend to be thin in the DVRFS

model.• Structural features are more complicated in the base model.

Hydrostratigraphic Models 3, 4, and 5

Figures modified from Bechtel-Nevada (2006)

West-East cross sections about5 km south of Climax stock outcrop

West-East cross sections throughClimax stock outcrop

Model 5 is a combination of Models 3 and 4

Base Model 3. CP Thrust

Base Model 4. Hydrologic Barrier

0 20000 400000

10000

20000

30000

40000

50000(a)

0 2000 4000 6000 8000 100000

5000

10000

15000

20000(b)

Contours of Qy in northern Yucca Flat for the calibrated G3R2 model at (a) cross section J=63 and (b) cross section J=101, andfor realization 1768 at (c) cross section J=63 and (d) cross section J =101.

Contours of Qy across the entire model domain for the calibrated G3R2 model at (a) cross section J=63 and (b) cross section J=101, and for realization 1768 at (c) cross section J=63 and (d) cross section J =101. The northern Yucca Flat area is marked with the black square.

The relationship between the Qyestimate and summed discharges based on 2,000 realizations of model G3R2.

The relationships between three kinds of SSWRs and Qy.