New Prosperity Gold-Copper Project Independent Technical Review of Seepage Predictions for the Storage Facility

Dr. Leslie Smith, Ph.D., FRSC

Prepared at the Request of the Canadian Environmental Assessment Agency

July 22, 2013

1. Scope of the Assignment

CEAA requested two issues be addressed in my review:

a) A technical review of the expected seepage and groundwater flow from the proposed tailings storage facility (TSF), and the adequacy of the proposed mitigation measures,

b) Assess and report on the potential risk of contaminated seepage reaching Fish , Wasp Lake, the Onion and Taseko River.

During the review, two additional requests were received from the Panel:

a) To provide an opinion on whether the intercalated basalts would impact the hydraulic conductivities used to model the water balance for the TSF given the discontinuous thickness of the overlying till in the upper walls, and if so, whether the various mitigations referenced in the SIR 12/14 response would enable the achievement of "equivalent conductance" for the shallow tills encountered in the uplands in particular, and/or tailings seepage issues encountered across the TSF in general, given the size (12 km2), surficial geology and lithologies encountered in the basin.

b) To comment on the recent Natural Resources Canada seepage model for the TSF, presented in a report entitled "Numerical modeling of groundwater seepage from the Tailings Storage Facility of the proposed Taseko New Prosperity gold- copper mine project", dated July 2013 (Document No. 587).

Water quality evaluations and estimates of solute loads to surface water systems are not within the scope of this review.

2. Principal Information Considered

Taseko Mines Limited - Baseline Groundwater Hydrology Assessment (August 17, 2012).

Taseko Mines Limited - Numerical Hydrogeologic Analysis (August 17, 2012).

Taseko Mines Limited - Report on Preliminary Design of the Tailings Storage Facility, Appendix B (August 30, 2012).

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Knight Piesold Consulting - Response to Questions of Clarification from Dr. Leslie Smith (July 9, 2013).

BGC Engineering Inc. - Response to Panel Expert Questions of Clarification (July 8, 2013).

Federal Review Panel - Supplemental Information Requests and Responses (relevant sections of Document #'s 272, 316, 400, 444, 460, 477, 489, 494, 539).

Natural Resources Canada, Numerical modeling of groundwater seepage from the Tailings Storage Facility of the proposed Taseko New Prosperity gold-copper mine project, July 2013.

3. Information Accepted Without Review

The following information was accepted without review:

a) The hydrogeological field investigation in the vicinity of the TSF provides representative results, and reliable numerical estimates of the hydrogeologic parameter values were obtained from in situ testing. Individual borehole logs were not reviewed.

b) There is no evidence to suggest that faults zones have a hydraulic conductivity substantially greater than the surrounding bedrock, and therefore they do not represent distinct hydrogeologic features.

c) The water balance for the TSF is in surplus, with water available to maintain a two metre water cover on the TSF at closure.

4. Comments on Modeling Approaches Used in Seepage Assessment

4.1 Introduction

Analysis Framework

The framework used by Taseko and their consultant BGC to evaluate the seepage of process water from the TSF to nearby streams and lakes follows accepted practice. This includes:

 Formulation of a conceptual groundwater model and construction of a simplified representation of the key hydrogeological units.

 Representation of this conceptual model in a computer-based simulation model, using industry-standard software (MODFLOW in this case).

 Selection of appropriate boundary conditions for the model domain that link the flow regime within the domain to the larger regional setting.

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 Model calibration using a trial and error adjustment of the hydraulic properties of the geologic units, and boundary conditions, to obtain a model structure and parameter values consistent with the field measurements of hydraulic head and, in the one location available, measurements of streamflow during the dry season.

 Use of the calibrated model to predict the influence of mine operations on subsurface flows and groundwater discharge, and to evaluate the feasibility of potential mitigation measures to manage seepage fluxes from the TSF.

 Sensitivity analysis to assess the influence of parameter uncertainty on the reliability of the predictions based on the model.

Taseko also commissioned BGC to carry out a transport analysis to predict solute concentrations in groundwater impacted by seepage from the TSF. This step is less common in practice, but it is appearing with greater frequency recently. In my experience, seepage pathways, and seepage interception, are more commonly presented using the results of the particle tracking module incorporated within MODFLOW. These tools provide clear graphical illustrations of the projected subsurface pathways of solutes, indicate the average rate of solute migration, and provide a visual evaluation of process water capture by seepage interception wells. However, this method does not provide predictions of solute concentration, which was the objective in developing a subsurface transport model. It is my understanding based on the response to my questions of clarification that BGC conducted a particle tracking analysis, but did not include these results in the modeling report (Document No. 603).

The solute transport analysis was carried out within a sub-domain extracted from the regional groundwater model. This technique allowed a computational grid with greater refinement, designed specifically for the TSF, to be constructed. This approach is reasonable. The simulation model MODFLOW-SURFACT was used for the transport calculations, this is a reasonable choice.

Model Predictions by the Proponent

The Taseko three-dimensional groundwater model provides the following insight:

 An estimate of the volume of process water seeping from the TSF and entering the geologic units in the foundation of the TSF. Their estimate of seepage rates peak at 47 l/s in year 3 of operations and then decline to approximately 9 l/s for the latter half of the mine life, and into closure. The average rate of seepage through the foundation, over the 17 year proposed mine life, is 15 l/s. These values are their expected case. They were derived with the assumption that the vertical hydraulic conductivity of the tailings will be 1 x 10-8 m/s, with estimates for the hydraulic conductivity of the till equal to 5 x 10-8 m/s, and 2 x 10-7 m/s in the upper 100 m of the flood basalts. BGC anticipate that the majority of the seepage leaving the TSF (70%) will originate from within the footprint of the submerged PAG rock, with the remaining 30% originating within the footprint covered by tailings.

 An evaluation of the uncertainty in the predicted quantities of seepage, which largely depend upon the uncertainty in the hydraulic conductivity of the tailings

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deposit, the PAG rock, and the geologic units within the upper few hundred metres of the pre-development ground surface. A sensitivity calculation provided in response to SIR 12/14 (Document 400, Response to IR12c) suggests a seepage rate later in the mine life of 42 l/s if higher values are assigned to the hydraulic conductivity of the glacial till (2.5 x 10-7 m/s) and the upper basalt zone (1 x 10-6 m/s).

 An identification of the seepage pathways that are likely to develop as the TSF level rises, and the identification of where and when natural hydrodynamic containment around the perimeter of the TSF is breached.

 An estimate of seepage volumes and solute travel time for migration to each of the nearby groundwater discharge points.

 A conceptual demonstration of a seepage interception strategy for the solute pathway beyond the main embankment.

The analysis framework used by Taseko and their consultant Knight Piesold (KP) to evaluate in two dimensions seepage through the embankment structures and shallow foundation follows accepted practice and uses industry-standard software (/W). The two dimensional analysis of seepage allows for inclusion of additional engineering details of the embankment structures in the model, and is required for the dam stability evaluation.

In the two dimensional model, KP assigned parameter estimates based on their synthesis of the well test data and other field measurements; the analysis does not incorporate a calibration. The hydrostratigraphy is represented with a somewhat different structure than the regional model, to reflect conditions thought to be representative of the hydrogeology along the lateral extent of each embankment structure. The two-dimensional model incorporates a thin, more permeable layer of weathered basalt (hydraulic conductivity of 3 x 10-6 m/s) below the till layer. A 15 m thick layer of till with a relatively low hydraulic conductivity (1 x 10-8 m/s) covers the floor of the TSF in these calculations.

This analysis provides the following insight with respect to process-water seepage:

 At full pond height, this analysis suggests a total seepage of 50 - 60 l/s for the embankment structures. KP indicates that of this flow, 65% reports to the embankment drainage systems, while 35% moves beyond the embankments in the shallow foundation (i.e. 18 – 21 l/s).

 A sensitivity calculation provided in response to SIR 12/14 indicates that if the large-scale effective hydraulic conductivity of the till is one order of magnitude higher (1 x 10-7 m/s) and the effective hydraulic conductivity of the weathered basalt is 5 x 10-6 m/s, the total seepage from the impoundment could be up to 160 l/s. Assuming the same proportionality factor as above, this suggests seepage of 50 - 60 l/s moving beyond the embankment structures in the shallow foundation.

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4.2 Model Construction

The three-dimensional, basin-scale model does not include the three embankment structures forming the TSF (main, west, south). Seepage estimates through the embankments are derived from the two-dimensional SEEP/W analysis. This approach is common practice, especially when a basin-scale model is developed using a finite difference model such as MODFLOW. Examination of the finite difference grid in the basin-scale model indicates greater emphasis was placed on representing the flow system in the vicinity of the open pit than at the TSF. This design decision was accommodated by using a second, inset model for the TSF to complete the solute transport evaluations.

The tailings and PAG rock zones in the TSF are incorporated in the basin-scale model using a head-dependent flux boundary, rather than incorporating these materials within the model grid. This is a valid approximation, although a model has greater flexibility if the TSF is explicitly included within the model grid. For information of the Panel, I surveyed groundwater models developed for 12 operating mine or project proposals that I have reviewed in the past several years; seven sites included the TSF within the model domain, while five sites represented seepage from the tailings via a boundary condition.

In my experience, it is uncommon for an EIA-level analysis to exclude from the model a representation of the seepage collection located down-gradient of the embankment structures. This approach eliminates the opportunity to calculate the volume of process-affected groundwater that might report to those collection locations. Such an analysis will be required to move the evaluation of seepage interception beyond the conceptual level.

4.3 Model Parameters

Hydraulic Conductivity of the Foundation

The packer test results carried out in bedrock yield a wide range of variation in hydraulic conductivity (10-9 to 10-5 m/s for the flood basalts). A four order of magnitude variation in hydraulic conductivity across a data set is commonly observed in packer test results conducted in a fractured rock setting. The variation observed, and the estimated mean value, depend in part upon the testing strategy adopted in the field program. In some investigations, the conductive elements seen in core, borehole logs, or inferred during drilling are specifically targeted for measurement, in others the data is collected by carrying out the tests in closely-spaced down-hole intervals.

Multiple basalt flows suggests an anisotropic hydraulic conductivity at the basin scale, with the horizontal hydraulic conductivity greater than the vertical hydraulic conductivity. This property is not expressed in the packer test data set; the degree of anisotropy is commonly derived during calibration of a groundwater model, or from longer-term pumping tests using multiple observation wells with measurements of water level changes at different depth intervals.

Hydraulic Conductivity of Tailings and Waste Rock

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In my experience, a considerable range of values for the hydraulic conductivity of tailings have been adopted in simulation models developed to aid in the assessment of seepage from a tailings storage facility. The hydraulic conductivity of tailings depends upon a number of factors, including ore type, clay content in the ore zone, mill grid, and sediment transport / deposition processes occurring within the TSF. For tailings derived from open pit operations, values as low as 1 x 10-8 m/s are used. The highest values I have seen used are a horizontal hydraulic conductivity of 3 x 10-5 m/s, with a vertical hydraulic conductivity of 6 x 10-6 m/s (on a tailings beach).

It is becoming more common to see model calculations that zone the interior of the TSF relative to distance from spigot points and/or the degree of tailings consolidation. To illustrate by way of a simple example, within the TSF, tailings deposited on a beach might have a horizontal hydraulic conductivity on the order of 10-6 m/s, a vertical hydraulic conductivity of 10-7 m/s, while in the interior of the pond, where the finer tailings are transported and settle, the hydraulic conductivity could be on the order of 10-8 m/s. The higher hydraulic conductivity of the beach deposits may extend 50 - 200 m beyond the spigot locations, and perhaps farther, depending upon the tailings discharge plan. In assigning a single value of hydraulic conductivity (1 x 10-8 m/s) to the entire deposit, the three-dimensional model adopts an estimate for the hydraulic conductivity of the tailings that I view as a lower bound value. The sensitivity run where the vertical hydraulic conductivity of the tailings was effectively increased to 1 x 10-7 m/s was reported to yield a seepage estimate twice as large as the base case (all other parameters equal to base case values).

Values assigned to the hydraulic conductivity of the PAG deposit are consistent with my expectation. I consider a base case value of 10-4 m/s to be conservative (ie. increasing the seepage estimate). The sensitivity case of 10-6 m/s is perhaps the expected case, if the waste rock contains a significant fraction of fine-grained material (say 20 - 30% finer than 2 mm), is placed in a dry state and constructed as a platform with relatively thin lifts.

Model Calibration

The calibration measure for the model of pre-development conditions (9.9% root mean square error - RMSE) is at the margin of acceptance according to conventional practice (the target is often quoted as <10% RMSE). The %RMSE is one of several standard measures used to guide the model calibration process; it is calculated from the difference between the observed and predicted water levels in piezometers located within the model domain. It is more common to see %RMSE values in the range of 5 – 8 %. I suspect the %RMSE value partially reflects a decision to adopt only three hydraulic conductivity zones for bedrock in the regional model (with a single, depth-dependent function). In general, the greater the number of hydraulic conductivity zones incorporated in a model, the easier it is to select a set of hydraulic parameters that reduce the magnitude of the %RMSE.

Plume Migration

The estimates of the plume migration rates, and in particular the component entering the fractured basalts, are subject to considerable uncertainty because of the difficulty in defining a reliable estimate for the effective porosity of the bedrock units. The solute transport model cannot be calibrated at this time, as there are no current data, nor data

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7 readily available, that could be collected for this purpose. The opportunity to calibrate the solute transport model would only arise after process water from the TSF was detected in monitoring wells adjacent to the TSF. This is the common situation in practice. The effective porosity of the till unit is more readily estimated because of its limited range of variation.

5. Natural Resources Canada Seepage Model

The local-scale, three dimensional analysis of the TSF developed by NRCan yields higher estimates of seepage through the foundation of the tailings pond than do the Taseko calculations. The NRCan model, like the BGC model, excludes consideration of the seepage pathway through the main, west, and south embankment structures. The NRCan model is intended to approximate the post-closure seepage flow out of the TSF. The base case presented by NRCan suggests a flow through the foundation of approximately 100 l/s.

The main differences between these two models are:

 The BGC model extends laterally to natural hydrologic boundaries, encompassing a larger domain than the NRCan model, which was purposely restricted to the footprint of the TSF. General head boundaries are used in the NRCan model to link the local-scale model to the hydrologic conditions in the far field, with hydraulic head controls extracted from the BGC regional model. This is a reasonable approach, given the intended purpose of the NRCan model.

 The NRCan model includes the tailings and PAG deposits within the computational grid; in the BGC model the seepage from the tailings and PAG rock is applied as a flux boundary. In the NRCan model, tailings are represented in two zones, shallow unconsolidated tailings with an assumed horizontal hydraulic conductivity of 5 x10-6 m/s and deeper, consolidated tailings with an assumed hydraulic conductivity of 1 x 10-6 m/s. The vertical hydraulic conductivity of the tailings is assumed to be a factor of 10 lower in each zone. The vertical hydraulic conductivity of the consolidated tailings (1 x 10-7 m/s) is a factor of ten higher than the hydraulic conductivity value adopted in the BGC model. To facilitate a comparison with the BGC model, the boundary conditions in the NRCan model specifically exclude a seepage pathway from the tailings into the embankment structure and its drainage system.

 The NRCan model is designed to accommodate a thinner layer of till on the valley flanks, in comparison to the minimum 5 m thickness applied in the BGC model.

 The BGC model adopts hydraulic conductivity values based on the borehole testing program and refined during model calibration, while the NRCan model applies hydraulic conductivity values derived from a direct synthesis of the borehole test data.

 A somewhat different hydrostratigraphy was used in the two models, with greater refinement in the NRCan model.

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The principal explanation for the differences in seepage estimates produced by these two models is likely the different values of hydraulic conductivity used in the two models (tailings, till, shallow bedrock), and the thickness of the till layers on the valley flanks.

There is no accepted methodology in practice for computing equivalent homogeneous hydraulic conductivity values from a suite of packer test data in a fractured rock mass. This issue is a subject of ongoing research. The issue has even greater complexity at this site because of the additional influence of basalt flow structures and vuggy porosity.

The NRCan base case model incorporates a measurement-based calculation of an effective homogeneous hydraulic conductivity for the till layer and the flood basalts (and the other units). Rather than estimate model-scale parameter values during model calibration by adjusting the initial estimates based on the geometric mean hydraulic conductivity, NRCan works directly with the packer test data to derive large-scale values for the horizontal and vertical hydraulic conductivity for each hydrostratigraphic unit. This procedure is described well in the NRCan report (page 13). It is assumed that the large-scale horizontal hydraulic conductivity is best estimated using an arithmetic mean, while the large-scale hydraulic conductivity in the vertical direction is best estimated using a geometric mean. This approach yields an effective horizontal hydraulic conductivity of 1 x 10-6 m/s for the upper basalt unit and a vertical hydraulic conductivity of 1 x 10-7 m/s. For the till, the effective horizontal hydraulic conductivity is calculated as 6 x 10-7 m/s and the vertical hydraulic conductivity is 2 x 10-7 m/s. The approach is novel; I have not encountered this method in reviews of seepage at other tailings facilities located on fractured rock.

Using the arithmetic mean to calculate a larger-scale hydraulic conductivity is likely to yield a conservative estimate of seepage because of the implicit approximation of lateral continuity of the higher hydraulic conductivity zones that were sampled in the field data set. For this setting, I agree with the argument that the horizontal hydraulic conductivity of the flood basalts is likely to be higher than a value computed by the geometric mean. This same effect is observed in the BGC analysis, where the site-wide packer test data set for the basalts (to depths of 100 m) has a geometric mean of 8.6 x10-8 m/s, and the value calibrated in their site-wide model is 2 x 10-7 m/s. It should be acknowledged that this example could either a real effect of scaling, or a fortuitous comparison influenced by the available data set.

It would be valuable to determine if the NRCan hydraulic conductivity estimates for till and basalt would yield an accepted model calibration to the hydraulic head data set and stream flow data when used in the basin-scale model, allowing for adjustment of groundwater recharge rates within realistic bounds.

6. Opinion on Seepage Predictions

In my recent experience at a number of operating metal mines, or for proposed mine developments, seepage rates (measured or predicted) through the foundation of a TSF have ranged from 10 to 300 l/s. The variation mainly reflects differences in facility design, footprint size, hydraulic conductivity of the foundation, characteristics of the tailings, and mitigation measures put in place to reduce seepage. The seepage will also depend upon the relative proportion of the TSF where groundwater enters the TSF due

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9 to upward groundwater flow from the adjacent ridge areas, and the relative proportion of the TSF with outflow in areas where natural hydrodynamic containment is absent. This latter condition will vary with the facility design and the topographic relief and geometry of the water table in the higher ground surrounding a tailings facility.

The Taseko three-dimensional model provides a reasonable basis for anticipating the general character of the seepage pathways from the proposed TSF to the surrounding streams and lakes. The quantity of seepage is uncertain. Based on the suite of scenarios that have been analyzed by Taseko and others; it is my recommendation that the range in seepage through the foundation of the TSF, for the latter part of the mine life and into closure, is 20 - 100 l/s, given the current data base.

No information was provided in the report presenting the basin-scale model on the depth to which process water originating from within the TSF may migrate. In response to a request for clarification, BGC indicated the maximum concentrations in the plume would be in a depth range from 50 - 100 m below ground surface. A depth of 100 m approximately coincides with the base of the upper, more permeable basalt layer specified in the hydrostratigraphic model. This interpretation was said to be consistent with particle tracking results obtained from the basin-scale model. The depth of plume penetration will depend, in part, on regional hydraulic head controls, a factor best examined in the regional model. Insight to the depth of plume penetration is important to the evaluation of seepage interception. This issue requires greater clarity to advance the seepage mitigation measures beyond a conceptual design.

The velocity of plume migration is likely to be higher than the values reported in the BGC calculations, given the assumption that the effective porosity of the fractured basalt is 0.01 (or 1%). The effective fracture porosity, especially below the shallow, weathered horizon, is likely to be lower than this value. Although data are sparse in the literature, a suggested range on the effective porosity of most near-surface fractured rock is from 0.01% to 1%. Groundwater velocity is inversely related to the connected void space (effective porosity) through which solutes will migrate. This would yield higher rates of plume migration in the bedrock units, although the total flow per unit area remains the same. [The same flow passing through a smaller cross-sectional area of void space must do so at a higher velocity].

7. Opinion on Seepage Mitigation Measures

The TSF pond, embankment structures, and seepage mitigation measures are best addressed within the framework of a single integrated system. In those locations around the perimeter of the TSF where natural hydrodynamic containment is absent, there will be seepage of process-affected water from the pond to the environment. This seepage will report to the seepage collection systems incorporated in the facility design, or bypass the collection systems and migrate toward groundwater discharge sites in neighbouring areas. Mitigation measures can be designed to either reduce the quantity of seepage moving out of the TSF, and/or a seepage interception system can be installed across the seepage pathways where natural hydrodynamic containment is absent.

Taseko has indicated their intention to re-contour and compact the till cover on the floor of the tailings storage facility, where necessary, to ensure a minimum thickness of 2 m of

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10 till everywhere within the footprint of the facility. There is precedent for construction of seepage blankets, composed of natural materials, at the base of a tailings storage facility. This method of seepage control is typically carried out in a rigorous manner, with design specifications on thickness and in-place hydraulic conductivity, and incorporating QC/QA procedures. Seepage blankets reduce but do not eliminate process water from entering the foundation rocks in regions of the TSF with downward fluid flow.

The suite of seepage interception measures Taseko has proposed have been evaluated at a conceptual level. However, performance of an integrated seepage management system is not illustrated in the project documents. For this reason, the water balance calculations that are presented in the report rely upon the experience and judgment of the designers in suggesting estimates for seepage collection efficiencies. The two key assumptions are the seepage collection ponds capture 50% of the foundation seepage, and the pump-back wells capture 60% of the water moving beyond the seepage collection ponds.

Pressure relief wells located below the main embankment to provide stability control are likely to have an important influence on interception of water originating from the pond. However, calculations have not been carried out to make this determination. Similarly, the seepage collection ponds, if they include an element to control the groundwater pathway (for example a grout curtain across the upper more-weathered horizon) may also have an important influence on interception of process water originating from the pond. The analysis presented by Taseko does not document in detail the influence of ground surface topography beyond the embankment structures on groundwater flow convergence toward the potential locations of seepage collection ponds. Flow convergence can be an important factor when attempting to contain process-affected water along an embankment length as long as that in the New Prosperity project design.

Groundwater pumping wells are a conventional method of intercepting process water moving beyond or outside the control region established by the embankment structures (eg. pressure relief wells, seepage collection ponds). Effective implementation of this strategy requires a comprehensive design process, an ongoing commitment to adaptive management, and financial resources for long-term operation and maintenance of the well field.

Seepage interception is challenging at the proposed location of the TSF because: (1) the generally low hydraulic conductivity of the basalts, (2) the heterogeneity of basalts and the likely occurrence of preferential flow paths that may not be easily identified in subsequent drilling programs, and (3) the considerable length of the Main and South embankments (4 km, and 3 km, respectively). Given the geologic properties of flood basalts, and the importance of fractures in contributing to the large-scale hydraulic conductivity of the rock mass, the design and operation of a pump-back system will need to incorporate a monitoring and action plan to defend against preferential flow paths that can go undetected in field investigations completed for feasibility-level evaluations, or in detailed design.

Once monitoring data triggers the initiation of groundwater pump-back, it may take many months of groundwater level and groundwater quality monitoring, and system adjustments to achieve high interception efficiency. As a basis for evaluation at this time, I suggest a realistic target may be 80 - 90% capture efficiency, assuming system monitoring and optimization.

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A conceptual demonstration of seepage interception at the Main Embankment has been provided in the model studies. The report does not illustrate a similar design for the South Embankment. Higher seepage flows out of the TSF will require a greater number of interception wells.

To advance the conceptual design of the migration control system, it will be essential to conduct one or more pilot tests for interceptions well in the upper basalt layer to evaluate pumping capacities and distance-drawdown relationships. Taseko has suggested conducting these investigations during detailed design of the seepage management system. For the EIA submission, Taseko has chosen what I consider a conservative value for interception efficiency - 60%.

It is accepted practice that the design of an effective seepage interception system should be based on an adaptive management approach, using observational data on hydraulic head changes and solute concentrations in a comprehensive monitoring network to adjust pumping rates and add extraction wells as required to achieve the required interception efficiency. This would be an essential feature of a seepage management system, given the heterogeneous nature of hydraulic conductivity variations in the flood basalts. The need for pilot tests of pump-back wells is noted in the BGC model report, in the first bullet of the Recommendations section (page 29).

8. Opinion on Potential Risks of Seepage from the TSF Entering Nearby Lakes

The Taseko three-dimensional model demonstrates that, without mitigation measures in place, seepage pathways exist to Fish Lake, Wasp Lake, and the Onion Lakes (Figure 42 of the BGC report). Estimates of seepage volumes to each water body are provided; these values will vary with the estimated magnitude of the total seepage from the TSF. The pathways to these lakes may be entirely within the subsurface, or the process- affected water may emerge in springs or stream channels where the water table intersects the ground surface, and then move as a component of surface flow or shallow interflow to the lakes.

The seepage mitigation measures described above have the potential to substantially reduce the volume of seepage, but not eliminate seepage from entering Fish Lake, Wasp Lake and the Onion Lakes. Each of these water bodies is located downstream of a sector of the TSF where natural hydrodynamic containment is not present, for the design height of the TSF impoundment.

Insufficient information was given in the reports I reviewed to provide a firm opinion on the potential for seepage originating from the TSF to reach the Taseko River. Without mitigation, it seems likely that this will be the case, based on the water table geometry in the general area of Big Onion Lake. However, this final leg of the seepage pathway, and solute concentrations, will depend upon the nature of the hydrogeologic connection between Big Onion Lake and the Taseko River. It is also possible , within the accuracy that can be attributed to the groundwater flow and solute transport models, that a process water plume (or part of the plume) could bypass Big Onion Lake and move directly to the river (Figure 42 of the basin-scale modeling report).

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To aid the Panel, I suggest a simple working estimate of a range in seepage volumes could be derived by taking the proportional seepage volumes reporting to these lakes as given in the Taseko three-dimensional model, applying those ratios to a range of seepage estimates (20 - 100 l/s), and adopting an assumed interception efficiency of 80 - 90% for solutes passing beyond the embankment structures. These estimates would be reduced further by an assumed efficiency of the planned seepage collection ponds.

The timing of impacts after startup will remain uncertain due to the difficulty in anticipating groundwater velocities in the fractured bedrock, until sufficient monitoring data is collected to benchmark the then-current groundwater flow and solute transport models (after revision of the models during detailed design). The only realistic way to address this uncertainty in timing is to have a "baseline" interception system in place at the start of mining operations, complemented by a well-crafted performance monitoring network located between the interception wells and the embankments.

Independent Technical Review of Seepage Predictions for the Tailings Storage Facility