Final Environmental Impact Statement (EIS), Dual Axis Radiographic Hydrodynamic Test (DARHT) Facility

APPENDIX E

WATER RESOURCES

This appendix provides background information on 1) estimates of recharge at the mesa top (i.e., firing sites), 2) the solubilities and distribution coefficients associated with the metals of interest when associated with LANL site sediments, 3) the approach taken to model surface water pathway, and 4) the approach taken to model the vadose zone and ground water pathways.

APPENDIX E1: DEEP DRAINAGE BENEATH THE

DARHT AND PHERMEX SITES

E1.1 ABSTRACT

Meteoric water that drains well below the lowest level of plant roots is called deep drainage and can transport solubilized contaminants through vadose zone deposits to ground water. This pathway for contaminant migration to the accessible environment must be evaluated to understand the potential for surface soil contamination to migrate through the mesa and underlying vadose zone to ground water. The objective of this study was to estimate the deep drainage rates at two locations, the DARHT and PHERMEX sites. Estimates of deep drainage were performed using the UNSAT-H computer code, daily weather data from 1980 to 1994, and, in lieu of site-specific data, surrogate information for the hydrologic properties of vegetation and soils. Drainage rates were determined for a variety of soil and vegetation scenarios; the actual rates depend explicitly on the site-specific surface conditions. For the scenarios studied, the drainage rates ranged from 4.7 to 520 mm/yr. For the center of the DARHT site, the rates for an unvegetated surface were 265 and 360 mm/yr depending on the soil type. Modifying the surface with a gravel cover increased the drainage rate to 520 mm/yr. For the center of the PHERMEX site, the rate was 124 mm/yr for the unvegetated surface. Allowing shrubs and grasses to grow on the sites reduced, but did not eliminate, deep drainage. The potential exists for deep drainage at both sites. Whether deep drainage actually exists can only be determined with site-specific measurements.

E1.2 INTRODUCTION

One component of the DARHT EIS is an analysis of the potential for deep drainage beneath the DARHT and PHERMEX sites to carry contaminants to the main aquifer. At other DOE sites, deep drainage has transported solubilized contaminants to underlying ground water systems. While such transport is not apparent beneath Threemile Mesa on which DARHT and PHERMEX are located, it does represent a pathway of interest and must be evaluated. The objective of this portion of the EIS was to estimate the deep drainage rate beneath the DARHT and PHERMEX sites.

E1.3 PRIOR ESTIMATES

Information on the rates of deep drainage beneath the DARHT and PHERMEX sites was unavailable. However, occasional monitoring at other locations at LANL indicates that deep drainage rates are highly variable, ranging from near zero to more than the annual precipitation rate, depending on the surface conditions at each of the specific locations.

Abeele et al. (1981) and Nyhan (1989a) reported water content profiles measured with neutron probes in several deep access wells. Some wells had low water contents in the tuff, indicating little, if any, deep drainage. Other wells had high water contents, particularly in the upper zones of tuff, possibly indicative of recent deep drainage. In one well, the high water contents implied that water was added in excess of precipitation rates. Nyhan (1989) speculated that an unlined drainage ditch routed surface water to the vicinity of the well, where the water subsequently infiltrated. Abeele et al. (1981) also alluded to the influence of surface topography as a factor in affecting infiltration rates and thus deep drainage rates.

Abeele et al. (1981) reported that the flux in the overburden above a waste disposal pit was always directed downward below a depth of about 13 ft (4 m) during a two-year period. In 1978, it was 3.5 in/yr (90 mm/yr); in 1979, it was 6 in/yr (150 mm/yr). The difference was attributed to extremely high precipitation at the end of 1978 and the beginning of 1979. At another location at LANL, Abeele et al. (1981) estimated a downward rate of 0.01 in/yr (0.3 mm/yr). It has been summarized as follows:

"Where the soil cover has not been disturbed, little if any water from precipitation infiltrates the underlying tuff (Purtymun and Kennedy 1971). Where the soil cover was disturbed, as in the waste disposal areas, the moisture content of the tuff indicates a much higher degree of infiltration than the one that might have been implied by the moisture content fluctuations found in the undisturbed tuff (Abeele et al. 1981)."

Rogers and Gallaher (Rogers 1995) reviewed the hydraulic properties of the Bandelier Tuff as well as other units. Their review included core data from several areas at the LANL facility; the data came from both mesa tops and canyon bottoms. They concluded that "[t]he canyon bottom and mesa top hydraulic head profiles suggest that downward flow of water occurs beneath the surface of the Pajarito Plateau" (Rogers 1995). They noted two exceptions where there was the suggestion of upward flow, one of which they speculated was caused by "increased external air circulation through the mesa sides."

Core data were unavailable for the DARHT and PHERMEX sites. In lieu of site-specific data, data reported by Rogers and Gallaher (Rogers 1995) for other mesa tops were used to estimate deep drainage. Assuming a hydraulic gradient close to unity, one can equate the in situ hydraulic conductivity to the drainage rate. Rogers and Gallaher lumped core data together to calculate mean in situ conductivity values. In their table 5, Rogers and Gallaher report both harmonic and arithmetic mean values of hydraulic conductivity. For Area TA-54, Rogers and Gallaher reported values ranging from 1.7 x 10^-6 to 0.06 in/yr (4.3 x 10^-5 to 1.5 mm/yr) for the harmonic and arithmetic means, respectively. For Area TA-16, the rates ranged from 3 to 55 in/yr (79 to 1,390 mm/yr). For Area TA-53, the rates ranged from 7 to 3,660 in/yr (180 to 93,000 mm/yr). While not from the DARHT or PHERMEX sites, these ranges indicate clearly that deep drainage can vary greatly from site to site.

The impact of early and recent LANL operations may not always be reflected in core data - and this makes interpretation difficult. For example, Allison et al. (1994) related the case of land clearing in Australia in which the recharge rate increased from 0.003 to 1.8 in/yr (0.08 to 45 mm/yr). The pressure front generated by the increase in recharge took nine years to reach the 25-ft (7.5-m) depth. Foxx and Tierney (1984) related the historical occurrence of grazing and logging as well as the impact of recent disturbances from LANL operations. Generally, such changes alter plant communities and reduce their ability to transpire water, thus increasing the potential for deep drainage. Depending on the pre-disturbance drainage rate, an increase in drainage may take decades or centuries to propagate downward through the tuff. Thus, core data collected today must be interpreted and used cautiously, especially if one does not know or account for the history of surface conditions at specific sites.

E1.4 METHOD

Deep drainage was estimated at the DARHT and PHERMEX sites using simulation modeling. Simulations were conducted using the UNSAT-H Version 2.02 computer code (Fayer and Jones 1990). The UNSAT-H computer code, developed for the Hanford site, was selected because it was developed for and has been applied to estimate deep drainage at DOE sites in the arid and semi-arid western United States. The code models one-dimensional, deep drainage, accounting for the hydrological characteristics of soil media, climate, and vegetation. The exhibit E1-1 contains a listing of an example input file for UNSAT-H. The model requires information on the domain, soil properties, initial conditions, boundary conditions, and plants.

E1.4.1 Domain

The model domain extended to 16 ft (5 m). This depth is well below the zone of evapotranspiration for most species. Some roots have been observed at greater depths within fractures (Tierney and Foxx 1987), but these were not considered in this one-dimensional modeling exercise. Also, because of the one-dimensional nature of this analysis, processes such as interflow (subsurface lateral drainage) were not addressed. The node spacing ranged from 0.1 in (0.2 cm) at the soil surface to 20 in (50 cm) at the 16-ft (5-m) depth. At the transition between different materials, the node spacing was reduced to 0.8 in (2.0 cm).

E1.4.2 Soil Properties

The soil at the center of the DARHT site is mapped as Pogna sandy loam (Nyhan et al. 1978). Some of the soil samples collected at the DARHT site for a geotechnical investigation report (Korecki 1988) indicated that there is more clay than expected for a Pogna sandy loam. Nyhan et al. (1978) indicated that the Pogna sandy loam has small inclusions of other soil types. Based on the descriptions reported by Korecki (1988), a likely candidate for some of the soil at the DARHT site is the "Typic Eutroboralf, fine," which includes layers of sandy loam, sandy clay, and clay. In the blueprints for the DARHT Facility (LANL 1993a), several drawings indicate surface modifications that include stripping the soil off and building directly on the tuff as well as covering the surface near the firing point with gravel. At some distance from the center of the DARHT site is another soil type, the Seaby loam,

Exhibit E1-1.-Example Input File for UNSAT-H Computer Code

DP1: Typic Eutroboralf, fine, with grass-shrub cover 40%, day 74 and 288

1 1 1 1 0 0 0 iplant,lower,ngrav,iswdif,etc.

0 365 365 1 1 0 0.0 nprint,dayend,ndays,nyears,etc.

1 2 0 1 0 nsurpe,nfhour,itopbc,et_opt,icloud

4 1 1 0 3 1 kopt,kest,ivapor,sh_opt,inmax,inhmax

0.0 1.00e+05 0.0 0.0 hirri,hdry,htop,dhmax

5.0e-05 1.00e+00 1.0e-08 24.0 dmaxba,delmax,delmin,stophr

0.66 288.46 0.24 1.0 tort,tsoil,vapdif,qhtop

0.0 0.0 0.0 0.0 tgrad,tsmean,tsamp,qhleak

0.5 1.6 1.0e-06 0.0e-00 wtf,rfact,rainif,dhfact

5 68 matn,npt

1 0.0 1 0.2 1 0.4 1 0.6

1 0.8 1 1.0 1 1.4 1 1.8

1 2.4 1 3.0 1 4.0 1 5.5

1 7.0 1 9.0 1 11.0 1 13.0

1 15.0 1 17.0 5 19.0 5 21.0

5 23.0 5 25.0 5 27.0 5 29.0

5 31.0 5 33.0 5 35.0 5 38.0

5 41.0 5 44.0 5 46.0 5 48.0

5 50.0 4 52.0 4 54.0 4 56.0

4 59.0 4 63.0 4 68.0 4 74.0

4 80.0 4 84.0 4 86.0 4 89.0

4 91.0 4 93.0 3 95.0 3 97.0

3 99.0 3 102.0 3 106.0 3 110.0

3 115.0 3 123.0 3 135.0 3 150.0

3 175.0 3 200.0 3 225.0 3 250.0

3 275.0 3 300.0 3 325.0 3 350.0

3 375.0 3 400.0 3 450.0 3 500.0

Sandy loam retention

0.4100 0.0650 0.0750 1.8900

Sandy loam conductivity

2 4.43 0.0750 1.8900 0.5

Gravel retention

0.419 0.0050 4.9300 2.19

Gravel conductivity

2 1260.0 4.9300 2.19 0.5

Tuff retention

0.4690 0.0450 0.0029 1.884

Tuff conductivity

2 0.1188 0.0029 1.884 0.5

Sandy clay retention

0.3800 0.1000 0.0270 1.230

Sandy clay conductivity

2 0.1200 0.0270 1.230 0.5

Clay retention

0.3800 0.0680 0.0080 1.090

Clay conductivity

2 0.2000 0.0080 1.090 0.5

*** Initial matric suction values go here

Exhibit E1-1.-Example Input File for UNSAT-H Computer Code - Continued

Plant information for shrubs and grasses

1 1 1 1 74 288 leaf,nfroot,nuptak,nfpet,etc

12 0.6 npoint,bare

0 0.70 91 0.70 105 1.00 121 1.33 135 1.70 ngrow,flai

213 1.70 227 1.60 244 1.50 258 1.28 274 1.08 ngrow,flai

305 0.70 366 0.70 ngrow,flai

0.000 0.0000 1.0000 aa,b1,b2

0 0 0 0 0 0 0 0 0 0 ntroot

0 0 0 0 0 0 0 0 0 0

366 366 366 366 366 366 366 366 366 366

366 366 366 366 366 366 366 366

4.0e+04 1.0e+03 30.0 hw,hd,hn

*** Meteorological data go here

which should be considered. Thus, five soil scenarios were envisioned for this analysis: 1) tuff, 2) gravel above tuff, 3) Pogna sandy loam, 4) Typic Eutroboralf, fine, and 5) Seaby loam. TableTable E1-1.-Soil Profile Descriptions for the Computer Simulations

Soil Profile	Depth Interval (cm)	Porous Material
Tuff	0 to 500	tuff
Gravel Above Tuff	0 to 30 30 to 500	gravel tuff
Pogna Sandy Loam	0 to 30 30 to 500	sandy loam tuff
Typic Eutroboralf, fine	0 to 18 18 to 51 51 to 94 94 to 500	sandy loam clay sandy clay tuff
Seaby Loam	0 to 13 13 to 25 25 to 30 30 to 66 66 to 500	loam clay loam, 40 percent gravel clay loam, 55 percent gravel gravel tuff
Nyjack Loam	0 to 8 8 to 61 61 to 99 99 to 500	loam clay loam sandy loam, 25 percent gravel tuff
Hackroy Sandy Loam	0 to 8 8 to 25 25 to 30 30 to 500	sandy loam clay clay, 25 percent gravel tuff

E1-1 shows the soil profile description for each scenario.

The soil type at the center of the PHERMEX site is mapped as Nyjack loam (Nyhan et al. 1978). Nearby soil types include the Seaby loam (included in the DARHT scenario list) and the Hackroy sandy loam. The Nyjack loam and Hackroy sandy loam were added to the list in table E1-1 to bring the total number of soil profile scenarios to seven.

Hydraulic properties were assigned to each porous material in table E1-1. Specifically, water retention and hydraulic conductivity were described using the van Genuchten (1980) retention function and the Mualem (1976) conductivity model; tableTable E1-2.-Parameters Used to Describe Hydraulic Properties in the Simulations


Porous Material	Gravel (vol %)	__s	__r	_ (1/cm)	n	K_s (cm/h)
Tuff	0	0.469	0.045	0.0029	1.88	0.119
Gravel	100	0.419	0.005	4.93	2.19	1260.0
Sandy loam	0	0.410	0.065	0.075	1.89	4.42
Sandy loam	25	0.308	0.049	0.075	1.89	2.83
Sandy clay	0	0.380	0.100	0.027	1.23	0.12
Loam	0	0.430	0.078	0.036	1.56	1.04
Clay loam	0	0.410	0.095	0.019	1.31	0.26
Clay loam	40	0.246	0.057	0.019	1.31	0.122
Clay loam	55	0.185	0.043	0.019	1.31	0.0846
Clay	0	0.380	0.068	0.008	1.09	0.200
Clay	25	0.285	0.051	0.008	1.09	0.130
__s Saturated moisture content. __r Residual moisture content. _ Fitted van Genuchten parameter, 1/cm. n Fitted van Genuchten parameter. K_s Saturated hydraulic conductivity, cm/h. Note: The van Genuchten parameter m was set equal to 1-1/n. The standard value of 0.5 was used for the pore interaction term.

E1-2 shows the parameters. Hydraulic properties specific to the site soils were unavailable. Instead, the particle size description (e.g., sandy loam, clay) was used to assign parameters based on the correlations reported by Carsel and Parrish (1988). For those materials with gravel, the hydraulic parameters reported by Carsel and Parrish (1988) were modified using the method proposed by Bouwer and Rice (1983). The actual properties of the tuff unit beneath the surface of the DARHT site were unknown. For this study, the properties of the Tshirege Unit 3 were used (Rogers 1995). This unit appears to be the highest in elevation for which hydraulic properties are available. All hydraulic properties were assumed to be isothermal and non-hysteretic. Soil freezing was not addressed.

E1.4.3 Initial Conditions

There was no information on the 1980 matric suction distribution at the DARHT or PHERMEX sites. Therefore, the first year (1980) of every simulation was repeated until the water balance variables (i.e.,evaporation, transpiration, drainage, and runoff) changed by less than 0.004 in (0.1 mm) from one year to the next. The reason for the iteration was to lessen the impact of the unknown initial conditions.

E1.4.4 Boundary Conditions

The surface boundary was described with weather data, which were summarized by Bowen (1990). The daily precipitation data were obtained for the TA-59 site for 1980 to 1990 and the TA-6 site for 1991 to 1994. During each day, the precipitation was added at the rate of 0.4 in/h (1 cm/h) until the day's total was applied to the surface. Snow was treated as an equivalent rainfall. No adjustment was made for delays in snowmelt.

Daily potential evapotranspiration (PET) values were calculated using the Penman Equation in Doorenbos and Pruitt (1977) and daily weather parameters from the TA-59 and TA-6 sites. These parameters included wind speed at 75 ft (23 m), maximum and minimum air temperature and dew-point temperature at 4 ft (1.2 m), solar radiation, and cloud cover. The dew-point temperature data set was sparse. When data existed, a comparison to measured minimum air temperature showed the dew-point temperature tobe less than or equal to the minimum air temperature. Because a relatively complete record of daily minimum air temperature existed, the daily dew-point temperature was approximated as the minimum air temperature. Cloud cover data were not available. Instead, cloud cover was approximated using the measured solar radiation and calculations of the potential solar insolation for Los Alamos (Campbell 1985).

During the evaporation process, the matric suction of the surface node was not allowed to exceed a predetermined value. For most of the simulations, the value was 1,450 lb/in² (10 MPa). For the gravel surface scenario, however, this limit increased the difficulty of the solution. Instead, a value of 14.5 lb/in² (0.1 MPa) was used.

The bottom boundary was described with a unit gradient condition. Observations at other sites indicate that unit gradient conditions exist in the tuff in certain zones at certain sites, but it is not universal. For these simulations, plant roots were assumed to be no more than 3.3 ft (1 m) deep. As long as the simulations indicated that deep drainage was greater than 0.04 in/yr (1 mm/yr), the unit gradient condition at 16 ft (5 m) was assumed to be valid.

E1.4.5 Plants

Plant information consisted of the method to partition potential evapotranspiration, active season, bare fraction, root length density, and maximum root depth during the year, as well as the effectiveness of plant water withdrawal as a function of soil matric suction. According to the Environmental Restoration Program (ERP), the plant community on the PHERMEX mesa is the piñon-ponderosa-juniper association (LANL 1993b). In the vicinity of the facilities, however, this community has been eliminated and replaced by structures (e.g., roads, parking lots, buildings), bare ground, and shrubs and grasses. Data for those plants pertinent to the DARHT and PHERMEX sites were not available. Instead, literature parameters or reasonable estimates of parameters were chosen. Plant responses to precipitation and temperature variations, fire, disease, nutrient cycling, grazing, and land use changes were not addressed in the simulations.

The leaf area method was used to partition potential evapotranspiration into potential evaporation and potential transpiration. Leaf area as a function of season was described using values reported by Nyhan (1989b) for a 40 percent cover of shrubs and grasses.

The active season of the plants determined when to calculate transpiration and when roots started or stopped growing. The active season was specified with starting and ending days during the year. The shrubs and grasses were started on March 15 (day 74) and stopped on October 15 (day 288). These dates were estimates only but are reasonable given the monthly temperatures experienced at Los Alamos (Bowen 1990).

The bare fraction of soil was used to scale potential transpiration based on the amount of soil surface covered by the vegetation. If the bare fraction was zero, the cover percentage would be 100 percent and there would be no reduction in potential transpiration. For the grasses and shrubs cover, the bare fraction was assigned as 0.6. This means that the vegetation covered 40 percent of the ground surface (Nyhan 1989b); therefore, potential transpiration was appropriately reduced by 60 percent. Any reduction to potential transpiration caused by a less than 100 percent cover is added to potential evaporation. After all the manipulations, the sum of potential evaporation and potential transpiration must equal potential evapotranspiration.

Root length density data were unavailable. The roots of the grasses and shrubs were considered to be at their maximum depth throughout the growing season. The maximum depth was defined as the surface of the uppermost tuff unit. This depth ranged from 12 in (30 cm) in the Pogna sandy loam to 39 in (99 cm) in the Nyjack loam. Roots have been observed in cracks and fissures in the tuff (Tierney and Foxx 1987). For this one-dimensional analysis, however, cracks and fissures were not considered in the conceptual model.

Data on plant water uptake as a function of matric suction were also unavailable. A matric suction of 0.4 lb/in² (0.003 MPa) was assumed to be the limit below which plants ceased transpiration because of anaerobic conditions. From 0.4 to 14.5 lb/in² (0.003 to 0.1 MPa), plants were assumed to withdraw water at the potential rate. Above 14.5 lb/in² (0.1 MPa), but below the permanent wilting point, plants were assumed to withdraw progressively less water as the matric suction increased. Typically, the matric suction above which plants cease to transpire is 220 lb/in² (1.5 MPa) (i.e., the permanent wilting point). Sagebrush was reported to operate in soils with matric suctions as high as 1,000 lb/in² (7.0 MPa) (Fernandez and Caldwell 1975; Branson et al. 1976). For this study, as an approximation, an intermediate value of 580 lb/in² (4.0 MPa) was chosen.

E1.5 RESULTS

Table Table E1-3.-Summary of Simulation Results for 1981 to 1994


Soil^a Profile	Max. Root Depth (cm)	Average Annual Rates (mm/yr)				Annual Drainage Rates (mm/yr)		Average Annual Mass Error
Soil^a Profile	Max. Root Depth (cm)	Evaporation	Transpiration	Runoff	Drainage	Max	Min	mm	% of drain
Tuff	na	505.5	0.0	0.4	33.8	44.3	16.5	0.1	0.3
Gravel	na	21.5	0.0	0.0	519.5	653.6	394.1	3.0	0.6
Pogna	na	183.5	0.0	0.0	359.9	449.2	261.4	0.5	0.1
Pogna	30	209.3	166.5	0.0	164.9	211.6	88.7	1.1	0.7
Typic Eutroboralf	na	272.6	0.0	3.7	265.3	328.1	192.4	1.5	0.6
Typic Eutroboralf	94	279.1	196.7	1.9	57.1	80.8	18.0	2.3	4.1
Seaby	na	464.8	0.0	30.0	32.4	54.1	5.1	0.5	1.5
Seaby	30	337.9	164.7	13.2	9.5	23.8	1.5	0.5	4.9
Nyjack	na	395.9	0.0	22.4	124.0	168.2	67.5	0.1	0.1
Nyjack	99	310.8	200.8	11.8	4.7	11.5	0.8	0.4	7.8
Hackroy	na	200.0	0.0	25.0	318.4	397.8	248.2	1.3	0.4
Hackroy	30	189.0	190.6	15.4	142.6	197.6	91.5	7.6	5.3
^a Tuff, Gravel, Pogna sandy loam, Typic Eutroboralf (fine), Seaby loam, Nyjack loam, Hackroy sandy loam.

E1-3 shows that the deep drainage rate is highly dependent on the soil profile and the presence of vegetation. Table E1-3 also shows that, for a given combination of soil profile and vegetation, the year-to-year rates [as estimated at the 16-ft (5.0-m depth)] can vary by more than a factor of two. Figures E1-1 to E1-6 illustrate the yearly variation more clearly.

The deep drainage rate at the center of the DARHT site was estimated to be 10 or 14 in/yr (265 or 360 mm/yr) depending on the soil type and assuming vegetation was not allowed to grow. Table E1-3 shows that the estimated rates were reduced by more than half when plants were included. If the immediate center of the site was covered with a layer of gravel (LANL 1993b), the drainage rate would nearly double to 20 in/yr (520 mm/yr), or 95 percent of the precipitation. If the tuff were left exposed at any point, the results in table E1-3 suggest that the drainage rate would be only 1.3 in/yr (34 mm/yr), which is much lower than the rates estimated for the soils. The reason is that the tuff holds infiltrating water relatively near the surface, and its soil hydraulic properties are conducive to upward unsaturated flow. Thus, higher evaporation rates occur from exposed tuff surfaces.

At some distance from the center of the DARHT site is the Seaby loam soil. The simulation results indicate the drainage rate in this soil type is much less than for either the Pogna sandy loam or Typic Eutroboralf soils.

The deep drainage rate at the center of the PHERMEX site was estimated to be 5 in/yr (124 mm/yr) (assuming vegetation was not allowed to grow). At some distance from the center of the PHERMEX site are the Seaby loam, with rates slightly higher than the Nyjack loam, and the Hackroy sandy loam, with rates three times greater than the Nyjack loam without plants, and thirty times greater than the Nyjack loam with plants.

These results are in accord with previous simulation results (Nyhan 1989a) for seepage through covers over waste disposal areas. Nyhan estimated seepage rates of 2.4 and 4.8 in/yr (60 and 120 mm/yr) for a cover with range grass and a bare cover, respectively, assuming a saturated conductivity of 0.08 in/h (0.2 cm/h) for the cover. For the years 1977 to 1987, Nyhan showed that the seepage rate varied between 0 and 6.3 in/yr (0 and 160 mm/yr) for the bare cover and for a cover with a poor range grass.

When the precipitation rate exceeds the ability of the soil to accept infiltration, water begins to accumulate on the soil surface. Once the storage capacity of the soil surface is exceeded, overland flow, or runoff, begins. The UNSAT-H model assumes zero surface storage; thus, water that does not infiltrate is considered to be runoff. Table E1-3 shows the average annual runoff for each of the simulations. Only those soil profiles that had one or more clay layers had runoff. The Nyjack loam, Seaby loam, and Hackroy sandy loams had the highest rates; the Seaby loam was highest with 1.2 in/yr (30 mm/yr). Some of these high rates were comparable to the drainage rate. For the Nyjack loam, the runoff rate was actually twice the drainage rate [which, in this case, was quite low at 0.02 in/yr (4.7 mm/yr)]. The impact of frozen soil, snow, and rapid snowmelt on runoff and deep drainage was not evaluated.

At LANL, Wilcox (1994) reported that runoff accounted for 10 to 18 percent of the precipitation received during a two-year study of the intercanopy zone of a piñon-juniper woodland. The soil was from the Hackroy series and the slope was about 4.4 to 5.3 percent. While not directly applicable to the DARHT and PHERMEX sites, the results from Wilcox (1994) demonstrate that runoff can be a significant component of the water balance at LANL and thus impacts the estimation of deep drainage rates at these two sites. The Wilcox study did consider snow and snowmelt processes. If actual runoff is higher than predicted (table E1-3) at the two sites, the predicted drainage rates are higher than they should be.

E1.6 SENSITIVITIES

Several issues that arose during this study included hourly versus daily precipitation, the use of the 14-yr record versus the longer term precipitation record, the calculation of the daily average dew-point temperature, the calculation of internodal conductances, the effect of initial conditions, and mass balance. Most of these issues were evaluated by conducting additional simulations and comparing to the originals summarized in table E1-3.

E1.6.1 Hourly Precipitation

As configured, the UNSAT-H computer code applies daily precipitation at the rate of 0.4 in/h (10 mm/h) starting at 0000 h until the day's amount has been applied to the soil surface. The concern is that the daily rates will underestimate runoff because they fail to represent the high intensities that sometimes occur. Four years (1991 to 1994) of 15-min precipitation data were used to provide hourly precipitation input for the UNSAT-H code. The Pogna sandy loam and Seaby loam profiles without plants were simulated. The Pogna sandy loam had no runoff using either daily or hourly precipitation data. In fact, the hourly precipitation resulted in a slight reduction in evaporation, mainly because hourly precipitation that occurred during the day reduced evaporation. Overall, estimated drainage increased by about 0.04 in/yr (1 mm/yr). For the Seaby loam, the hourly precipitation data resulted in a 13 percent reduction in runoff. The seemingly contradictory result is understandable. For the daily precipitation, all the rates were 0.4 in/h (10 mm/h). For the hourly precipitation, most of the rates were far less than 0.4 in/h (10 mm/h) while some rates were more. The net result of using hourly precipitation was a 0.05 in/yr (1.3 mm/yr) reduction in annual runoff.

E1.6.2 Precipitation Record

The drainage rate varies from year to year as a function of the precipitation distribution and amounts and the weather. The question that remains unanswered is whether the 14-yr record used for this study adequately represents the longer term weather that has been observed or can be reasonably expected to occur. Bowen (1990) reported precipitation extremes for LANL for the period from 1911 to 1988. The record shows that the largest annual precipitation amount was 30.3 in (770.6 mm), which occurred in 1941. That amount is about 17 percent greater than the highest value used in this study. Bowen (1990) also reported that the highest seasonal snowfall occurred in 1986-1987. That period is within the period used for this study. Both the highest annual precipitation and seasonal snowfall records are very near the estimated 100-yr values reported by Bowen (1990). If this analysis of deep drainage were to extend much beyond 100 years, consideration would have to be given to analyzing for greater precipitation amounts and intensities than used for this study.

E1.6.3 Dew-point Temperature

A clean and continuous record of daily average dew-point temperature was not available for the period 1980 to 1994. In lieu of actual data, daily dew-point temperatures were approximated as equivalent to the minimum daily air temperatures. Daily dew-point temperature from 1982 showed that the minimum air temperature may be roughly 9_F (5_C) higher than the dew-point temperature. The Pogna sandy loam scenario with and without plants was simulated using dew-point temperatures that were 9_F (5_C) lower than the minimum daily air temperature. In both cases, estimated evapotranspiration increased and drainage decreased (2 percent reduction without plants; 16 percent with plants). Similar results are expected for the other soil profiles.

E1.6.4 Internodal Conductance

For all of the simulations without plants, the geometric mean was used to approximate internodal conductances. The Pogna sandy loam simulation without plants was repeated with arithmetic averaging. The result was a much higher evaporation rate and a 24 percent reduction in the drainage rate. All of the simulations with plants were conducted using the arithmetic mean. The Pogna sandy loam simulation with plants was repeated with geometric averaging. The result was significantly reduced evaporation and a 25 percent increase in the drainage rate. One way to view the results overall, in the context of the averaging scheme, is that the simulations with plants and arithmetic averaging represent the lower estimate of deep drainage, and the simulations without plants but with geometric averaging represent the upper estimate.

E1.6.5 Initial Conditions

To overcome the lack of initial conditions, the simulation of 1980 was repeated until there was less than a 0.004-in (0.1-mm) annual change in the water balance components and in the drainage flux through the tuff. This requirement was relaxed for some of the simulations with plants because the rates under the 1980 weather conditions were either very low or the flux was actually upward. Using these initial conditions, the simulation results for some soil profiles showed drainage rates that increased slowly during part or all of the 14-yr period, indicating some sensitivity to the initial conditions. To ascertain the degree of sensitivity to initial conditions, the Pogna sandy loam and Seaby loam profiles without plants were simulated with a uniform initial matric suction profile of 39 in (100 cm), which is very wet. Figure E1-7 shows that, after two years, the annual drainage rates from the initially wet (open triangles) Pogna sandy loam were nearly identical to what was predicted using the drier initial conditions (filled triangles). The 14-yr average rate was also nearly identical to the average rate predicted using drier initial conditions. In contrast, figure E1-7 shows that the annual drainage rates from the initially wet Seaby loam took the entire 14 years to come within 3 percent of the original simulation reported in table E1-3. Also, the 14-yr average rate was double the average rate predicted using drier initial conditions. When drainage rates are high, the initial conditions appear to become unimportant after only 1 to 2 years. When the rates are low, the initial conditions appear to influence the simulation results for at least as long as 14 years. The technique of conducting two simulations, one initially dry and one initially wet, can be used to illustrate the impact and provide bounding drainage predictions. Based on testing, the limited results suggest that the initial conditions used in the study caused an underestimate of deep drainage of no more than 12 to 16 in/yr (30 to 40 mm/yr).

E1.6.6 Mass Balance

The allowable mass balance error of a given simulation is controlled by the user. As more control is exerted, the simulation time requirement increases. Generally, the mass balance error was kept to less than 1 percent of the drainage rate. For the very low rates, this requirement was relaxed to 10 percent. In two cases, the Seaby loam and Nyjack loam, even this requirement was initially not met. These soil profiles with vegetation were simulated again with tighter convergence criteria. The estimated water balance components changed by less than 0.04 in/yr (1 mm/yr), but the mass balance errors were reduced to less than 10 percent relative to the drainage estimates. Further reductions in the mass balance errors could be obtained but the results and conclusions would not likely be affected.

E1.7 SUMMARY

The results of this study showed clearly that deep drainage at the DARHT and PHERMEX sites is possible. Estimated rates ranged from 0.2 to 14 in/yr (4.7 to 360 mm/yr) and could be as high as 20 in/yr (520 mm/yr) if the surface was graveled and unvegetated. These estimates are reasonably similar to other estimates (e.g, Abeele et al. 1981; Rogers 1995).

APPENDIX E2: SOLUBILITY

AND SORPTION OF METALS

Mobilization of contaminants from the firing sites to and within Potrillo and Water canyons, and the associated subsurface environment is significantly affected by the contaminants' solubility in water and sorption onto soil and sediments. Thus, estimated solubility limits and distribution coefficients were determined for depleted uranium, beryllium, lead, nickel, copper, aluminum, iron, and silver at the LANL sites. The metals studied represent two classes: 1) those metals assigned annual expenditure rates (e.g. depleted uranium, beryllium, lead, and copper) (see chapter 3, table 3-4) and 2) those metals identified as included in the "other metals" category of the materials expended (see appendix B, table B-4) that werealso listed in the primary and secondary drinking water standards (i.e., 40 CFR 141 and 143) (e.g. aluminum, iron, nickel, and silver). Note, aluminum and stainless steel (hence iron) make up the majority of the "other metals" category of materials expended during tests.

Because the numerical values for solubilities, distribution coefficients (K_d), and constants in the equations defining K_d are interrelated, these numerical values are given only in the metric units used by geochemists.

E2.1 METHODOLOGIES FOR ESTIMATION

OF SOLUBILITY AND DISTRIBUTION COEFFICIENTS

Since no solubility experiments specific to the DARHT and PHERMEX sites were conducted previously, these values, except for depleted uranium, were obtained by running the geochemical model, MINTEQ (Felmy et al. 1984) with water quality data measured at Beta Hole in the Water Canyon and in Well PM-4 of the Pajarito Field (LANL 1988; LANL 1989; LANL 1990; LANL 1993c; Purtymun et al. 1994). The MINTEQ computer code was selected because it is a state-of-the-art geochemical code capable of calculating complex geochemical equilibria for reactions involving gases, aqueous solutions, adsorbed species, and minerals within a wide range of geochemical conditions and constraints. The code has associated with it a thermochemical database containing aqueous speciation and solubility data. The code was developed in the mid-1980s for the EPA as part of a system to model the migration and fate of pollutant metals; the code was subsequently modified for the Nuclear Regulatory Commission and DOE. For depleted uranium, field data measured at the E-F site (Hanson and Miera 1977), Aberdeen Proving Ground in Maryland (Erickson et al. 1993), and Yuma Proving Ground in Arizona (Erickson et al. 1993) were used to estimate solubility. Water quality data for the surface and subsurface water used for the MINTEQ modeling are shown in table Table E2-1.-Water Quality at the Beta Hole in Water Canyon

and Well PM-4 in the Pajarito Field

Location

Calcium

(mg/L)

Magnesium

(mg/L)

Potassium

(mg/L)

Sodium

(mg/L)

Carbonate plus Bicarbonate (mg/L)

Chloride (mg/L)

Sulfate

(mg/L)

Beta Hole

3.3

7.5

7.8

PM-4

2.5

7.85

E2-1. Distribution coefficients for depleted uranium, beryllium, lead, nickel, copper, aluminum, iron, and silver were estimated by using laboratory experimental results from other sites (e.g., Yucca Mountain in Nevada and the Hanford Site in Washington).

E2.2 DEPLETED URANIUM

Depleted uranium is the isotopic form present in the studies cited here. The physical chemistry of various isotopic forms of uranium is essentially identical, so the general term "uranium" is used in this section.

E2.2.1 Solubility of Uranium

Many studies have obtained data on uranium distributions at LANL and physical/chemical characteristics (Hanson 1974; Hanson and Miera 1976; Hanson and Miera 1978; Elder et al. 1977; and Becker 1993). Common oxidation states of uranium are designated as uranium(III), uranium(IV), uranium(V), uranium(VI), but in the LANL geologic environment uranium(IV) and uranium(VI) are the most important (Onishi et al. 1981). Uranium(VI) species control the total uranium concentration in oxidizing environments. The uranyl ion (UO₂⁺²) is a dominant species under oxidizing conditions. This cation can form many soluble and stable complexes with common ground water anions such as carbonate and sulfate (Onishi et al. 1981). In reducing conditions, uranium (IV) dominates and generally precipitates as uranium dioxide. Uranium content in solution, and thus also a distribution coefficient K_d, are a function of oxidation-reduction potential (Eh), pH, solution carbonate content, sediment characteristics (particle size, carbonate, phosphorous, and hydrous oxide contents), and organic matter content (organic carbon and humic substances) (Onishi et al. 1981). Data reviewed by Onishi et al. (1981) indicate that the uranium K_d for sediments from the Great Miami River (Ohio) ranged between 1,000 and 1,600 mL/g, while K_d values for sediments in 40 Japanese rivers varied between 1,000 and 6,000 mL/g.

Erickson et al. (1993) performed a series of experiments and geochemical modeling to determine corrosion rate, solubility, and adsorption potential for uranium at Aberdeen Proving Ground in Maryland and the Yuma Proving Ground in Arizona. Uranium pieces corrode with a corrosion rate of 0.02 to 0.04 in/yr (0.05 to 0.10 cm/y) to form uranium (VI) hydrated oxides, mostly the yellowish mineral schoepite (UO₃·H₂O). The corrosion rate is fast enough that uranium is available for transport through dissolution of schoepite and subsequent surface and subsurface migration. The LANL E-F site exhibits a yellow corrosion product of uranium on the soil surface, a sign of schoepite. Soils (two types) at Aberdeen Proving Ground are predominantly silt with moderate cation exchange capacity (CEC), low calcium carbonate content, and low paste pH values (pH of 4 to 6). Soils (one set) at Yuma Proving Ground are predominantly gravel and sand with higher CEC, high carbonate minerals, and slightly basic (pH of 8 to 8.5) saturation paste. Erickson et al. (1993) reported that the solubility of uranium at Aberdeen Proving Ground and Yuma Proving Ground is 10 to 280 mg/L, and 20 to 130 mg/L, respectively. They attributed the higher corrosion rate and uranium mobility measured at Yuma Proving Ground as primarily controlled by the higher dissolved carbonate, derived from the dissolution of carbonate minerals in this soil. Soil characteristics (especially carbonate content) at the LANL site fall between one of the Aberdeen Proving Ground soils and the Yuma Proving Ground soil types (LANL 1995).

Furthermore, uranium concentrations in standing water at the detonation center of the E-F site were 86 and 235 mg/L in 1975 and 1976, respectively, with nearly all of the uranium being in solution as opposed to suspended as fine solids (Hanson and Miera 1977). The uranium concentration in standing water at 66 ft (20 m) to the southwest away from the detonation center was only 63 µg/L in 1975, i.e., three orders-of-magnitude less than the concentration measured in standing water at the detonation center. A uranium concentration in runoff water measured in 1975 at 330 ft (100 m) to the southwest (still on mesa top) away from the detonation center was 52 µg/L. These concentration differences between the detonation center and the short distances away imply that not enough uranium was transported from the firing point to maintain the uranium concentration in solution at the solubility limit of uranium even 65 ft (20 m) away.

Based on these studies, we selected uranium solubility limit to be 300 mg/L for the current study. We also assumed that corrosion of uranium is fast enough for uranium to be available for subsequent surface/subsurface migration.

E2.2.2 Sorption of Uranium

Erickson et al. (1993) also conducted adsorption experiments and geochemical modeling with the chemical code, MINTEQ (Felmy et al. 1984). Experimental values for uranium distribution coefficients on the two soil types at Aberdeen Proving Ground were reported to be 4,360 and 328 mL/g. The Yuma Proving Ground site has the lowest K_d value (54 mL/g) due to the high carbonate solution concentrations despite the Yuma Proving Ground environment having the highest pH and CEC, two attributes that normally portend high adsorption. Since soil characteristics (especially carbonate concentrations) at the LANL site (Longmire 1995) fall between one of the Aberdeen Proving Ground soil types and the Yuma Proving Ground soil type, an expected K_d value with soil at the LANL site is estimated to be between 54 and 328 mL/g. We selected distribution coefficient values for the LANL soil to be 50 mL/g, and 100 mL/g as conservative and more realistic estimates. Since suspended sediment in LANL canyon streams have finer particle size, and since it is generally believed that finer sediments exhibit greater K_d values (Onishi et al. 1981; Becker 1993), we selected K_d values of 100 and 200 mL/g to be conservative and more realistic estimates for the in-stream suspended sediment.

E2.3 LEAD

E2.3.1 Solubility of Lead

The release rate of lead from the metal compounds into water depends largely on the oxidation rate of metallic lead, the dissolution of secondary minerals (e.g., lead carbonates), and the amount of water available to react with lead (Rhoads et al. 1992). However, we are not aware of any solubility and adsorption data for lead in contact with LANL waters or tuff. Thus, we performed geochemical modeling with MINTEQ to obtain lead solubility estimates for the LANL sites. The water quality data shown in table E2-1 was used to represent the LANL surface water and ground water conditions. The mineral cerrusite (PbCO₃) was imposed as the solubility limiting solid in this case.

MINTEQ predicted lead solubility in canyon streams and ground water to be 48.2 and 45.7 µg/L, respectively. Hence, we selected the lead solubility to be 50 µg/L for both surface and subsurface waters at the LANL sites.

Rhoads et al. (1992) conducted experiments and chemical modeling to determine the lead solubility in Hanford ground water. Assuming lead was in equilibrium with cerrusite, they used the geochemical code MINTEQ (Felmy et al. 1984) to predict the lead solubility to be 287 µg/L, which is close to solubility limits of 236 to 482 µg/L which they obtained in laboratory experiments. This result confirms the general validity of the MINTEQ simulation with cerrusite limiting lead solubility.

E2.3.2 Sorption of Lead

Adsorption of dissolved lead depends on water and soil chemistry, and properties of the lead species in solution (Rhoads et al. 1992). However, a main factor affecting lead adsorption is the amount of iron oxides in the soil.

According to Rhoads et al. (1992), batch experiments with Hanford ground water and relatively fine sediment (sand, silt, and clay mixture) yielded distribution coefficients varying from 1,190 mL/g at dissolved lead concentration of 200 µg/L to 56,000 mL/g at dissolved lead concentration of 0.005 µg/L, showing the following functional relationship:

K_d = 9550 C^-0.335

where C is a dissolved lead concentration in µg/L. This relationship yields K_d values of 2,580 mL/g at the dissolved lead concentration of 50 µg/L, 1,410 mL/g at the dissolved lead concentration of 300 µg/L, and 1,150 mL/g at the dissolved lead concentration of 550 µg/L.

Based on this Hanford study, conservative and realistic distribution coefficient values of 1,000 and 10,000 mL/g, respectively, for lead transport in the subsurface of the LANL site were selected. Because of the finer suspended sediment in canyon streams, their conservative and realistic distribution coefficient values were selected to be twice the values of ground water, e.g., 2,000 and 20,000 mL/g, respectively.

E2.4 BERYLLIUM

E2.4.1 Solubility of Beryllium

Beryllium solubility was calculated using the geochemical code MINTEQ (Felmy et al. 1984) by imposing beryllium hydroxide (Be(OH)₂) as the solubility limiting solid. Thermodynamic data used for this study on beryllium hydride were not a part of the original MINTEQ code but are incorporated in MINTEQA2 (Version 3.0) and are reported in Serne et al. (1993). Beryllium solubility was calculated for water from Water Canyon at the Beta Hole, and ground water from water supply Well PM-4 in the Pajarito Field (see table E2-1).

Beryllium solubility for Water Canyon at the Beta Hole and Well PM-4 predicted by the MINTEQ geochemical code are 3.95 and 3.62 µg/L, respectively. The MINTEQ simulation shows the strong dependency of beryllium solubility to pH. By using MINTEQA2 (i.e., with the same thermodynamic data base as those used under the current study), Serne et al. (1993) calculated beryllium solubility for Hanford ground water (pH of 8.1) to be 2.3 µg/L, which is comparable to the 3.62 to 3.95 µg/L range we estimated for the LANL waters.

Based on these model results, the beryllium solubility selected was 4 µg/L for both the canyon streams and subsurface flow.

E2.4.2 Sorption of Beryllium

Very few data are available for beryllium adsorption on soil (Serne et al. 1993), and we are not aware of any beryllium adsorption data for LANL soils and sediments. Beryllium adsorption data for 11 soils reviewed by Rai et al. (1984) show that beryllium adsorption is greater than adsorption of other divalent metals such as zinc, cadmium, nickel, and the monovalent metal mercury.

Adsorption of divalent beryllium is expected to be somewhat similar to that of divalent strontium. Thus, we used a strontium distribution coefficient obtained from experiments on tuff deposits for beryllium adsorption values. Strontium adsorption is significantly influenced by calcium and magnesium ions. There are many strontium adsorption studies performed with Yucca Mountain tuff. These include strontium distribution coefficients of:

· 50 to 84 mL/g obtained in batch tests and 30 to 52 mL/g obtained by column tests (Erdal et al. 1980)

· 50 to 300 mL/g with batch tests and 30 to 106 mL/g with column tests (Vine et al. 1981a)

· 51 to 283 mL/g with batch tests and 19 to 395 mL/g with column tests (Vine et al. 1981b)

Based on data from five samples of devitrified tuff, the range in strontium K_d values for the LANL soil was reported to be 53 to 190 mL/g with an average value of 116 mL/g (Wolfsburg 1980).

Based on these values, we selected conservative and realistic strontium distribution coefficient values to be 50 and 100 mL/g, respectively, for subsurface water. Because beryllium adsorption by soil is expected to be similar to that of strontium, these values were also used for the beryllium distribution coefficient for subsurface flow modeling.

Because the suspended sediments in canyon streams are expected to be finer than soils in the subsurface (Becker 1993), and the finer the sediment the greater the K_d values (Onishi et al. 1981), we selected conservative and realistic beryllium K_d values for canyon stream modeling to be 100 and 200 mL/g, respectively.

E2.5 NICKEL

E2.5.1 Solubility of Nickel

The solubility of nickel was estimated by using the MINTEQ code with its existing data base, and the LANL water quality data shown in table E2-1. Geochemical simulation indicates that the most stable solid phase of nickel in both surface and ground water is nickel hydroxide (Ni(OH)₂) as was found for a Hanford ground water case (Serne et al. 1993). The calculated nickel solubilities for canyon streams and ground water were 1.16 and 0.904 mg/L, respectively, assuming equilibrium with nickel hydroxide. Thus, we selected the nickel solubility to be 1.0 mg/L for both surface and subsurface waters at the LANL sites.

E2.5.2 Sorption of Nickel

No nickel adsorption experiments have been conducted with LANL soils and water. Thus, we used Hanford Site nickel adsorption data to obtain an appropriate nickel distribution coefficient for this study. By using Hanford ground water with Trench-8 soil, Serne et al. (1993) obtained K_d values of 440 mL/g and 2,350 mL/g after 5 and 44 days. With Trench-94 soil, they obtained K_d values of 48 and 337 mL/g at a dissolved nickel concentration of 2 and 1,000 µg/L, respectively. Serne et al. (1993) then derived the following empirical K_d expression:

K_d = 240 C^-0.155

where C is the dissolved nickel concentration in µg/L, and the K_d is the distribution coefficient in mL/g. The above equation yields K_d values of 118, 167, and 240 mL/g at the dissolved nickel concentrations of 100, 10, and 1 µg/L, respectively. Note that a dissolved nickel concentration at the LANL sites is expected to be less than 100 µg/L.

In addition, Brookins (1984) and Serne (1994) reported the conservative nickel distribution coefficients to be 50 mL/g for devitrified tuff and 20 mL/g for sandy soil, respectively.

From these data, we selected conservative and realistic nickel distribution coefficients to be 20 and 200 mL/g, respectively, for the LANL ground water. For the LANL canyon streams suspended sediments, we selected conservative and realistic values of 40 and 400 mL/g, respectively.

E2.6 COPPER

E2.6.1 Solubility of Copper

The mineral malachite (Cu₂CO₃(OH)₂) was specified as the copper solubility controlling solid for MINTEQ calculations of copper solubility in the canyon stream and ground water described in table E2-1. MINTEQ predicted the copper solubility to be 10.5 µg/L for both the LANL site surface and ground water. Thus, the copper solubility for this study was selected to be 10 µg/L for both canyon stream and subsurface modeling.

E2.6.2 Sorption of Copper

There are no copper adsorption data available for the LANL waters and soils or sediments. Since copper and nickel are both divalent and are expected to have similar sorption behavior, we elected to use the same K_d values for copper as for nickel. Serne (1994) reported the conservative copper K_d value for Hanford sandy soil to be 20 mg/L, the same as our conservative K_d value for nickel.

Thus we assigned the conservative and realistic K_d values for the LANL ground water to be 20 and 200 mL/g, respectively. The conservative and realistic K_dvalues for the canyon stream water were assigned 40 and 400 mL/g, respectively.

E2.7 ALUMINUM

E2.7.1 Solubility of Aluminum

Aluminum solubility was also calculated using the geochemical code MINTEQ (Felmy et al. 1984) by assigning the solubility limiting solid to be the mineral gibbsite (Al(OH)₃). With the water quality data shown in table E2-1 for Water Canyon and Well PM-4, MINTEQ predicted the aluminum solubility at equilibrium with gibbsite to be 1.22 and 1.36 µg/L for the canyon streams and ground water in the study area. Thus, we selected aluminum solubility to be 1 µg/L for both surface and subsurface flow modeling.

E2.7.2 Sorption of Aluminum

Since aluminum is a major constituent of soil, and the bulk of aluminum in the soil is not undergoing adsorption/desorption reactions with water, no meaningful adsorption experimental data for aluminum exist. Nonetheless, we selected the conservative aluminum K_d value to be 300 mL/g for the LANL ground water, as indicated by Serne (1994) for the Hanford sandy soil's conservative value. We selected a more realistic K_d value for aluminum to be 5,000 mL/g for the ground water. Because suspended sediment is finer than the bulk surface soil, we selected K_d values for the canyon streams to be twice the corresponding K_d values of the subsurface. Thus, the conservative and more realistic K_d values for canyon streams were assigned to be 600 and 10,000 mL/g, respectively.

E2.8 IRON

E2.8.1 Solubility of Iron

The solubility of iron was estimated using the MINTEQ code with its existing data base and water quality data shown in table E2-1. Because there were no redox data available for Water Canyon stream water and Well PM-4 ground water, we assumed that the water is oxidized. With this assumption, the geochemical simulation indicates that the most probable controlling solid phase of iron in both surface and ground water is amorphous iron hydroxide (Fe(OH)₃). The predicted iron solubility for both the canyon stream and ground water was 0.0022 µg/L. This value is very similar to the 0.002 µg/L value Morel (1983) reported for the ferric iron solubility at equilibrium with iron hydroxide at a pH of 7.8. Thus, we selected the iron solubility to be 0.002 µg/L for both surface and subsurface waters in the study area. Note that if the ground water of Well PM-4 is in a reduced condition, the iron solubility would be much higher than 0.002 µg/L due to the higher solubility of ferrous iron.

E2.8.2 Sorption of Iron

Similar to the aluminum case discussed above, iron is also a major constituent of soil and the bulk of the iron in the soil is not undergoing adsorption/desorption reactions with water. Thus, there is no meaningful adsorption experimental data for iron. However, Serne (1994) found a conservative K_d value for iron in sandy soil to be 15 mL/g, and we selected this value for subsurface flow modeling at the LANL sites. We assigned a realistic iron K_d value of 1,000 mL/g for the subsurface model. Conservative and realistic K_d values for iron in canyon streams were assigned to be 30 and 2,000 mL/g, respectively.

E2.9 SILVER

E2.9.1 Solubility of Silver

Silver chloride (AgCl) was specified as the silver solubility controlling solid for MINTEQ calculations of silver solubility in the canyon streams and ground water whose chemical quality is shown in table E2-1. MINTEQ predicted silver solubility to be 76.4 and 286 µg/L for the LANL sites' surface and ground water, respectively. Thus, the silver solubility for this study was selected to be 80 and 300 µg/L for canyon stream and subsurface models, respectively.

E2.9.2 Sorption of Silver

Serne (1994) stated that 1 mL/g may be taken as a conservative K_d value for silver in a sandy soil. Consequently, we selected the conservative K_d for the LANL subsurface water to be 1 mL/g. For canyon streams water, we assigned a conservative silver K_d value of 2 mL/g. Since silver is monovalent, we assumed a realistic K_d value for silver to be half of the divalent nickel K_d value. Thus, we selected realistic K_d values for silver in the subsurface environment and canyon streams at the LANL study area to be 100 and 200 mL/g, respectively.

E2.10 SUMMARY OF SOLUBILITY AND SORPTION OF METALS

IN LANL SURFACE AND GROUND WATERS

Mobilization of contaminants released to surrounding surface and subsurface water environments from the firing sites is significantly affected by their solubility and affinity to sorb onto soils and sediments. Thus, the solubility and distribution coefficients of depleted uranium, beryllium, lead, nickel, copper, aluminum, iron, and silver were estimated here for LANL site surface and ground waters.

Except for depleted uranium, the solubility of the metals of interest were obtained by running the geochemical model, MINTEQ (Felmy et al. 1984). Water quality data from samples taken at the Beta Hole on Water Canyon and at Well PM-4 of the Pajarito Field (LANL 1988; LANL 1989; LANL 1990; LANL 1993c; Purtymun et al. 1994) were assumed to be representative of surface and ground water quality for the study area (see table E2-1). For depleted uranium, solubility was estimated using field data measured at the E-F site at LANL (Hanson and Miera 1977), Aberdeen Proving Ground in Maryland (Erickson et al. 1993), and Yuma Proving Ground in Arizona (Erickson et al. 1993).

TableTable E2-2.-Estimated Solubilities and Distribution Coefficients for Metals

in LANL Surface and Ground Water


Metals	Solubility, µg/L unless otherwise noted	Distribution Coefficients, K_d, (mL/g)
		Subsurface Sediments and Ground Water		Suspended Sediment and Surface Water
		Conservative	Realistic	Conservative	Realistic
Depleted Uranium	300 mg/L	50	100	100	200
Lead	50	1,000	10,000	2,000	20,000
Beryllium	4	50	100	100	200
Nickel	1000	20	200	40	400
Copper	10	20	200	40	400
Aluminum	1	300	5,000	600	10,000
Iron	0.002	15	1,000	30	2,000
Silver	300 and 80 for surface and ground water	1	100	2	200

E2-2 shows a summary of both the solubility and sorption values estimated for the metals of interest in LANL surface and ground waters. Note that except for silver, solubility for each metal is the same for surface and ground waters of the LANL study area. Both conservative and realistic estimates of distribution coefficients, K_d, are shown in the table for depleted uranium, lead, beryllium, nickel, copper, aluminum, iron, and silver.

APPENDIX E3: SURFACE WATER MODELING

Contaminant movement in runoff, stream flow, and sediment transport from both PHERMEX and DARHT has been identified as a key set of processes leading to exposure and health effects. Pathways of interest include stream flow and sediment discharge through the Water and Potrillo Canyon watersheds leading to the Rio Grande and stream flow transmission losses to the underlying ground water. This section of the appendix describes the modeling procedures used to estimate the transport and fate of depleted uranium, beryllium, and lead in the Water and Potrillo Canyon watersheds.

E3.1 MODEL DESCRIPTION

The transport and fate of depleted uranium, beryllium, and lead in the Water and Potrillo Canyon watersheds were estimated using one-dimensional event-based procedures (Lane et al. 1985) originally developed to simulate the movement of plutonium in the Los Alamos Canyon watershed. The procedures developed by Lane et al. (1995), hereafter referred to as the Lane model, were selected because they were specifically formulated to represent the hydrologic, hydraulic, sediment, and contaminant transport processes occurring in the Los Alamos region. The Lane model accounts only for the transport of contaminants sorbed to sediments and does not consider contaminant transport in the dissolved phase. Since this EIS is concerned with the transport of depleted uranium, beryllium, and lead which are soluble in LANL waters, the Lane model procedures were extended to include dissolved phase transport and sorption/desorption with sediments using partition coefficients as described by Mills (Mills et al. 1985). The model was also extended to include the transport of dissolved contaminants from the firing sites into the neighboring canyon channels. The extended model transports contaminants sorbed to sediments or dissolved in the water column. The model also estimates dissolved contaminants that infiltrate to the subsurface from mesa top firing sites and through channel transmission losses. It is important to note that the long-term observations of precipitation, stream flow, and sediment yield necessary to calibrate and validate the model were not available for the Water and Potrillo Canyon watersheds. A very conservative approach has been taken in this model to account for the substantial uncertainty that exists in the performance of the water resource system. The simulated concentrations leaving the LANL site are well below drinking water standards.

E3.2 MODEL APPLICATION

The extended Lane model was developed and applied to the Water Canyon and Potrillo Canyon watersheds. These watersheds were divided into a series of representative channel reaches. Figure E3-1 shows a schematic of the channel network and the individual reach identification numbers.

Total daily precipitation values used to drive the model for the 32-year historical period of PHERMEX operations were obtained from gage data collected at LANL (Bowen 1990). Snowmelt runoff was not explicitly included because there was not adequate information to characterize these events. Precipitation occurring as snow was simply applied as rainfall on the day of occurrence. Following Lane et al. (1985), the daily average precipitation was converted to a 1-hour rainfall and used as the input to the hydrology model.

Because stream flow in Water and Potrillo Canyons is ephemeral, a very long time may be required for contaminants to be transported downstream from the release point and attain a maximum concentration. Since the model is driven entirely by rainfall events, a hypothetical future precipitation record was required. A 5,000-year daily average precipitation record was created using the methods described by Sharpley and Williams (Sharpley and Williams 1990) and statistics computed from the measured daily rainfall record from 1947 through 1994.

Watershed subbasin areas, composite runoff curve numbers, channel widths, lengths, and slopes were obtained from McLin (1992) and are listed in table Table E3-1.-Channel Characteristics

Canyon

Reach No

Drainage Area (mi²)

Curve

Number

Length

(mi)

Average Width (ft)

Water

4.07

2.63

0.52

0.90

1.97

0.32

3.41

3.36

1.33

2.27

2.60

0.95

3.0

Cañon de Valle

2.33

0.78

1.17

4.26

1.42

2.37

3.0

Potrillo

0.68

0.49

0.93

0.96

1.33

0.95

1.80

1.85

3.0

40.0

3.0

Fence

1.03

3.41

3.0

Canyon

Hydraulic

Conductivity

(in/hr)

Slope

Manning

Median

Grain Size

(mm)

Silt-Clay

Percentage

Water

1.5

0.13

0.04

0.02

0.04

0.08

0.040

1.3

0.8

2.5

0.5

2.5

1.5

Cañon de Valle

1.5

0.12

0.05

0.04

0.040

1.6

3.5

Potrillo

1.5

0.03

0.02

0.040

1.2

0.9

2.0

2.5

Fence

1.5

0.02

0.040

1.1

0.5

E3-1. Note that overbank areas (floodplains) were not included and the active channels were assumed to have a rectangular cross section. These assumptions are conservative in that they lead to increased rates of sediment and contaminant transport and thus an accelerated movement of contaminants toward the Rio Grande. Channel widths of 3 ft (0.91 m) have been used except for the section of Potrillo Canyon (reach 3) termed the "discharge sink" by Becker (Becker 1993). The discharge sink has been noted to be a wide area without a distinct channel with a high vertical infiltration rate (Becker 1993).

Additional channel characteristics used in the model (hydraulic conductivity, Manning's n, median grain size, and silt-clay fraction) were estimated using the values chosen by Lane (Lane et al. 1985) for Los Alamos Canyon as guidance. Only two sediment size classes were considered in the model; bedload was represented as material with a median grain size diameter (d₅₀), and suspended load was represented bythe silt-clay size fraction. As recommended by Lane (Lane et al. 1985), a constant value of 5 was used for the suspended sediment transport coefficient in the model. To improve confidence in model results, future studies should be undertaken to characterize the channel sediments in Water and Potrillo Canyons. The values selected for each channel reach are listed in table E3-1. The depth of channel bed sediments available for contaminant storage was assumed to be 11.81 in (30 cm) for all reaches, which is consistent with the value selected by Lane (Lane et al. 1985).

For each reported simulation, the entire yearly contaminant mass release is assumed to be distributed uniformly over a 100-ft (30-m) radius circle centered at the firing site (PHERMEX or DARHT) at the start of each year. For days during which rainfall occurs, the contaminants are mobilized by assuming that they go into solution at the solubility limit. The volume of rainfall and associated contaminant mass is split between infiltration to the vadose zone and runoff to the canyons using the curve number method (Lane et al. 1985). Use of the runoff curve method neglects evapotranspiration; all precipitation is used for transporting contaminant as infiltration and runoff. Note, the runoff curve number used for the firing site area is the same as that used for the watershed subbasin containing the firing site listed in table E3-1. This assumes that the firing site area will be restored to natural soil and vegetation conditions after the facility is closed. Contaminants travel from the firing site to the canyon channel only through runoff; soil erosion and contaminant movement associated with the eroded soil was not considered. This assumption was made in order to avoid the additional complexities and uncertainties associated with the simulation of soil erosion and overland contaminant transport from the firing sites to the channel system. The dissolved contaminants associated with rainfall runoff are input to Potrillo Canyon in reach number 1 and to Water Canyon in reach number 12 (see figure E3-1).

Application of the curve number for the natural soils and vegetation to partition between runoff and infiltration at the DARHT Facility implies one of two situations: 1) the grounds of the DARHT Facility are seeded after construction and maintained during operation such that only a small portion of the facility grounds contaminated with depleted uranium, beryllium, and lead (e.g., the firing point) exhibit altered storm water runoff characteristics, and/or 2) the release is so long term (e.g., hundreds to tens of thousandsof years) that the different storm water runoff characteristics of the 30-year operational period are not significant to the overall release. The facility and its surrounding grounds, including access roads and parking, will certainly increase impervious surface area, and, therefore, increase peak rates of runoff from the facility. However, runoff from these surfaces will be routed into rip-rap lined ditches and culverts. The increased runoff caused by the structure and asphalt surfaces will, by design, be routed away from the firing point and surrounding contaminated soils. The storm water pollution prevention plan being implemented under the construction program calls for the placement of rip-rap at site drainage areas toprotect against erosion, and the revegetation of all areas disturbed and not covered by pavement, structures, or rip-rap. Thus, storm water runoff that would impact the contaminated soils of the firing point and adjacent grounds may not be significantly greater than that experienced in a natural setting. Concerning the second situation, the release is believed to be very long term. Becker (1993) estimated that the majority of the uranium inventory used in experiments during the last 50 years remains on the firing sites. Furthermore, the results of the present analysis demonstrated that beryllium and lead releases will require tens of thousands of years to leave the firing site. Thus, it is believed that conditions are met for the application of the curve number representative of long-term site conditions.

A source of additional runoff associated with operation of the facility is the cooling water blowdown discharge. When the facility is in operation, an estimated average of 2,000 gal/d (267 ft³/d; 7.6 m³/d) of cooling water will be discharged underground to a rip-rap lined trench that is drained by a culvert to a discharge point to the southeast of the east accelerator hall of the DARHT Facility. (Note, discharge of this cooling tower blowdown water has been approved and it is included in the National Pollutant Discharge Elimination System (NPDES) Permit issued to LANL by the EPA.) The discharge point is approximately 370 ft (113 m) from the firing point and is shielded from the firing point by the east accelerator hall. At this distance and being shielded, it is not anticipated that the discharge point will exhibit depleted uranium concentrations in soils that are significantly above background. Furthermore, because the culvert discharges to a rip-rap drainage area, it is anticipated that this cooling water will infiltrate into the subsurface and not discharge to Water Canyon except when cooling water discharge coincides with storm water discharge. Because this discharge is not expected to contact firing site soils and is expected to seep into the mesa rather than discharge to Water Canyon, the cooling water discharge has been neglected in this analysis.

Inclusion of runoff from storm water and cooling water discharges during the 30-year operation of the DARHT Facility could lead to minor increases in discharge to Water Canyon from the facility grounds (e.g., the 7 ac (3 ha) of the facility including structures and paved surfaces) but would not result in significantly greater flows within the canyon. Water Canyon and Cañon de Valle provide drainage to approximately 7,000 ac (11 mi²) of upstream watershed. The relatively small increase in discharge from operation of this 7-acre facility will not significantly impact the total discharge of the canyon.

In all cases, the partition coefficients (K_d) and solubility limits for the depleted uranium, beryllium, and lead used were the conservative estimates for suspended sediments as given in appendix E2.

E3.3 NO ACTION ALTERNATIVE SIMULATIONS

In this alternative, the transport by surface runoff during the past 32 years for releases of depleted uranium, beryllium, and lead and for releases during the next 30 years from the PHERMEX site were assumed to be evenly split between Water and Potrillo Canyons with 50 percent of the release going to each canyon. The amount of depleted uranium released is assumed to be 30 percent of total mass indicated in section 2 of appendix E. For the next 30 years in the No Action Alternative, the annual releases of depleted uranium, beryllium, and lead would be 460, 22 and 33 lb/yr (210, 10, and 15 kg/yr), respectively. Table 5-3 shows the simulated peak concentration of contaminants in the infiltrated water at the discharge sink in Potrillo Canyon (reach 3) and at Water Canyon channels below the source (Reaches 12, 13, 14, and 15).

Because of their low solubility, the concentrations of beryllium and lead reach a plateau at the end of the 5,000-year simulation, but still remain well below drinking water standards. Using the average simulated transport rates, the inventories of beryllium and lead at the firing site will be exhausted in approximately 300,000 and 40,000 years, respectively. Although beryllium and lead have relatively low solubilities, depleted uranium has a relatively higher solubility in LANL surface and ground waters. Consequently, the source of depleted uranium on the soil surface would be completely removed from the firing site in less than 1,000 years.

Table 5-3 also lists the peak concentration of dissolved and sediment-sorbed contaminant concentrations entering the Rio Grande. The Rio Grande is the nearest off-LANL access point for surface water carrying contamination from the firing point. The quality of surface water entering the Rio Grande is forecast to be more than an order-of-magnitude below the proposed water quality standard for uranium and several orders-of-magnitude below the drinking water standard MCLs for beryllium and lead.

The long-term average annual water volume (over the 5,000-year simulation) infiltrating at the Potrillo Canyon discharge sink was computed to be 37,400 ft³/yr (1,000 m³/yr). This is lower, but in the range of the 183,600 ft³ (5,200 m³) volume that was reported for 1990 from the short-term measurements by Becker (Becker 1993). The average annual simulated water discharge and sediment discharges entering the Rio Grande from the Water-Potrillo Canyon watersheds were 237,000 ft³/yr (6,700 m³/yr) and 165 tons/yr (150,000 kg/yr), respectively. No direct measurements of stream flow volume and sediment discharge to the Rio Grande were available for Water Canyon.

E3.4 DARHT BASELINE ALTERNATIVE SIMULATIONS

The annual expenditures from the DARHT site of depleted uranium, beryllium, and lead were 460, 22, and 33 lb/yr (210, 10, and 15 kg/yr), respectively. The amount of depleted uranium released is assumed to be 30 percent of total mass indicated in section 2 of appendix E. These annual expenditures from DARHT were released onto the firing site for the first 30 years of the simulation. All surface runoff from the firing site was directed to Water Canyon. Table 5-8 shows the peak concentration of contaminants and years to peak in the infiltrated water along Water Canyon (Reaches 12, 13, 14, and 15).

Because of their low solubility, the concentrations of beryllium and lead reach a plateau at the end of the 5,000-year simulation, but still remain well below drinking water standards. Using the average simulated transport rates, the inventories of beryllium and lead at the firing site will be exhausted in approximately 74,000 and 9,000 years, respectively. Although beryllium and lead have relatively low solubilities, depleted uranium has a relatively high solubility in LANL surface and ground waters. Consequently, the source of depleted uranium on the soil surface would be completely removed from the firing site in less than 1,000 years.

Table 5-8 also lists the peak and time to peak for the dissolved and sediment-sorbed contaminant concentrations entering the Rio Grande. The Rio Grande is the nearest off-LANL access point for surface water carrying contamination from the firing point. The quality of surface water entering the Rio Grande is forecast to be more than an order-of-magnitude below the proposed water quality standard for uranium and several orders-of-magnitude below the drinking water standard MCLs for beryllium and lead.

E3.5 ENHANCED CONTAINMENT ALTERNATIVE SIMULATIONS

Under this alternative three options were analyzed: the Vessel Containment Option, the Building Containment Option, and the Phased Containment Option (preferred alternative). The annual expenditures of depleted uranium, beryllium, and lead for each of these options are listed in table Table E3-2.-Annual Expenditures of Depleted Uranium, Beryllium, and Lead

for the Enhanced Containment Alternative


Containment Option	Depleted Uranium lb (kg)	Beryllium lb (kg)	Lead lb (kg)

Vessel (30 yr)	185 (84)	6.5 (3)	10 (4.4)

Building (30 yr)	92 (42)	1.3 (0.6)	2 (0.9)

Phased (0 to 5 yr) (6 to 10 yr) (11 to 30 yr)	444 (200) 315 (143) 185 (84)	21 (9.5) 14 (6.2) 6.5 (3)	31 (14) 21 (9.4) 10 (4.4)

E3-2.

These annual expenditures from DARHT were released onto the firing site for the first 30 years of the simulation. All surface runoff from the firing site was directed to Water Canyon. Table 5-11 shows the peak concentration of contaminants and years to peak in the infiltrated water along Water Canyon (Reaches 12, 13, 14, and 15) for the three options.

Because of their low solubility, the releases of beryllium and lead are long term. Beryllium concentrations plateau before the end of the 5,000-year simulation and remain well below drinking water standards. Based on release projections, we estimate beryllium release will require 4,420, 22,000, and 34,000 years for the Vessel Containment, Building Containment, and Phased Containment options, respectively. Similarly, lead concentrations plateau within the 5,000-year simulation and remain well below drinking water standards. Because its solubility is greater than that of beryllium, lead release times are shorter. We estimate lead release to the environment will require 530, 2,590, and 4,062 years for the three options, respectively. Depleted uranium has a relatively high solubility in LANL surface and ground waters. Based on this high solubility concentration, the source of depleted uranium at the soil surface would be completely removed from the firing site in 30 years for the various containment options. Such a release is conservative or aggressive because it routes the depleted uranium into the environment more quickly than field observations (Becker 1993) indicate is occurring. The model indicates that the reach of Water Canyon (reach 12) receiving runoff from the facility could discharge water to the streambed or to the downstream reach (depending on canyon flow conditions) containing concentrations of depleted uranium at or slightly above the drinking water standard for uranium (i.e., 20 µg/L).

Table 5-11 also lists the peak and time to peak for the dissolved and sediment-sorbed contaminant concentrations entering the Rio Grande. The Rio Grande is the nearest off-LANL access point for surface water carrying contamination from the firing point. The quality of surface water entering the Rio Grande is forecast to be more than an order-of-magnitude below the proposed drinking water standard for uranium and several orders-of-magnitude below the drinking water standards for beryllium and lead.

APPENDIX E4: VADOSE ZONE AND

GROUND WATER MODEL

E4.1 INTRODUCTION

Ground water constitutes one potential environmental pathway by which contaminants originating at the DARHT and PHERMEX firing sites may, after centuries to millennia, become accessible to members of the public. Some canyons in the Los Alamos area (notably Los Alamos and Mortandad Canyons to the north of TA-15) have shallow alluvial and intermediate-depth perched aquifer systems that provide a relatively fast path for contaminants leached through canyon bottoms to appear in ground water. However, the canyons of concern in this study, Water Canyon and Potrillo Canyon, do not appear to havesuch shallow aquifer systems. Potrillo Canyon is cut directly on the Bandelier Tuff, and there is little to no alluvial fill in the upper reaches of the watershed. Therefore, it is unlikely that a permanent alluvial aquifer exists in this canyon (LANL 1993b). Water Canyon is a large canyon that heads on the flanks of the Sierra de Los Valles. A short distance downstream from the confluence of Water Canyon and Cañon de Valle, near the DARHT and PHERMEX sites, is Beta Hole, a dry well extending 187 ft (57 m) into the Bandelier Tuff (LANL 1993b; Purtymun 1995). The lack of water in Beta Hole and two other shallow wells completed in the alluvium confirm that Water Canyon in the vicinity of TA-15 contains no permanent perched or alluvial aquifers, though there is a possibility of perched zones at intermediate depth (LANL 1993b).

In the absence of a perched aquifer, water infiltrating through the vadose (unsaturated) zone may transport contaminants in liquid phase from the surface to the regional or main aquifer. However, this would occur over a long period of time, and has not been observed at LANL. Once in the main aquifer, contaminants may be transported down gradient through the saturated zone down gradient to the Rio Grande, where these contaminants may be discharged in springs or directly to the Rio Grande and become accessible in that surface water body to members of the public. Alternatively, once in the main aquifer, contaminated water might be pumped from wells for municipal and industrial use, again becoming accessible. Although no water supply wells currently exist in TA-15, which includes the DARHT and PHERMEX sites, Purtymun (Purtymun 1984) identified an area that included TA-15 as most suitable for additional water supply wells for Los Alamos County based on the desired attributes of high yield and low drawdown wells. It is surmised that these desirable attributes for well placement will make the area subject to future water well development. However, regulations would require testing before public use, and during subsequent use. The average yield from the five wells in the Pajarito Field [the PM wells are located in the zone identified by Purtymun (Purtymun 1995)] was 1,215 gpm (2.7 ft³/s, 0.08 m³/s) (Purtymun 1984). Therefore, well extraction of dissolved contaminant mass from the regional aquifer, if transported to the aquifer, is a possible consideration.

In spite of the above considerations with regard to the main aquifer, it may be unnecessary to model the flow and transport of contaminants in the main aquifer depending on the results of vadose zone modeling. To reach the main aquifer, contaminant mass must 1) be available at the surface for leaching into the soil profile and 2) be transported vertically downward from the surface to the water table. The travel time for recharge water through unsaturated volcanic tuffs in a semi-arid climate can be centuries to millennia. Sorption further extends the time required for contaminants to migrate to the main aquifer, and dispersion acts to reduce peak concentrations.

Ground water modeling and analysis for this study necessarily follows the assumptions made for the runoff-sediment-contaminant transport model (see appendix E3, Surface Water Modeling). Water infiltration into the bottom sediments of Water Canyon and the contaminant mass loading associated with that water as predicted by the runoff-sediment-contaminant transport model constitute the inputs to the vadose zone model for Water Canyon.

The discharge sink in Potrillo Canyon identified by Becker (1993) is taken to be the controlling feature in that canyon. Evidence in Becker (1993) demonstrated that all surface water from the Potrillo Canyon watershed above this feature drains to the subsurface very rapidly via the discharge sink (except for flood events with a recurrence frequency greater than a 1-in-10-year event). The mechanism that enables such large water intake rates to the subsurface is not well characterized. Becker (1993) concluded that the discharge sink is an area of increased sedimentation, that it contains significant amounts of uranium adsorbed onto the surface soils with depth, and that leaching and deep infiltration transport uranium (dissolved phase) to ground water. Becker (1993) could only hypothesize as to the feature that creates the discharge sink, an underlying fault with a 29-ft (9-m) offset. Because no defensible mechanism can be proposed to account for the discharge sink's hydrologic behavior at this time, no attempt was made to model the discharge sink. Instead, the approach to stream flow losses in Potrillo Canyon was to compute the concentrations of contaminants in water arriving at the sink (as all water in the upper reach of Potrillo Canyon usually collects at the discharge sink), and if those concentrations are low enough to meet regulatory criteria, no further analysis is required. If not, we would make the conservative assumption that contaminated water from the discharge sink is transferred instantly to the main aquifer (i.e., taking no credit for time delay and dispersion in the vadose zone), and examine the consequences of water supply well uptake or surface water discharge of contaminated water at the Rio Grande.

Water Canyon does not appear to exhibit any feature analogous to the discharge sink Becker discovered in Potrillo Canyon (Becker 1993). Nor does Water Canyon appear to have a perched aquifer system, based on the dry Beta Hole located in Water Canyon adjacent TA-15 (LANL 1993b; Purtymun 1995). Therefore, it was decided that modeling the vadose zone below Water Canyon might enable evaluation of the downward flow of water and transport of contaminants from stream losses to the stream bed as predicted by the surface water and sediment transport analysis model.

Finally, the vadose zone from the firing sites atop Threemile Mesa to the main aquifer was modeled. The mesa top in the vicinity of DARHT and PHERMEX is over 300 ft (91 m) above the bottom of Water Canyon. Thus, a model of vadose zone flow and transport from the bottom of Water Canyon to the main aquifer simulates a significantly shorter pathway. However, the contaminant loading at the firing sites into the soil is large enough (e.g., infiltration carrying contaminants at their solubility limit) to require vadose zone flow and transport modeling also.

E4.2 VADOSE ZONE STRATIGRAPHY

There are no deep wells in TA-15 that would provide certain knowledge of the geologic stratigraphy at the DARHT, PHERMEX, or nearby Water Canyon and Potrillo Canyon locations (LANL 1993b; Purtymun 1995). The closest wells that penetrate to the regional aquifer are the test wells DT-5A, DT-9, and DT-10 to the south of TA-15, and the municipal and industrial supply wells PM-2 and PM-4 located to the northeast of TA-15. Figure E4-1 depicts the locations of these wells and the DARHT and PHERMEX firing sites. A cross-section from test well DT-5A to supply well PM-4, based on well log data reported in Purtymun (Purtymun 1995), is shown in figure E4-2. The Tshirege, Otowi, and Guaje members are all sequences within the Bandelier Tuff. Figure E4-2 illustrates the transition in geologic units expected over the area in the vicinity of DARHT and PHERMEX. Based on this cross-section, the location of the DARHT site, and the anticipated stratigraphy (LANL 1993b), the expected geologic stratigraphy for this EIS was developed, and is shown in figure E4-3. The elevation axis at the left of figure E4-3 shows how the expected stratigraphy corresponds to elevation above mean sea level, and includes arrows to show the elevations at the DARHT and PHERMEX sites, Water Canyon (near Beta Hole), and the Potrillo Canyon discharge sink location. The water table elevation at 6,000 ft (1,830 m) (Purtymun 1984; Volzella 1994; LANL 1993b; Purtymun 1995) is shown on the stratigraphic column at 800 ft (244 m) below the well head surface. The depth of the alluvium is designated as 8 ft (2 m) based on the geologic log of the Beta Hole (Purtymun 1995). The fingered layers of Basalt Unit 2 shown in figure E4-2 are assumed not to be present based on the stratigraphy presented in the RFI Work Plan (LANL 1993b) and the trend of basalt layers fingered into the Fanglomerate Member of the Puye Formation to decrease from east to west as a result of the geologic processes in which they were laid down.

E4.3 VADOSE ZONE HYDROLOGIC PROPERTIES

The expected stratigraphy for Water Canyon depicted in figure E4-3 shows five hydrogeologic units in the vadose zone for which hydrologic properties are required for modeling purposes: alluvium, three members of the Bandelier Tuff (Tshirege, Otowi, and Guaje), and the Puye Formation. The properties required for water flow modeling are saturated hydraulic conductivity, porosity or saturated moisture content, residual moisture content, and the empirical curve-fitting van Genuchten (van Genuchten 1980) water retention parameters _ and n for use in the water retention and liquid relative permeability models chosen for this analysis.

Values for the vadose zone flow model parameters for each unit are reported in tableTable E4-1.-Hydrologic Properties for Vadose Zone Flow Modeling


Stratigraphic Layer	Water Content Parameters		van Genuchten Model Parameters		Saturated Hydraulic Conductivity
Stratigraphic Layer	__r Residual	__s Saturated	_ (1/m)	n	K_s (m/s)
Alluvium	0.038	0.433	3.85	1.558	4.40 x 10^-6
Tshirege	0.021	0.498	1.20	1.759	6.00 x 10^-7
Otowi	0.026	0.469	0.66	1.711	1.30 x 10^-6
Guaje	0.022	0.492	1.13	1.716	7.00 x 10^-7
Puye^§	0.0283	0.4982	1.76	1.338	2.42 x 10^-8
__r Residual water content. __s Saturated water content. _ Fitted van Genuchten parameter, 1/m. n Fitted van Genuchten parameter. K_s Saturated hydraulic conductivity, m/s. ^§ Ringold Unit (Rockhold et al. 1993) properties used as analogue for Puye Formation.

E4-1. All values for the alluvium and Bandelier Tuff members are based on mean values reported in Rogers and Gallaher (Rogers and Gallaher 1995). No values were reported in that document directly for the Guaje Member, so the average of all Bandelier Tuff measurements was used to provide the hydrologic properties given in table E4-1 for the Guaje Member. Figure E4-4 provides the graphical interpretation of the water retention and relative permeability parameters by showing the retention and conductivity curves resulting from the use of the parameter values given in table E4-1.

No published hydrologic data, other than field coefficients of conductivity (Purtymun 1984), were found in the literature pertaining to the Puye Formation. The Puye Formation is derived from the Tschicoma volcanic centers located in the northeastern range of the Jemez Mountains. It consists of stream flowdeposits, debris flow and block flow deposits, and ash fall and pumice fall deposits (LANL 1993b). The hydrologic properties of a similar undifferentiated unit, the Ringold Unit found at the Hanford Site in Washington State, were chosen. The Ringold Unit is taken to be an analogue to the Puye Formation, andtherefore properties used are largely approximate. Further precision will require a characterization and data collection program aimed at the Puye Formation and would only be necessary if the results of this analysis indicated that the unit imposed a significant control over the flow and transport results, which it did not. Properties for the Ringold Unit, reported in table E4-1, were taken from those reported in Rockhold et al. (1993).

E4.4 VADOSE ZONE MODELING APPROACH

We modeled the vadose zone below Water Canyon and Threemile Mesa as one-dimensional vertical stratigraphic columns extending from the regional aquifer piezometric surface (water table) at the lower boundary to the surface of Water Canyon or Threemile Mesa at the upper boundary. The upper boundary was treated as a Neumann boundary with a constant water flux rate based on the average water infiltration predicted by the runoff-sediment-contaminant transport model. Temporal variation in water infiltration was neglected because such variation is greatly damped within a few meters of the surface. The lower boundary was treated as a Dirichlet boundary and assigned a constant atmospheric pressure to representthe presence of the water table. Fracture flow was neglected because published information on this flow mechanism is incomplete (Loeven and Springer 1992); fractures are sparse features where documented (Purtymun et al. 1978), and in the low-saturation regimes such as that modeled here, fractures constitute barriers to moisture flow rather than preferential pathways (Klavetter and Peters 1986).

A computer code was used to perform the flow and transport simulations. The code we chose was the Multiphase Subsurface Transport Simulator, or MSTS (White and Nichols 1993; Nichols and White 1993). The MSTS computer code was chosen based on the following considerations:

· MSTS solves the nonlinear water mass conservation equation for variably saturated media necessary to model the vadose zone

· MSTS was developed for the Yucca Mountain Site Characterization Project, a program concerned with deep vadose zone flow and transport in arid site volcanic tuff environments, characteristics similar to the site under consideration in this study

· MSTS simulates dilute species mass transport using a convection-dispersion model with linear sorption coupled with the water mass conservation simulation, providing an integrated capability for flow and transport modeling that is much simpler than using separate flow and transport models

· Radioactive decay in the transport equation (dilute species mass conservation equation) is accounted for by the MSTS code

· The code is well documented, has been favorably reviewed (Reeves et al. 1994), and has a proven track record for flow and transport simulation in the numerically difficult volcanic tuff environment (Eslinger et al. 1991).

Numerical stability criteria were examined to construct a grid of computational cells and enable stable simulation of water flow and contaminant transport for this vadose zone model. Calculations indicated that a grid discretization of 0.5 ft (0.15 m) or less would be required, yielding 1,600 grid elements over the 800 ft (244 m) high stratigraphic column. Other calculations indicated that time steps for the transport simulations should not exceed 20 years to avoid numerical dispersion effects. Because the transport model was restricted to 1-yr time steps to match the temporal rate of contaminant mass loading resulting from the runoff-sediment-contaminant transport model, and 20-yr time steps after mass loading ended, this criterion presented no additional limitation.

E4.5 VADOSE ZONE FLOW MODEL RESULTS

Hydrologic conditions (e.g., water flow) in the unsaturated zone will depend on similar occurrences under any of the alternatives. For example, the presence of the DARHT and PHERMEX facilities does not affect the hydrology of Water Canyon appreciably, and infiltration would move water through Threemile Mesa at either location of the firing point. Therefore, the results of the vadose zone flow simulations were performed and the results reported here for all alternatives and options. Contaminant mass transport simulations that are based on the water pressure fields calculated here are reported with respect to individual alternatives and options in section 5.

A steady-state pressure field was simulated for Reach 12 of Water Canyon. Reach 12 in the surface water model is immediately downstream of the confluence of Cañon de Valle and Water Canyon (seeappendix E3). Another was simulated for a location representative of the DARHT and PHERMEX facilities on Threemile Mesa. The surface elevation difference between the two sites was neglected; the firing sites differ in elevation by approximately 36 ft (11 m) (Fresquez 1994; Korecki 1988). The conditions vary in the different reaches of the Water Canyon model depending upon the water infiltration predicted in each reach by the runoff-sediment-contaminant transport model. The liquid-phase pressure and saturations predicted from the steady-state simulation with the MSTS code for Reach 12 are plotted in figure E4-5. The abrupt changes in pressure and saturation shown in figure E4-5 reflect the variations in hydrologic properties corresponding to the stratigraphic units identified. Liquid-phase mean travel time, that is, the mean time for water to travel from the base of Water Canyon to the regional aquifer, was predicted with the MSTS code. Travel times for Reaches 12 and 13, and for the mesa-top-to-aquifer vadose zone model, are reported in tableTable E4-2.-Liquid Phase Vadose Zone Water Travel Times for Threemile Mesa

and Water Canyon Reaches 12 and 13 Predicted by MSTS

Vadose Zone	Water Travel Time (yr)
Threemile Mesa	298
Water Canyon Reach 12	179
Water Canyon Reach 13	174

E4-2. Water travel times provide an upper bound on the arrival time of the mean concentration of a nonretarded, nondecayed contaminant. Retarded (sorbed) species, such as those under consideration in this study, will have even longer arrival times.

E4.6 CONTAMINANT TRANSPORT SIMULATIONS

Review of the similarities between alternatives for the concentration of infiltration waters predicted by the runoff-sediment-contaminant transport model reduced the number of vadose zone contaminant transport cases that were necessary to simulate for this EIS. The ground water impacts of the Plutonium Exclusion and Single Axis alternatives were the same as the DARHT Baseline Alternative; and the Upgrade PHERMEX Alternative was the same as the No Action Alternative. This review implied that simulations were necessary only under the No Action, DARHT Baseline, and Enhanced Containment alternatives. For these three alternatives, the peak concentrations of depleted uranium, beryllium, and lead in water infiltrating into the vadose zone in the four reaches of Water Canyon downstream from the firing sites, and on Threemile Mesa at the firing sites, were compared to the drinking water standards for these metals. Because transport and dispersion in the vadose zone will only further decrease the concentrations of these metals in solution, it was necessary to simulate only those cases in which the concentration of contaminants in infiltrating water at the surface exceeded the drinking water standard. Finally, comparison of concentrations of contaminants in infiltrating water in the four reaches of Water Canyon showed that the uppermost reach (Reach 12) was always subject to the highest infiltration contaminant concentration levels of the four reaches. Because no simulation of Reach 12 resulted in contaminant concentrations at the regional water table exceeding the drinking water standard for any contaminant, no simulation was necessary for the less-impacted reaches downstream. Thus, a total of 10 simulation cases were required for depleted uranium: transport through Threemile Mesa for the No Action, DARHT Baseline, and Enhanced Containment alternatives (including the three options) and transport through the sediments beneath the uppermost reach of Water Canyon (Reach 12) for the same five alternatives and options. We also simulated beryllium and lead transport from the mesa and the uppermost reach of Water Canyon to the main aquifer to examine the transport of these dissolved contaminants in the vadose zone.

Initial conditions for all simulations specified the liquid pressure field obtained for the respective reach or mesa top simulation (section E4.5, above) and zero contaminant concentration throughout the profile. Mass transport was simulated using the one-year constant time steps of the surface water model (matching the temporal rate for which the contaminant mass input values were provided by the runoff-sediment-contaminant transport model) and then using 20-year constant time steps for periods after mass input rates specified by the surface water model ceased (20-year steps being the maximum permissible under the Courant Number stability criteria). Parameters related to dilute contaminant species mass transport includevalues of the sorption coefficient (K_d), longitudinal hydraulic dispersivity coefficient (__L), and molecular dispersion coefficient (D_d,l). Sorption coefficient values were estimated in appendix E2 ("Solubility and Distribution Coefficients") where both conservative and best-estimate values were provided. We chose to use conservative (i.e., less sorption) values in all vadose zone modeling of contaminant transport. For moderate travel distances (on the order of kilometers), longitudinal dispersivity roughly varies between 0.01 and 0.1 of the mean travel distance of the solute. Choosing the more often used and higher value, with the travel distance through the vadose zone of 800 ft (240 m), we obtained the 80 ft (24 m) value. The molecular diffusion coefficient was that of water, 1.076 x 10^-8 ft²/s (1.0 x 10^-5 cm²/s).

Contaminant mass input rates were obtained from the results of the runoff-sediment-contaminant transport model. The infiltrated volume for each year reported by the runoff-sediment-contaminant transport model was multiplied by the corresponding water concentration of the infiltrated water, and divided by the channel reach area or the area for mass distribution around the firing point to obtain a value for annual mass flux per unit area. This value was converted to appropriate units for the vadose zone flow and transport code and treated as a mass source rate in the uppermost node of the model. For each simulated case, contaminant transport was modeled for 100,000 years. For depleted uranium, 1,000 years of mass input was provided, after which the surface supply of depleted uranium on the mesa surface and in the channel reaches was exhausted (the remainder of the simulation was carried out with no contaminant source term). For beryllium and lead, 5,000 years of mass input was provided. For the simulation beyond 5,000 years, estimates (based on surface modeling) of the time to "plateau" for releases for beryllium and lead and average input concentrations thereafter were used to specify an average contaminant mass source rate and duration for the balance of the 100,000-year simulations. Table E4-3Table E4-3.-Vadose Zone Numerical Transport Simulation Predictions of Peak

Concentrations and Associated Times for Water Arriving at the Regional Main

Aquifer from the Vadose Zone for All Simulated Cases

Alternative, Location

Contaminant

(µg/L)

(µg/L)

Drinking Water Standard

[56 FR 33050]

[40 CFR 141.62]

[40 CFR 141.80]

No Action,

Threemile Mesa (PHERMEX)

145

(42,850 yr)

3.4

(>100,000 yr)

(55,740 yr)

No Action,

Water Canyon Reach 12

0.017

(18,450 yr)

0.00069

(>100,000 yr)

2.6 x 10^-6

(>100,000 yr)

DARHT Baseline,

Threemile Mesa (DARHT)

(42,950 yr)

3.1

(84,680 yr)

6.3

(33,800 yr)

DARHT Baseline,

Water Canyon Reach 12

0.018

(18,430 yr)

0.0014

(>100,000 yr)

5.2 x 10^-6

(>100,000 yr)

Vessel Containment Option

Threemile Mesa (DARHT)

(42,880 yr)

1.2

(41,880 yr)

0.0012

(>100,000 yr)

Vessel Containment Option

Water Canyon Reach 12

0.054

(18,390 yr)

0.0027

(>100,000 yr)

1.0 x 10^-5

(>100,000 yr)

Phased Containment Option

Threemile Mesa (DARHT)

(42,060 yr)

1.8

(50,640 yr)

0.0018

(>100,000 yr)

Phased Containment Option

Water Canyon Reach 12

0.055

(18,430 yr)

0.0027

(>100,000 yr)

1.0 x 10^-5

(>100,000 yr)

Building Containment Option

Threemile Mesa (DARHT)

16.1

(41,980 yr)

0.233

(45,099 yr)

1.5 x 1.0^-7

(>100,000 yr)

Building Containment Option

Water Canyon Reach 12

0.0365

(18,468 yr)

3.4 x 10^-4

(>20,870 yr)

4.5 x 10^-7

(>100,000 yr)

presents the peak concentration of water arriving at the regional main aquifer for each simulated case and time of the peak occurrence, and the related drinking water standard. The significance of the arrival concentrations listed in table E4-3 is provided in the discussions of individual alternatives in sections 5.1.4.2, 5.2.4.2, and 5.4.4.2.

E4.7 GROUND WATER ISSUES AT LANL

Two issues exist with respect to ground water resources in the vicinity of LANL. The first involves the recent discovery of tritium in the main aquifer at four points in the northern portion of the LANL site. The second involves the general observation that private ground water wells located north of Pojoaque can exhibit levels of alpha contamination in excess of drinking water standards.

E4.7.1 Tritium in the Main Aquifer

Since 1991, advanced techniques, not commonly applied to ground water samples, have been used to detect tritium at ultra-low levels and to determine that recent water (no more than a few decades old) has recharged the main aquifer from the land surface in several locations at LANL (Gallaher 1995). Many samples of well and spring water taken at LANL have shown only the natural background levels of tritium and no apparent recent recharge. However, four locations have indicated tritium migration to the main aquifer from overlying contaminated perched aquifers. The levels of tritium measured range from approximately 1 percent to less than a hundredth of a percent of current drinking water standards. Thus, measured levels of tritium are significantly below drinking water standards and below levels measurable using standard measurement techniques. All four confirmed main aquifer tritium measurements indicatingyoung water are in Los Alamos, Pueblo, and Mortandad Canyons, all in the northern part of the Los Alamos site. No main aquifer samples from the southern portion of the site have shown tritium concentrations above natural background. LANL scientists are studying whether the communication between intermediate perched and deep aquifer formations is a result of poor well construction (leaks in well bore seals with casing) or recharge of the main aquifer through either fractures or faults. If the ongoing studies determine the old construction methods are resulting in communication, efforts may be undertaken to abandon and plug the older test wells (Gustafson 1995).

E4.7.2 Alpha Concentrations in Regional Ground Water

High alpha concentrations have been observed in ground water drawn from private wells in the vicinity of Nambe and Pojoaque, New Mexico (Nickeson 1994). These wells are located on the opposite side ofthe Rio Grande from LANL and to the north of Pojoaque. The relationship between LANL activities and the observed alpha concentrations was questioned at the DARHT public hearings. Nickeson noted there was no one to blame for the high alpha concentrations found in her well water. The levels found are related to the abundance of naturally occurring uranium deposits in the highly volcanic region of northern New Mexico. The Santa Fe Reporter (Bird 1995) presented a broader portrait of the high alpha contamination problem in the region, and its relation to natural uranium levels in the region. Bird indicated that the Ground Water Division of the Environment Department (State of New Mexico) was being asked to consider a study of the area's private wells. Such a study may relate the levels of natural uranium in the aquifer formation to levels observed in ground water, determine the origin of ground water in the Pojoaque area (i.e., origin to the east or west of the Rio Grande), or determine isotopic ratios of uranium species (i.e., identifying natural versus depleted uranium sources, man-made isotopes, or other alpha emitters). Because it is a regional water quality issue and is acknowledged by State of New Mexico officials as being related to natural uranium levels, resolution of this issue is clearly beyond the scope of the DARHT EIS.

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accelerator E-29

aquifer E-1, E-31, E-32, E-33, E-34, E-38, E-40, E-43, E-42, E-43, E-44, E-48

aquifers E-32, E-42

beryllium E-16, E-17, E-20, E-21, E-24, E-25, E-24, E-25, E-26, E-27, E-29, E-30, E-31, E-32, E-31, E-40, E-42

containment E-31, E-32, E-31, E-40, E-43, E-46

contaminant E-1, E-25, E-26, E-27, E-30, E-31, E-32, E-33, E-38, E-39, E-40, E-42, E-43, E-48

contaminants E-1, E-16, E-24, E-25, E-26, E-27, E-29, E-30, E-31, E-32, E-33, E-40

depleted uranium E-16, E-17, E-24, E-25, E-24, E-25, E-26, E-27, E-29, E-30, E-31, E-32, E-31, E-40, E-42, E-44, E-45, E-46

detonation E-18, E-45

drinking water standard E-30, E-31, E-40, E-43, E-42

drinking water standards E-17, E-26, E-30, E-31, E-40, E-42

firing point E-3, E-18, E-27, E-28, E-29, E-30, E-31, E-39, E-42

ground water E-1, E-18, E-19, E-20, E-21, E-22, E-23, E-24, E-25, E-31, E-33, E-40, E-42, E-43, E-44, E-47, E-48

groundwater E-33, E-44, E-45, E-48

monitoring E-2, E-44

NPT E-4

phased containment E-31, E-43

pit E-2

plutonium E-25, E-40

primary E-17

radiation E-6, E-7

radioactive waste E-44

secondary E-17, E-19

soil E-1, E-2, E-3, E-5, E-6, E-5, E-8, E-9, E-10, E-14, E-15, E-16, E-18, E-19, E-20, E-21, E-22, E-23, E-24, E-27, E-30, E-31, E-33, E-44, E-45, E-47, E-49

soils E-1, E-5, E-9, E-18, E-21, E-22, E-24, E-27, E-28, E-29, E-33, E-48, E-49

surface water E-1, E-2, E-19, E-25, E-30, E-31, E-32, E-33, E-39, E-40, E-47

tritium E-42, E-43, E-45

vessel containment E-31, E-43

water resource E-26

water resources E-1, E-42

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