The suite of constituents to be analyzed may vary over the life of a wellfield. A full suite of samples including all the species listed by EPA and the additional species listed by NRC in its Standard Review Plan (NRC 2003), shown above in Table 3-3, Columns 2 and 3, would provide the basis for a sample suite to be used for establishing the wellfield baseline, Phase 1 in Figure 3-1. Some of the listed constituents may not be detected in the baseline ground water. However, since there is a possibility that nondetectable concentrations of specific constituents could become measurable because of the introduction of the lixiviant and geochemical changes within the aquifer during mining, the same suite of samples should be used to characterize the ground water at the end of mining (Phase 2 of Figure 3-1). If some of the sampled constituents are not detected in Phase 1 or Phase 2, then consideration should be given to eliminating those constituents from monitoring during Phases 3, 4, and 5 as defined in Figure 3-1. In addition, it may be appropriate to eliminate other constituents from Phases 3, 4, and 5 monitoring if the constituents are not deemed to provide significant incremental information about ground water quality. Species such as sodium, potassium, ammonia (unless it is added to the lixiviant), and SiO2 might fall into this category. However, if geochemical modeling is required, elimination of these species may not be possible since an anion/cation balance will be needed. Temperature and TDS may also be needed to confirm that the thermodynamic database for the geochemical model is valid. The next section discusses these requirements in greater detail.

In summary, the initial list of analytes for monitoring during Phase 1 and Phase 2 would include all of the inorganic species listed in the EPA regulations (Column 2 of Table 3-3), in addition to any species listed in the NRC Standard Review Plan (Column 3 of Table 3-3) that are not on the EPA list. For ground water monitoring during Phases 3 - 5, the initial list would be reduced by eliminating those species not detected during Phase 1 and Phase 2. The monitoring list for Phases 3 - 5 could be further condensed by eliminating certain nonhazardous species judged not to significantly impact ground water quality or adversely impact the ability to perform geochemical modeling.

Compiling listings of species to be determined for an ISR operation can be regarded as a "tiering" approach in that the contaminants regulated by various regulatory authorities would comprise the top tier in an analytical scheme. These species would include radionuclides and other species with adverse health effects. They would always require measurement. Those species used for other purposes, such as detecting excursions, determining water quality, and geochemical modeling exercises would be the next "tier" in a sampling and analysis plan. Many of these species would also be required to demonstrate compliance with regulatory requirements, although not directly tied to assessing potential adverse health effects. An example would be a species used as an indicator of excursions and as a measure restoration. Species on the lower tier list may be dropped from a sampling and testing protocol at different stages of the ISR operation if they are determined to have no role in controlling radionuclide and toxic metal concentrations and contaminant migration. For any specific ISR operation, the listing of species for measurement should be stated initially in the licenseing process and subject to revision on the basis of data collected during operations (see Section 3.5.6 below for an example).

Well Construction and Low-Flow Sampling Methodologies

The construction of the production, injection or monitoring wells involves sealing the units overlying the production zone with steel, fiberglass or PVC casing that is grouted in place (NRC 2009).  A typical well completion is shown in Figure 3-8. Other potential types of well construction are described in NMA (2007).

The type of grout, screen and casing materials are selected based upon the chemistry of the lixiviant and ground water, the depth of the target interval and the expected injection pressures. PVC or fiberglass casings are generally used in wells less than 1,000 ft deep, while deeper wells or wells that will be subject to high pressures are generally constructed with steel or fiberglass casing and well screens (NRC 2009). The potential that chemical reactions may take place between the casing material and the dissolved constituents in the ground water also needs to be considered in selecting well construction materials.

As described in Puls and Barcelona (1996) and EPA (2010d), the water in the well casing may not be representative of the aquifer, and therefore needs to be excluded from the ground water samples. Wells are purged to some extent prior to sampling for the following reasons: the presence of the air interface at the top of the water column resulting in an oxygen concentration gradient with depth, leaching from or sorption to the casing or filter pack, chemical changes due to clay seals or backfill, and potential surface water infiltration into the annular space of a poorly constructed or deteriorating well.
Low-flow refers to the velocity with which water enters the pump intake and that is imparted to the formation pore water in the immediate vicinity of the well screen. Water level drawdown within the well provides the best indication of the stress imparted by a given flow-rate for a given hydrological situation. The objective is to pump in a manner that minimizes vertical flow within the borehole, and draws formation water through the well screen to the pump.

Ground water sampling at ISR facilities is typically based on low-flow methods stabilization of the water quality parameters within pre-determined ranges based upon historical data (NRC 2006). Stabilization parameters generally include electrical conductance, pH, oxidation-reduction potential, turbidity, dissolved oxygen and temperature (NRC 2006). Major differences between typical procedures used in low-flow sampling at RCRA and CERCLA sites versus ISR facilities are the pumping rates are generally much higher at ISR facilities (5 to 10 gpm versus 0.1 to 0.25 gpm), the screened intervals are generally greater than 25 feet (versus 10 feet) (NRC 2006), and the well diameters for the ISR wells are much larger (4 to 6 inches versus 2 inches for typical RCRA and CERCLA wells).

                               Source:  NMA 2007

Figure 3-8.	Cross Section of a Typical Injection, Production, or Monitoring Well

Species Required for Geochemical Modeling

To adequately comprehend the potential mobility of uranium in ground water, a sufficient degree of site characterization has to be conducted to understand hydrogeologic and geochemical conditions and also the extent and distribution of any contaminant plumes and sources. As discussed in EPA 2002c, sample collection programs are designed around goals associated with specific project objectives. Data quality objectives (DQOs) define the types, quality, and quantity of data required by the various aspects of a project. Once the DQOs are developed, appropriate sampling methodologies, analytical protocols, and specific methods may be considered and selected. For instance, the DQOs may be different if project goals emphasize detection and monitoring of contaminant concentrations rather than geochemical speciation modeling. The types of data required to fulfill the conceptual model needs related to the geochemistry are presented below.

Aqueous Chemistry

A simplified conceptualization of the major speciation reactions that geochemical modeling attempts to simulate are shown in Figure 3-9. During active mining, an oxidant (lixiviant) is injected that releases oxygen (O2) in order to solubilize the uranium from the uraninite (upper mineral shown in Figure 3-9) into uranyl carbonate complexes (UO2CO3[0]), which are extracted in solution to the surface. The injected oxidant also reacts with pyrite that releases dissolved iron and subsequently precipitates some form of hydrous ferric oxide (HFO). The HFO precipitate that forms is a mixture of iron-bearing minerals that often includes microcrystalline goethite. Uranyl ions derived from the uraninite will also be adsorbed to the surface of the goethite and as uranyl surface complexes (Hfo_wOUO2[+2]) and removed from solution. This surface complexation reaction could be particularly important in the restoration phase (Gard and Mahoney 2012).

Characterization of geochemical conditions within an aquifer requires careful collection of data (e.g., major ions) necessary for input into geochemical models. The sensitivity of uranium to redox conditions also requires that precautions be taken during sampling and analysis to ensure that results obtained are representative of ground water chemistry. The following are considered "core parameters for ground water" for predicting uranium concentrations (EPA 2002c) in ground water:

   * Temperature.
   * Oxidation-reduction potential (corrected to redox), pH, alkalinity.
   * Turbidity.
   * Total and ferrous iron.
   * Dissolved oxygen.
   * Specific conductance.
   * Dissolved organic carbon.
   * Major ions (Ca[2+], Mg[2+], Na[+], K[+], Cl[-], S[2-], SO4 [2-], NO3[2-], ammonium, phosphate).
   * Aluminum, silica, manganese.
Collection of turbidity data is important for a variety of reasons, including its usefulness as a sampling equilibration parameter using low-flow techniques where metals are contaminants of concern. Turbidity data can also be helpful in explaining data anomalies (e.g., high total iron concentrations under oxidizing conditions) and evaluating the influence of particulates on metals concentrations. The collection of major anion and cation data is important for proper evaluation of the aqueous geochemistry of the system and for performance of accurate geochemical modeling in support of a site conceptual model. Fluoride is important in some hydrogeologic settings because of its high complexing capacity and thus, is needed to determine the adequacy of ion balances for geochemical modeling purposes. Additional information on this topic is covered in EPA 2002c.

                        Source:  Gard and Mahoney 2012

Figure 3-9.	Major Chemical Reactions Involved in Uranium Recovery and Restoration

Specification of the appropriate methodology for the collection and analysis of the above listed parameters is beyond the scope of this document; however, descriptions of techniques and methods can be found in EPA 2002c, ASTM procedures (e.g. ASTM 2010), and the USGS online field manuals. Certain parameters must be measured in the field because of stability issues, and others are recommended to be field measurements (EPA 2002c). Parameters that must be measured in the field include temperature, pH, Eh, dissolved oxygen, and turbidity. The use of low-flow sampling is recommended as described in EPA 2010a. Specific conductance and alkalinity are also recommended for field analysis (EPA 2002c). Redox indicators such as Fe(II), S[2-], and H2 should be measured in the field rather than in the laboratory; EPA 2002c describes special considerations with respect to their measurements.

Solid Phase Geochemistry

Solid phase characterization should be included for sites where uranium or other inorganic contaminants in ground water are being evaluated. The solid phase should be tested to confirm the form of the uranium associated with the mineralogy of the solid phase, and to determine its stability or mobilization potential (EPA 2002c). Examples of useful solid phase characterization techniques include optical analysis of the mineralogy by a geologist/geochemist, x-ray diffraction and petrographic studies, scanning electron microscopy, high resolution transmission electron microscopy or microprobe analysis to determine the presence of elements and minerals, cation exchange capacity, neutralization or acid-generation capacity, and extraction of amorphous iron or aluminum coatings to assess the mass of sorptive material on mineral surfaces. Depending on site-specific needs, a useful approach would be to use mineralogical identification tools to confirm mineralogy, followed by chemical extraction to quantify mass of the mineral. Organic coatings or other organic matter on the solid phase can exert significant geochemical influence on ground water and should be characterized. Mineral phases that are commonly used in geochemical modeling include uraninite, pyrite, calcite and goethite (Gard and Mahoney 2012). A summary of  site-specific parameters that can be used to characterize solid-phase materials is presented in Table 3-4. The subsurface material bulk density should also be measured, so that the chemical parameters listed in Table 3-4 can be reported on a mass basis. Furthermore, a sufficient number of core samples should be collected to adequately characterize the spatial variability of the lithology.

Table 3-4.	Parameters for Solid Phase Characterization
                             Solid Phase Parameter
                             Parameter Description
Oxidation Capacity
Capacity of sediment to oxidize a reduced chemical (uranium or introduced remedial reagent)
Reduction Capacity
Capacity of rock matrix to reduce an oxidized chemical (uranium or introduced remedial reagent)
Neutralization Capacity
Capacity of solid phase to buffer change in pH (acid or alkaline)
Sorption Capacity
Total mass of  uranium (and other trace metals) that can be partitioned to solid phase by various mechanisms
Ion Exchange Capacity
Total mass of charged ions that can be partitioned to solid phase via an electrostatic mechanism
Sorbed Uranium
Mass of uranium that is partitioned to solid phase
Solubilized Non-Target Trace Metals
Mass of non-target trace metals  associated with solid phase that may be solubilized as a result of remediation
Reagent Stability
Identification of undesirable by-products produced during reaction between remedial reagent and contaminant/ solid phase ore
Mineralogy (Bulk and Trace)
Identity of mineral phases present in various size fractions of solid phase
Non-Target Solid Phase Contaminant
Non-target constituents that may negatively interact with remedial technology
Extractable Fe/Al/Mn
Mass of Fe/Al/Mn extracted from solid phase using reagents designed to attack specific mineral phases
Extractable Sulfide
Mass of sulfide extracted from solid phase using reagents designed to attack specific sulfidic mineral fractions
Total Organic Carbon
Mass of carbon associated with organic solid phases in sediment
Total Inorganic Carbon
Mass of carbon associated with inorganic solid phases in the rock matrix
Reduction/Oxidation Reaction Rate
The rate at which solid phase will reduce/oxidize (consume) oxidizing/reducing reagent
Microbial Activity or Physiology
Characterization of the microbial processes/characteristics controlling redox reactions by lowering activation energies
Microbial Population
Identification of the species of microbes that inhabit contaminated solid phase
Aquifer Permeability
The ability of aquifer material to transmit ground water based on measurement of porosity
Bulk Density
Defined as the mass of many particles of the material divided by the total volume they occupy
Source:  Modified from EPA 2002c

Collection of solid phase samples in the field for later mineralogical analysis also requires careful attention and handling in order to preserve conditions as they are in the aquifer. Minerals that are stable under a reducing environment (such as in an aquifer) will be subject to alteration when exposed to oxygen. Removal of pore water from the sample may also cause some transformations. Significant changes in reactivity may result from changes in mineral structure and surface area due to drying at even slightly elevated temperatures. Careful handling is necessary for proper preservation of solid samples for subsequent characterization. Specification of precise procedures for sampling and handling solid-phase samples is beyond the scope of this report but is discussed in EPA 2002c. If it is necessary, however, that solid-phase characterization be included as part of site investigations where ground water is contaminated with uranium, then additional planning and expense will be involved compared to typical current site characterization practices. For example, recommended procedures for sample cores obtained in the field for mineralogical or other solid phase characterization are that they should be immediately capped and frozen, placed in a cooler or freezer, and later thawed under an oxygen-free or inert atmosphere (EPA 2002c). Procedures will vary depending on site-specific concerns and the analyses being performed. It is reasonable to expect that characterization will be necessary at locations within contaminated and uncontaminated areas of an aquifer with the number of samples related to the degree of heterogeneity.

Species Required for Excursion Monitoring

While the focus of this report is on post-restoration monitoring, to ensure completeness of the discussion of constituents requiring monitoring at ISRs, this section briefly discusses excursion monitoring. Monitoring of chemical species that can serve as leading indicators in detecting excursions before the arrival of hazardous constituents is an essential operational feature at ISR facilities. NRC requires use of three such indicators and notes the following (NRC 2003):

      The choice of excursion indicators is based on lixiviant content and ground-water geochemistry. Ideal excursion indicators are measurable parameters that are found in significantly higher concentrations during in situ leach operations than in the natural waters. At most uranium in situ leach operations, chloride is an excellent excursion indicator because it acts as a conservative tracer, it is easily measured, and chloride concentrations are significantly increased during in situ leaching. Conductivity, which is correlated to total dissolved solids, is also considered to be a good excursion indicator (Staub[et al.], 1986; Deutsch [et al.], 1985). Total alkalinity (carbonate plus bicarbonate plus hydroxide) is an excellent indicator in well fields where sodium bicarbonate or carbon dioxide is used in the lixiviant. If conductivity is used to estimate total dissolved solids, measurements will be normalized to a reference temperature, usually 25 °C, because of the temperature dependence of conductivity.

      Calcium, sodium, and sulfate are usually found at significantly higher levels in in situ solutions than in natural ground-water concentrations. The use of cations (e.g., calcium [2+], sodium[+]) as excursion indicators is generally not appropriate because they are subject to ion exchange with the host rock. The use of sulfate may give false alarms because of induced oxidation around a monitor well (Staub [et al.], 1986; Deutsch [et al.], 1985)...  Although water level changes in artesian aquifers are quickly transmitted, water levels are generally not considered good indicators, because water levels tend to have significant natural variability. The applicant may choose to add a non-reactive, conservative tracer to in situ leach solutions to act as an excursion indicator. The applicant is required to provide the technical bases for the selection of excursion indicators.

Case History  -  Evolution of Constituent Monitoring List

Experience at the Crow Butte ISR site in Nebraska provides an example of how the list of ground water analytes required to be monitored evolves during operations. The original NRC license (SUA-1534, dated March 4, 1998) specified in Section 10.3B that the following species be analyzed to establish the baseline (and by inference the parameters to be monitored after the cessation of mining): alkalinity, barium, bicarbonate, boron, cadmium, calcium, carbonate, chloride, chromium, copper, fluoride, iron, lead, magnesium, manganese, mercury, molybdenum, nickel, nitrate, nitrite, pH, potassium, Ra-226, selenium, silica, sodium, specific conductivity, sulfate, temperature, total dissolved solids, uranium, vanadium, and zinc. The highlighted items here are parameters that were included in the license agreement but were not listed in the NRC Standard Review Plan (NRC 2003) and shown in Table 3-3, Column 3 above. In addition, silver, gross alpha, and gross beta are listed in the Standard Review Plan but not included in the Crow Butte license.

Crow Butte subsequently requested that NRC remove alkalinity, bicarbonate, boron, carbonate, chromium, nitrate, specific conductivity, and temperature from the list of monitored parameters, and NRC granted the request as part of License Amendment 11, dated June 26, 2001 (Leach 2001).

Crow Butte's rationale for the requested changes was as follows:

   * Alkalinity, bicarbonate, and carbonate can be evaluated as a single parameter  -  total carbonate.
   * Boron was a constituent of concern because it could affect crop growth. Although small amounts of boron were detected in pre- and post-mining ground water, there is virtually no use of ground water for irrigation in the area, so boron would not affect surface plants.
   * Post-extraction concentrations of chromium in the ground water were below the limit of detection, thus negating the need for further analyses.
   * Specific conductivity is a general indicator of the ionic concentration of the ground water. However, the same information can be derived from measurement of TDS, which is a required parameter.
   * Measurements of nitrate showed that baseline and post-mining results were essentially the same and were a factor of two lower than levels which might give rise to concerns about health effects.
   * Comparison of baseline and post-mining levels of silica showed that the silica concentrations were essentially the same before and after leaching.
   * Crow Butte argued that the uranium recovery process does not affect ground water temperature, and NRC accepted this reasoning.

NRC allowed some constituents to be removed from the required monitoring list because they found that the elements duplicated information provided by other parameters, because they believed that the ISR process had little effect on baseline values, because the quantity present in the ground water was below the limit, or because health effects would be insignificant. All of these determinations were based on site-specific information, regulatory review, and license amendment. EPA did not participate in these determinations.

Formal Approach to Acceptable Restoration

The primary goal of restoration is to return all analytes to the value determined by baseline monitoring. According to NRC practice, this value may be the baseline mean value or some higher value based on the statistical variability of the mean. However, it is well documented throughout this report that restoration of all analytes to baseline conditions is a difficult task, and baseline values may not be re-established for some species even after extensive remediation measures. Addressing the behavior of those analytes that EPA has defined as hazardous should be the focus during restoration (see Table 3-2).

For those analytes with EPA quantitative regulatory limits, as described in Table 3-2, any analyte that is above baseline after restoration but below the prescribed regulatory limit should be acceptable without further action in accordance with EPA requirements. As noted above, this will require reconciliation of certain limits in §264.94 and the MCLs in 40 CFR Parts 141 and 143.

For analytes that exceed the nonmandatory MCLs, as described in 40 CFR Part 143 [Secondary Drinking Water Regulations (SDWRs)], the operator is allowed to demonstrate to the NRC or its Agreement States through geochemical and ground water modeling or other techniques that the measured concentrations do not pose a significant risk to human health or the environment. For example, it might be possible to demonstrate that the ground water transport time to the nearest receptor well is on the order of thousands of years. In the case of high sulfate content, it might be possible to demonstrate through geochemical modeling that the excess sulfate is important in ensuring that radium is removed by precipitation. While iron has a nonmandatory limit of 0.3 mg/L, the existence of high soluble iron (Fe[+2]) may be indicative of reducing conditions that tend to suppress the solubility of uranium. However, according to 40 CFR 264.94, approval of such higher levels requires a rigorous license modification approval process for individual ACLs for hazardous substances in the ground water. To date, this formal approval practice has not been carried out by NRC for ISR licenses.

For analytes not defined as hazardous by EPA (see Table 3-2), but monitored to assess how leaching affects the ground water, it may be possible for a licensee through geochemical modeling to demonstrate to the Regulatory Authority that restoration levels above baseline are acceptable. This would involve analytes such as alkalinity, carbonate, bicarbonate, calcium, potassium, magnesium, silica, and specific conductivity. For example, such modeling might demonstrate that, at equilibrium, the calcium and the carbonate would react to form additional calcite, in turn reducing the potential for solubilizing uranium as a carbonate complex, or the modeling might show that, at the measured carbonate levels, uranium carbonate complexes would not form. Still another possible alternative is that, in solutions with high magnesium concentrations, the complex MgUO2( CO3)32-  can form  (Dong and Brooks 2008).

Table 3-5 summarizes the various analytes that may require monitoring for the following reasons:

   *       May be required based on EPA regulations
   *       May be used for excursion monitoring
   *       May be required to assess the chemical state of the lixiviant during operations and restoration
   *       May be needed for geochemical modeling
   *       May be required by state regulations in addition to EPA requirements

Table 3-5.	Basis for Inclusion of Various Analytes in ISR Ground Water Monitoring Program
                                    Species
                                EPA Regulations
                       Used to Assess State of Lixiviant
                        Needed for Geochemical Modeling
               Required by State Regulations but Not by EPA[a]
                         Used for Excursion Monitoring
Trace and Minor Elements
Aluminum
Yes

Yes

Antimony
Yes

Arsenic
Yes
Yes

Barium
Yes

Beryllium
Yes

Boron

Yes

Cadmium
Yes

Chromium
Yes

Cobalt
Yes

Copper
Yes

Fluoride
Yes

Yes

Iron
Yes
Yes
Yes (total & Fe[+2])

Lead
Yes

Manganese
Yes

Yes

Mercury
Yes

Molybdenum
Yes

Nickel
Yes

Selenium
Yes
Yes

Silver
Yes

Strontium

Thallium
Yes

Tin
Yes

Uranium
Yes
Yes
Yes

Vanadium
Yes &V2O5

Zinc
Yes

Common Constituents
Alkalinity

Yes
Yes

Yes
Ammonia

Yes
Yes (NH[4+])
Yes

Bicarbonate

Yes
Yes
Yes

Calcium

Yes
Yes
Yes

Carbonate

Yes
Yes
Yes

Chloride
Yes
Yes
Yes

Yes
Magnesium

Yes
Yes

Nitrate
Yes
Yes
Yes

Nitrite
Yes

Phosphate

Yes

Potassium

Yes
Yes
Yes

Silica

Yes
Yes

Sodium

Yes
Yes
Yes

Sulfate
Yes
Yes
Yes

Sulfide
Yes
Yes
Yes

Chemical and Physical Indicators
Anion/Cation Balance

Yes

Sodium Adsorption Potential

Specific Conductivity

Yes
Yes
Yes
Yes
pH
Yes
Yes
Yes

Redox Potential

Yes

Total Dissolved Solids
Yes
Yes
Yes

Yes
Temperature

Yes

Turbidity

Yes

Dissolved Oxygen

Yes

Dissolved Organic and Inorganic Carbon

Yes

Eh

Yes

Radiological Parameters
Gross Alpha
Yes

Yes
Yes

Gross Beta

Gross Gamma

Lead-210

Polonium-210

Radium-226
Yes + Ra-228
Yes
Yes

Radon-222

Radium-228

Yes
Yes

Thorium-230

Thorium-232

Beta + Gamma
Yes

a  -  Texas and/or Wyoming

It should be emphasized that Table 3-5 provides generic lists that will need modification on a site-specific basis. This is particularly true of the geochemical modeling parameters, which will vary depending on the type(s) of modeling that is planned or required.
Technical Considerations for ISR Ground Water Monitoring

Monitoring wells within an in-situ mining area and site vicinity serve vital functions necessary for efficient uranium recovery with minimal adverse environmental impacts. Proper monitor well placement and data collection from these wells ensure that the aquifer constituents are detected and then restored to pre-mining levels. Without adequate placement of monitoring wells and proper data collection, which includes consideration of sample frequency and sampling time frame, mine operators and regulators (1) may not detect excursions of lixiviant outside the mining area during operations, and (2) may not be able to confidently determine whether the impacted aquifer needs further restoration or has been restored to its pre-mining state or to predetermined conditions specified by regulators.

This section focuses on technical considerations for ground water monitoring through all operational phases of an ISR facility. Because the monitoring goals and practices depend on the characteristics of the ore body, this section begins with a discussion of geographic, geologic, and chemical characteristics typical of uranium deposits suitable for leaching.

Uranium Geology

The geographic areas that are considered to be potential resources of uranium in the United States are shown in Figure 4-1. The principal regions of uranium recovery by ISR are the Wyoming basin, the Colorado Plateau, and the Gulf Coastal Plain of Texas (Figure 4-2). The southern Black Hills in South Dakota and northeast Colorado/western Nebraska within the Great Plains region also contain sedimentary uranium deposits amenable to ISR. Furthermore, exploration is ongoing elsewhere in the U.S. that could expand the extent of production to other states, such as Michigan or Alaska, and to types of uranium deposits (other than roll-front) that could be extracted through ISR methods.

                              (Source: DOE 1980)

Figure 4-1.	Uranium Resource Areas of the United States

                              (Source: NMA 2007)

Figure 4-2.	Pending, Licensed, and Active ISL Operations

Formation of Uranium Containing Ore Deposits

Based on the shape of the ore body and relationship to the depositional or structural environment, sandstone uranium deposits can be subdivided into three types (these may be gradational into each other): tabular, roll-front, and remnant-primary sandstone (Hou 2004). Tabular and roll-front mineralized bodies form along the contact of sand and intercalated clay horizons and at paleochannel margins (Figure 4-3), while remnant-primary sandstone deposits may occur in sandstones adjacent or vertically stacked along a permeable fault zone (Figure 4-4). Precipitation of uranium minerals in most tabular deposits is thought to begin shortly after sedimentation and burial. Mineral detritus and rock fragments derived from weathered bedrock are deposited, along with channel sediments. The uranium is leached under oxidizing and slightly acidic conditions and is mobilized in ground water moving through the sediments, with mineralization commonly accompanying diagenesis of the sediments.

                              (Source: Hou 2004)
Figure 4-3.	Three-Dimensional Depiction of Uranium Ore Deposited in Paleochannels

                               Source:  NRC 2006
Figure 4-4.	Schematic Diagrams of the Different Geometries for Tabular, Roll-front, Fault Displaced, and Remnant Ore

In Nebraska, New Mexico, Texas and Wyoming, the general geology and formation of roll-front deposits is nearly identical with the host rock being relatively near-surface sandstone that was deposited in fluvial or lacustrian environments (NMA 2007). Aquifers and lithologic units underlying topographically high areas, such as ridges, are recharged by rainfall that has elevated oxygen and carbonic acid, which solubilizes low concentrations of uranium (and other metals) from the soils and rocks. The mobilized uranium moves deeper into the formation into areas where the ground water is being reduced by organic carbon, carbonized fossil wood, pyrite and/or hydrogen sulfide gas (URI 2006; Devoto 1978). As the oxidized ground water and dissolved uranium move into the reduced zone, the uranium is precipitated in its reduced mineral form and removed from solution (Figure 4-5). Therefore, the roll is located at the interface between the reduced and oxidized facies in the paleoaquifer (Devoto 1978).

                              (Source: NMA 2007)

Figure 4-5.	Conceptual Cross-Section of Uranium Roll-front Deposits

At the reduction-oxidation (redox) interface, uranium (and other metals) will become concentrated and form an ore body within the sandstone matrix. The redox interface may extend laterally for miles, consisting of a string of ore bodies of variable size and cross-sectional shape, but often the interface is only a few tens of feet in the down gradient direction of ground water flow.

Figure 4-6 illustrates an idealized model of uranium roll-front mineralization in which existing mineral phases control the solubility of constituents and, therefore, their concentrations in the ground water. Down gradient of the richest uranium ore is a zone associated with abundant pyrite or marcasite (Ore-Stage Pyrite Zone), and is deposited at the interface between the oxidized (up gradient) Ore-Stage Uranium Zone and the reduced (down gradient) unaltered reduced sandstone. Up gradient of the Ore-Stage Pyrite is a zone that is less reducing and ore grade deposits of uraninite are present. Futher up gradient is the alteration zone, which grades into the oxidizing conditions of the hematitic core. The oxidized sandstone on the concave side of the roll front is generally reddish to light yellow, due to the oxidation of iron disulfides to ferric oxide and hydroxide minerals and, compared with the reduced sandstone on the convex side, contains very little or no uranium minerals, carbonized fossil wood, calcite or pyrite (Misra 2000). The uranium mineralization is hydrologically confined by an upper and lower confining layer of shale or mudstone. A range of permeabilities is commonly observed within the host sedimentary unit because of spatial differences in depositional environments (URI 2006). An excellent discussion of the geochemical processes controlling the mobility of uranium, radium and associated metals is presented in Demuth and Schramke (2006).

                             (Source: Devoto 1978)

Figure 4-6.	Conceptual Model of Uranium Roll-front Deposit

Leachable uranium deposits are found in sandstones that have been deposited in intermontane basins, along mountain fronts, and in near-shore marine and deltaic environments. The deposited sediments were created as a complex and heterogeneous rock sequence that may be thicker than 2,000 meters (Rojas 1989). This rock sequence can be composed of a number of water-bearing units separated by confining units. The water-bearing unit containing the ore body is separated (at least locally) from other water-bearing units above and below.

Zones of uranium mineralization follow a general trend of drainage channels. Individual ore bodies in sandstone lenses rarely exceed a few hundred meters in length (Rojas 1989). These are typically "roll-front" deposits that are formed when oxygenated water enters the sandstone aquifer by local recharge dissolving the uranium. Deeper into the aquifer, the oxygen becomes depleted, and typically a convex curved redox interface is formed, with reducing conditions on the down gradient side and oxidizing conditions on the up gradient side. Contact with carbonaceous material and pyrite can cause the reducing conditions.
Freshly precipitated uranium along with uranium in the arkosic sandstone minerals is continuously dissolved by oxygenated ground water and displaced further down gradient (Rojas 1989). As the uranium comes in contact with the reducing conditions down gradient, an economically recoverable deposit of uranium may eventually be formed. The term "roll front" is used because over time, the redox interface rolls down gradient as more oxygen is transported into the aquifer. The inner contact of ore and altered sandstone is generally sharp, whereas the uranium concentration on the reduced side of the interface is gradational.
The depth of the ore body varies significantly from site to site. Ore bodies in the Texas Gulf Coastal Plain tend to be shallow-lying, while those in the Wyoming Basin show considerable variability, as illustrated by the following:
   * Burns/Moser TX (Lower Oakville)  -  230 to 280 ft (http://www.wise-uranium.org/udusail.html#KINGSV).
   * Clay West TX (Lower Oakville)  -  250 to 400 ft (http://www.wise-uranium.org/udusail.html#KINGSV).
   * Crow Butte (Basal Chadron)  -  400 to 800 ft (NRC 1998).
   * Dewey-Burdock (Lakota and Fall River)  -  500 to 800 ft (Dewey); 300 to 500 ft (Burdock) (SRK 2011).
   * Irigaray WY  -  100 to 300 ft (Irigary 2004).
   * Palangana TX (Goliad Formation)  -  230 to 390 ft (http://www.wise-uranium.org/udusail.html#PALANGANA).
   * Smith Ranch/Highlands, A-Wellfield WY (20-Sand)  -  530 ft avg (Kearney 2004).
   * West Cole TX (Soledad member of Catahoula Formation)  -  225 to 270 ft (http://www.wise-uranium.org/udusail.html#WESTCOLE).
   * Zamzow TX (Oakville sand)  -  35 to 225 ft (http://www.wise-uranium.org/udusail.html#ZAMZOW).

It is expected that deeper lying ore bodies will be less susceptible to seasonal variations in ground water chemistry associated with areal recharge than shallower ore bodies.
Aquifer Exemption Requirement

An aquifer exemption is required if the proposed injection zone is an underground source of drinking water. Applicants submit a Petition for Aquifer Exemption to the state for review. Although the state reviews the aquifer exemption petition, it cannot grant the final aquifer exemption. After the state makes a decision on the aquifer exemption petition and it is duly public noticed, the state makes a recommendation of the decision to EPA. EPA makes the final decision regarding aquifer exemptions.

As part of the aquifer exemption Petition, the Applicant must evaluate potential impacts on the water resources in the vicinity of the proposed mine. This evaluation generally involves water quality and use surveys within at least a 2-mile radius of the site. Water level measurements and ground water samples collected during this phase of the application process often provide some of the earliest baseline data.

Establishing Baseline Conditions

Before initiating leaching activities, knowledge of the aquifer baseline characteristics is needed to help determine restoration goals for the post-mining phase. Pre-mining monitoring and testing wells are installed to collect data that define the ground water flow regime through the extraction zone and surrounding areas and determine the chemical characteristics of the ground water. Monitoring wells should be installed at well locations up gradient, down gradient, and tangential to the proposed ISR field, as well as within the "ore-zone." Well placement should be designed to measure all potential "escape" pathways for introduced constituents and mobilized metals, as well as to provide data to determine the choice and effectiveness of aquifer restoration actions. Selected up gradient and down gradient wells outside the wellfield should be continuously monitored throughout all phases of the operation illustrated in Figure 3-1. This will provide data that may assist in interpreting changes in ground water chemistry within the wellfield during steady state and long-term stability monitoring and possibly to detect seasonal variations in ground water chemistry in shallow deposits.

The design of the monitoring network is largely a site-specific decision predicated on a thorough knowledge of the ground water flow regime and the effects of the injection and withdrawal rates on the flow system behavior. A system of wells should be emplaced to monitor the horizontal and vertical ground water velocity and flow paths, the ground water chemical conditions, and the potential for hazardous constituents to migrate beyond the ISR mine field, both within the mined aquifer and through transmission of contamination to overlying and underlying aquifers. These areas beyond the ISR may experience contamination from the mined area.

The following components and parameters need to be considered in establishing baseline site characteristics (see Section 3.5, and particularly Table 3-3, for more details on analytes to be monitored in ground water):

  (1) Hydrogeochemical Conditions  -  Eh (including redox-sensitive couples), dissolved oxygen, pH, major ions, TDS, carbonate alkalinity, pCO2, radioactive constituents, colloids, organic constituents, hydrogen sulfide, trace elements (to be compared against post-restoration measurements).
  (2) Concentrations of those constituents listed in 40 CFR Part 192  -  arsenic, barium, cadmium, chromium, lead, mercury, molybdenum, nickel, Ra-226 and Ra-228, selenium, silver, uranium, etc.
  (3) Uranium Ore Deposit Types and Oxidation States  -  The site-specific and varied diagenic processes that formed the uranium deposits will determine how ISR operations will affect baseline conditions and which restoration approach is likely to be most effective. Knowledge of these processes can be used as a framework in estimating the time needed for the aquifer to reach baseline conditions once post-mining restoration and monitoring are initiated.
  (4) Hydrogeologic Setting  -  Pre-mining ground water velocities (unstressed), flow paths, and solute transport time frames. A reliable and defensible characterization survey of the ISR site requires thorough core and water sampling from all monitoring wells and exploration boreholes. Sufficient data must be collected before the mining activity commences to understand when baseline levels have been reached after mining. Aquifer pump/stress tests and core sample analysis will determine aquifer characteristics within and surrounding the ore body and be used to determine:
         a. Host rock and ore zone permeability, porosity, storativity, and thickness
         b. Whether more monitoring wells are needed for postclosure activities and to assess the time frame of postclosure monitoring
         c. Time frame estimates after mining has ceased, in order for the system to reach pre-ISR conditions
         d. Recharge/discharge points
         e. Impermeable layers above and below the ore zone
         f. Proximity to ground water barriers
         g. Proximity to surface water bodies  -  natural or manmade

Sampling the ground water may require special sample collection techniques, depending on the chemical constituents of concern. For major ions and some other chemical species, sampling may be relatively simple, in that these species are not susceptible to change upon exposure to atmospheric conditions. For species that are susceptible to re-equilibration in response to atmospheric conditions, particularly redox-sensitive species and the carbonate-bicarbonate system, water sampling may require that the sampled interval be "packed off" within the well and water samples taken in containers, which were placed within the sealed intervals prior to the "packing-off" and left to equilibrate in the flowing ground water for a period of time before removal. Redox-sensitive couples typically examined include ferrous (II)/ferric (III) iron, and the arsenic (III) /arsenic (V) couple. In addition to dissolved oxygen levels, these couples can produce important characterization of the redox conditions in the production zone before, during, and after the leaching process and can also be important in determining the effectiveness of various aquifer restoration processes.

In addition, uranium speciation is strongly affected by pH and carbonate concentrations in the ground water, which, in turn, are a function of the pCO2 in the ground water. Exposure of the ground water sample to the atmosphere can result in the escape of CO2 and re-equilibration of the uranium-carbonate system due to the out-gassing. Then the uranium concentrations in the reequilibrated water would not reflect the actual speciation in situ, and, consequently, could result in misleading calculations of uranium speciation and solubility constraints in the subsurface waters. Because of these effects and their relative importance to characterizing the in-situ ground water chemistry, monitoring water chemistry in and around the "ore body" may well require differing sampling methods.
Figure 4-7 illustrates the spatial variability that exists between the ore zone and its surroundings. The figure summarizes results for pre-mining sampling of excursion monitor wells (designated as EM) and production zone wells (EMP) for Wellfield H-E at the Highland uranium project in Wyoming (Hoy 2006). Within the production zone, most of the baseline wells showed elevated concentrations of uranium and radium as compared to the excursion monitor wells located a few hundred feet from the production zone wells. Within the production zone, radium (Ra-226) was generally >100 picocuries per liter (pCi/L), while at the excursion monitor wells, Ra-226 was generally <5 pCi/L. Uranium was generally >0.03 mg/L in production zone baseline wells, while it was always <0.030 mg/L in the baseline monitor wells. The median uranium concentration was about 0.04 mg/L within the production zone and about 0.015 mg/L in the monitor ring. It is possible that different geochemical conditions within the ore zone, as compared to the host rock, precluded the movement of uranium and radium down gradient. (See also Figure 4-4 and Figure 4-6.)

The wide variablitity and sharp concentration gradients of background uranium concentrations observed at the Rosalita ISR project are shown in Figure 4-8 (URI 2010).  The isolated areas of elevated uranium concentrations within the ore body present a challenge to establishing statistically representative background concentrations as described below in Section 4.2.1.

Recent studies (Hall 2009; NRDC 2012), as well as administrative hearings for the Goliad ISR aquifer exemption that took place in 2010, have focused attention on a lack of guidance on statistical establishment of background levels for hazardous constituents in ground water, and selective use of well data, which could distort the chosen background levels for restoration. Use of statistics in setting these numbers is discussed further in Section 7 of this report.

       Source: Hoy 2006

Figure 4-7.	Well and Production Zone Locations and Baseline Concentrations of TDS, Uranium, and Radium  - Wellfield H-E

                              (Source: URI 2010)

Figure 4-8.	Baseline Uranium Concentrations at the Rosita ISR Facility

Variability in Baseline Measurements

The two principal sources of variability in ground water quality data are "natural" variability and variability that results from the network design and operation. The components of natural variability arise from temporal or spatial variability related to hydrologic processes such as pumpage, recharge, or discharge, as well as influences of these processes on the release and distribution of chemical constituents from a variety of chemical sources. The sources may be natural mineral assemblages, precipitation, and percolation through the unsaturated zone, in addition to numerous point (e.g., ISR injection wells) and nonpoint sources (e.g., agricultural application) of chemical contaminants. In general, natural sources of variability cannot be controlled, although they may be quantified through an effective monitoring network design.

Variability in water quality data may also arise from the sampling and analytical components of the monitoring network design. Sampling variability includes variations due to the selection of the locations and construction of sampling points in space, sampling frequency, well purging, and the execution of the sampling protocol. The sampling protocol consists of the procedures used to collect, handle, preserve, and transport water samples to the analytical laboratory. Several authors have evaluated elements of the sampling protocol for their relative contributions to variability or errors in water quality data (Barcelona et al. 1983, 1984, 1985a, 1985b; Garske and Schock 1986; Barcelona and Helfrich 1986).

Analytical variability in water quality data arises principally from the errors involved in analytical methods and the subsequent data processing steps. These errors can be controlled once suitable water quality indicators or chemical constituents have been selected and a thorough data quality assurance/quality control program has been designed and executed.

Optimization of sampling frequency in ground water quality monitoring networks should provide sufficient sensitivity for chemical constituent detection and adequate characterization of average chemical conditions. This should be accomplished with a minimum number of sampling times, but this sampling should provide important information for determining the adequacy of restoration and necessitates a high degree of confidence. This may then require more lengthy sampling periods.

The hydrology of the ground water system will influence the impact of the sources of variability mentioned above. Although aquifer hydraulic properties may not vary significantly at a single measurement point over time, spatial variability may be substantial. This is a very active area of research with application to monitoring network design (Christensen and Doherty 2008, Meyer et al. 2007, Cooley 2004, Doherty and Hunt 2009). Results of such research will be important for determining the efficacy of restoration efforts and regulatory decisionmaking about the long-term stability of the restored wellfield.

Temporal and spatial variations in ground water elevation may affect ground water flow rate and the direction of movement. Such changes may influence the quality of the ground water in the vicinity of a sampled well by directing water from a different up gradient area or changing the velocity with which dissolved constituents move along a flow path. Examples abound in the literature detailing ground water response (i.e., elevation change) to a wide variety of influences. In addition to seasonal fluctuations produced in response to short-term (i.e., months to 1 year) events, ground water levels also reflect changes in long-term (i.e., years to decades) conditions. Natural and artificial (man-induced) influences can cause changes in ground water elevation, including natural (e.g., rainfall and snowmelt) and artificial recharge (e.g., pipe leaks, injection wells) and natural (e.g., evapotranspiration) and artificial discharge (e.g., pumping). These variations may be important in situations where multiple ore zones are mined sequentially, and decisions on when and where restoration efforts are to be carried out and regulatory decisions on these efforts must be made.
Ground water quality monitoring networks are designed for a number of purposes, including ambient resource studies, contaminant detection and assessment, contaminant source evaluation, and research investigations. The effective design of virtually any such network, regardless of purpose, depends on knowledge of the hydrogeologic system of interest, an indication of the presumed contaminants or preferred water quality indicators, and an assessment of the relative contributions of sources of variability. These aspects of monitoring network design have been addressed in the literature (Todd et al. 1976, Sanders et al. 1983, Moss et al. 1978, Liggett 1984, Liggett 1985, Gillham et al. 1983). The common recommendation in these works is that background information must be supplemented with the results of a preliminary sampling to progressively refine the network design to account for error and variability in the chemical results.

Variability in the analytical results for particular ground water chemical constituents may arise from "natural" causes such as nonhomogeneous spatial distributions of the constituents and temporal variability in recharge. Variability may also arise due to network design-related factors such as well design, sampling devices, and sampling protocols. The apparent sources of variability in water quality data, which are often attributed to natural (i.e., temporal and spatial) effects, include hydrologic transience, the fluctuations in contaminant source strength and composition and the interactions between reactive chemical, biochemical, and mineral constituents in recharge water and ground water. A detailed understanding of the interdependence of hydrologic, biological, and chemical processes in the subsurface is limited. However, it may not be necessary to fully understand the relationship between these processes, contaminant sources, and the resultant chemical distributions in order to establish representative background concentrations, monitor potential contaminant releases (e.g., excursions), and predict remediation times.

The temporal and spatial variability, which is observed in water quality results over time at discrete monitoring points, is the result of the processes noted in the preceding discussion, as well as the sample collection and measurement errors inherent to network design and operation. This variability, or "noise," in the data encompasses the stochastic distribution of possible values for particular chemical constituents and the effects of both determinate (i.e., systematic) and indeterminate (i.e., random) error. Determinate error can be measured as inaccuracy or bias if the "true value" is known. Indeterminate error can be estimated as imprecision or irreproducibility if enough replicate determinations can be made to faithfully estimate the mean or the "true" value. In practice, determinate errors can be estimated and controlled only by careful quality assurance/quality control measures exercised over appropriate sampling and analytical procedures because the true value in environmental distributions is unknown, and some disturbance of the subsurface is inevitable in ground water quality work. Identifying and controlling these design-related errors are described in several sources (Barcelona et al. 1983, Barcelona et al. 1985a, Barcelona 1988, Barcelona et al. 1986, Barcelona and Gibb 1986, Puls and Barcelona 1996, and EPA 2010d).

Statistical measures of short-term temporal variability include seasonal effects (e.g., consequences of recharge or temperature effects), which can be assigned to the seasons of the year, periodic effects (e.g., consequences of anthropogenic contaminant sources or pumping effects), and serial correlation or dependence effects, which tend to make data points following maxima or minima in temporal data series higher or lower, respectively, than one would attribute to random processes alone. Trends in data, on the other hand, are long-term variations compared to those that may occur within a hydrologic year (Porter and Trautman 1984). This categorization of temporal effects is somewhat artificial in that the combination of seasonal, periodic, or correlative components may result in a water quality time series that cannot be differentiated quantitatively. Because of this factor, the identification of short- or long-term trends in water quality is conditional on some knowledge of the proximity of the sampling location to the location and time of chemical release, as well as the statistical characteristics of ground water quality variables.

Statistical measures of temporal variability have been reviewed by Loftis et al. (1986), Montgomery et al. (1987), and Harris et al. (1987). They cite numerous examples of both short- and long-term temporal variability, which supplement the earlier reviews of Porter and Trautman (1984) and Colchin et al. (1978). The Air Force Center for Environmental Excellence (AFCEE) has also developed two computer software packages that employ sophisticated geostatistical/ statistical analysis algorithms to facilitate the optimization and termination of current long-term monitoring (LTM) programs (Aziz et al. 2006). The Monitoring and Remediation Optimization System (MAROS) software assists in optimizing monitoring networks both spatially and temporally.

A recent development in MAROS is the addition of the Modified Cost-Effective Sampling (CES) Method, which is designed to set the sampling frequency for a well based on the analysis of time series concentration data at each sampling location, considering both recent and long-term trends of the concentration data. In contrast to the spatially based Delaunay Method originally used in the MAROS sample location optimization, the Modified CES Method is based on temporal analysis. Its use, combined with the Delaunay Method and trend analyses, leads to a comprehensive process of sampling optimization. The second program developed by AFCEE is the geostatistical temporal/spatial (GTS) optimization algorithm, which is a robust and powerful computer application designed for use by mid-level geostatisticians. GTS software can optimize individual input data sets for LTM networks containing analytical data from more than one aquifer or hydrogeologic unit (MAROS can optimize only a single hydrogeologic unit). Additional technical information, user's manuals, and executable computer code for MAROS and GTS can be obtained from the AFCEE website. Section 7.0 provides a more detailed discussion of the statistical approaches to address both spatial and temporal variability.

A sufficiently high sampling frequency (i.e., quarterly) is required to statistically distinguish seasonal effects from those of serial dependence or autocorrelation (Loftis et al. 1986). In many instances, limited ground water quality data sets, combined with quality variables that are frequently not normally distributed, constrain the use of simple parametric statistical tests of significance to compare means or identify trends (Montgomery et al. 1987).

The adoption of a minimum sampling frequency of "quarterly" can be useful during the characterization phase of ground water monitoring to evaluate seasonality, rate of change and variability, especially for fast-moving plumes. However, for more stable plumes, the default adoption of quarterly monitoring may be determined to be unnecessary if long-term monitoring can demonstrate no harm by utilizing longer intervals. Conversly, if variability in the ground water compositions is relatively high and the concentrations of the analyte of concern over time is changing slowly, more frequent sampling may be necessary to define the presence or absence of trends with a reasonably high degree of confidence (see Sections 7.7 and 7.8 for an example of these situations). The use of sampling intervals ranging from quarterly, semiannual, annual, to biennial levels is very common in long-term ground water monitoring (Air Force 1997; NFESC 2000).
Spatial and temporal variability in ground water quality may affect the sensitivity of contaminant detection and the estimation of mean chemical concentrations. To some extent, spatial chemical data collected at discrete points along a horizontal flow path may be quite similar to data collected over time at a single point in the path. This supposition depends, of course, on a number of factors related to hydrologic conditions, as well as the nature of the chemical source, reactivity, and mobility constraints. The substitution of spatially intense samples for use in temporal variability studies could be applied to studies of ambient concentrations of conservative chemical species for regional assessments in unique hydrologic situations.

Extraction Operations Phase

During the ISR mining operations phase, wells are placed in the active ISR treatment zone, fringe zone (wells at the perimeter of the ISR mine), and outside the affected areas (Figure 4-9). The recovery wells (shown as red squares in Figure 4-10) are pumped at a slightly higher rate than what is reintroduced into the aquifer through the injection wells (i.e., blue squares). The injection creates ground water mounds around the injection wells (e.g., 98-foot contour) and the pumping forms ground water depressions around the pumping wells (i.e., multiple concentric circles of lower elevation). The net effect of this pumping/injection is the formation of capture zones (Figure 4-11) in which the water/lixivant introduced through the injection wells (blue dots in Figure 4-11) flows to the pumping wells (red squares in Figure 4-11) and is withdrawn.

The functions of a monitoring system during the extraction phase include:

  (1) Monitoring the extraction process to determine uranium recovery rates within the mining zone.
  (2) Assessing the mass-balance of the lixiviant fluids.
  (3) Monitoring excursions beyond the ore zone (both within the ore-bearing aquifer and in overlying and underlying aquifers).
  (4) Monitoring ground water chemical composition in wells surrounding and down gradient of the extraction field.
  (5) Monitoring the chemical composition of ground water up gradient of the extraction field to determine if these waters are chemically stable over the course of the extraction effort.

                              (Source: NRC 2006)

Figure 4-9.	Schematic Diagram of a Wellfield Showing Typical Injection/Production Well Patterns, Monitoring Wells

                        (Source: Gard and Mahoney 2012)

Figure 4-10.	Example of  MODFLOW Predicted Potentiometric Surface during Active Mining

                        (Source: Gard and Mahoney 2012)

Figure 4-11.	Example of  MODPATH Predicted Flow Paths During Active Mining

Post-extraction Phase

The post-extraction monitoring system should be designed to assess the effectiveness of the remediation process, assess when final remediation objectives have been met, and assure that the affected aquifer is at steady state, long-term stability has been demonstrated,  and the site is ready for decommissioning. A system of wells located in the active treatment zone, as well as outside the boundary of the affected area, is required to monitor the horizontal and vertical ground water velocity and flow paths in the vicinity of the ISR site. The functions of a post-mining monitoring system include:

  (1) Measuring ground water chemical constituents to determine if and/or when the ground water chemistry has returned to pre-ISR (baseline) compositions.
  (2) Determining if additional chemical components have been added to the ground water as a product of the extraction process (e.g., metals mobilized with the uranium).
  (3) Demonstrating when the ground water chemistry has reached "stable" levels (i.e., statistically equivalent compositions over an extended time period).
  (4) Determining if post-mining restoration levels for ground water constituents have been met.
Factors Affecting Post-mining Time Frames and Wellfield Stability

Post-restoration monitoring must be of sufficient duration to ensure that once ground water chemistry appears to have reached acceptable restoration levels, these levels are at steady state and the ground water system is at equilibrium. Steady-state restoration levels are not just for uranium, but also for other hazardous constituents that may have been mobilized by ISR operations, such as radium, manganese, and selenium. Chemical speciation and solubility, as well as natural attenuation processes, must be understood in order to determine when the affected aquifer has reached a steady-state condition. Both geochemical and advective-dispersive modeling should be used as tools to assist in designing the most effective means of restoring the aquifer. The approach that is generally taken to couple the geochemical processes with ground water flow and contaminant transport is to first use MODFLOW to create a calibrated flow field that reasonably resembles the actual field conditions. Once the flow conditions are established, a transport code (e.g., MT3D) is applied to simulate simple geochemical behavior (e.g., sorption). A more complex geochemical code is then applied (e.g., PHT3D) to simulate reactive transport and surface complexation.

The environmental chemistry of uranium is largely dictated by its oxidation state; the solubility, and therefore mobility, of uranium is greatest when it is in the U(VI) state. Because different chemicals may be used during the restoration process than were used during ISR operation, the chemical form of uranium or other hazardous constituents may differ during restoration. Since most of the available computer codes do not have a method of calculating reaction rates, these reactions may be unexpected, and the monitoring program must last long enough to accommodate such unexpected conditions. There are a few sophisticated codes, however, that  allow the reactive transport processes to be coupled to the ground water flow regime, such as PHAST or PHT3D. These codes have intensive data requirements, and EPA recognizes the importance of understanding the geochemical processes and has entered into a corporative agreement with the U.S. Geological Survey under a Regional Applied Research Effort (RARE). The main objective of this work is to provide a predictive model that describes the ground water flow and geochemical changes along with longer-term transport of dissolved constituents during and after the uranium ISR mining process (see also Section 4.3.7 below).

One of the most important factors affecting restoration times is that there may be significant quantities of uraninite remaining after mining is complete (Figure 4-12). Post-mining sampling and core analysis, as well as more complete tracking of the water balance and uranium mass removal rates during mining, would assist in designing a more effective restoration.

Another factor affecting the post-monitoring time frame and wellfield stability is the form of remediation used. Pump and treat techniques are common remediation approaches. One consideration, however, are the large volumes of water required when pump and treat technologies are used to restore the aquifer to pre-mining conditions. Issues related to both water quality and quantity have resulted in EPA denying the Applicants Aquifer Exemption Request until additional work is performed at the Goliad mine in Texas to demonstrate that nearby water resources will not be adversely impacted for the next 75 years (EPA 2012).

                        (Source: Gard and Mahoney 2012)

Figure 4-12.	Example of  PHT3D Predicted Post-mining Uraninite Concentrations

Geochemically based methods are promising as potential remedial alternatives, in that significantly less water could be used during site restoration since strong reducing agents (e.g., hydrogen sulfide) are injected to induce chemical precipitation of the uranium from solution.  Monitored natural attenuation is another response action that may be effective in certain situations. Natural attenuation processes include a variety of physical, chemical, and biological processes that can act to reduce the mass, mobility, volume, or concentration of contaminants in ground water. Attenuation mechanisms important at ISR sites are described in Table 3-4 and include processes such as pH buffering and acid neutralization, adsorption at the mineral-water interface, mineral precipitation, dilution, and biological activity.
Pump and Treat

Alternative approaches included in pump and treat remediation are:

   * Ground Water Transfer  -  This involves transferring ground water between the wellfield starting restoration and another wellfield where uranium leach operations are beginning. No liquid effluents are generated as water is transferred between one wellfield and another.
   * Ground Water Sweep  -  Injection of lixiviant is stopped, and the contaminated liquid is pumped from the leaching zone via all of the injection and production wells. Fresh ground water flows into the leaching zone from the outside, which displaces lixiviant in the pore spaces. Typically, an ion-exchange system is used to process the sweep water, which is disposed of either in evaporation ponds or via a deep injection well in accordance with the site permit. The pumping rates are site specific, and the duration and volume of water removed depend on the aquifer affected by the ISR. Due to heterogeneities in the aquifers, ground water sweep alone may be insufficient and uneconomical for complete restoration. In addition, ground water sweep may create oxic conditions when up gradient waters enter the ore zone, making it more difficult to re-establish chemically reducing conditions.
   * Reverse Osmosis (RO)  -  To return ground water to baseline conditions, it is usually necessary to remove contamination from the mined zone water while minimizing disposal of waste liquids. RO, which involves passing the water being restored through pressurized, semipermeable membranes, is a common way of treating ground water. The RO treatment results in clean water or permeate that can be reinjected into the aquifer and brine that is water with concentrated ions. The brine is usually sent to an evaporation pond, injected into deep disposal wells, or dried (using an evaporator) for subsequent disposal at a licensed facility.
   * Permeate Injection  -  Many aquifers are characterized by porosity where ground water with decreased mobility resides in regions of moderate to low permeability. It is very difficult to remove all of the lixiviant and associated contamination from this portion of the ground water, which will act as a source of contaminants, even after long periods of pumping and treating.

Geochemically Based Techniques

Another component of aquifer restoration is accomplished by establishing a chemical environment that alters the solubility of dissolved constituents. Chemicals may be added to injection water in the latter stages of restoration to assist in re-establishing baseline conditions. These methods typically invoke chemical reactions in which some species are reduced to a lower valence state. Addition of reagents such as hydrogen sulfide and sodium hydrosulfide tend to convert dissolved species such as uranium, selenium, molybdenum and arsenic to a lower valence state with attendant reductions in solubility (NRC 2007, p. 17).

Monitored Natural Attenuation

Monitored natural attenuation (MNA) refers to the reliance on natural processes to achieve site-specific remediation objectives within a reasonable time frame. These processes include biodegradation, dispersion, dilution, sorption, and volatilization; radioactive decay; and chemical or biological stabilization, transformation, or destruction of contaminants. The overall impact of MNA at a given site can be assessed by evaluating the rate at which contaminant concentrations are decreasing either spatially or temporally.

However, USGS has suggested a note of caution regarding the efficacy of natural attenuation (NRC 2007, p. 17):

      Because the ore zone typically is under chemically reducing conditions prior to mining, it has frequently been argued or assumed that the natural reducing conditions will return over a period of time. However, it is difficult to predict how much time is required or even if the reducing conditions will be returned via natural processes. The mining disturbance introduces a considerable amount of oxidant to the mined region and may oxidize all the pyrite associated with the original ore zone.

EPA has prepared a technical resource document (EPA 2007a and 2007b) that presents a four-tiered assessment of MNA as a viable response action for selected metal, metalloid, and radionuclide contaminants encountered in ground water. The assessment involves the following: (1) demonstrating contaminant sequestration mechanisms; (2) estimating attenuation rates; (3) estimating attenuation capacity of aquifer solids; and (4) evaluating potential reversibility issues. EPA has a number of guidance documents that pertain to MNA (e.g., EPA 1999b) and specifically to radionuclides (EPA 2010a).

Section 6.4 of this report presents additional details on MNA.

Modeling

Objectives and Conceptual Model Development

Modeling of ground water flow, contaminant fate and transport, and chemical speciation is often utilized to predict the spatial and temporal behavior of the hydrogeochemical system. Ground water flow and geochemical modeling is commonly implemented to assist in meeting different objectives during each phase of the ISR process as described below:

Pre-Mining

   * Establish background concentration of important ground water constituents and determine geochemical constraints that may control contaminant concentrations, e.g., solubility constraints.

Active Mining

   * Determine spacing of injection and pumping wells.
   * Optimize the monitoring well spacing to detect injection fluid excursions into non-mined aquifer zone(s).

Aquifer Restoration

   * Evaluate changes to hydraulic conductivities, gradients and flow directions.
   * Estimate the number of pore volumes needed during site remediation activities to adequately reduce contaminant concentrations.
   * Estimate remediation times.
   * Predict potential off-site impacts on water levels and quality.

Post-Remedial Monitoring

   * Evaluate the long-term stability of the contaminants within the mined area, as well as any that have migrated further down gradient.
   * Establish a specific period of monitoring for ISR facilities once uranium extraction operations are completed.

Prior to starting remediation of in-situ leach mining sites, modeling can be used to predict the behavior of the ground water system during and after ground water restoration. To make such a prediction, a conceptual model must be formulated that includes the most important physical and geochemical processes that are occurring in the system at the end of restoration and that will occur in the system in the future. In formulating such a model, three fundamental processes must be included: ground water flow, solute transport, and chemical reactions. Secondary processes such as microbial degradation may also be considered. Microbial action may not be important during restoration since the ground waters are being moved through the system rather quickly, but may have a more important role when the pumps stop and long-term stability is evaluated. In addition, the initial conditions of certain physical and chemical variables in the system must be specified, as well as any known changes to these variables that may occur in the future. It is important to recognize that a model is only a tool for approximating a field system.

Data collected during pilot studies at an ISR field site should be useful in constructing the conceptual model. For a ground water flow system, the nature of the conceptual model will determine the dimensions of the physical model and the design of a grid for numerical calculations. It is important to distinguish between the conceptual model of the hydrogeologic system and a computer code. A computer code is a set of instructions for performing calculations, whereas the conceptual model represents the physical and chemical understanding of the system.

Ground Water Flow and Contaminant Transport Modeling

After the conceptual model is developed, a computer code may be used to simulate the controlling processes that affect ground water flow and chemical transport. Computer modeling frequently used to meet the performance objectives at ISR facilities includes five primary types: (1) ground water flow, (2) advective-dispersive transport, (3) advective transport (i.e., particle tracking  -  no dispersion), (4) geochemical speciation, and (5) reactive-transport modeling.  These modeling approaches are described in greater detail below and in Section 4.7.3.

The ground water flow and advective transport modeling typically performed for ISR sites use finite-difference techniques, which require that the ground water system be divided ("discretized") into finite-sized blocks or "cells." Each cell is assigned unique hydraulic properties depending on the available field data and the goals for the analysis. In this way, the model can accommodate complex features of the ground water system. The time represented by the modeling effort must also be divided into discrete periods or "time steps." These steps must be short enough to provide an accurate solution, but not so short that they require an excessive number of calculations to run a simulation. The finite-difference method also requires that values for hydraulic head be assigned at flow boundaries (referred to as "boundary conditions"), as well as for the initial time period of the simulation (referred to as "initial conditions"). This is a requirement for producing a unique solution with any numerical method that depends on iteration, as does the finite-difference method.

The most popular computer code to simulate ground water flow is MODFLOW2000 (Harbaugh et al. 2000). The output from this code is a three-dimensional flow field (an array of hydraulic head elevations) representing average conditions in the model area.

Once the flow field is established, the most widely used contaminant transport code, MT3DMS is used to predict future concentrations of selected constituents at ISR facilities (Zheng and Wang 1999). MT3DMS does not explicitly simulate geochemical reactions but can be used to simulate changes in concentrations of miscible contaminants in ground water, while considering advection, dispersion, diffusion, and some aggregate chemical reactions (i.e., distribution coefficient), with various types of boundary conditions and external sources and/or sinks. The basic chemical reactions included in the model are equilibrium-controlled or rate-limited linear or nonlinear sorption, and first-order irreversible or reversible kinetic reactions. Somewhat more sophisticated, multispecies chemical reactions can be simulated by add-on reaction packages.

MODFLOW2000 and MT3DMS are commonly applied at ISR facilities to evaluate how the average flow field, together with other transport parameters, affects chemical movement in ground water and plume development from lixiviant sources. The chemical transport model is often used to simulate the expansion of the plume, during both the time of active leaching activities and the post-closure stage.

If diffusive and dispersive processes are not important to the transport analysis, the computer code MODPATH is frequently used to compute three-dimensional advective flow paths. The code uses output from steady-state or transient ground water flow simulations from MODFLOW. MODPATH is described in USGS Open-File Report 94-164 (Pollock 1994). MODPATH uses a semianalytical particle tracking scheme that allows an analytical expression of the particle's flow path to be obtained within each finite-difference grid cell. Particle paths are computed by tracking particles from one cell to the next until the particle reaches a boundary, an internal sink or source, or satisfies some other termination criterion.

After the modeling objectives are defined (Section 4.7.1), modeling of the ground water flow and contaminant fate and transport generally follows the set of steps detailed below:

  (1)   Developing a conceptual model to guide creation of model attributes.
  (2)   Selecting an appropriate computer code(s) for the analysis.
  (3) Establishing the time period represented by the model and the duration of subdivisions of this period (time steps) required for modeling.
  (4) Selecting a suitable model domain and determining the dimensional (horizontal and vertical) limits of the analysis.
  (5) Establishing the model structure by determining the number of model layers and the grid spacing requirements for the flow analysis.
  (6) Incorporating hydraulic boundaries and features, including the shape and characteristics of constant-head boundaries, precipitation/recharge, and pumping/injection.
  (7) Assigning hydraulic conductivity values.
  (8) Specifying initial head values (ground water surface elevation).
  (9) Evaluating and assigning appropriate model computational characteristics (e.g., solution method, iteration limits, and convergence criteria) to enhance model stability, computational efficiency, and solution accuracy.
  (10) Evaluating the sensitivity of model results to changes in model parameters.
  (11) Establishing the model structure, including determining the number of model layers and the grid spacing requirements for the transport analysis.
  (12) Assigning the characteristics of chemical sources (e.g., lixiviant), consisting of dimensions, locations, concentrations, and time dependency.
  (13) Assigning transport parameters, including the distribution coefficients, dispersivities, and porosities.
  (14) Defining chemical interactions among dissolved and solid phases.
  (15) Developing remedial design scenarios and conducting chemical transport simulations and exporting the observed concentrations at prespecified locations.
  (16) Post-processing the data with Graphical User Interface (GUI) tools.

Although the ISR method of uranium mining has a less disruptive overall environmental impact compared to open-pit mining, this mining method significantly alters the ground water chemistry and flow patterns during mining. One of the common strategies at all of the ISR facilities is to better understand the most probable fate and transport of uranium and other constituents during and after ISR operations. To achieve this goal, mathematical modeling of chemical reaction kinetic equations or equilibrium thermodynamic equations can be used to describe chemical interactions among dissolved chemical species, the dissolution of immobile solid phases, or the formation and precipitation of new, immobile solid phases. The following section presents a more detailed discussion of the role that geochemical modeling plays in the understanding of important chemical processes at ISR facilities.

Geochemical Modeling

Geochemical reactions along ground water flow paths can lead to regional variations in water composition that evolve in the direction of flow. Iso-concentration contours of reacting dissolved constituents drawn on maps of water composition tend to align perpendicular to the direction of ground water flow. It is these geochemical reactions that have created the sandstone-hosted uranium roll-front deposits along the interface between oxidized and reduced sandstones. The geochemistry associated with these deposits is complex and variable. The deposits contain a mixture of U[+6] minerals on the oxidized side of the front and reduced U[+4] minerals on the reduced side of the front (Harshman 1974). Oxidizing ground water flowing through sandstones transports uranium U[+6] in solution down dip until reductants in the host sandstones precipitate uranium as U[+4] minerals. Associated elements are often found distributed across the roll in zones determined by their redox potential and solubility in alkaline, oxidizing ground water that comes into contact with pH neutral, reducing sediments at the reaction front (Deutsch et al. 1985; Harshman 1972). Ground water within the ore zone of roll-front deposits often contains high concentrations of uranium and its daughter products, as well as elevated selenium, arsenic, lead, and other dissolved constituents (Johnson et al. 2010).

Modeling of any type does not lead to a unique solution, but the number of possibilities are reduced with greater amounts of carefully collected field data. Martin et al. (2005) summarized the benefits and limitations of geochemical modeling as follows:

      Benefits

   *             Provide insight into potential future conditions.
   *             Determine which variables are most important in determining future conditions.
   *             Assess potential effects of uncertain parameters.
   *             Establish objectives and test conditions for field and laboratory studies.
   *             Integrate available information.

      Limitations

   *             Insufficient input data.
   *             Modeling can be challenging and results misinterpreted.
   *             Uncertain and variability of the results.
   *             Difference between modeled and actual field conditions.

Approaches to Geochemical Modeling

All geochemical models are based on principles of mass conservation (mass balance accounting). Mass is neither created nor destroyed in the system, but transferred between solid, aqueous, and gaseous phases. Geochemical models can be generally sorted into two distinct categories, however, depending on the extent to which they incorporate transport processes. Models that do not consider transport processes are referred to as "geochemical reaction models" or simply "batch models." Models that consider both transport processes and geochemical reactions are referred to as "coupled transport and reaction models." Three basic modeling approaches have been used with geochemical data: inverse geochemical modeling, forward geochemical modeling, and reaction path modeling.

Inverse modeling attempts to establish reaction mechanisms that explain measured chemical changes that occur as water composition evolves along a flow path; it assumes that a water flow path is known and that water samples have been analyzed along that flow path. Such data can then be converted into amounts of minerals dissolved or precipitated along that flow path. Several assumptions are still made regarding the choice of minerals and their relative proportions contributing to the water chemistry, but the calculations are constrained with actual data. Inverse modeling can also be done without any recourse to kinetic or thermodynamic data, in which case it represents a relatively simple mass balance calculation. When speciation and thermodynamic and kinetic properties are included for additional constraints, the possible reactions become quite limited, and the modeling is much more meaningful. Inverse modeling calculations provide a way to evaluate the most probable chemical reactions between water and minerals.

Forward modeling is also known as "simulating" (i.e., potential reactions between rock and water are simulated from initial conditions of a known rock type and composition). Reactions are allowed to proceed in equilibrium or kinetic or combined modes. Changes in temperature and pressure can be invoked, changes in water flow rate can be assessed, and minerals can be allowed to precipitate as they reach equilibrium solubility or dissolve as they become undersaturated. Potential reactions can be simulated to see what the consequences are. This type of modeling is the least constrained. A great many assumptions are either invoked as input data or invoked as dictated by the program that may not apply to the specific system being simulated. This approach assumes the modeler has a significant amount of information on the ability of minerals to maintain equilibrium solubility or their rates of reaction. A typical example of forward modeling would be the calculation of the final water composition in an aquifer where infiltrating rainwater is allowed to equilibrate with calcite and dolomite (as might occur in a limestone aquifer).

Reaction path modeling or mass transfer modeling is dynamic in the sense that it allows the simulation of how changes in water and mineral phase composition occur over time as defined primary minerals are dissolved incrementally. At each step in the calculation, the aqueous speciation is calculated, and secondary minerals are dissolved or precipitated in order to maintain equilibrium. These models have been widely used to evaluate the chemical weathering processes that occur in natural systems (diagenetic processes). The gradual weathering of igneous rocks to produce clay minerals is a good example of a process where reaction path modeling may be useful. As these models consider the dissolution of primary minerals as a stepwise process, the variable of time is not included implicitly in the calculations. If kinetic data are available, however, that can be used to relate reaction progress to time, and the aqueous composition may be calculated as a function of time in a kinetic geochemical reaction model.

Mathematical Formulation

In all geochemical models, the reactions that describe the aqueous composition must be defined in terms of a minimum set of fundamental basis species that are required to describe all the free and derived species (complexes) present in the aqueous solution (e.g., H2O, H+,CO3[-2],OH[-]). The basis species do not need to be real species that exist in the solution; the only limitations are that they are mutually independent (i.e., they cannot be described in terms of combinations of each other) and that they provide a complete stoichiometric description of the system.

"Speciation" refers to the distribution of chemical species or elements among the different possible forms or species. Aqueous speciation is the distribution of chemical species among dissolved free ions, ion pairs and triplets, and other complexes. This concept is important because research has shown that some processes, including mineral precipitation and dissolution, biological uptake and toxicology, and sorption, are all affected by speciation. Some species, such as redox species, must be determined analytically. This is because most geochemical modeling codes erroneously assume that redox equilibrium is maintained, while in reality, disequilibrium among redox species is the rule, not the exception.

Most geochemical reaction programs are based on an approach in which the conservation of total component concentrations is combined with a description of chemical equilibrium. Chemical equilibrium may be computed in terms of Gibbs' free energy minimization or in terms of mass action equations involving equilibrium constants. The method of Gibbs' free energy minimization is generally regarded as being more mathematically robust than the method using equilibrium constants. Because of the lack of reliable and internally consistent Gibbs' free energy data, however, geochemists have tended to favor the equilibrium constant method. The vast majority of programs available today are therefore based on the equilibrium constant approach.

Aqueous speciation results are used for a variety of modeling objectives, including modeling of saturation-index calculations for mass transfer, modeling of mineral precipitation and dissolution, modeling of adsorption and desorption, and reactive-transport modeling.

For speciation reactions, the computer code solves a reduced set of simultaneous nonlinear equations that define equilibrium for a water, solute, gas, mineral, ion-exchanger, and surface-complexer chemical system. Equilibrium is based on an ion-association model for the aqueous phase and mass-action equations for mineral, gases, exchangers, and surface complexers. The complete set of equations includes a mole balance equation for each element in the system; mass-action equations for each aqueous species, each gas component, each mineral, each exchange species, and each surface complexer; an activity coefficient equation for each aqueous species; a charge-balance equation for the aqueous phase; a charge-balance or charge-potential equation for each surface complex; an equation for the activity of water; and an equation for the ionic strength of a solution. Subsets of this set of equations are solved for a particular geochemical calculation. The equations are solved by a modified Newton-Raphson calculation. The modification involves the use of an optimization routine based on linear programming. During the iterative Newton-Raphson process, some of the equations are included as objective functions rather than strict equalities. This approach is useful for determining the stable set of minerals and the presence or absence of a gas phase in a chemical system; it also makes the numerical algorithm more robust. The solution to the equations provides the activities and molalities of each aqueous species and the moles of each mineral, gas component, exchange species, and surface species present in the system.

In inverse modeling, one aqueous solution is assumed to react with minerals and gases to produce the observed composition of a second aqueous solution. The inverse model calculates the amounts of these gases and minerals from the difference in elemental concentrations between the two aqueous solutions. It is also possible to determine mixing fractions for two or more aqueous solutions and the mole transfers of minerals necessary to produce the composition of another aqueous solution. Inverse modeling is based strictly on a mole-balance approach and does not rely on the ion-association model except to determine the total number of moles of each element and redox state in each aqueous solution. The inverse model is formulated including uncertainty in each analytical datum. A linear set of equations is formulated including mole balance for each element and element redox state in the system, a charge-balance equation for each aqueous solution, and a water-balance equation. In addition, inequality constraints are included to ensure that any adjustments to the analytical data are smaller than the uncertainties and to constrain the sign of mole transfers of mineral (if specified). The system of equalities and inequalities is solved by an optimization routine based on the Simplex method. An additional algorithm is used to find all sets of minerals that are feasible solutions to the inverse problems.

Processes Simulated

Modeling of mineral precipitation and dissolution and gas-transfer reactions can take place conceptually in one of three possible systems: equilibrium state, steady-state, or transient state. The equilibrium state assumes that the system under investigation is isolated from any external exchanges of energy or mass. Although an unrealistic concept, equilibrium state is actually quite practical because many reactions approximate equilibrium even though there are gradients in water pressure or temperature. For example, in many ground waters, calcite and gypsum quickly reach their equilibrium solubility. Even with gradients in CO2 pressure or mixing with other sources of sulfate, these minerals adjust to maintain saturation, and the assumption of equilibrium may be valid. In addition, even when geochemical reactions of interest do not reach equilibrium rapidly, such reactions may achieve equilibrium over the time scale of the modeling simulation (i.e., the life of a mine and beyond). Therefore, the majority of geochemical modeling can be conducted under the assumption of equilibrium conditions.

The most simplistic geochemical models are empirical sorption models and describe experimental adsorption data without any theoretical basis. These models rely on adsorption isotherms that plot the concentration adsorbed to the solid surface versus the concentration in aqueous solution for different total concentrations of a chemical species. One of the most widely used adsorption isotherm equations is a linear function written in terms of the distribution coeffient, Kd:
                                    x = Kdc

where x is the amount of chemical species adsorbed per unit mass of solid and c is the equilibrium solution concentration of the chemical species.

Due to the complexity of the processes involved, a single partition or distribution coefficient is often used that describes the degree to which the contaminant's transport is retarded relative to water. This approach starts with defining the retardation factor:

where:
      Rf = the retardation factor
      νp= the velocity of water through a control volume
      νc = the velocity of contaminant through a control volume.

Langmuir (1997) noted that the retardation factor is related to the distribution coefficient
through the expression below:

where:
      ρb is the porous media bulk density, and
      ne is the effective porosity at saturation given as a volume fraction.

In addition to empirical sorption models, chemical surface complexation models have been developed to describe the potentiometric titration and metal (e.g., uranium, arsenic, selenium, molybdenum, iron, and vanadium) adsorption data at the oxide-mineral solution interface. Surface complexation models of the solid-solution interface share at least six common assumptions: (1) surfaces can be described as planes of constant electrical potential with a specific surface site density; (2) equations can be written to describe reactions between solution species and the surface sites; (3) the reactants and products in these equations are at local equilibrium and their relative concentrations can be described using mass law equations; (4) variable charge at the mineral surface is a direct result of chemical reactions at the surface; (5) the effect of surface charge on measured equilibrium constants can be calculated; and (6) the intrinsic (i.e., charge and potential independent) equilibrium constants can then be extracted from experimental measurements (Koretsky 2000).

More sophisticated geochemical modeling approaches allow for the precipitation and dissolution of gases and minerals, as well as the possibility of fixing the activity of specified components (the hydrogen ion activity, pH, for example). Reaction types that can be handled usually include complexation, ion-exchange, redox reaction, precipitation/dissolution, surface complexation, and other kinds of adsorption. The major limitation is the quality and availability of thermodynamic data for carrying out reaction calculations. Many programs contain databases of relevant aqueous, gaseous, and mineral phase reactions, and the more sophisticated programs can automatically select mineral or gaseous phases that are likely to precipitate and include them in the calculations. Some programs can be used to simulate titrations, evaporative processes, and mixing of different solutions or to perform isotope mass balances. Mass balances based on radiogenic isotopes are used primarily for estimating the age of ground water (i.e., the time elapsed since it entered a ground water system). Mass balances that consider stable isotopes are used to understand the source of water or the processes that may have influenced the chemical properties of the water over time.

Two general approaches are used in geochemical reaction models to calculate activity coefficients of aqueous species. The first type consists of the Debye-Hückel equation and its variant, the Davies equation, and its extended B-dot equation form. This approach limits the field of applicability for these models to solution ionic strengths less than or equal to that roughly corresponding to seawater (Parkhurst 1995). The second approach involves the use of Pitzer equations, which can be applied accurately to systems of high ionic strengths such as brines and highly saline ground waters (Pitzer 1979). Due to the high TDS concentrations within the mined area at the ISR sites, the application of geochemical models that include the Pitzer equations is important to accurately model geochemical reactions. However, because redox reactions, especially for the Fe(II)/Fe(III) system and the aluminum system, have not been fully parameterized for the Pitzer model, use of the Pitzer method currently will not adequately address geochemical reactions involving iron or aluminum associated with certain geochemical systems.
An increasing number of programs allow the simulation of kinetically mediated processes. These programs generally require user input to define kinetic parameters and sometimes the kinetic reaction equations themselves. As in the Pitzer method for calculating aqueous phase activities, a noted problem is the lack of kinetic data in the literature for many important mineral reaction processes.

Reactive Transport (Coupled Models)

Coupled transport and reaction models differ from the geochemical reaction models described previously in that transport processes are included explicitly in the mathematical formulation of the model. The idea is to couple flow models with chemical reaction models to determine the effects of flow on reactions, including the effects of dispersion.

Coupled transport and reaction models can be used to simulate how a geochemical system evolves over time along a fluid flow path in one, two, or even three dimensions. Like geochemical reaction models, coupled transport and reaction models are based on the principle of mass conservation. Whereas the mathematical formulation of a geochemical reaction model generally regards a single control volume that is formally decoupled from flow considerations, coupled transport and reaction models discretize the flow medium into a network of interconnected control volumes. Reactive-transport modeling for ground water has also progressed substantially over the last three decades, and many of the recent codes have been applied to ISR mine sites. Mayer et al. (2003) provide an overview of the theoretical foundations for ground water reactive-transport modeling, methods of coupling flow with reaction, and the various codes available.
Critical to the success of a coupled transport and reaction model is detailed knowledge of the hydrology of the site to be modeled. Frequently, it is not possible to obtain the necessary amount or quality of data to satisfactorily characterize the subsurface system for the purpose of a reliable predictive simulation. This problem arises largely from issues of heterogeneity. Heterogeneity in subsurface soils and rock manifests itself in the form of preferential flow paths, fracture zones, regions of variable hydraulic conductivity and porosity (layered sedimentary rocks and soils), as well as stagnant zones (clay lenses and other flow-isolated porosities in the rock matrix. Other factors that may affect the reliability of coupled transport and reaction models are the transient nature of contaminant sources and the variable boundary conditions relating to the ISR injection and pumping wells.

Some programs have been developed that can simulate heterogeneous reaction systems. These models consider alterations that may occur in the distribution of minerals in the system under the influence of reactive-transport processes. The mathematical formulation of models for heterogeneous reaction systems is much more complicated than that for homogeneous reaction systems, as zones of dissolution and precipitation form and slowly advance. One of the problems associated with the simulation of heterogeneous reaction systems is the necessity to track the position of these mineral reaction fronts over time. The programs that simulate heterogeneous reaction systems are frequently unable to simulate the entire suite of geochemical reactions that can be simulated by nontransport-enabled geochemical reaction programs.

In general, it is difficult to accurately simulate kinetic processes involving heterogeneous reactions. Kinetic interactions with solid phase materials are usually quite strongly dependent on the mineral surface area exposed to pore water ground water conditions (i.e., complexing ion concentrations, pH and redox potential), and the residence time of water in the random pores and fractures that characterize most geological media. The exposed mineral surface area and the porosity of the medium change during diagenesis as a result of the precipitation and dissolution of various minerals. The exposed surface area of some minerals may decrease as a result of the precipitation of other minerals that block their access to the pore water.

Local changes in the porosity of the medium may also give rise to preferential flow paths. Because of relationships between mineral surface area and porosity, the creation of preferential flow paths can lead to the formation of fingered mineral alteration zones. These processes are virtually impossible to predict. Fortunately, however, it is rarely necessary to know specific details about the formation of fingered zones, and it is often sufficient to assume a relatively homogeneous porous medium. Although small-scale heterogeneities are often neglected, some information about mineral surface area is still required in order to estimate mineral reaction rates. Mineral dissolution and precipitation rates are frequently modeled using semiempirical approaches such as the transition state theory (Lasaga 1981; Aagaard and Helgesson 1982).
Conceptual models for reactive-transport modeling are necessarily complex and will likely require that alternative conceptual models be considered in order to examine the range of simulation results and the sensitivity of predictions to conceptual model error. Conceptual models for reactive-transport modeling represent the scientific understanding of processes controlling the movement and transformation of system components, including contaminants, for a specific water rock system (Davis et al. 2004). For example, a conceptual model for the ISR mined region might include knowledge of (1) initial spatial distribution of chemical species (including uranium, arsenic, iron, sulfur, selenium) and mineralogy, (2) hydrologic sources and sinks, porosity, and spatial dependence of hydraulic conductivity, and (3) aqueous solute speciation and chemical reactions controlling phase distribution. Alternative conceptual models for ground water restoration at ISR facilities might include different initial concentrations of various minerals or variable redox status of ground water flowing into the subsurface region that was mined.

Predictive Modeling Strategies

USGS, in conjunction with EPA, is in the process of developing modeling strategies to address three primary questions (Johnson et al. 2010): (1) How well do identified aquitards limit ground water flow between aquifers? (2) What is the ground water quality at the end of mining after restoration efforts are complete? and (3) What are the long-term fate and transport of any ground water contaminants away from the mined zone? These strategies will be generic for any uranium ISR mine, but will be applied to a current site in South Dakota that is in the permitting phase. This research is designed to assist EPA, mining companies, the general public, and other stakeholders with specific strategies for understanding and modeling subsurface hydrogeology and geochemistry. The types of information that are important to support detailed modeling studies include the development of geologic models based upon exploratory drill holes, solid phase mineralogy acquired from core analysis and ground water chemistry obtained from ground water sampling.
Once the site data are successfully collected, the researchers outline four general components of a strategy beginning with the development of a conceptual model that establishes the basic hydrogeologic and geochemical system, using available data and professional expertise. The conceptual model includes information such as ground water flow direction and velocities, boundary conditions, and current ground water and solid-phase geochemistry. The second step involves numerical modeling with reactive-transport models, which simulate ground water flow and geochemical interactions between the aqueous and solid phases. For this step to be successful, initial solid phase geochemistry is required. The third step applies modeling to better understand the potential impact of the mining activities on surrounding ground water quality under various design options. The final step in the process focuses on the evaluation of the model limitations and uncertainty in the model input parameters (e.g., geochemistry and hydraulic conductivities).
Examples of Major Codes

The computer codes that are applied to modeling at ISR facilities are typically selected to be consistent with the modeling objectives and the available data. For instance, if the intention is to calculate uranium migration velocities and travel times, then it may be appropriate to apply a code that utilizes an empirical sorption model (Section 4.7.3), rather than a geochemical reaction model based upon thermodynamics. Estimating restoration time frames, however, may require a geochemical reaction path or mass transport code(s). The discussion below provides a general overview of the types of computer codes that are available to explicitly simulate thermodynamically based reactions. Although the complexity of the codes varies, their applicability will be largely dependent upon the modeling goals and whether the underlying  kinetics and thermodynamics are well understood.
Inverse Modeling. Inverse modeling is used to explain the observed chemical and isotopic evolution of natural (or contaminated) waters, rather than to predict future compositions. This modeling approach applies geochemical mass balances to the observed chemical and isotopic composition of evolutionary ground waters to estimate masses of mineral and gas transfer in water-rock systems. Inverse geochemical modeling software includes BALANCE (Parkhurst et al. 1982), NETPATH (Plummer et al. 1994), PHREEQC (Parkhurst 1995; Parkhurst and Appelo 1999), PHREEQCI (Charlton et al. 1997; Charlton and Parkhurst 2002), SPREADBAL (Bowser and Jones 2002), Geochemist's Workbench(R) (Bethke and Yeakel 2009), and CrunchFlow (Steefel 2009).

The inverse modeling capabilities of the PHREEQC and PHREEQCI codes consider the uncertainties associated with the definition of initial and final solution compositions (chemical and isotopic) and with the isotopic composition of reacting phases. The NETPATH code offers a complete suite of adjustment models for C-14 dating.

Forward Modeling. The "forward modeling" approach has been extended to geochemical transport codes capable of simulating ground water flow and the advection and dispersion of solutes, coupled with a complex array of geochemical processes. Completely specified isotopic reactions have been incorporated into geochemical mass-transfer and mass-transport codes [specifically into PHREEQCI and PHAST (Thorstenson and Parkhurst 2002, 2004)], allowing a forward modeling description of the isotopic evolution of a ground water system, along with its concurrent chemical evolution.

Progress has also been made to numerically simulate the coupling of ground water flow, solute transport, and geochemical processes. Geochemical mass-transport codes [e.g., MST1D (Engesgaard and Kipp 1992); PHREEQC/PHREEQCI; PHAST (Parkhurst et al. 2004)] incorporate all the limitations and uncertainties associated with the use of (1) geochemical reaction codes and (2) nonreactive solute transport codes.

Reaction Transport Codes. Glynn (2003) contrasts the use of highly simplified reactive-transport codes with the PHREEQC geochemical transport code, a code limited to a one-dimensional description of flow and transport, but with a more complex, conceptually more accurate description of sorption mechanisms and multispecies geochemical processes. Inverse and forward geochemical modeling were conducted, including a three-dimensional geochemical transport model using the USGS code PHAST.

Table 4-1 shows some of the more popular codes used primarily for ground water geochemistry but also for sites affected by mining. More detail on geochemical modeling, modeling codes, and associated uses and limitations is presented in Alpers and Nordstrom (1999), Mayer et al. (2003), and Maest and Kuipers (2005).

Table 4-1.	Summary of Commonly Applied Geochemical Modeling Codes
                                     Codes
                                     Type
                                   Reference
CrunchFlow
Lawrence Berkeley National Laboratory supported code: Multicomponent Reactive Flow and Transport.
Steefel 2009
EQ 3/6
Lawrence Livermore National Laboratory code: mass transfer and reactive transport
Wolery 1992
Geochemist's Workbench
University of Illinois code: mass transfer, saturated flow
Bethke 2002, 1996, Bethke and Yeakel 2009
MIN3P
Waterloo code: saturated and unsaturated flow
Mayer et al. 2002
MINTEQA2
EPA supported code: speciation and mass transfer
Allison et al. 1991
NETPATH
USGS codes: mass transfer and reactive transport
Plummer et al. 1994
PHAST
USGS codes: mass transfer and reactive transport
Parkhurst et al. 2004, 2010
PHREEQC
USGS codes: mass transfer and reactive transport
Parkhurst and Appelo 1999
PHRQPITZ
USGS codes: mass transfer and reactive transport in high ionic strength solutions
Plummer and Parkhurst 1990
SOILCHEM
University of California: Chemical Speciation
Sposito and Coves 1988
SOLMINEQ.GW
USGS code: mass transfer and high temperature
Perkins et al. 1990
WATEQ4F
USGS code: speciation and low temperature only
Ball and Nordstrom 1991

Modeling Case Histories
GROUND water modeling is often performed at ISR facilities to gain a better understanding of various processes such as mineral dissolution/precipitation, oxidation/reduction and adsorption/desorption. The material presented below documents historical modeling activities together with research currently being conducted. The material is excerpted and paraphrased from the original documents.

Modeling of the Moore Ranch ISR Project (NRC 2010)

The simulated sand unit was assumed to be partially saturated over the proposed license area. To assess potential drawdown, a ground water flow model was developed to simulate partially saturated conditions. The model was created within the Ground Water Vistas GUI platform and applied MODFLOW-SURFACT (Version 3.0). The model was calibrated to site-specific conditions and verified by site-specific field pumping test data. The model analyzed drawdowns during various phases of ISR production and aquifer restoration. The model was also used to estimate the potential impact of the simulated drawdown on private well users within 2 miles of the facility boundary. The estimated drawdown was determined to have a negligible impact on private well yield. The model was also used to determine the impact of production on water levels in other water-bearing sandstone lenses. This modeling effort was only focused on the physical ground water flow processes and did not consider geochemical reactions.
Consideration of Geochemical Issues in Ground Water Restoration at Uranium ISR Mining Facilities (NRC 2007)

This report discusses various ISR topics including developing and applying a conceptual model that considers the ground water flow, solute transport, and geochemical reactions associated with the Ruth ISR. The modeling was designed to provide a quantitative and dynamic method for estimating the number of pore volumes associated with ground water restoration as a function of both historical conditions and potential variations (i.e., under different assumptions of future site conditions). Once the conceptual model was developed, the data collected from the site were input into PHREEQC to estimate the number of pore volumes that must be removed to return the system to initial conditions.

A series of reactive-transport simulations using ground water restoration data from the Ruth ISR pilot-scale study was used to evaluate variations in the geochemical processes. The calculations showed that a computer code like PHREEQC can be used to make predictive calculations of how different geochemical conditions may affect evolving water quality during geochemical restoration.

Irigaray Mine Wellfield Restoration Report, Johnson County, Wyoming (COGEMA 2005)

A ground water flow and transport model was developed to assess fate and transport of residual constituents derived from the Irigaray ISR mine. The objective was to demonstrate that residual concentrations would be below regulatory standards at prescribed observation points. The model was used to evaluate continued migration under steady-state conditions, without pumping or injection. Therefore, the emphasis was on adequately representing steady-state advective-dispersive flow within and across the production zone. The approach taken was to develop a model that predominantly depended on advective-dispersive transport of constituents and minimized reliance on geochemical reactions. The parameters required included hydraulic conductivity, hydraulic gradient, dispersivity, and effective porosity. These parameters were quantified for the site and were incorporated into the model. Dispersivity values were based on the scale of the site/plume and literature review.

A distribution coefficient (Kd) was included for some constituents using the lowest reasonable Kd available from the literature. Uncertainty was addressed in model parameters with a sensitivity analysis. The codes used to develop the model included:

   * MODFLOW: for simulation of the flow field.
   * MODPATH: for simulation of ground water flow paths.
   * MT3DMS: for simulation of transport of site-derived constituents.

Although MT3DMS was calibrated to simulate migration of selenium, manganese, uranium, Ra-226, and TDS, it uses the simplified distribution coefficient approach to calculate retardation factors as described in Section 4.7.3. The modeling results demonstrated that remaining concentrations at distances 400 feet down gradient of the wellfield were below the regulatory standards for all the constituents.

Ross ISR Project, NRC License Application, Crook County, Wyoming (Strata Energy 2010, Addendum 2.7H Ground Water Model)
The model was developed to analyze the potential direct, indirect, and cumulative hydrological effects of the project on both regional and individual wellfields. As stated in the document, the primary goals of the regional ground water model were to (1) identify potential impacts (if any) to adjacent water rights, (2) estimate long-term impacts from ISR operation, and (3) identify potential impacts to the surficial aquifer and surface impoundments. Modeling goals for individual wellfields were to:

   * Estimate adequate perimeter monitoring well offset/setback distances for the wellfield.
   * Demonstrate the ability to identify and remedy a lateral excursion (i.e., lixiviants moving past the monitor wells).
   * Optimize the wellfield design and pumping rates including bleed rate.
   * Evaluate restoration time/efficiency.

The hydrogeology of the area ground water use was presented as a basis for the model. The numerical ground water model was the USGS modular finite-difference model MODFLOW and Ground Water Vistas was used as the pre- and post-processor. These codes were selected because of their wide use and acceptance by the industry and regulators. Hydraulic parameters used in the model were based on site data or taken from the literature. The model was first calibrated to a steady-state solution based on pre-1980 conditions. Once a satisfactory calibration to steady-state conditions was achieved, a transient calibration was conducted with the goal of matching the drawdown that had occurred over 30 years due to withdrawals from industrial wells. To assist in the calibration, PEST (a model independent parameter estimation program) was used.

The calibrated model was used to simulate ISR operations within the Ross Project area. The ISR simulation was a generalized scenario based on current mapped mineralization. Impacts were also determined along with recovery simulation and flare evaluation. The general conclusion from the modeling was that impacts of the facility would be minor. Lastly, the model is expected to be a useful tool for the final wellfield planning and operations and assist in balancing wellfields, progression planning, and bleed rate optimization.

Wellfield Restoration Report, Christensen Ranch Project, Wyoming (COGEMA 2008a)

While this report presents a transport assessment:

      ... no groundwater modeling specific to the Christensen Ranch MUs is included in this report. Christensen Ranch site conditions, including the constituents of concern, are similar to those at the Irigaray Mine. Groundwater modeling included in the Irigaray Mine Aquifer Restoration Report (COGEMA 2003) is referenced where applicable to the Christensen Ranch Site.

The transport assessment comprised the geochemical assessment and hydrological assessment. The geochemical component of the transport assessment addressed the physical and chemical behavior of constituents of concern under the prevailing environmental conditions at the site. These included uranium, radium, iron, manganese, selenium, and sulfate. In addition to the geochemical assessment, the effects of long-term ground water flow, including advective mixing and dispersion, on constituent concentrations were considered under the transport assessment. Direction and velocity of ground water flow are critical hydrologic factors with respect to solute transport. Determination of the direction of ground water flow was based on water-level data that were routinely collected from the monitor well networks.
As previously stated, no ground water modeling was performed specifically for the Christensen Ranch site. However, extensive modeling of ground water flow and solute transport was performed for the Irigaray Mine site located 6 to 10 miles northwest of Christensen Ranch. The Irigaray Aquifer Restoration Report includes those modeling results, which were accepted by the Wyoming Department of Environmental Quality (WDEQ) and NRC. These results apply in a general sense to Christensen Ranch.
The model focused on the impacts of advective mixing on constituent concentrations migrating from the Irigaray site, but did not address the effects of geochemical processes along the flow path. The results of the model indicate that the maximum concentration at a distance of 400 feet from the wellfield was approximately 7 times lower than the initial average wellfield concentration, after subtracting the average background concentration. The background concentration was subtracted from the affected concentrations to normalize the data. The monitor well ring is located 400 feet from the wellfield.

Highland Uranium Project A-Wellfield

The operator used modeling to show that natural attenuation processes would reduce ground water contamination to acceptable levels. (See Attachment B for details.) The attenuation modeling involved both ground water flow modeling with MODFLOW and PHREEQC geochemical modeling. The calculations showed that a maximum of 15 years would be required to achieve the full benefits of natural attenuation. To support the modeling results, the operator was required to perform semiannual monitoring of four wells (a "hot spot" well with elevated levels of uranium and selenium, an up gradient well, a down gradient well, and a lateral well) beginning in 2004. At the current time, field measurements indicate that the uranium and selenium concentrations are stable, but not declining, as would be expected from natural attenuation and predicted by the geochemical modeling.

International Mine Water Association

A review of the meetings of the International Mine Water Association (IMWA) uncovered two relevant publications discussing predictive modeling for ISR facilities (Johnson et al. 2010; Johnson 2011). As observed by Dr. Johnson, this effort is still preliminary. Below is a review of the two papers.
Predictive Modeling Strategies for Operations and Closure at Uranium In-Situ Recovery Mines (Johnson et al. 2010) was presented at the IMWA 2010 symposium, "Mine Water and Innovative Thinking." In this paper, the authors present a predictive strategy, which will be applied at the IRS facility in Edgemont, South Dakota (the proposed Dewy-Burdock facility in Fall River and Custer Counties).

The following describes the steps proposed by Johnson et al. 2010:

      First, a conceptual model must be established to understand the basic hydrogeologic and geochemical system, based on available data and professional expertise. Such a conceptual model includes information such as groundwater ﬂow direction, boundary conditions, along with current groundwater and solid-phase geochemistry.

      Second, predictive modeling using numerical reactive transport models can be used to simulate future groundwater conditions (during mining, restoration, and post-restoration). This requires the coupled simulation of groundwater ﬂow and geochemical reactions using such models as PHT3d (Prommer 2002), which simulates groundwater ﬂow using MODFLOW (Harbaugh and others 2000) and geochemistry using PHREEQC (Parkhurst and Appelo 1999). In any reactive transport modeling, input data linking the solid-phase mineralogy to the groundwater quality is very important to understand the rock-water interaction. For predictive modeling purposes, the collection of solid-phase geochemistry before mining is required. For ﬁnal model calibration, postmining solid-phase geochemistry is optimal. Theoretical reactive transport simulations of uranium ISR mining have been examined (Davis and Curtis 2007 [NRC 2007]); however, ﬁeld applications have been limited.

      Third, predictive modeling can be used to evaluate the impact on surrounding groundwater quality under the proposed mine plan design and to evaluate possible design alternatives. Since many uranium ISR-amenable deposits occur within sandstones that are drinking water aquifers outside of the ore zone, protection of groundwater quality is of great importance. Predictive reactive transport modeling provides a tool for evaluating potential impacts on surrounding groundwater quality based on initial mine plans. This is part of the second modeling strategy discussed above, but more importantly, alternate well ﬁeld design and possible restoration procedures can be evaluated before ﬁnalizing any mine operation and closure plans.