Nevada Water Science Center


Aquifer Tests

Contact Information

Phil Gardner
Groundwater Specialist
Phone: (775) 887-7664
Email:pgardner@usgs.gov

 

Mailing Address
USGS
Nevada Water Science Center
2730 N. Deer Run Rd.
Carson City, NV 89701

 

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Wells ER-20-1, ER-20-4, ER-20-7, ER-20-8, ER-EC-1, ER-EC-11, ER-EC-12, and ER-EC-6

Primary Investigator: Keith Halford

Well Data

USGS Site ID
Local Name Altitude Uppermost
Opening
Lowermost
Opening
Primary Aquifer Transmissivity
(ft2/d)
371321116292301 ER-20-1 6180.9 VOLCANIC ROCKS 5300
371143116262503 ER-20-4 5736.1 VOLCANIC ROCKS 1200
371247116284502 ER-20-7 6208.9 VOLCANIC ROCKS 18000
371135116282601 ER-20-8 5848.3 VOLCANIC ROCKS 140000
371223116314701 ER-EC-1 6025.6 VOLCANIC ROCKS 7500
371151116294101 ER-EC-11 5656.3 VOLCANIC ROCKS 25000
371024116293101 ER-EC-12 5532 VOLCANIC ROCKS 940
371120116294801 ER-EC-6 5604.4 VOLCANIC ROCKS 30000

 

Aquifer Test

Aquifer Test Report (30.5MB) - 2012-09-21_NNSS-PM_AqTestReport.v4.zip

Aquifer Test Models (143 MB) - 2012-09-21_NNSS-PM_AQtest_PEST_MODFLOW.zip

Aquifer Test Supporting Memos (1.41 GB) - 2012-09-21_NNSS-PM_SupportingMEMOS.zip

 

ER-20-1, ER-20-4, ER-20-7, ER-20-8, ER-EC-1, ER-EC-11, ER-EC-12, and ER-EC-6 Groundwater Levels (NWISweb)

ER-20-1 || ER-20-4 || ER-20-7 || ER-20-8 || ER-EC-1 || ER-EC-11 || ER-EC-12 || ER-EC-6

 

This memorandum documents the simultaneous numerical analysis of eight aquifer tests to estimate hydraulic properties on Pahute Mesa, Nevada National Security Site. During 2010 and 2011, the U.S. Geological Survey (USGS) analyzed data from four multi-well aquifer tests (ER-20-8 #2, ER-EC-11 main, ER-20-7, and ER-20-8 main upper zone) on Pahute Mesa that were conducted between 2009 and 2011 by Navarro-Intera, LLC (N-I). Multi-well aquifer-test packages for these tests have been completed and approved for release by the USGS (Halford and others, 2010, 2011). Interpretation of drawdown estimates from four recent multi-well aquifer tests (ER-20-8 main lower zone, ER-20-4, ER-EC-12 main upper zone, and ER-EC-12 main lower zone) conducted on Pahute Mesa recently were completed (Garcia and others, 2012; Mirus and others, 2012a, 2012b). Hydraulic properties were estimated for two of the wells (ER-20-4 and ER-EC-12 main lower zone) by analyzing as single-well aquifer tests (Halford and others, 2012; Halford and Reiner, 2012).

Numerical models of the recent multi-well aquifer tests were simultaneously analyzed with the models of the four earlier multi-well aquifer tests. Aquifer tests that occurred in the same borehole but from different open intervals were analyzed with a single model. In total, six models were created to simulate drawdowns in the eight aquifer tests:

  1. ER-20-8 #2
  2. ER-EC-11 main
  3. ER-20-7
  4. ER-20-8 main upper zone and ER-20-8 main lower zone
  5. ER-20-4
  6. ER-EC-12 main upper zone and ER-EC-12 main lower zone

The models were used to estimate a single set of hydraulic properties for the hydrostratigraphic units in the vicinity of the eight aquifer tests. The aquifers tests were analyzed simultaneously because they affect overlapping volumes of aquifer. By analyzing the tests together, a consistent set of hydraulic properties is estimated. These estimates will be revised as more aquifer tests occur beneath Pahute Mesa. The primary scope of this analysis is to estimate total transmissivity around each pumping well. Estimates of transmissivity and storage properties for the volcanic rocks at Pahute Mesa are needed to constrain hydraulic properties in groundwater flow and contaminant transport models at the Nevada National Security Site.

The eight aquifer tests used pumping wells that consisted of a main casing with a single or a dual completion. In wells with a dual completion in the main casing, each completion was separated by a packer and pumped as a separate aquifer test. Many of the pumping wells also had additional piezometers completed in the annulus alongside the main completion zone or in shallower or deeper zones within the borehole. During an aquifer test, water levels in the multiple completions within the pumping well and in a network of observation wells were monitored with transducers (Figure 1; Appendix A). Observation wells are located a few hundred feet to a few miles away from each pumping well.

A typical “aquifer test”, as simulated in the numerical model, consisted of about 10 days of intermittent pumping to develop the well and to perform step-drawdown tests followed by about 10 days for a constant-rate test. Pumping periods were shorter in low-productivity wells where pumping could not be sustained (ER-EC-12 main lower zone) or in contaminated wells with limited capacity for storage of discharge water (ER-20-7). Pumping periods and total volumes pumped for each of the aquifer tests are summarized in table 1.

 

Table 1. Pumping periods and volumes pumped during each aquifer test.

table 1

fig1

Figure 1. Location of well sites and geologic structures associated with multi-well aquifer tests at Pahute Mesa, Nevada National Security Site and vicinity, 2009-2012.

 

Hydrogeology

The wells monitored during multi-well aquifer testing at Pahute Mesa are completed in Tertiary volcanic rocks. The volcanic rocks of Pahute Mesa are dominated by lavas and tuffs of rhyolitic composition (Laczniak and others, 1996). Geologic structures at Pahute Mesa include normal faults with surface exposure and buried structural zones and caldera margins (Figure 1).

Structural features offset the hydrostratigraphy encountered in wells at Pahute Mesa. The Northern Timber Mountain Moat Structural Zone (NTMMSZ) is a buried west-northwest trending fault zone (Figure 1) that displaces rocks by more than 1,000 ft (U.S. Department of Energy, 2010a). The area that is bounded on the north by the NTMMSZ and on the south by the Timber Mountain caldera complex structural margin is referred to as “the Bench” (U.S. Department of Energy, 2009). South of the Bench is the Timber Mountain moat structural domain, a structural region that is the northwestern moat area of the Timber Mountain caldera complex (U.S. Department of Energy, 2011a).

Observation wells north of the Bench and west of the Boxcar fault (Figure 1) penetrate about 2,000 ft of unsaturated rock. Major water-producing hydrostratigraphic units (HSUs) are the Tiva Canyon aquifer (TCA) and Topopah Spring aquifer (TSA), with some production from lava-flow aquifers in the Calico Hills zeolitic composite unit (CHZCM) (Appendix A). North of the Bench but east of the Boxcar fault, well ER-20-4 penetrates about 1,500 ft of unsaturated rock and produces water from a lava-flow aquifer within the CHZCM.

Observation wells on the Bench (Figure 1) penetrate about 1,200 to 1,800 ft of unsaturated rock. Wells on the Bench were constructed to monitor five water-producing HSUs: the upper Paintbrush lava-flow aquifer (UPLFA), Benham aquifer (BA), Scrugham Peak aquifer (SPA), TCA, and TSA. The CHZCM and Crater Flat composite unit (CFCM) also supply water to observation wells on the Bench (Appendix A).

Observation wells south of the Bench (Figure 1) penetrate about 750 to 1,000 ft of unsaturated rock. The two water-producing HSUs in wells in this area are lava-flow aquifers within the FCCM and welded-tuff aquifers of the Timber Mountain composite unit (TMCM).

The lithologies of major water-producing HSUs in the aquifer-test area are rhyolitic lava flows (UPLFA, BA and SPA) and partially to densely welded ash-flow tuffs (TCA and TSA) (U.S. Department of Energy, 2010b and 2011b). The FCCM, CHZCM, and CFCM are composite units of rhyolitic lava-flow aquifers and nonwelded tuff confining units with local to common zeolitization (Laczniak and others, 1996, p.11; U.S. Department of Energy, 1997; 2000). The CFCM also contains welded-tuff aquifers. The TMCM in the study area is a composite of welded-tuff aquifers and nonwelded tuff confining units (U.S. Department of Energy, 2002).

 

Aquifer-Test Analysis

Numerical models were developed for each of the aquifer tests and used to obtain estimates of hydraulic properties for the volcanic rocks underlying Pahute Mesa. Numerical methods were used to estimate hydraulic properties because the groundwater beneath the study area flows through a complexly layered sequence of volcanic-rock aquifers and confining units that have been faulted into distinct structural blocks. The observation wells were vertically separated and distant from the pumping wells. Therefore, water-level responses in the observation wells could not be analyzed with simple analytical methods, such as the Theis solution (Theis, 1935), because simplifying assumptions of the methods were violated grossly.

Hydraulic properties of aquifers and confining units were estimated by interpreting pumping responses from multiple aquifer tests using a single, three-dimensional hydrogeologic framework and multiple groundwater-flow models. Multiple groundwater-flow models allowed grid refinement near each pumping well and different pumping schedules to match each aquifer test. Multiple groundwater-flow models also facilitate incorporating additional aquifer tests because each test is interpreted with an independent groundwater-flow model. This allows for each model to be developed and tested individually and assures that simulated drawdowns and sensitivities are computed and extracted correctly.

Hydrogeologic Framework Model

Aquifer-test results were interpreted with a single conceptual model because of project limitations. However, many conceptual models exist for distributing hydraulic properties beneath Pahute Mesa, including those where hydraulic properties of mapped faults differ from hydraulic properties of the HSUs. Interpretation of hydraulically unique fault structures was beyond the primary scope of estimating total transmissivity around each of the pumped wells. Because fault structures were not differentiated in the hydrogeologic framework model and in the groundwater flow models, the hydraulic properties of fault structures could not be estimated.

Hydraulic properties were distributed spatially with a single, three-dimensional hydrogeologic framework that was constructed from wellbore data, refined cross sections using data from newly drilled wells (Sigmund Drellack, written commun., National Security Technologies, LLC., 2011), and HSU picks from the Pahute Mesa Corrective Action Unit (CAU) framework model (Bechtel Nevada, 2002) (Figure 2). The hydrogeologic framework was discretized vertically into 251 layers between 1,700 ft below sea level to 6,500 ft above sea level, where each layer was about 33 ft thick. The hydrogeologic framework for this study used 9 simplified HSUs (Table 2). HSUs were simplified to create a more efficient and simple model. Major aquifers and confining units were differentiated that are thought to be hydraulically important in the study area.

The TCVA, THLFA, THCM, TMA, and PVTA units (Table 2) are above or mostly above the water table. The joint Benham and Scrugham Peak aquifers (BA/SPA) simplified HSU incorporate the original BA and SPA units. A simplified Upper Paintbrush confining unit (sUPCU) combined the original UPCU and MPCU units. A simplified Calico Hills zeolitic composite unit (sCHZCM) aggregated the original CHZCM, CHCM, CHCU, and IA units. A simplified Crater Flat composite unit (sCFCM) was created and combined the original CFCM, CFCU, BFCU, BRA and PBRCM units.

 

figure 2

 

Figure 2. Simplified, three-dimensional, hydrogeologic framework of hydrostratigraphic units for distributing hydraulic properties. The Paintbrush units, which were subdivided into four units in the hydrogeologic framework, are shown here as one unit for illustrative purposes.

 

Table 2. Categorization of hydrostratigraphic units to simplified hydrostratigraphic units.

table 2

1Comprises the majority of the saturated thickness of the sFCCU simplified HSU in the vicinity of the aquifer tests

 


Displacements of HSUs along the Northern Timber Mountain Moat Structural Zone (NTMMSZ), Area 20 caldera structural margin, Thirsty Canyon lineament, M4 fault, ER-20-7 fault, ER-20-8 fault, West Boxcar fault, and West Greeley fault were simulated (Figure 1). Displacements along all other fault structures were considered minor and were not simulated explicitly.

Hydraulic conductivity was distributed throughout each of the simplified HSUs with pilot points, which are points in the model domain where hydraulic properties are estimated (RamaRao and others, 1995). Pilot points were assigned to simplified HSUs at 89 mapped locations (Figure 3), with a denser spacing of pilot points specified around the pumped wells (Figure 4). Less than 89 pilot points existed in any given HSU because pilot points were not defined where a HSU was absent. Hydraulic conductivity was distributed with a total of 498 pilot points. Hydraulic properties were interpolated from pilot points with kriging to node locations as defined for each groundwater-flow model (Doherty, 2008b). The spatial variability of log-hydraulic conductivity was defined with an isotropic, exponential variogram, where the specified range was 15,000 ft and no nugget was specified.

Hydraulic properties were assigned in each HSU beyond the pumping and observation wells from previous aquifer-test results (Figure 3, Table 3). Between one and eight HSUs were penetrated by wells from previous aquifer tests. Well ER-EC-2A and other wells in the TMCM penetrated this single HSU. Well ER-EC-1 penetrated the most HSUs; sFCCU, BA/SPA, sUPCU, TCA, LPCU, TSA, sCHZCM, and sCFCM between 0 and 3,000 ft below the water table. The vertical distribution of hydraulic conductivity was defined by flow-log data where multiple HSUs existed (Garcia and others, 2010). Assigned hydraulic conductivities from previous aquifer tests, that were not estimated independently, totaled 75 of the 498 pilot points and are shown on figure 3 as fixed pilot points.

Hydraulic-property estimates are affected by groundwater-flow model discretization; consequently, structural inconsistencies were avoided with a common vertical discretization in all groundwater-flow models. Geologic framework and groundwater-flow model layers were discretized finely between 2,300 and 3,700 ft above sea level where most pumped intervals are present (Figure 5). Groundwater-flow model layers gradually thickened below 2,300 ft above sea level to the base of the models where vertical discretization was relatively coarse. Hydraulic properties were not interpolated vertically within a HSU, but rather the laterally interpolated values from each simplified HSU were assigned directly to all layers with a corresponding simplified HSU in the groundwater-flow model (Figure 5).

 

Table 3. Transmissivity estimates from previous aquifer tests

 


Well Name

U.S. Geological Survey site identification number

Reference

Transmissivity, in feet squared per day

ER-20-6-3

371533116251801

Belcher and others, 2001

2,000

ER-EC-1

371223116314701

Garcia and others, 2010

7,000

ER-EC-2A

370852116340502

Oberlander, 2001

200

ER-EC-4

370935116375302

Garcia and others, 2010

50,000

ER-EC-5

370504116335201

Oberlander, 2000

14,000

ER-EC-7

365910116284401

Oberlander, 2007

10,000

PM-3

371421116333703

Belcher and others, 2001

50

TW-8

370956116172101

Graves, 2002

11,000

U-20a2WW

371434116251601

Graves, 2002

2,400

U-20bg

371414116242901

Garcia and others, 2011

4,000

U-20WW

371505116254501

Garcia and others, 2011

4,000

UE-18r

370806116264001

Belcher and others, 2001

3,000

UE-19b-1

371852116175701

Belcher and others, 2001

7,500

UE-19c

371608116191001

Belcher and others, 2001

1,600

UE-19d

372054116191901

Belcher and others, 2001

3,000

UE-19e

371750116195901

Belcher and others, 2001

1,100

UE-19fs

371329116220302

Graves, 2002

1,000

UE-19gS

371830116215300

Graves, 2002

2,500

UE-19h

372034116222501

Belcher and others, 2001

19,000

UE-19i

371459116204812

Graves, 2002

160

UE-20d

371452116284901

Belcher and others, 2001

6,000

UE-20e-1

371901116272501

Belcher and others, 2001

1,100

UE-20f

371617116291701

Graves, 2002

30

UE-20h

371618116260201

Belcher and others, 2001

1,400

UE-20j

371801116320301

Belcher and others, 2001

8,000

 

figure 3

Figure 3. All pilot points that were simulated in the numerical models for the ER-20-8 #2, ER-EC-11, ER-20-7, ER-20-8 main upper zone, ER-20-8 main lower zone, ER-20-4, ER-EC-12 main upper zone, and ER-EC-12 main lower zone aquifer tests.

figure 4

Figure 4. Pilot points near pumped and monitored observation wells that were simulated in the numerical models for the ER-20-8 #2, ER-EC-11, ER-20-7, ER-20-8 main upper zone, ER-20-8 main lower zone, ER-20-4, ER-EC-12 main upper zone, and ER-EC-12 main lower zone aquifer tests.

figure 5

Figure 5. Vertical discretization and assignment of simplified hydrostratigraphic units to layers in numerical flow models.

Groundwater-Flow Models

Drawdowns from each multiple-well aquifer test (Halford and others, 2010, 2011; Garcia and others, 2012; Mirus and others, 2012a, 2012b) were interpreted with a three-dimensional MODFLOW model (Harbaugh and others, 2000). Each model was centered on the pumping well and rows in the model grid paralleled the NTMMSZ fault (figure 3). Each model grid extended laterally about 200,000 ft away from the pumping well. All models were about 5,900 ft thick and extended vertically from 1,700 ft below sea level to 4,200 ft above sea level, which is the water table (Figure 5). Rows and columns in the grid were assigned widths of 5 ft at the pumped well. Columns and rows expanded successively by a factor of 1.25 away from the pumped well until a mid-point between well and faults or the model edge was reached. The number of rows and columns in each model differed, but ranged between 90 and 119 (Table 4). All external boundaries were specified no-flow boundaries. Changes in the wetted thickness of the aquifer system were not simulated because the maximum drawdown near the water table was small relative to the total thickness. Simulation periods were subdivided into stress periods that simulated simplified pumping schedules for each pumping well with between 6 and 12 stress periods (Table 4).

 

Table 4. Number of pumping wells, layers, rows, columns and stress periods for each MODFLOW model.

table 4

All groundwater-flow models were discretized vertically into 29 layers that were defined with the water table and the discretization of the geologic framework (Figure 5). Layer 1 was 1-foot thick to better approximate drainage from the water table. Groundwater-flow model layers 5 to 20 were each 82-ft thick to capture thin HSUs such as the sUPCU and LPCU in the vicinity of borehole ER-EC-11. Some simplified HSUs such as the TCA and sCHCZM occur in multiple groundwater-flow model layers (Figure 5). Other simplified HSUs such as the BA/SPA are locally absent because the HSUs were locally absent in the hydrogeologic framework model. A common vertical discretization was used to ensure consistency of simulated geometries of HSUs in all groundwater-flow models.

Specific yield and specific storage also were distributed with the same distribution of pilot points that were used to assign hydraulic conductivity (Figure 3). The distribution of specific yield was defined with all 89 pilot points regardless of the HSU present at the water table. A single specific-storage value was estimated for each HSU, where one pilot point was adjustable. Specific-storage values at all other pilot points in a HSU equaled the adjustable pilot-point value. Specific yield of fractured rocks was expected to range between 0.001 and 0.05. Specific-storage initially was assigned as 1.5 x 10-6 1/ft and was allowed to range between 1 x 10-7 and 3 x 10-6 1/ft. These values are typical for most aquifer materials (U.S. Geological Survey, 2010). Vertical-to-horizontal anisotropy was assumed equal to 1 and was not estimated.

 

Parameter Estimation

Hydraulic-conductivity, specific-yield, and specific-storage distributions were estimated by minimizing a weighted composite, sum-of-squares objective function. These distributions were defined with 1,085 pilot points where 543 pilot points were adjusted with PEST (Doherty, 2008a). The majority of adjustable pilot points, 445, defined the hydraulic conductivity distributions.  Differences between measured and simulated observations defined the goodness-of-fit or improvement of calibration. These differences, or residuals, were weighted and summed in the objective function,

equation 1

Although the sum-of-squares error serves as the objective function, root-mean-square (RMS) error was reported because RMS error was compared easily to measurements. Root-mean-square error is,

equation 2

Measurement and regularization observations controlled model calibration. The models used 24,563 drawdowns as measurement observations. Hydraulic conductivity and specific yield estimates were guided by regularization observations to preferred conditions in areas that were insensitive to measurement observations. This approach is Tikhonov regularization (Doherty, 2008a).

The number of measurement observations reported from drawdown analyses (Halford and others, 2010, 2011; Garcia and others, 2012; Mirus and others, 2012a, 2012b) was reduced by averaging drawdowns from each well every 6 hours. Averaging reduced the number of measurement observations from more than 257,000 to 24,563 and suppressed high-frequency noise (Table 5). Reliable drawdowns that were not affected by pumping losses, heating effects, leaking bridge plugs, or abridged records totaled 18,055 and were observed in 61 of 83 pumping-observation well pairs. These reliable observations were assigned weights of 1, except at distant well clusters where calibration would be weighted towards sites with similar drawdowns in multiple wells. For example, weights of 0.5 were assigned to large measured drawdowns from the ER-EC-6 cluster to reduce sensitivity to these observations during the ER-EC-11 main aquifer test.

 

Table 5. Numbers of observation wells, original drawdown estimates, and averaged drawdown estimates during each aquifer test.

table 5

 

Compromised observations in wells that were affected by head losses, heating effects, or packer leakage in the pumping well cluster were assigned small weights so that hydraulic-conductivity estimates were minimally affected. Measured drawdowns in observation wells directly adjacent to and monitoring the pumped intervals were uncertain because of entry losses to the well, wellbore storage, and heating effects. These effects were not simulated and can be significant where drawdowns exceed 100 ft and transmissivity of the pumped interval is less than 1,000 ft2/d. Parameter sensitivity also is proportional to the magnitude of simulated drawdowns, which can skew calibration toward fitting less certain measurements that are simulated poorly. Assigned weights between 0.0001 and 0.01 were assigned to these observations because of measurement uncertainty, simulation inadequacy, and sensitivity adjustment. Measured drawdowns in observation wells in the annulus of the pumping well that were not adjacent to the pumped intervals were uncertain because of the effects of heating and leakage across bridge plugs. Assigned weights between 0.01 and 0.1 reflected the uncertainty associated with these observations. Effects of weighting are reported with unweighted and weighted sum-of-squares errors for each hydrograph (Appendix B).

Tikhonov regularization limited hydraulic-conductivity estimates at pilot points to reasonable values (Doherty and Johnston, 2003). Sharp differences between nearby values in similar simplified HSUs were penalized to ensure relatively continuous hydraulic-conductivity and specific-yield distributions. Tikhonov regularization was unnecessary for specific-storage because a single value was estimated for each HSU.

Regularization observations were equations that defined preferred relations between hydraulic-conductivity estimates and specific-yield estimates. Regularization observations affected calibration most where the models were insensitive to measurement observations. Imposing preferred states, such as homogeneity, with regularization observations was preferable to rigid zones of assigned homogeneity. This was because hydraulic-conductivity and specific-yield estimates could differ where dictated by measured drawdowns.

Homogeneity within simplified HSUs was the primary preferred relation between pilot points that defined hydraulic conductivity. Variance between specific-yield estimates was minimized regardless of HSU. About 18,000 regularization observations constrained hydraulic-conductivity and specific-yield estimates with these preferred relations.

Unrealistic hydraulic-conductivity and specific-yield distributions were avoided by limiting the fit between measured and simulated observations (Fienen and others, 2009). Irreducible measurement and numerical model errors were specified with the expected measurement error, PHIMEAS, which is a weighted, sum-of-squares error. Water-level modeling results suggest that the expected measurement RMS error should range between 0.02 and 0.025 ft (Garcia and others, in press). The range of PHIMEAS that equals the range of expected RMS errors ranges between 6.3 and 9.8 ft2. A PHIMEAS of 7 ft2 was specified and measurement error was reduced to 7 ft2.

Goodness of Fit and Investigated Volumes

Misfit between simulated and measured drawdowns was gauged with RMS error, which was 0.02 ft. RMS error could have been reduced further, but was limited by PHIMEAS, which was the estimated uncertainty of the drawdown estimates. Simulated and measured drawdowns had RMS errors less than 0.04 ft in 66 of the 83 pumping-observation well pairs (Appendix B). Drawdowns were analyzed during seven of the eight aquifer tests and detected during five aquifer tests in the ER-EC-6 wells. Differences between simulated and measured drawdowns in well ER-EC-6 shallow during seven of the eight aquifer tests are shown in Figure 6. Drawdowns were not estimated in well ER-EC-6 shallow during the ER-20-4 main aquifer test. This was because drawdown was not detected in ER-20-8 deep, which is 9,800 ft away from ER-20-4 main while ER-EC-6 shallow is 16,600 ft away from ER-20-4 main.

Detected drawdowns in observation wells outside of the annuli of pumping wells defined most of the hydraulic-property estimates and matched simulated drawdowns with a RMS error of 0.022 ft. These were observation wells where the maximum measured drawdown ranged between 0.05 and 0.5 ft during an aquifer test. For these wells, the fit between simulated and measured drawdowns was best in well ER-EC-11 lower intermediate during the ER-20-7 aquifer test, a RMS of 0.007 ft relative to a maximum measured drawdown of 0.11 ft (Appendix B, page 16). The fit between simulated and measured drawdowns was worst in well ER-EC-6 deep during the ER-EC-11 main aquifer test, a RMS error of 0.041 ft (Appendix B, page 75).

The 33 mi3 volume of aquifer that was investigated with these aquifer tests reasonably can be defined by the volume where simulated drawdowns exceeded 0.05 ft during the simulated periods (Figure 7). The investigated-volume threshold of 0.05 ft was supported by the drawdown-detection threshold of 0.05 ft. The investigated volume would increase to 50 mi3 if the threshold was defined by the RMS error of 0.02 ft.

 

Figure 6

Figure 6. Simulated and measured drawdowns in well ER-EC-6 shallow during the ER 20-8 #2, ER-EC-11 main, ER-20-7, ER-20-8 main upper and lower zones (ER-20-8I+D), and ER-EC-12 main upper and lower zones (ER-EC-12S+I) aquifer tests.

figure 7

Figure 7. Maximum simulated drawdowns that occurred at any time during one of the eight aquifer tests, where contouring was limited to a range between 0.05 and 0.1 ft.

Hydraulic-Property Estimates

Total transmissivity estimates at each well site are integrated samples in this report, as has been reported previously (Halford and others, 2011).Transmissivity was averaged horizontally in approximately 4,000-ft diameter circles around each well site in this report and summed vertically within selected groupings of HSUs (Figure 8). Transmissivity was averaged because of the additional variability in hydraulic conductivity that has been introduced by many pilot points.

 

Figure 8

Figure 8. Hydraulic conductivity distributions in 4,000 ft diameter circles around selected well sites. Translucent patches in the lower parts of circles are volumes where hydraulic conductivity is less than 1 ft/d.

Transmissivities were estimated for groupings of HSUs around locations that include all the pumping wells (Table 6). Five locations exist where pumping occurred rather than eight because three aquifer tests occurred in the ER-20-8 well cluster (ER-20-8 #2, ER-20-8 main upper zone, and ER-20-8 main lower zone) and two aquifer tests occurred in the ER-EC-12 well cluster (ER-EC-12 main upper zone, and ER-EC-12 main lower zone). The BA/SPA, which comprises lava flows, is the most transmissive aquifer in the model area, with a transmissivity estimate of 130,000 ft2/d around the ER-20-8 well cluster. High transmissivity of the BA/SPA around the ER-20-8 well cluster may be caused by the presence of the SPA, which is limited primarily to the area east of ER-20-8 (Prothro and Drellack, 1997). High transmissivity also could result from the contact between BA and SPA HSUs or inferred fault structures.

 

Table 6. Estimated transmissivities of selected groupings of hydrostratigraphic units around mapped locations of selected wells.


[All values are in feet squared per day; na is Not Applicable; FCCU is the Fluorspar Canyon confining unit; BA/SPA is the Benham and Scrugham Peak aquifers; Paintbrush Tuffs includes the Upper Paintbrush confining unit (UPCU), Middle Paintbrush confining unit (MPCU), Tiva Canyon aquifer (TCA), lower Paintbrush confining unit (LPCU), and Topopah Spring aquifer (TSA); sCHZCM includes the Calico Hills zeolitic composite unit (CHZCM), Belted Range aquifer (BRA), and Inlet aquifer (IA)]

Table 6

Transmissivity around well site ER-EC-11 totaled 25,000 ft2/d and the vertical distribution of transmissivity among the HSUs likely is correct (Table 6). More than 90 percent of the transmissivity is attributed to the BA/SPA, which lies above the pumped interval. The dominance of transmissivity in the BA/SPA is consistent with higher concentrations of tritium that were measured in this HSU while drilling ER-EC-11 (U.S. Department of Energy, 2012). Flow logs in ER-EC-1 and ER-EC-6 also indicate that most of the transmissivity occurs in the BA/SPA (Garcia and others, 2010).

Specific-yield and specific-storage estimates averaged 0.02 and 1.4 x 10-6 1/ft, respectively. About 90 percent of the specific-yield estimates ranged between 1 and 3 percent and no estimates exceeded the expected range between 0.001 and 0.05. Specific-storage estimates were limited to a single value per HSU and only one HSU specific-storage value was constrained by the lower limit of 0.1 x 10-6 1/ft.


 

References Cited

Bechtel Nevada, 2002, A hydrostratigraphic model and alternatives for the groundwater flow and contaminant transport model of Corrective Action Units 101 and 102--Central and western Pahute Mesa, Nye County, Nevada: U.S. Department of Energy Report DOE/NV/11718--706, 383 p.

Doherty, J., 2008a, PEST: Model-Independent Parameter Estimation. Brisbane, Australia: Watermark Numerical Computing.

Doherty, J., 2008b, PEST Groundwater Data Utilities. Brisbane, Australia: Watermark Numerical Computing.

Doherty, J., and J.M. Johnston, 2003, Methodologies for calibration and predictive analysis of a watershed model: Journal of American Water Resources Association, v. 39, no. 2, p. 251-265.

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