Sustainable Reuse of Mine Tailings and Waste Rock As Water-Balance Covers

minerals

Article Sustainable Reuse of Mine Tailings and Waste Rock as Water-Balance Covers

Mohammad H. Gorakhki and Christopher A. Bareither *

Civil & Environmental Engineering, Colorado State University, Fort Collins, CO 80523, USA; [email protected] * Correspondence: [email protected]; Tel.: +1-970-491-4660

Received: 1 June 2017; Accepted: 18 July 2017; Published: 24 July 2017

Abstract: The focus of this study was to evaluate the potential reuse of mixed mine tailings and waste rock in water-balance covers (WBCs). Reuse of mine waste in geoengineering applications can provide an economic advantage via offsetting raw material requirements and reducing waste volumes to manage. Water-balance covers are designed to minimize percolation and/or oxygen ingress into underlying waste via moisture retention while also providing resistance against slope failure and erosion of cover materials. Water-balance simulations were conducted using a variably-saturated one-dimensional numerical model to assess hydrologic behavior of an actual WBC as well as hypothetical mixed mine waste WBCs. The actual water balance cover included a 1.22-m-thick silty-sand storage layer and a 0.15-m-thick topsoil layer. Three scenarios were evaluated via hydrologic modeling that focused on replacing the actual storage layer with a layer of mine waste: (1) storage layers were simulated as 1.22-m-thick layers of pure mine tailings (i.e., copper, gold, coal, and oil sand tailings); (2) storage layers were simulated as 1.22-m-thick layers of mixed mine tailings and waste rock; and (3) mixed mine tailings and waste rock storage layer thicknesses were redesigned to yield comparable percolation rates as the actual cover.

Keywords: covers; hydrology; sustainability; tailings; waste rock

1. Introduction The increased consumption of raw materials due to population growth has increased demand on natural resources. In turn, the generation of mine waste has increased, which require innovative and sustainable waste management considerations. In the mining industry, waste materials include waste rock discarded from mining operations and ﬁne-grained tailings produced during ore extraction processes. The Mining, Minerals, and Sustainable Development Project (MMSD) reports that approximately 3500 active mine waste facilities exist worldwide. Disposal and management of mine tailings in impoundments and waste rock in gravity piles can be challenging due to variability in physical and chemical properties of the mine waste. Using mine tailings and waste rock as earthwork materials (e.g., water balance cover) can provide a sustainable and cost effective alternative to mitigate disposal and management challenges. Mine waste is categorized as a non-hazardous material based on Subtitle D of the Resource Conservation and Recovery Act [1]. Non-hazardous waste facilities are required to have covers to minimize percolation into the underlying waste. Permeability of cover soils must be less than or equal to the permeability of the liner system or ≤10−5 cm/s [2], such that water passing through a cover does not exceed the volume of water exiting through the liner. Considerably higher cover permeability can lead to a “bathtub effect” [2], whereby water ponds inside the waste on the liner and increases leachate generation. There are two main types of cover systems used to close waste facilities: (i) conventional covers and (ii) water-balance covers (WBCs). Conventional cover systems rely on low-permeability soil layers

Minerals 2017, 7, 128; doi:10.3390/min7070128 www.mdpi.com/journal/minerals Minerals 2017, 7, 128 2 of 17 and/or impermeable geomembranes to minimize percolation [3,4]. Water-balance covers (also known as store-and-release, evapotranspirative, or alternative covers) rely on a balance between precipitation, soil water storage, evaporation, and transpiration to limit percolation. Thus, WBCs function based on principles of unsaturated flow to control percolation into underlying waste [5–8]. These covers are viable for long-term isolation of waste, particularly in semi-arid and arid regions where precipitation is balanced by evaporation and transpiration. The costs associated with WBCs are typically less than conventional covers when suitable soil is available; for example, constructing a 1200-mm-thick WBC in OR, USA resulted in 64% cost savings relative to a 460-mm-thick compacted clay cover [2]. Water-balance covers are intrinsically sustainable as they employ natural hydrologic processes congruent with the surrounding landscape, which reduces long-term maintenance requirements. Local materials are typically employed to minimize transportation costs, which can reduce energy consumption and emissions. An additional opportunity to enhance the sustainability of WBCs is to use waste materials or industrial by-products in the cover system. Mining provides an opportunity to reuse waste materials in cover systems considering that (i) enormous volumes of mine wastes are generated during ore extraction processes and (ii) mine waste management facilities (e.g., tailing storage facilities, waste rock piles, heap leach pads) require covers for site closure. The two predominant mine wastes that require short- and long-term management are tailings and waste rock [9,10]. Tailings typically are fine grained and have high water contents (low solids contents), whereas waste rock generally is gravel- to cobble-sized material with sand and fines. Mine tailings have been shown to have moisture retention characteristics comparable with naturally occurring fine sand, silt, and clay [11–13] and field-scale studies have documented the effectiveness of using mine tailings in the water storage layers of WBCs [14–16]. An effective WBC for a mine waste management facility shall provide long-term resistance against percolation of precipitation and ingress of oxygen into underlying waste (hydrologic performance) as well as resistance against slope failure and erosion of the cover materials (mechanical performance). The potential leaching of contaminants (e.g., heavy metals) from mine wastes used in WBCs is also a concern. However, mine wastes with the propensity to generate contaminated leachate are not candidate materials for use in WBCs. The focus herein is on the hydraulic behavior of WBCs composed of mixed mine waste, and the mine waste considered in this study are assumed to have negligible leaching concerns. Fine-grained soils and mine tailings can have low shear strength and high susceptibility to erosion that can preclude their use in cover systems; however, these materials also have ideal hydrologic properties for use as water storage layers in WBCs [15,16]. Mine waste rock has been shown to have shear strength parameters comparable with naturally occurring gravels [13]. The addition of waste rock to mine tailings, known as co-mixed waste rock and tailings (WR&T), has been proposed as an alternative mine waste management approach to enhance impoundment stability, reduce acid rock drainage, reduce storage volume and land required for waste management facilities, and reduce liquefaction potential of tailings [13,17,18]. Waste rock and tailings can be mixed proportionately to develop a material with enhanced strength via waste rock and lower hydraulic conductivity via mine tailings [9,19]. The use of mine tailings in cover systems at mine facilities has been evaluated on a trial basis [14,20], but broad-scale adoption has not occurred. Cover test sections consisting of co-mixed WR&T have not been evaluated due to uncertainty in hydrologic behavior of the co-mixed material as well as mixing and deployment of the material as a homogeneous layer in a cover system. The objective of this study was to assess the viability of using a co-mixed layer of WR&T as the storage layer in a WBC via hydrologic modeling. Three tasks were completed to address this objective: (i) evaluate theoretical WBCs containing mine tailings; (ii) evaluate the effect of waste rock addition on hydrologic behavior; and (iii) evaluate storage capacity of co-mixed WR&T covers that have the potential to yield comparable percolation rates to covers with no waste rock inclusions. Water-balance modeling was completed using meteorological data for a semi-arid site in the Western U.S. where an actual WBC test section has been constructed [21]. This actual WBC was used for comparison to all theoretical WBCs created with mine tailings and waste rock. Minerals 2017, 7, 128 3 of 17

Minerals 2017, 7, 8 3 of 17 2. Materials and Methods 2.1. Soils and Mine Tailings 2.1. Soils and Mine Tailings Geotechnical properties of the cover soils from Benson and Bareither [21] and mine tailings from QiuGeotechnical and Sego [12] properties are summarized of the cover in Table soils 1. from The particle-size Benson and distribution Bareither [(PSD)21] and of minethe silty-sand tailings from Qiustorage and Sego layer [12 soil] are and summarized four mine tailings in Table are shown1. The in particle-size Figure 1a. The distribution silty-sand contained (PSD) of 33% the gravel; silty-sand storagehowever, layer all soil mine and tailings four mine contained tailings only are sand shown and fine-grained in Figure1a. particles The silty-sand (Table 1). contained The fines content 33% gravel; however,(particles all mine< 0.075 tailings mm) of containedthe mine tailings only sandranged and from fine-grained 21% for oil sand particles tailings (Table to 77%1). for The gold fines mine content tailings. Soil water characteristic curves (SWCCs) of the cover soils and mine tailings are shown in (particles < 0.075 mm) of the mine tailings ranged from 21% for oil sand tailings to 77% for gold mine Figure 1b. These SWCCs were obtained from Qiu and Sego [12] and Benson and Bareither [21], and tailings.are shown Soil water in Figure characteristic 1b as SWCCs curves fitted with (SWCCs) the van of Genuchten the cover [22] soils equation: and mine tailings are shown in Figure1b. These SWCCs were obtained from Qiu and Sego [ 12] and Benson and Bareither [21], and are m shown in Figure1b as SWCCs fitted with the van Genuchten 1  [22] equation: θθ=+() θ − θ (1) rsr+⋅αψn 1 () 1 m θ = θr + (θs − θr) (1) where θ is volumetric water content, θs is saturated1 + (volumetricα · Ψ)n water content, θr is residual volumetric water content, Ψ is soil suction, α and n are fitting parameters, and m = (1 − 1/n). All van whereGenuchtenθ is volumetric parameters water for content,the SWCCsθs is shown saturated in Figure volumetric 1b are compiled water content, in Tableθ 1.r is residual volumetric water content, Ψ is soil suction, α and n are fitting parameters, and m = (1 − 1/n). All van Genuchten Table 1. Characteristics of soils and mine tailings evaluated for water balance covers. parameters for the SWCCs shown in Figure1b are compiled in Table1.

α, Ψa Sand Silt Clay ks (cm/s) ks (cm/s) SoilTable 1. Characteristicsθs θr of soilsn and mine tailings evaluated for water balance covers.Ropt 1/cm (cm) (%) (%) (%) (Actual) (Modified)

−6 −5 Top Soil 0.50 0.00α , 0.0049 1.33 Ψ 205.76a Sand -- Silt -- --Clay 2.8 × 10ks (cm/s)2.8 × 10 ks (cm/s)- Soil θs θr n Ropt Silty-Sand 0.35 0.001/cm 0.0142 1.27 (cm) 70.27 (%) 34 (%) -- -- (%) 6.0 × 10(Actual)−5 6.0 × 10−4(Modiﬁed) 2.01 Top Soil 0.50 0.00 0.0049 1.33 205.76 ––– 2.8 × 10−6 2.8 × 10−5 - Copper 0.46 0.01 0.0196 1.453 50.99 69 30 1 7.6 × 10−5 7.6 × 10−4 2.43 Silty-Sand 0.35 0.00 0.0142 1.27 70.27 34 – – 6.0 × 10−5 6.0 × 10−4 2.01 CopperGold 0.46 0.450.01 0.000.0196 0.01631.453 1.33 50.99 61.18 69 23.5 71.5 30 5 1 4.3 × 107.6−5 × 10 4.3−5 × 10−47.6 ×2.3810 −4 2.43 Gold 0.45 0.00 0.0163 1.33 61.18 23.5 71.5 5 4.3 × 10−5 4.3 × 10−4 2.38 Coal 0.47 0.04 0.0054 1.249 183.50 35 39 26 1.2 × 10−6 1.2 × 10−5 2.49 Coal 0.47 0.04 0.0054 1.249 183.50 35 39 26 1.2 × 10−6 1.2 × 10−5 2.49 Oil Sand aOil Sand0.39 a 0.390.00 0.000.0167 0.01671.34 1.34 61.18 61.18 67 67 24 24 9 9 2.7 × 102.7−7 × 10 2.7−7 × 10−62.7 ×2.1610 −6 2.16 Note: θs = saturated volumetric water content; θr = residual volumetric water content; α and n = Van Note: θs = saturated volumetric water content; θr = residual volumetric water content; α and n = Van Genuchten ﬁttingGenuchten parameters, fittingΨa = parameters, air entry pressure; Ψa = airks entry= saturated pressure; hydraulic ks = saturated conductivity; hydraulic and R conductivity;opt = optimum and mixture Ropt ratio. a Low= optimumks of oil sand mixture tailings ratio. attributed a Low k tos of presence oil sand oftailings bitumen attributed [12]. to presence of bitumen [12].

100 6 10 (a) 5 (b) 80 10 4 Oil Sand Tailings 10 60 3 Coal Tailings 10 2 Gold Tailings 40 10 1 Copper Tailings Suction (kPa) Suction 10 Percent (%) Passing 20 0 Silty Sand 10 -1 0 10 100 10 1 0.1 0.01 0.001 0 0.1 0.2 0.3 0.4 0.5 Particle Size (mm) Water Content

FigureFigure 1. Particle-size-distributions 1. Particle-size-distributions ((aa) and soil soil water water characteristic characteristic curves curves (b) for (b) silty-sand for silty-sand in the in the NaturalNatural Cover Cover from from Benson Benson and and Bareither Bareither [21] [21] and and go gold,ld, copper, copper, coal, coal, and and oil sand oil sand tailings tailings from fromQiu Qiu andand Sego Sego [12 ].[12].

The θs (which is equivalent to porosity) of copper, gold, and coal mine tailings were similar (0.45 The θs (which is equivalent to porosity) of copper, gold, and coal mine tailings were similar to 0.47), whereas θs of the silty-sand and oil sand tailings were lower (Table 1). These lower θs were (0.45due to 0.47),to higher whereas coarse-grainedθs of the contents silty-sand (i.e., and sand oil and sand gravel). tailings Thewere air entry lower pressure (Table (Ψ1).a) Theseof the silty lower θs weresand, due oil to highersand, gold, coarse-grained and copper mine contents tailings (i.e., were sand similar and and gravel). ranged The from air 5 entry to 6.9 pressure kPa; however, (Ψa) of the siltythe sand, Ψa oilof coal sand, mine gold, tailings and copperand top mine soil were tailings higher were (Table similar 1) due and to ranged the higher from clay 5 to content 6.9 kPa; of however,the the Ψcoala of tailings coal mine and tailingshigh fines-fraction and top soil of the were top higher soil. (Table1) due to the higher clay content of the coal tailings and high ﬁnes-fraction of the top soil. Minerals 2017, 7, 128 4 of 17

Saturated hydraulic conductivity (ks) of the soils and mine tailings are also in Table1. The ks of the −5 −5 silty sand, copper, and gold mine tailings were in a close range of 4.3 × 10 to 7.6 × 10 cm/s. The ks of coal mine tailings and top soil were approximately one order of magnitude lower (~2 × 10−6 cm/s) −7 and ks of the oil sand mine tailings was two orders of magnitude lower (3 × 10 cm/s). The lower ks of coal and oil sand mine tailings is due to the higher clay fraction of these mine tailings (Figure1a and Table1). Saturated hydraulic conductivity was increased by one order of magnitude (modiﬁed ks) to be the representative of in-service, post-construction covers [23]. Details on the SWCC and ks measurements are provided in [12,21,24].

2.2. Water Balance Cover Design and Modeling

2.2.1. Storage Assessment Design of a WBC includes (i) preliminary design and (ii) numerical modeling [2]. Preliminary design is completed to estimate the required cover thickness from a water storage analysis:

∆S = P − R − β · PET − L − Pr (2) where ∆S is soil water storage, P is precipitation, R is surface runoff, β is ET/PET ratio, PET is potential evapotranspiration, L is lateral drainage, and Pr is percolation. The required storage (Sr) for a WBC can be computed via summing storage (∆S in Equation (2)) for months where ∆S > 0 [2]. The available water storage (SA) in a given soil layer is computed as the difference between water content at ﬁeld capacity and wilting point:

SA = H · (θc − θm) (3) where θc is volumetric water content at ﬁeld capacity (Ψ = 33 kPa), θm is volumetric water content at the wilting point (Ψ = 1500 kPa), and H is thickness of the water storage layer. The H in Equation (3) is optimized in a WBC design to determine a water storage layer meeting the requirement of SA ≥ Sr.

2.2.2. Water-Balance Modeling Prior to construction of a WBC, water-balance modeling is completed to evaluate hydrologic behavior of the proposed WBC design. Water-balance modeling was completed in this study using the code WinUNSAT-H, which simulates variably saturated flow, root water uptake, and climatic interaction [24–27]. WinUNSAT-H is an implementation of the variably-saturated flow code UNSAT-H [28] used for near surface hydrology. When properly parameterized, WinUNSAT-H provides a reliable prediction of hydrology for WBCs, and modestly overpredicts percolation [26,27,29]. Water-balance modeling is typically completed for climate conditions representative of the wettest years or wettest periods (i.e., 5 to 10 sequential years) on record [2]. Water-balance metrics considered in the hydrologic performance of a WBC include runoff, evapotranspiration (ET), soil water storage (SWS), and percolation. Percolation often is the main parameter of interest to compare with prescribed percolation rates or regulatory thresholds for a given site. For example, the WBC at the solid waste site described in Benson and Bareither [21] has a maximum percolation rate of 4 mm/year. In general, an average annual percolation rate <3 mm/year is required for a WBC [21]. Variably-saturated flow in UNSAT-H is simulated via the modified-Richards’ Equation [25,28]:

∂θ ∂Ψ ∂ ∂θ = − [k + ku + qvt] − S(z, t) (4) ∂Ψ ∂t ∂z T ∂Ψ where t is time, z is the vertical coordinate, ku is unsaturated hydraulic conductivity, kT = ku + kvΨ, where kvΨ is isothermal vapor conductivity, qvt is thermal vapor flux density, and S(z,t) is a sink term representing water uptake by vegetation. The relationship between θ and time at each node in a numerical simulation is obtained from Equation (4). The sink term was simulated by applying the Minerals 2017, 7, 128 5 of 17 transpiration demand among nodes in the root zone in proportion to the root density profile. Potential evapotranspiration (PET) is computed in WinUNSAT-H via the Penman [30] equation: ∆ · Rn γ U PET = + 0.27 1 + (ea − e ) (5) ∆ + γ ∆ + γ 100 d where ∆ is the slope of the saturation vapor pressure–temperature curve, γ is the psychrometric constant, Rn is net solar radiation, U is average 24-h wind speed measured at 2 m above the ground surface, ea is saturation vapor pressure at mean air temperature, and ed is actual vapor pressure. The θ-Ψ relationship (i.e., SWCC) and θ-ku relationship are required for variably-saturated flow. The θ-Ψ relationship was represented with Equation (1) and model parameters summarized in Table1. The θ-ku relationship was simulated with the van Genuchten–Mualem function as:

λ 2 1 m 1 m ku = ks · 1 − 1 − (6) 1 + (α · Ψ)n 1 + (α · Ψ)n where λ is the pore interaction term, which was assumed −2 for all simulations [31], and m = (1 − 1/n).

2.2.3. Test Site, Vegetation Characteristics, and Meteorological Data The baseline WBC used in this study for comparison to covers composed of tailings and co-mixed WR&T is a monolithic cover located at a disposal site in the Western U.S. [21,24]. This WBC consisted of a 150-mm-thick top soil layer overlaying a 1220-mm-thick storage layer composed of silty sand (Table1). Average annual precipitation for this site was 337 mm for 1949 to 2010 and average potential evapotranspiration was 842 mm [24]. Thus, the ratio of precipitation to potential evapotranspiration (P/PET) was 0.40, which is representative of a semi-arid climate in the Western U.S. and is comparable to a broad range of mining sites in the U.S. and throughout the world. Vegetation characteristics for water-balance modeling were obtained from site-speciﬁc measurements reported in Benson and Bareither [21]. A leaf area index (LAI) of 1.42 and root density function from Bareither et al. [24] were used in all hydrologic models. The wilting point was set at 3532 kPa, the anaerobiosis point at 32 kPa, and the limiting point at 146 kPa [24,32].

2.2.4. Boundary and Initial Conditions Boundary conditions included an atmospheric flux boundary for the cover surface and a unit gradient boundary at the base of the cover [24]. An initial water balance simulation was conducted with data from 2004 that was run 5-year sequentially to develop an initial θ-Ψ distribution for the cover profile to use as an initial condition [2]. Data from 2004 were used to represent a typical year within the 20-year period from 1990 to 2010 (period evaluated for this study) and favor a wetter initial soil profile such that percolation would not be underestimated. An initial distribution of θ-Ψ was obtained for each model simulation that incorporated a different material used to represent the storage layer (e.g., mine tailings or WR&Ts). Each model conducted for this study included yearly simulations for each year in the 20-year data set from 1990 to 2010. Following the simulation in Year 1, initial conditions for each subsequent year (e.g., Year 2, 3, 4, etc.) were obtained from the final soil moisture profile at the end of the previous year. The 20-year water-balance model completed for the actual WBC was adopted from Bareither et al. [24] and is referred to herein as the Natural Cover. Full 20-year simulations were completed for each of the mine tailings used as a replacement material for the silty-sand water storage layer.

2.3. Water-Balance Covers Composed of Mine Waste Water-balance models consisting of 20-year simulations for 1990–2010 were completed for the following scenarios: (i) mine tailings used to replace the 1220-mm-thick storage layer in the Natural Cover; (ii) co-mixed WR&T with different fractions of waste rock used to replace the 1220-mm-thick Minerals 2017, 7, 128 6 of 17 storage layer in the Natural Cover; and (iii) co-mixed WR&T with storage layer thickness adjusted to compensate for reduced storage due to waste rock particle inclusions. Storage layers in the water-balance models that consisted of pure tailings incorporated the hydrologic properties in Table1. The ks of mine tailings storage layers were assumed unchanged by the inclusion of waste rock particles since the tailings fraction controls flow through the mixed material. The SWCC parameters were modified to account for a reduction in water storage capacity of the tailings fraction via inclusion of solid waste rock particles following recommendations in Bareither and Benson [33]. The effect of gravel content on ks of a fine-grained material was evaluated in Shelley and Daniel [34]. They reported that gravel addition did not considerably change ks of mixtures for gravel contents up to 50%, by mass. However, the addition of ≥60% gravel content increased ks 5 to 6 orders of magnitude. Wickland et al. [19] compared ks of tailings and WR&T mixtures that contained 80% waste rock, and reported similar ks for effective stress ≤20 kPa. This magnitude of effective stress is representative of WBCs [2]. Thus, ks was assumed unchanged by the addition of waste rock particles such that the finer, tailings matrix controlled flow for all water-balance simulations completed for this study. Bareither and Benson [33] investigated the influence of gravel inclusions on the SWCC of sandy soils. They reported that the SWCC of material containing a coarser and finer fraction can be approximated based on (i) modifying θs of the mixed material in accordance with the Bouwer–Rice method [35] and (ii) using van Genucthen SWCC parameters (α and n) of the finer fraction. The Bouwer–Rice equation used to compute the corrected θs (θs−c) is

θs-c = (1 − VR) · θs- f ine (7) where θs-fine is θ of the finer soil fraction and VR is the volumetric fraction of coarse particles. Thus, for all co-mixed WR&T water storage layers simulated in this study, van Genuchten parameters tabulated for the mine tailings in Table1 were used with θs-c computed based on Equation (7). Waste rock and mine tailings mixtures can range from fine-dominated mixtures that consist predominantly of the tailings fraction, to coarse-dominated mixtures that consist predominantly of the waste rock fraction. The mixture ratio (R) commonly used for WR&T mixtures is defined as

R = Mwr/Mt (8) where Mwr is dry mass of waste rock and Mt is dry mass of tailings. The optimum mixture ratio (Ropt) is defined as a mixture where the finer fraction (tailings) just fills the void space between the coarse particles (waste rock). Co-mixed WR&T prepared at Ropt have been reported to have shear strength representative of the waste rock and hydrologic behavior representative of the tailings fraction [18]. An equation for Ropt is Ropt = (1 + et)/eWR (9) where et is the tailings void ratio and eWR is waste rock void ratio. Equation (9) was developed assuming that the specific gravity of tailings and waste rock are the same and density of water = 1 g/cm3. Optimum mixture ratios were computed for each mine tailings via determining et that corresponded to θs and accounting for an eWR = 0.76, which was reported for a crushed gravel with a PSD representative of hard rock mine waste rock in a loose particle arrangement [18]. Two methods were evaluated in this study to redesign the water storage layer thickness for a co-mixed WR&T cover. In both methods, Sr was assumed constant since this was computed based on historical MET data, and SA was re-calculated. The first method, referred to as Method 1, followed the same design criteria as recommended in Albright et al. [2] with SA computed via Equation (3). Thickness of the storage layer including waste rock (HWR) was computed as

HNWR · (θc-NWR − θm-NWR) HWR = (10) (θc-WR − θm-WR) Minerals 2017, 7, 8 7 of 17

MineralsThe2017 second, 7, 128 method, referred to as Method 2, was developed to maintain a consistent 7void of 17 volume between the pure tailings storage layers and storage layers consisting of WR&T. The redesigned storage layer thickness based on Method 2 was computed as where HNWR is thickness of the storage layer with no waste rock, θc-NWR is volumetric water content of soil with no waste rock at field capacity, θ is volumetric water contentH NWR of soil with no waste HHVH⋅=θθ−−()m-NWR(1 − )  = NWR s NWR WR R s NWR WR 1 − V (11) rock at the wilting point, θc-WR is volumetric water content of soil with wasteR rock at field capacity, and θm-WR is volumetric water content of soil with waste rock at the wilting point. where θs-NWR is saturated volumetric water content of a tailings layer with no waste rock and VR is the volumetricThe second fraction method, of coarse referred material to as (i.e., Method waste 2, wasrock). developed to maintain a consistent void volume betweenA summary the pure of tailings the co-mixed storage layers WR&T and storage storage layers layers redesigned consisting offollowing WR&T. TheMethods redesigned 1 and storage 2 is in Tablelayer thickness2. Methods based 1 and on 2 Methodwere applied 2 was to computed redesign as storage layers containing coal mine tailings with VR = 30% and 45%, whereas only Method 2 was used to redesign storageH NWRlayers containing copper HNWR · θs-NWR = (HWR(1 − VR))θs-NWR ⇒ HWR = (11) mine tailings with VR = 30% and 45%. An example of the Method 1 redesign1 − procedureVR for coal mine tailings is shown in Figure 2. The difference in volumetric water contents used to compute SA (θc − where θs-NWR is saturated volumetric water content of a tailings layer with no waste rock and VR is the θm) for the storage layer with only coal mine tailings was 0.20 (Figure 3). This difference (θc − θm) volumetric fraction of coarse material (i.e., waste rock). decreased to 0.135 and 0.102 for coal mine tailings with 30% and 45% waste rock addition, A summary of the co-mixed WR&T storage layers redesigned following Methods 1 and 2 is in respectively (Figure 2). The storage layer thickness for each of the 30% and 45% waste rock additions Table2. Methods 1 and 2 were applied to redesign storage layers containing coal mine tailings with was computed via Equation (11) to yield thicknesses reported in Table 2. As anticipated, higher waste VR = 30% and 45%, whereas only Method 2 was used to redesign storage layers containing copper rock content led to an increase in storage layer thickness due to reduced water storage of the material. mine tailings with VR = 30% and 45%. An example of the Method 1 redesign procedure for coal The Method 2 redesign procedure is independent of soil type in the storage layer and only mine tailings is shown in Figure2. The difference in volumetric water contents used to compute depends on waste rock content and initial θs (Equation (11)). The redesigned storage layer thickness SA (θc − θm) for the storage layer with only coal mine tailings was 0.20 (Figure3). This difference with coal mine tailings based on Method 2 with 30% waste rock was 1740 mm and with 45% waste (θc − θm) decreased to 0.135 and 0.102 for coal mine tailings with 30% and 45% waste rock addition, rock was 2220 mm. Method 2 yielded thinner cover thicknesses in comparison with Method 1 (i.e., respectively (Figure2). The storage layer thickness for each of the 30% and 45% waste rock additions reduced thickness by 70 and 170 mm) for both waste rock contents simulated with the coal tailings. was computed via Equation (11) to yield thicknesses reported in Table2. As anticipated, higher waste rock content led to an increase in storage layer thickness due to reduced water storage of the material. Table 2. Water balance covers simulated with coal and copper mine tailings that had varying waste rock contents. Cover thicknesses were fixed and adjusted following Methods 1 and 2. Table 2. Water balance covers simulated with coal and copper mine tailings that had varying waste rock contents. CoverWaste thicknesses Rock were fixed and adjusted followingStorage Methods Layer 1 and 2.Percolation Soil/Tailings Modeling Condition Content (%) Height (mm) Rate (mm/year) Waste Rock Storage Layer Percolation Rate Soil/Tailings 0 Modeling- Condition 1220 0.200 Content30 (%) Fixed height Height1220 (mm) (mm/year)0.260 30 0Adjusted height-Method - 1 12201810 0.2000.135 Coal mine 3030 Adjusted Fixed height-Method height 2 12201740 0.2600.135 tailings 30 Adjusted height-Method 1 1810 0.135 Coal mine 4530 AdjustedFixed height-Method height 2 17401220 0.1350.830 tailings 4545 Adjusted Fixed height-Method height 1 12202390 0.8300.075 4545 Adjusted Adjusted height-Method height-Method 2 1 23902220 0.0750.075 0 45 Adjusted height-Method- 2 22201220 0.0753.17 Copper mine 30 0Fixed height - 1220 3.174.71 Coppertailings mine 3030 Adjusted Fixed height-Method height 2 12201770 4.713.36 tailings 30 Adjusted height-Method 2 1770 3.36 4545 Adjusted Adjusted height-Method height-Method 2 2350 3.093.09

1000000 Storage WR = 0% Coal mine 100000 Storage tailings WR = 30% 10000 ψ = 1500 kPa WR=0% 1000 WR=30% WR=45%

Suction (kPa) 100 ψ = 33 kPa

10 Storage WR = 45% 1 00.10.20.30.40.5 Water Content FigureFigure 2. Method 2. Method 1 redesign 1 redesign for water for balance waterbalance cover height cover with height waste with rock waste addition rock to addition coal mine to tailings. coal mine tailings.

Minerals 2017, 7, 8 8 of 17

3. Results

3.1. Fixed Storage Layer Thickness Composed of Mine Tailings Water-balance metrics predicted by WinUNSAT-H for the 20-year simulations on the Natural Cover and WBCs that included pure mine tailings are compiled in Table 3. Annual average precipitation was 331.8 mm for the 20-year period, which was higher than the annual average evapotranspiration (ET) for all five simulated WBCs. The higher precipitation relative to ET resulted in runoff, percolation, and/or an increase in average soil water storage (SWS).

Table 3. Water-balance metrics for the Natural Cover and WBCs with copper, gold, coal, and oil sand tailings.

Simulated Evapo- Runoff Average Soil Water Average Saturation Percolation Water Balance transpiration (mm/year) Storage (mm) Degree (%) (mm/year) Cover (mm/year) Natural Cover 328.6 0.215 151.6 30.3 2.36 Copper Tailings 327.4 0.185 91.1 18.3 3.17 Gold Tailings 329.6 0.18 144.1 28.9 1.69 Coal Tailings 325.6 0.18 303.7 60.9 0.20 Oil Sand 314.9 2.17 120.4 24.1 0.00 Tailings

Relationships between ks and annual average runoff, ET, and percolation for the silty-sand cover and four WBCs with mine tailings are shown in Figure 3. The higher annual runoff predicted for the oil sand tailings cover resulted from a low ks (Figure 3a) combined with large precipitation events that occurred over a short time. Runoff was relatively low since the models were designed to be conservative, which led to reduced runoff and increased percolation and SWS. Runoff was <0.7% of total precipitation in the oil sand tailings cover and runoff was <0.07% for all other models. Thus, the effect of runoff on hydrologic performance of the WBCs in this study was considered negligible. Annual average ET of the Natural Cover and four WBCs with mine tailings ranged from 314.9 to 329.6 mm/year (Table 3) and increased with decreasing ks (Figure 3b). The potential ET for each simulation was independent of cover soil and calculated with the Penman–Monteith equation in WinUNSAT-H. Evapotranspiration for the different covers was a function of how fast water could be delivered to the soil surface via evaporation and the accessibility of water to plant roots for transpiration. Evapotranspiration was in a similar range for the Natural Cover, gold tailings, and copper tailings since these materials had comparable ks (Figure 3b). The trend line in Figure 3b suggests that a modest decrease in ET can be anticipated with a decrease in ks when all other water- Minerals 2017, 7, 128 8 of 17 balance modeling factors are held constant (e.g., meteorological data, vegetation data, etc.).

3 350 4 (a) (b) (c) 340 3 2 330 2 320 1

Runoff (mm/yr) Runoff 1 310 Percolation (mm/yr) Percolation

0 Evapotranspiration (mm/yr) 300 0 -6 -5 -4 -3 -6 -5 -4 -3 -6 -5 -4 -3 10 10 10 10 10 10 10 10 10 10 10 10 k (cm/s) k (cm/s) k (cm/s) s s s

FigureFigure 3.3. RelationshipsRelationships betweenbetween annualannual averageaverage ((aa)) runoff;runoff; ((bb)) evapotranspiration;evapotranspiration; andand ((cc)) percolationpercolation versus saturated hydraulic conductivity (k ) of silty sand and mine tailings. versus saturated hydraulic conductivity (ks s) of silty sand and mine tailings.

The Method 2 redesign procedure is independent of soil type in the storage layer and only depends on waste rock content and initial θs (Equation (11)). The redesigned storage layer thickness with coal mine tailings based on Method 2 with 30% waste rock was 1740 mm and with 45% waste rock was 2220 mm. Method 2 yielded thinner cover thicknesses in comparison with Method 1 (i.e., reduced thickness by 70 and 170 mm) for both waste rock contents simulated with the coal tailings.

3. Results

3.1. Fixed Storage Layer Thickness Composed of Mine Tailings Water-balance metrics predicted by WinUNSAT-H for the 20-year simulations on the Natural Cover and WBCs that included pure mine tailings are compiled in Table3. Annual average precipitation was 331.8 mm for the 20-year period, which was higher than the annual average evapotranspiration (ET) for all ﬁve simulated WBCs. The higher precipitation relative to ET resulted in runoff, percolation, and/or an increase in average soil water storage (SWS).

Table 3. Water-balance metrics for the Natural Cover and WBCs with copper, gold, coal, and oil sand tailings.

Evapo- Average Soil Average Simulated Water Runoff Percolation Transpiration Water Storage Saturation Balance Cover (mm/year) (mm/year) (mm/year) (mm) Degree (%) Natural Cover 328.6 0.215 151.6 30.3 2.36 Copper Tailings 327.4 0.185 91.1 18.3 3.17 Gold Tailings 329.6 0.18 144.1 28.9 1.69 Coal Tailings 325.6 0.18 303.7 60.9 0.20 Oil Sand Tailings 314.9 2.17 120.4 24.1 0.00

Relationships between ks and annual average runoff, ET, and percolation for the silty-sand cover and four WBCs with mine tailings are shown in Figure3. The higher annual runoff predicted for the oil sand tailings cover resulted from a low ks (Figure3a) combined with large precipitation events that occurred over a short time. Runoff was relatively low since the models were designed to be conservative, which led to reduced runoff and increased percolation and SWS. Runoff was <0.7% of total precipitation in the oil sand tailings cover and runoff was <0.07% for all other models. Thus, the effect of runoff on hydrologic performance of the WBCs in this study was considered negligible. Annual average ET of the Natural Cover and four WBCs with mine tailings ranged from 314.9 to 329.6 mm/year (Table3) and increased with decreasing ks (Figure3b). The potential ET for each simulation was independent of cover soil and calculated with the Penman–Monteith equation in WinUNSAT-H. Evapotranspiration for the different covers was a function of how fast water could be delivered to the soil surface via evaporation and the accessibility of water to plant roots for transpiration. Minerals 2017, 7, 8 9 of 17

The relationship between average annual percolation and ks in Figure 3c suggests that larger ks facilitated water movement from the top to the bottom of the cover profile that led to higher percolation rates. These results are in agreement with Zornberg et al. [6]. Temporal trends of percolation during the 20-year simulation period for the Natural Cover and four WBCs that included pure mine tailings are shown in Figure 4. The 3 mm/year percolation rate line in Figure 4 corresponds to a typical upper-bound percolation rate [2] and the 4 mm/year line corresponds to the regulatory threshold for the Natural Cover. All WBCs simulated with mine tailings for the 1220-mm-thick storage layer met the 4 mm/year percolation rate, and only copper tailings exceeded the 3 mm/year percolation line for the 20-year simulation. The other three mine Minerals 2017, 7, 128 9 of 17 tailings WBCs (i.e., gold, coal, and oil sand tailings), as well as the Natural Cover, all met the 3 mm/year percolation rate threshold for the 20-year simulation period. EvapotranspirationPronounced periods was inof apercolation similar range occurred for the in Natural Years 6 Cover, and 9 gold(Figure tailings, 4) for and the copperNatural tailings Cover andsince WBCs these with materials gold hadand comparablecopper tailings.ks (Figure These3b). peri Theods trend of high line percolation in Figure3b were suggests preceded that a by modest years ofdecrease high precipitation in ET can be (i.e., anticipated precipitation with a= decrease 412 mm inin kYears when 5 and all other526 mm water-balance in Year 8) that modeling resulted factors in a higherare held degree constant of saturation (e.g., meteorological in the water data, storage vegetation layers. data,Higher etc.). saturation yields less available water storageThe capacity relationship and leads between to increased average percolat annual percolationion with subsequent and ks in Figureprecipitation3c suggests events that [24]. larger ks facilitatedCumulative water movementpercolation from from the the top WBC to the simulated bottom of wi theth coveroil sand proﬁle tailings that as led the to higherstorage percolation layer was 0rates. mm (Table These results3). Although are in agreementoil sand tailings with Zornberghad the lowest et al. [storage6]. capacity (θs in Table 1), the one- to two-orderTemporal of magnitude trends of percolationlower ks for oil during sand the tailings 20-year (2.7 simulation × 10−7 cm/s) period compared for the to Naturalall other Cover materials and (Tablefour WBCs 3) contributed that included to the pure zero mine percolation. tailings areThe shown influence in Figure of ks on4. percolation The 3 mm/year was also percolation observed rate in percolationline in Figure predicted4 corresponds from WBCs to a typical with upper-boundcoal and copper percolation tailings. rateThese [ 2two] and materials the 4 mm/year had nearly line identicalcorresponds volumetric to the regulatory storage capacity threshold (θ fors = the0.46 Natural and 0.47); Cover. however, All WBCs ks for simulated coal tailings with minewas over tailings 60 timesfor the smaller 1220-mm-thick than ks for storage copper layer tailings. met the Additionally, 4 mm/year coal percolation tailings rate,had anda high only Ψ coppera, which tailings when combinedexceeded thewith 3 mm/yearthe lower percolationks resulted in line a storage for the 20-yearlayer with simulation. reduced ability The other to convey three mine water. tailings This comparisonWBCs (i.e., gold,highlights coal, andthe importance oil sand tailings), of variation as well in ashydraulic the Natural parameters Cover, allbetween met the storage 3 mm/year layer materialspercolation that rate have threshold similar forvolumetric the 20-year storage simulation capacity. period.

4 mm/yr 60 Natural Cover Copper 40 Oil Sand Coal 3 mm/yr Gold 20 Percolation (mm) Percolation Oil sand tailings percolation = 0 mm 0 0 5 10 15 20 Time (yr) FigureFigure 4. 4. TemporalTemporal trends trends of of percolation percolation for for the the Natu Naturalral Cover Cover and and WBCs WBCs simu simulatedlated with with copper, copper, oil sand,oil sand, coal, coal, and and gold gold mine mine tailings tailings over over the the20-year 20-year model model simulation simulation period. period.

ThePronounced relationship periods between of percolation Ψa and n occurred(van Genuchten in Years fitting 6 and parame 9 (Figureter)4) forversus the Naturalaverage Cover soil water and storageWBCs with and goldaverage and saturation copper tailings. of in the These cover periods soil is of shown high percolation in Figure 5. were Water preceded storage by and years saturation of high increasedprecipitation with (i.e., an precipitationincrease in Ψa = and/or 412 mm decrease in Year in 5 andn. Air 526 entry mm inpressure Year 8) is that the resulted minimum in aapplied higher pressuredegree of required saturation to indrain the waterthe largest storage pores layers. in the Higher soil, and saturation n is related yields to less the available pore size water distribution storage incapacity the soil. and A leadslarger to Ψ increaseda and lower percolation n mean that with the subsequent soil has a precipitation higher moisture events holding [24]. capacity via smallerCumulative and more percolationuniformly-sized from thepores. WBC A soil simulated with low with moisture oil sand capacity tailings asresults the storage in lower layer storage was in the storage layer and a greater ability to drain water at the bottom of the cover. Coal mine tailings 0 mm (Table3). Although oil sand tailings had the lowest storage capacity ( θs in Table1), the one- to had the highest storage capacity and average saturation due− 7to the highest air entry pressure and two-order of magnitude lower ks for oil sand tailings (2.7 × 10 cm/s) compared to all other materials lowest n. Copper mine tailings had the lowest soil water storage and average saturation due to a high (Table3) contributed to the zero percolation. The influence of ks on percolation was also observed sandin percolation content (≈ predicted70%) and no from clay, WBCs which with results coal in and a lower copper field tailings. capacity These water two content. materials had nearly identical volumetric storage capacity (θs = 0.46 and 0.47); however, ks for coal tailings was over 60 times smaller than ks for copper tailings. Additionally, coal tailings had a high Ψa, which when combined with the lower ks resulted in a storage layer with reduced ability to convey water. This comparison highlights the importance of variation in hydraulic parameters between storage layer materials that have similar volumetric storage capacity. The relationship between Ψa and n (van Genuchten fitting parameter) versus average soil water storage and average saturation of in the cover soil is shown in Figure5. Water storage and saturation increased with an increase in Ψa and/or decrease in n. Air entry pressure is the minimum applied pressure required to drain the largest pores in the soil, and n is related to the pore size distribution in the soil. A larger Ψa and lower n mean that the soil has a higher moisture holding capacity via smaller and more uniformly-sized pores. A soil with low moisture capacity results in lower storage in the Minerals 2017, 7, 128 10 of 17 storage layer and a greater ability to drain water at the bottom of the cover. Coal mine tailings had the highest storage capacity and average saturation due to the highest air entry pressure and lowest n. Copper mine tailings had the lowest soil water storage and average saturation due to a high sand Mineralscontent 2017 (≈,70%) 7, 8 and no clay, which results in a lower field capacity water content. 10 of 17

400 (a) (b) Oil Sand Tailings 300 Coal Tailings

200 Gold Tailings Copper Tailings

Average Soil Average 100 Silty Sand Water Storage (mm) 0

0.8 (c) (d) Oil Sand Tailings 0.6 Coal Tailings 0.4 Gold Tailings Copper Tailings 0.2 Natural Soil Average Saturation Average 0.0 0501001502001.21.31.41.51.6 Air Entry Pressure, ψ (cm) a Fitting Parameter, n

Figure 5. Relationships of average soil water storage versus (a) air entry pressure (Ψa) and (b) van Figure 5. Relationships of average soil water storage versus (a) air entry pressure (Ψa) and (b) van Genuchten’s n parameter, and relationships of average saturation of the soil water storage layer versus Genuchten’s n parameter, and relationships of average saturation of the soil water storage layer (c) Ψa and (d) n. versus (c) Ψa and (d) n.

AnAn average average percolation percolation rate rate ranging ranging between between 0.0 and 0.0 and3.2 mm/year 3.2 mm/year suggests suggests that the that mine the tailings mine consideredtailings considered in this study in this meet study the meet percolation the percolation requirement requirement for WBCs. for WBCs. Hard rock Hard mine rock tailings mine tailings (e.g., copper(e.g., copper and gold and mine gold minetailings tailings in this in study) this study) typica typicallylly classify classify as low as plasticity low plasticity silt and silt contain and contain 33% to33% 100% to 100% fine-grained ﬁne-grained particles particles [36], [36 which], which are are similar similar characteristics characteristics to to materials materials typically typically used used in in WBCs. Covers Covers simulated simulated with with coal coal and and oil oil sand sand tailings tailings had had low low percolation percolation rates rates due due to to higher higher clay clay contentscontents (clay (clay = = 26% 26% for for coal coal tailings tailings and and 9% 9% for for oil oil sand sand tailings). tailings). In In genera general,l, WBCs WBCs constructed constructed with with tailingstailings with with high high clay clay contents contents (e.g., (e.g., coal coal and and oil oil sand sand tailings tailings in in this this study) study) result result in in low low percolation percolation rates.rates. However, However, post-construction post-construction changes changes (biota (biota intrusion, intrusion, freeze-thaw, freeze-thaw, and and wetting-drying wetting-drying cycles) cycles) shouldshould be be considered considered due to the propensity fo forr clayed materials to change with time [[23].23].

3.2.3.2. Fixed Fixed Storage Storage Laye Layerr Thickness Thickness Composed Composed of Tailings and Waste Rock TheThe second second task task in in this this water-balance water-balance model model analys analysisis was was to to replace replace the the storage storage layer layer soil soil of of the the NaturalNatural Cover Cover with with WR&T. WR&T. These models were completed with with a a fixed fixed storage layer thickness of 1220 mm that was simulated with with WR&T. WR&T. Waste Waste rock and gravel particles were assumed to to act act as as inclusionsinclusions inin thethe finer finer fraction fraction with with zero zero water water retention retention capacity capacity to correct to correct SWCCs SWCCs of the mineof the tailings mine tailingsand silty-sand and silty-sand storage layersstorage [33 layers]. Hydraulic [33]. Hydraulic conductivity conductivity of the WR&T of the and WR&T silty-sand and silty-sand with additional with additionalgravel content gravel were content assumed were constant assumed based constant on literature based on [ 19literature,34]. [19,34]. AA summary summary of of the the water-balance water-balance mo modelsdels completed completed for for the the evaluati evaluationon with with a a fixed fixed storage storage layer layer thicknessthickness ofof 12201220 mmmm is is in in Table Table4. Each4. Each model model simulation simulation that includedthat included a waste a waste rock content rock content (or gravel (or gravelfor the for silty-sand the silty-sand cover) cover) above above the baseline the baseline content content (i.e., 0%(i.e., for 0% all for mine all mine tailings tailings and and 33% 33% for thefor thesilty-sand silty-sand cover) cover) required required a corrected a corrected SWCC. SWCC. Examples Examples of corrected of corrected SWCCs SWCCs for coal for minecoal mine tailings tailings with with0, 15, 0, 30, 15, 45, 30, and 45, 71.3% and waste71.3% rockwaste addition rock addition are shown are in shown Figure 6in. TheseFigure corrected 6. These SWCCs corrected include SWCCs the includesame van the Genuchten same van fittingGenuchten parameters fitting (parametersα and n) as the(α and baseline n) as SWCC the baseline with 0% SWCC waste with rock, 0% but waste with rock, but with θs corrected in accordance with Equation (7). An increase in waste rock content yielded a decrease in θs that also decreased the available storage capacity for a constant thickness (Equation (3)). Average annual water-balance metrics for the 20-year model simulations summarized in Table 4 include runoff, ET, percolation, average SWS, and average degree of saturation of the storage layer soil. The addition of waste rock particles decreased porosity and correspondingly reduced storage capacity. Thus, the simulations summarized in Table 4 indicate a reduction in average SWS, increase

Minerals 2017, 7, 8 11 of 17 Minerals 2017, 7, 128 11 of 17 in saturation, and increase in percolation with increase in waste rock content. However, percolation of oil sand tailings WBCs remained negligible with increasing waste rock content for all simulations. θs corrected in accordance with Equation (7). An increase in waste rock content yielded a decrease in θ that also decreased the available storage capacity for a constant thickness (Equation (3)). s Table 4. Water balance metrics for the Natural Cover and WBCs simulated copper, gold, coal, and oil sand tailings with varying waste rock inclusions for the 20-year simulation period. Table 4. Water balance metrics for the Natural Cover and WBCs simulated copper, gold, coal, and oil sand tailings with varying waste rock inclusions for the 20-year simulation period.Average Soil Average Waste Runoff Evapotranspiration Percolation Soil/Tailings Water Storage Saturation Rock (%) (mm/year) (mm/year) (mm/year) Average(mm) Soil AverageDegree (%) Waste Rock Runoff Evapotranspiration Percolation Soil/Tailings Water Storage Saturation 33(%) 0.215(mm/year) (mm/year) 328.6 (mm/year) 2.36 151.1 30 (mm) Degree (%) Natural Cover 48 0.170 328.1 2.69 139.4 32 33 0.215 328.6 2.36 151.1 30 Natural 63 0.190 327.1 3.41 112.8 30 48 0.170 328.1 2.69 139.4 32 Cover 0 0.185 327.4 3.17 91.1 14 Copper 63 0.190 327.1 3.41 112.8 30 15 0.180 330.5 4.08 80.3 15 Tailings 0 0.185 327.4 3.17 91.1 14 Copper 30 150.180 0.180 330.5 325.9 4.08 4.71 80.3 75.3 15 16 Tailings 0 2.170 314.9 0.00 120.4 22 Oil Sand 30 0.180 325.9 4.71 75.3 16 30 02.140 2.170 314.9 328.3 0.00 0.00 120.4 93.5 22 23 TailingsOil Sand 45 301.040 2.140 328.3 301.0 0.00 0.00 93.5 71.8 23 24 Tailings 0 450.180 1.040 301.0 321.7 0.00 0.20 71.8 303.7 24 47 15 00.190 0.180 321.7 333.9 0.20 0.32 303.7 274.0 47 49 Coal Tailings 30 150.320 0.190 333.9 317.8 0.32 0.26 274.0 212.4 49 45 Coal Tailings 45 300.265 0.320 317.8 328.9 0.26 0.83 212.4 215.0 45 55 45 0.265 328.9 0.83 215.0 55 71.371.3 0.525 0.525 315.0 315.0 1.85 1.85 124.4 124.4 52 52

6 10

5 10

4 WR = 0% 10 WR = 15% 3 10 WR = 30%

2 WR = 45% 10

Suction (kPa) WR = 71.3% 1 10

0 10 0 0.1 0.2 0.3 0.4 0.5 Volumetric Water Content (m/m)

Figure 6. SoilSoil water water characteristic characteristic curve curve for for coal coal mine mine tailings tailings (solid (solid line), line), and and 15, 15%, 30, 30%,45, and 45% 71.3% and waste71.3% rock waste addition. rock addition. The mixture The mixture ratio (R ratio) is the (R) optimum is the optimum mixture mixture ratio in ratio WR in= 71.3%. WR = 71.3%.

TheAverage relationships annual water-balance between average metrics annual for the ET 20-year and waste model rock simulations content for summarized the silty-sand in Table cover4 andinclude all co-mixed runoff, ET, WR&T percolation, WBCs averageare shown SWS, in Figure and average 7. The degree annual of average saturation ET was of the approximately storage layer constantsoil. The with addition varying of waste waste rock rock particles content decreased (315 to porosity334 mm/year). and correspondingly As discussed reducedpreviously, storage the potentialcapacity. Thus,ET was the constant simulations for each summarized model as inthis Table was4 a indicate function a of reduction MET data, in averageand the SWS,actual increase ET varied in assaturation, a function and of increaseks (Figure in 4b). percolation Considering with increaseks of the instorage waste layer rock content.was assumed However, constant percolation for varying of oil wastesand tailings rock content, WBCs there remained was no negligible observable with tren increasingd between waste ET rockand waste content rock for content all simulations. (Figure 7). TemporalThe relationships trends betweenof percolation average for annual the WBC ET and simulations waste rock on content the Natural for the Cover, silty-sand copper cover mine and tailingsall co-mixed cover, WR&T and coal WBCs mine are tailings shown cover in Figure with7. di Thefferent annual waste average rock ETcontents was approximately are shown in Figure constant 8. Percolationwith varying increased waste rock with content an increase (315 to 334in waste mm/year). rock content As discussed when the previously, storage thelayer potential thickness ET was fixed. This was attributed to reduced storage capacity when fine-grained, water-retaining material is constant for each model as this was a function of MET data, and the actual ET varied as a function of ks replaced with waste rock particle inclusions with zero water retention capacity. However, addition (Figure3b). Considering ks of the storage layer was assumed constant for varying waste rock content, ofthere waste was rock no observableto the WBCs trend did betweennot considerably ET and waste affect rockpercolation content rate (Figure in the7). first 5 year. TheTemporal influence trends of waste of percolation rock addition for the on WBCpercol simulationsation was more on the pronounced Natural Cover, from Year copper 6 to mine the endtailings of the cover, 20-year and simulation coal mine tailingsperiod (Figure cover with 8). The different percolation waste in rock Year contents 6 followed are shown a year inwhen Figure SWS8. increased,Percolation resulting increased in withelevated an increasesaturation in and waste higher rock propensity content when for thepercolation storage layer[24]. From thickness Year was6 to theﬁxed. end This of the was 20-year attributed simulation, to reduced higher storage saturation capacity within when the ﬁne-grained, storage layers water-retaining combined with material reduced is storage capacity via waste rock addition increased percolation. These observations suggest that the

Minerals 2017, 7, 8 12 of 17 addition of waste rock to the storage layer of a WBC may become detrimental to meeting percolation rates in years following high precipitation that can leave little remaining SWS capacity.

350 Minerals 2017, 7, 128 12 of 17 Minerals 2017, 7, 8 12 of 17 340 Natural Cover replacedaddition withof waste waste330 rock rock to the particle storage inclusions layer of with a WBC zero may water become retention detrimental capacity. to However,Copper meeting percolation addition of rates in years following high precipitation that can leave little remaining SWS capacity.Gold waste rock to the320 WBCs did not considerably affect percolation rate in the ﬁrst 5Oil year. sand Coal 350310

Evapotranspiration (mm/yr) 300 340 0 1020304050607080 Natural Cover Waste Rock Content (%) 330 Copper Gold Figure 7. Relationship320 between average annual evapotranspiration and waste rock Oilcontent sand for the 20- year simulations with the Natural Cover and copper, gold, oil sand, and coal mineCoal tailings. 310

Water-balanceEvapotranspiration (mm/yr) 300 simulations on oil sand tailings with varying waste rock content did not follow these observed relationships0 1020304050607080 between reduced SWS and increased percolation (Table 4). Total Waste Rock Content (%) percolation in the oil sand tailings simulations was 0 mm for all waste rock contents evaluated (Table 4). ThisFigure exception 7. RelationshipRelationship in observed between between behavior average average annual was annual attributed evapotra evapotranspirationnspiration to the low and and kwastes of waste the rock rocksoil content contentsand for tailings forthe the20- that compensated20-yearyear simulations simulations for the with reduced with the theNatural storage Natural Cover capacity Cover and and copper, such copper, that gold, gold, no oil percolation oilsand, sand, and and coal was coal mine simulated. mine tailings. tailings.

100Water-balance simulations on oil sand tailings with varying waste rock content did not follow (b) (c) (a) WR=0% WR=0% Coal Mine these observedWR=33% relationships between reduced SWS and increased percolation (Table 4). Total WR=15% WR=15% Tailings WR=48% percolation in the oil sand tailings simulationsWR=30% was 0 mm for all waste rock contentsWR=30% evaluated (Table 75 WR=63% 4 mm/yr WR=45% 4). This exception in observed behavior was attributed to the low ks of the soil sand tailings that WR=71% compensated for the reduced storage capacity such that no percolation was simulated. 50 4 mm/yr 4 mm/yr 3 mm/yr 100 3 mm/yr (b) Coal Mine (c) Percolation (mm) Percolation (a) WR=0% WR=0% 25 WR=33% 3 mm/yr WR=15% WR=15% Tailings WR=48% WR=30% WR=30% 75 WR=63% 4Natural mm/yr Cover Copper Mine Tailings WR=45% 0 0 5 10 15 20 0 5 10 15 20 0 5WR=71% 10 15 20 Elapsed Time (yr) Elapsed Time (yr) Elapsed Time (yr) 50 4 mm/yr 4 mm/yr Figure 8.8. TemporalTemporal trends trends of of percolation percolation for for the the (a) ( Naturala) Natural Cover, Cover, (b) copper (b) copper3 tailings,mm/yr tailings, and ( cand) coal (c) mine coal 3 mm/yr Percolation (mm) Percolation 25tailingsmine tailings with varyingwith varying waste waste rock (WR) rock content.(WR) content.3 mm/yr

Natural Cover Copper Mine Tailings Relationships between annual average percolation and waste rock content for the silty-sand 0The influence of waste rock addition on percolation was more pronounced from Year 6 to the 0 5 10 15 20 0 5 10 15 20 0 5 10 15 20 endcover of and the three 20-year mine simulation tailings WBCs period simulated (Figure8). with The percolationco-mixed WR&T in Year are 6 followedshown in aFigure year when 9a. Data SWS in Elapsed Time (yr) Elapsed Time (yr) Elapsed Time (yr) increased,Figure 9a support resulting the in elevatedobservation saturation of an increase and higher in percolation propensity with for percolation increase in [waste24]. From rock Year content 6 to thefor WBCs endFigure of simulated the 8. Temporal 20-year with simulation, trends a fixed of percolation storage higher saturationlayer for the thic (akness.) within Natural The the Cover, linear storage (b trend) copper layers lines combinedtailings, fitted and for with the(c) coal reducedNatural 2 storageCover,mine copper capacity tailings tailings viawith waste varying cover, rock waste and addition coalrock tailings(WR) increased content. cover, percolation. all yielded These coefficients observations of determination suggest that (R the) > addition0.83, which of wastesupports rock the to theobserved storage effect layer of of increa a WBCsed may percolation become detrimentalwith reduced to SWS meeting capacity percolation due to Relationships between annual average percolation and waste rock content for the silty-sand ratesthe addition in years of following waste rock. high precipitation that can leave little remaining SWS capacity. cover and three mine tailings WBCs simulated with co-mixed WR&T are shown in Figure 9a. Data in Water-balanceAlthough the addition simulations of waste on oil rock sand to tailings the storage with layer varying of wasteWBCs rockincreases content percolation, did not Figure 9a support the observation of an increase in percolation with increase in waste rock content follownumerous these of observedthe water-balance relationships simulations between that reduced included SWS waste and increasedrock met the percolation 3 and 4 (Tablemm/year4). for WBCs simulated with a fixed storage layer thickness. The linear trend lines fitted for the Natural Totalpercolation percolation thresholds in the (Figure oil sand 9a). tailings The rate simulations of increase was in 0 percolation mm for all wastewith waste rock contentsrock addition evaluated (i.e., Cover,slopes ofcopper trend tailings lines in cover, Figure and 9a) coal can tailingsbe used cover, to assess all yielded the amount coefficients of waste of rockdetermination addition that(R2) is> (Table4). This exception in observed behavior was attributed to the low ks of the soil sand tailings that 0.83, which supports the observed effect of increased percolation with reduced SWS capacity due to compensatedreasonable to formeet the a reducedprescribed storage percolation. capacity Larger such that trend no percolationline slopes in was Figure simulated. 9a suggest a higher the addition of waste rock. sensitivityRelationships of percolation between with annual waste averagerock addition. percolation Slopes and of the waste trend rock lines content in Figure for the9a are silty-sand plotted Although the addition of waste rock to the storage layer of WBCs increases percolation, coverversus and ks of three the minefine-grained tailings fraction WBCs simulated in Figure with 9b. Da co-mixedta in Figure WR&T 9b areand shown the logarithmic in Figure9 a.trend Data line in numerous of the water-balance simulations that included waste rock met the 3 and 4 mm/year Figuresuggest9a that support the rate the of observation increase in of percolation an increase with in percolation addition of with waste increase rock is in larger waste for rock storage content layer for percolation thresholds (Figure 9a). The rate of increase in percolation with waste rock addition (i.e., WBCsmaterials simulated that have with higher a fixed ks storage. As a result, layer thickness.percolation The in linearWBCs trend with lines finer-grained fitted for theparticles Natural (e.g., Cover, oil slopes of trend lines in Figure 9a) can be used to assess the amount of waste rock addition that is copper tailings cover, and coal tailings cover, all yielded coefficients of determination (R2) > 0.83, reasonable to meet a prescribed percolation. Larger trend line slopes in Figure 9a suggest a higher which supports the observed effect of increased percolation with reduced SWS capacity due to the sensitivity of percolation with waste rock addition. Slopes of the trend lines in Figure 9a are plotted addition of waste rock. versus ks of the fine-grained fraction in Figure 9b. Data in Figure 9b and the logarithmic trend line suggest that the rate of increase in percolation with addition of waste rock is larger for storage layer materials that have higher ks. As a result, percolation in WBCs with finer-grained particles (e.g., oil

Minerals 2017, 7, 8 13 of 17

sand tailings and coal mine tailings) that typically have lower ks are less sensitive to waste rock addition in comparison with covers constructed with coarser-grained materials (e.g., copper and Mineralssilty-sand2017 ,soil).7, 128 13 of 17

6 0.08 (a) Natural (b) 5 Cover 0.06 4 Copper Slope = 0.113 + 0.0164log(K) 2 3 0.04 R = 0.87

Gold Slope 2 Oil 0.02 Percolation (mm/yr) 1 Sand Coal 0 0 -7 -6 -5 -4 020406080 10 10 10 10 K (cm/s) Waste Rock Content (%) sat

FigureFigure 9.9.Relationships Relationships between between (a )(a average) average annual annual percolation percolation and wasteand waste rock contentrock content for ﬁxed-height for fixed- waterheight storage water layersstorage containing layers containing waste rock; waste and rock; (b) the and rate (b of) the percolation rate of percolation increase with increase increase with in wasteincrease rock in contentwaste rock and content saturated and hydraulic saturated conductivity hydraulic conductivity of the water of storage the water layer. storage layer.

3.3. AdjustedAlthough Storage the addition Layer Thickness of waste rockComposed to the of storage Tailings layer and ofWaste WBCs Rock increases percolation, numerous of theAn water-balance alternative approach simulations to meeting that included a prescribed waste pe rockrcolation met rate the 3with and the 4 mm/yearaddition of percolation waste rock thresholdsto a storage (Figure layer9 a).with The WR&T rate of is increase to redesign in percolation the storage with layer waste thickness rock addition to meet (i.e., the slopes required of trendpercolation lines in rate. Figure As discussed9a) can be previously, used to assess the thestorage amount layer of thickness waste rock of WBCs addition created that isfrom reasonable coal and tocopper meet atailings prescribed were percolation. redesigned Larger following trend two line methods: slopes in FigureMethod9a suggest1—thickness a higher re-computed sensitivity via of percolationEquation (3) with to maintain waste rock a constant addition. SASlopes with modified of the trend SWCC lines parameters, in Figure9 aand are Method plotted versus2—thicknessks of therecomputed fine-grained to maintain fraction ina Figureconstant9b. void Data volume in Figure to9 bthe and waste the logarithmicrock-free storage trend linelayer suggest (Table that2). A thesummary rate of of increase the redesigned in percolation WBCs with for coal addition tailings of wasteand copper rock is tailings larger is for in storage Table 2 layer along materials with average that haveannual higher percolationks. As a result,obtained percolation from the in 20-year WBCs with simulations. finer-grained Water-balance particles (e.g., covers oil sand redesigned tailings and for coalcopper mine tailings tailings) only that are typically included have for lower Methodks are 2 lesssince sensitive both methods to waste yielded rock addition similar in storage comparison layer withthicknesses. covers constructed with coarser-grained materials (e.g., copper and silty-sand soil). Temporal trends of percolation for WBCs simulated with only coal mine tailings (height = 1220 3.3. Adjusted Storage Layer Thickness Composed of Tailings and Waste Rock mm), with 30% and 45% waste rock plus fixed height (height = 1220 mm), and with 30% and 45% wasteAn rock alternative plus adjusted approach height to meeting with Method a prescribed 1 (height percolation = 1810 mm rate and with 2390 the mm, addition respectively) of waste rock and toMethod a storage 2 (height layer with = 1740 WR&T mm is toand redesign 2220 mm, the storage respec layertively) thickness are shown to meet in theFigure required 10a,b. percolation The total rate.percolation As discussed for coal previously, mine tailings the with storage no waste layer thicknessrock was of4.0 WBCs mm and created percolation from coal increased and copper with tailingswaste rock were addition redesigned and followingno change two to the methods: thickness Method of the 1—thicknessstorage layer re-computed(i.e., percolation via Equation= 5.2 mm for (3) to30% maintain waste rock a constant and 16.6SA withmm for modified 45% waste SWCC rock). parameters, The redesigned and Method WBC 2—thickness thickness following recomputed with toboth maintain Method a constant1 and Method void volume2 decreased to the percolatio waste rock-freen relative storage to the layer constant (Table thickness2). A summary WBC with of thewaste redesigned rock (Figure WBCs 10a,b). for Results coal tailings from andcoal coppermine tailings tailings suggest is in Tablethat the2 along redesigned with average WBCs can annual yield percolationcomparable obtained low percolation from the rates 20-year in comparison simulations. with Water-balance WBCs containing covers redesigned no waste rock. for copper tailings only areTemporal included trends for Method of percolation 2 since bothfor WBCs methods simula yieldedted with similar only storage copper layer mine thicknesses. tailings (height = 1220Temporal mm), with trends30% waste of rock percolation plus fixed for height WBCs (height simulated = 1220 mm), with and only with coal 30% and mine 45% tailings waste (heightrock plus = 1220 adjusted mm) ,height with 30% with and Method 45% waste 2 (hei rockght plus= 1770 fixed mm height and 2350 (height mm, = 1220respectively) mm), and are with shown 30% andin Figures 45% waste 10a,b. rock The plus redesigned adjusted heightWBCs withthicknesses Method with 1 (height coal =mine 1810 tailings mm and and 2390 waste mm, respectively)rock yielded andlower Method total percolation 2 (height = relative 1740 mm to WBCs and 2220 with mm, wast respectively)e rock and aare fixed shown thickness. in Figure Results 10a,b. from The copper total percolationmine tailings for analysis coal mine further tailings support with no that waste comparable rock was percolations 4.0 mm and percolationrates can be increased achieve with with WR&T waste rockWBCs addition when the and storage no change layer to is the redesigned thickness to of a theccount storage for layerthe reduced (i.e., percolation storage capacity = 5.2 mm due for to 30% the wastewaste rockrock andinclusions. 16.6 mm for 45% waste rock). The redesigned WBC thickness following with both Method 1 and Method 2 decreased percolation relative to the constant thickness WBC with waste rock

(Figure 10Noa,b). WR ResultsWith from WR + Fixed coal Height mine tailingsWith WR suggest + Adjusted that Height the (Method redesigned 1) With WBCs WR + canAdjusted yield Height comparable (Method 2) low percolation rates in comparison with WBCs containing no waste rock. Temporal trends of percolation for WBCs simulated with only copper mine tailings (height = 1220 mm), with 30% waste rock plus ﬁxed height (height = 1220 mm), and with 30% and 45% waste rock plus adjusted height with Method 2 (height = 1770 mm and 2350 mm, respectively) are shown in Figure 10a,b. The redesigned WBCs thicknesses with coal mine tailings and waste rock Minerals 2017, 7, 8 13 of 17

6 0.08 (a) Natural (b) 5 Cover 0.06 4 Copper Slope = 0.113 + 0.0164log(K) 2 3 0.04 R = 0.87

Gold Slope 2 Oil 0.02 Percolation (mm/yr) 1 Sand Coal 0 0 -7 -6 -5 -4 020406080 10 10 10 10 K (cm/s) Waste Rock Content (%) sat

Figure 9. Relationships between (a) average annual percolation and waste rock content for fixed- height water storage layers containing waste rock; and (b) the rate of percolation increase with increase in waste rock content and saturated hydraulic conductivity of the water storage layer.

3.3. Adjusted Storage Layer Thickness Composed of Tailings and Waste Rock An alternative approach to meeting a prescribed percolation rate with the addition of waste rock to a storage layer with WR&T is to redesign the storage layer thickness to meet the required percolation rate. As discussed previously, the storage layer thickness of WBCs created from coal and copper tailings were redesigned following two methods: Method 1—thickness re-computed via Equation (3) to maintain a constant SA with modified SWCC parameters, and Method 2—thickness recomputed to maintain a constant void volume to the waste rock-free storage layer (Table 2). A summary of the redesigned WBCs for coal tailings and copper tailings is in Table 2 along with average annual percolation obtained from the 20-year simulations. Water-balance covers redesigned for copper tailings only are included for Method 2 since both methods yielded similar storage layer thicknesses. Temporal trends of percolation for WBCs simulated with only coal mine tailings (height = 1220 mm), with 30% and 45% waste rock plus fixed height (height = 1220 mm), and with 30% and 45% waste rock plus adjusted height with Method 1 (height = 1810 mm and 2390 mm, respectively) and Method 2 (height = 1740 mm and 2220 mm, respectively) are shown in Figure 10a,b. The total percolation for coal mine tailings with no waste rock was 4.0 mm and percolation increased with waste rock addition and no change to the thickness of the storage layer (i.e., percolation = 5.2 mm for 30% waste rock and 16.6 mm for 45% waste rock). The redesigned WBC thickness following with both Method 1 and Method 2 decreased percolation relative to the constant thickness WBC with waste rock (Figure 10a,b). Results from coal mine tailings suggest that the redesigned WBCs can yield comparable low percolation rates in comparison with WBCs containing no waste rock. Temporal trends of percolation for WBCs simulated with only copper mine tailings (height = 1220 mm), with 30% waste rock plus fixed height (height = 1220 mm), and with 30% and 45% waste Mineralsrock plus2017 adjusted, 7, 128 height with Method 2 (height = 1770 mm and 2350 mm, respectively) are shown14 of 17 in Figures 10a,b. The redesigned WBCs thicknesses with coal mine tailings and waste rock yielded yieldedlower total lower percolation total percolation relative relativeto WBCs to with WBCs wast withe rock waste and rock a fixed and athickness. ﬁxed thickness. Results Resultsfrom copper from coppermine tailings mine tailings analysis analysis further furthersupport support that comparable that comparable percolations percolations rates can rates be achieve can be achieve with WR&T with WR&TWBCs WBCswhen the when storage the storage layer is layer redesigned is redesigned to account to account for the for reduced the reduced storage storage capacity capacity due due to the to thewaste waste rock rock inclusions. inclusions. Minerals 2017, 7, 8 14 of 17 No WR With WR + Fixed Height With WR + Adjusted Height (Method 1) With WR + Adjusted Height (Method 2)

20 (a) Coal Tailings (b) Coal Tailings 15 30% Waste Rock 45% Waste Rock

5 Percolation (mm)

0 100 (d) (c) Copper Tailings 80 Copper Tailings 30% Waste Rock 45% Waste Rock 60

Percolation (mm) 20

0 0 5 10 15 20 0 5 10 15 20 Elapsed Time (yr) Elapsed Time (yr) FigureFigure 10. 10. TemporalTemporal trends trends of of percolation percolation for for water water balance balance covers covers with with (a ()a )coal coal tailings tailings +30% +30% waste waste rock,rock, (b (b) )coal coal tailings tailings +45% +45% waste waste rock, rock, (c ()c )copper copper tailings tailings +30% +30% waste waste rock, rock, and and (d (d) )copper copper tailings tailings +45%+45% waste waste rock. rock.

3.4.3.4. Contribution Contribution to to the the Circular Circular Economy Economy and and Mining Mining Sustainability Sustainability TheThe U.S. U.S. EPA EPA has has outlined outlined the the following following wast wastee management management hierarchy hierarchy that that progresses progresses with with decreasingdecreasing impact impact onon sustainability:sustainability: (i) (i) prevention prevention of wasteof waste generation, generation, (ii) reuse (ii) ofreuse waste, of (iii)waste, recycling (iii) recyclingof waste, of (iv) waste, recovery (iv) recovery from waste, from and waste, (v) disposaland (v) disposal of waste of [ 37waste]. In [37]. applying In applying this hierarchy this hierarchy to mine totailings mine tailings and waste and rock,waste the rock, prevention the prevention of mine of waste mine generationwaste generation is the mostis the sustainablemost sustainable option. option.Preventing Preventing the generation the generation of mine of waste mine reduceswaste reduces costs associated costs associated with transferring with transferring waste, reduceswaste, reducesthe land the area land required area required for waste for disposal,waste disposal, and reduces and reduces costs associatedcosts associated with monitoringwith monitoring the closed the closedwaste impoundment.waste impoundment. Preventing Preventing waste generation waste generation is not always is not a viable always option, a viable and implementingoption, and implementingmeasures toreuse measures and recycleto reuse mine and waste recycle are mine more waste practical are optionsmore practical to enhancing options sustainability to enhancing of sustainabilitymine waste management. of mine waste McLellan management. et al. [38 McLellan] emphasized et al. the [38] role emphasized of reuse and the recycling role of in reuse mine wasteand recyclingmanagement in mine and waste considered management reuse and and recycling considered of mine reuse waste and asrecycling a “key elements” of mine waste for a sustainableas a “key elements”waste management for a sustainable practice waste in mineral management industry. practice The reuse in mineral opportunity industry. central The reuse to this opportunity paper is the centralreuse ofto mixedthis paper WR&T is the in WBCs,reuse of which mixed can WR&T be financially in WBCs, beneficial which can and be reducefinancially landfilled beneficial waste and via reduceoffsetting landfilled the amount waste of via waste offsetting to be managed. the amount Creating of waste WBCs to from be managed. mixed mine Creating waste canWBCs also from create mixedemployment mine waste in new can industries also create and employment raise a given in mine’s new imageindustries in society and raise for protecting a given mine’s the environment. image in societyRecovery for ofprotecting mine waste the isenvironment. also a sustainable Recovery option of mine that involveswaste is recoveryalso a sustainable of economically option viablethat involvesminerals recovery from older of economically mine waste that viable been minerals processed from [39 older]. mine waste that been processed [39]. LottermoserLottermoser [37] [37 listed] listed the the following following potential potential reuse reuse and and recycling recycling options options for for mine mine waste waste rock: rock: (i)(i) resource resource for for additional additional extraction extraction of minerals of minerals and and metals; metals; (ii) backfill (ii) backfill material material for open for openvoids; voids; (iii) landscaping(iii) landscaping materials; materials; and and(iv) (iv)additive additive to asphalt. to asphalt. Lottermoser Lottermoser [37] [37 and] and Corder Corder [40] [40 identified] identified the the followingfollowing potential potential reuse reuse and and recycling recycling options options for for tailings: tailings: (i) resource (i) resource for foradditional additional extraction extraction of mineralsof minerals and metals; and metals; (ii) cement-ame (ii) cement-amendednded tailings tailings for use foras backfill use as in backfill underground in underground mines; and mines; (iii) clay-rich tailings amendment for sandy soils for manufacturing of bricks, cement, floor tiles, sanitary ware, and porcelain. Many of these applications are not located on the mine site, which can limit their economic benefit and overall impact on mining sustainability and the circular economy. The possibility of reusing mixed WR&T as the storage layer in WBCs was evaluated in this study. When compared to the other reuse and recycling applications listed previously, WBCs that employ mixed WR&T focus on waste reuse at the mine site, which limits potential off-site contamination and exposure to humans and the environment. On-site reuse reduces costs associated with transporting and handling these waste sources off-site for other uses and reduces costs associated with acquiring

Minerals 2017, 7, 128 15 of 17 and (iii) clay-rich tailings amendment for sandy soils for manufacturing of bricks, cement, ﬂoor tiles, sanitary ware, and porcelain. Many of these applications are not located on the mine site, which can limit their economic beneﬁt and overall impact on mining sustainability and the circular economy. The possibility of reusing mixed WR&T as the storage layer in WBCs was evaluated in this study. When compared to the other reuse and recycling applications listed previously, WBCs that employ mixed WR&T focus on waste reuse at the mine site, which limits potential off-site contamination and exposure to humans and the environment. On-site reuse reduces costs associated with transporting and handling these waste sources off-site for other uses and reduces costs associated with acquiring raw materials for site closure. Additional investigations are needed to evaluate the leaching of contaminants from WR&T mixtures, mechanical properties of WR&T mixtures, and potential to sustain vegetation in WR&T. These investigations need to be coupled with full-scale cover tests sections to transform the potential reuse of mixed WR&T in cover systems to a viable solution for sustainable mine closure.

4. Conclusions Water-balance modeling was conducted to evaluate the viability of using mixed waste rock and tailings (WR&T) as the water storage layer in water balance covers (WBCs). Theoretical WBCs were created with (i) mine tailings and (ii) mixed WR&T to assess the effect of waste rock addition on hydrologic performance. Two methods for redesigning the storage layer of a WBC were evaluated that consist of mixed WR&T to yield comparable percolation rate as covers with no waste rock inclusions. The following conclusions were drawn from this study.

• Percolation rates for WBCs simulated with hard rock mine tailings met the prescribed percolation rate of the Natural Cover (i.e., 4 mm/year). Lower percolation rates were representative of tailings with higher clay content and lower hydraulic conductivity (ks). • Evapotranspiration and percolation increased and runoff decreased with an increase in ks of the storage layer. Storage layers with larger ks results in faster inﬁltration through the cover (percolation) and faster transfer of water out of the soil via evapotranspiration. • Addition of waste rock to WBCs increased percolation when the storage layer thickness was ﬁxed due to reduced storage capacity. The effect of waste rock addition was more pronounced in WBCs that included tailings with higher ks. • Two methods were presented to redesign the storage layer thickness in a WBC that includes mixed WR&T: Method 1—redesign for the constant available storage and Method 2—redesign for the constant void volume. Both methods yielded similar WBC thicknesses and similar percolation rates that compared favorable to the percolation rate with no waste rock. • Reuse of mixed WR&T in on-site WBCs provides an opportunity to enhance mine site sustainability via reduced costs associated the acquisition of raw materials required for closure as well as reduced waste volumes requiring storage.

Acknowledgments: Financial support for this study was provided in part by National Science Foundation to Colorado State University. Support also was provided by Colorado State University. The opinions, findings, conclusions, or recommendations expressed herein are those of the authors and do not necessarily represent the views of the National Science Foundation, or Colorado State University. Funds were made available at Colorado State University to publish in open access. Author Contributions: Christopher A. Bareither and Mohammad H. Gorakhki conceived and designed the water-balance models for this study and Mohammad H. Gorakhki completed all model simulations. Christopher A. Bareither and Mohammad H. Gorakhki collaborated on data analysis, preparation of figures and tables, and writing the manuscript. Conflicts of Interest: The authors declare no conflict of interest. Minerals 2017, 7, 128 16 of 17

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