Session 4: Prediction of Impacts. Dr. Rob Bowell SRK Consulting (UK)

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1 Session 4: Prediction of Impacts Dr. Rob Bowell SRK Consulting (UK)

2 Developing Conceptual Models Why develop models? Concept validation Explanation Basis of quantification of inputs and outputs Regulatory assessment Risk based assessment Management tool Where does this fit in? Mine development Mine operation Closure and reclamation Runoff from high wall GW inflow during pit filling Direct precipitation Pit lake / wall rock interaction Lake evaporation Mixing Gas transfer O2 Mineral precipitation and Adsorption CO2 Seepage to groundwater Static water level

3 What is a Model? Anything used in any way to represent an other item, idea, concept or action Qualitative or Quantitative Analyze a system to be controlled or optimized Hypothesis of how the system could work Analyse how an unforeseeable event could affect the system. Determine different control approaches in simulations. A mathematical model is the set of functions that describes a system using variables and equations that establish relationships between the variables.

4 Generic Concepts Source: Figure 5-3. Chapter 5. Prediction. GARD guide

5 Flow Diagram Source: Figure 5-4. Chapter 5. Prediction. GARD guide

6 3-Phase Approach for Assessing Baseline Chemistry and Predicting Future Water Quality Define Contributing Processes Management and Mitigation Engineering Geological Analytical Quantify Magnitude of Impact

7 Check List Conceptual thinking about the interaction of a mine with the environment requires tools: Geological Hydrological Climate Geochemical characterization Land use

8 Influence of Geology on Geochemistry

9 Key Geological Controls Host rock Limestone/Marble Porous vs. crystalline Hydrothermal alteration Mineralogy Carbonates present? Sulfides present? Trace element secondary minerals? Buffering silicates? Structure Flow paths Geochemistry Source: Stillitoe, EG fig 6. v.105, pp3-41

10 Key Alteration Types Alteration hydrothermal Contrasting mineral assemblage from parent rock Contrasting element enrichment/depletion Essential to characterize Source: Stillitoe, EG fig 10. v.105, pp3-41

11 Hydrothermal Alteration & ABA NET NEUTRAL PREDICTION NP eq kg CaCO 3 /t Carbonate UNCERTAIN ZONE Propylitic Deutric Argillic KFSP QSP AP. eq kg CaCO 3 /t Silica NET ACID PREDICTION

12 Alteration control on ABA

13 Chemical Zonation

14 Chalcophile Corridor Chalcophile corridor Existence of regional geochemical trends of chalcophile and associated elements Smith et al., 1989 Several exist in north central Nevada Carlin trend Battle Mountain Getchell Bald Mountain

15 (Co+Ni+Cu+Zn+Cd+Pb)mg/L Metal Chemistry/Mineralogical Controls High sulfide-au Porphyry Low sulfide-au Carlin-type VMS SEDEX Tin veins 0.01 ph (su)

16 Younger Diagram ALKALINITY 100% 100 Carbonate Pb-Zn Low Sulfidation Clay pits % total as mg/l CaCO Porphyry Carlin PUMPED DEEP BRINES GROUND WATERS NET ALKALINE Shear zone Au NET ACID ACIDITY 100% SO4 100% High Sulfidation %S (SO +Cl ) meq/l Cl 4 100%

17 Geochemical Change with Time Mass Loading to groundwater Release of Process water high ph, sulfate Chronic seepage from reactive tailings Tailings seepage mixes with groundwater TIME years >10,000 years Process water Buffering Natural attenuation capacity in foundation soils Seepage co-mingles with groundwater No control other than dilution

1908-1993 operation 5Mt Cu, 9.5 Mt Pb 2.

Co, Hg, Ga, In, Sb Current resource (post

18 Example: Tsumeb, Namibia Polymetallic pipe-like deposit Precambrian age operation 5Mt Cu, 9.5 Mt Pb 2.1 Mt Zn Ag, Au, Cd, Ge, As, Sn, W, V, Mo, Co, Hg, Ga, In, Sb Current resource (post 1996) 5 4.3% Cu, 7% Pb, 2% Zn, 3 opt Ag, ppm Ge,

19 E(V) Eh-pH Groundwaters H O H 2 2 O H O ph First oxidation zone Second oxidation zone 2 2 S Surface Sulfide ore Upper oxide zone N North Break Fracture Zone Lower oxide zone 0 Metre 1000 First sulfide zone Second sulfide zone

20 Mineralogy/Geochemistry, First Oxidation Zone First oxidation zone More resistant or low solubility, higher pco 2 secondary minerals

21 Mineralogy/Geochemistry, Second Oxidation Zone Second oxidation zone alkali to neutral ph greater range Eh-pH, therefore more secondary minerals Even reduced!

Water Groundwater Is there water regolith or protolith Fracture flow? Seasonal water table Groundwater yield from different rock types does it change?

$Relation to potential active mining zone particularly important with fracture flow where water utilizes same zones as mineralization Surface water Is$

22 Water Groundwater Is there water regolith or protolith Fracture flow? Seasonal water table Groundwater yield from different rock types does it change? Water quality does it change proportional to host rock, depth, water shed? Relation to potential active mining zone particularly important with fracture flow where water utilizes same zones as mineralization Surface water Is there water seasonal rivers? Relationship to land use Groundwater yield from different water sheds does it change? Water quality does it change proportional to host rock, water shed? Relation to mineralization/zone of mining

Frequency Background Groundwater Histogram 400 300 200 100 0 x<10

23 Frequency Background Groundwater Histogram x<10 10<x<5050<x<100 x> % % 80.00% 60.00% 40.00% 20.00%.00% Frequency Cumulative % As, µg/l Frequency Percentage x< % 10<x< % 50<x< % x> % Total % Arsenic standard of 50 µg/l

in WATER BUDGET EQUATION: Ground Water out Q IN = Q

24 Water Budget Precipitation Snowpack Recharge Infiltration Evapotranspiration Well Ground Water in WATER BUDGET EQUATION: Ground Water out Q IN = Q OUT SW IN + RECHARGE + GW IN = SW OUT + ET + PUMPING + GW OUT

25 Water Balance

26 Water Relationship to Mining Features

humidity greater biological activity, greater air

27 Climate Control Not political just natural cycles Seasonality of climates Promote salt production High humidity greater biological activity, greater air moisture Diurnal variation, e.g. UV light, influences cyanide breakdown

28 Environmental and Cultural Setting Receptors do they exist? Evaluation level for water Purpose of land and water resources in the area Upstream issues

29 Pre Mining Conceptual Model Overburden Oxide zone Transition zone Sulfide zone Waste Ore zone Waste Pit Shell

30 Post Mining Conceptual Model Air + Water Ore Tailings Waste rock Sulfide mine Waste Oxide zone Transition zone Sulfide zone ARDML Unrecovered ore

31 Groundwater Flowpath

32 Pit Lake Conceptual Model Runoff from high wall Direct precipitation Lake evaporation Mixing Gas transfer O2 CO2 Static water level GW inflow during pit filling Mineral precipitation and Adsorption Pit lake / wall rock interaction Seepage to groundwater

33 Waste Rock/Heap Leach

34 Conceptual Model: Tailings Precipitation Evaporation Gas Transfer Surface ponding Cyanide + metals in entrained decant waters Tailings drawdown and meteoric leaching Groundwater flow

35 Interpretation of TMF Geochemistry Alkalinity being removed (net alkaline) Evaporation Precipitation Surface of Tailings Leached of reactive components (Net Acid) Leached Layer Limit of Entrained Moisture Runoff Alkalinity has been consumed (Net Acid) Core of Unreacted Tailings Limit of Oxygen Transfer Reaction Layer Moves with time? Alkalinity being removed (Net Alkaline) Geosynthetic Liner Bedrock

36 Mine Life Cycle

37 Prediction timing Early Exploration Stage Advanced Exploration & Pre- Feasibility Stage Feasibility & Development Stage Mine Design Operational Stage Monitoring and Management Geoenvironmental models Geologic characterization Limited number of tests Representative number of static tests to assess AD & ML risk in rocks Combine test results with block model Evaluate site specific factors (climate, hydrology, receiving waters) Create appropriate mitigation measures Conduct management program outlined in permits Plan for closure Assess / manage impacts to receiving waters Monitor performance of constructed facilities Periodically assess operations and closure method Revise design as necessary

38 Predicting Metal Leaching Risk in Waste Rock Typical criteria Degree of AD risk Examples Validation of field assessment Predicting lag time to metal leaching Validation of ion specific WQ prediction 38

39 How Successful is Selective Handling and Placement? PAG criterion developed prior to mining Blasthole testing (1 in 10) Modeling Dispatch routing to controlled placement areas Three zones tested PAG Non-PAG Mixed 39

41 Predicting ARDML Risk We can reliably predict ARDML risk Requires professional judgment cookbook methods don t work Need to consider population distribution averages alone can be misleading 41

42 Geochemical models WATEQ MINSOLV MINTEQ PHREEQC GWB PHAST Choice, regulatory acceptance, database value

43 Importance of thermodynamic database Parameter Observed Value Standard Model Prediction Refined Model Prediction ph Sulfate (mg/l) Arsenic (mg/l) Iron (mg/l) Calcium (mg/l) Sources: Bowell et al., 1998; Parshley et al., 2000; SRK, 2000; SRK, 2001; Bowell & Parshley, 2004

44 Size matters! kg in exposed pit walls

45 45 Size distribution - important

46 46 Degree of Saturation

47 47 Degree of Saturation versus GOR

48 Convert Laboratory data to field scenario R field = R lab x SF moist x SF size x SF contact x SF temp x SF O2 R lab SF moist SF size = HCT leach rates = reduced oxidation due to low moisture = reactivity reduction due to HCT vs field PSD SF contact = reduction due to unflushed mass (retained solutes) in field vs HCT SF temp SF O2 limits = rate relationship for temperature: Arrhenius = reactive mass reduction due to O 2 diffusion Method Modified from Kempton et al., 2012

49 Sensitivity of inputs on results Sensitivity Scenario Availability of hydrous ferric oxide (HFO) for adsorption Base case Assumes that 25% of the potential hydrous ferric oxide produced during pyrite oxidation is available for solute adsorption Sensitivities 10% and 50% availability of HFO used. 10% is likely very low and therefore conservative Oxidation rate scaling factor No adjustment of the combined factor 50% and 200% of the combined rate used. 200% is considered very conservative Humidity cell averaging High sulfur humidity cell use Infiltration rate Assumes that an average of all humidity cell weeks is representative of the waste rock dump weathering at any one time. Assumes that using the average of humidity cells is representative Assumes that post closure, infiltration into the WRD will return to catchment baseline infiltration) while the rest reports as surface of run-off Average of last 20 weeks of humidity cell test data used Average of cells replaced with high sulfur material humidity cell only Lower infiltration of around half base case or 10% of annual precipitation used which would result in higher concentrations but likely slightly lower loading due a greater degree of mineral saturation and mass of solutes adsorbed to mineral surfaces.. 49

50 SULFIDOX modelling Sulfidox represents the following processes in waste rock dumps: Gas transport via diffusion and/or advection; Oxidation of sulfide minerals Heat transport via thermal conduction and/or fluid flow; Infiltration of water down through the waste rock dump 50

51 Input Parameters WRD cross-section parameters NAF PAF 2D cross-section dimensions Height (m) Width (m) Slope Ratio : :1 2D cross-sectional area (m2) Mass of cross-section (tonnes) 34,804 34,804 Specific density of the rock (kg.m -3 ) Sulfur mass fraction (%) Effective sulfur mass fraction (%) Porosity Intrinsic oxidation rate (kg.m -3.s -1 ) 9.10E E-08 Water infiltration rate (ma -1 ) Liquid volume fraction (%) 5 5 Atmospheric conditions and gas properties Annual average ambient air temperature ( C) 5 5 Gas permeability (m -2 ) 10E-10 10E-10 Atmospheric oxygen content kg (O 2 )kg -1 (air)

atmospheric concentration) temperature distribution (blue

52 Prediction Sulfidox results: Uncovered PAF oxygen distribution (blue indicates near zero oxygen, red indicates oxygen at atmospheric concentration) temperature distribution (blue indicates ambient temperature, red indicates over 28 C above ambient) 52

53 Apply to Geochemical Predictions 0.1 mole/m 2 /yr 0.2 mole/m 2 /yr 0.5 mole/m 2 /yr 1 mole/m 2 /yr NAF seepage PAF seepage Mixed seepage/ groundwater NAF seepag e PAF seepage Groundwater NAF seepage PAF seepage Groundwater NAF seepage PAF seepage Groundwat er as 280 < < < < E E E E December NWMA 53 - Reno, NV 3, 2008

54 Account for Oxygen in Predictions Seepage composition Solute loading (g/yr) Base case All weeks HCT source term Base case All weeks HCT source term NAF seepage PAF seepage Seepage/ groundwater NAF seepage PAF seepage Groundwater NAF seepage PAF seepage Groundwate r NAF seepage PAF seepage Groundwate r < < E E E E

55 Predicting ARDML Risk in Tailings Problem formulation A dry stack tailing contains >20% pyrite, but is also high carbonate Will it form acid during operation? Can it be closed in a way that prevents acidification? 55

56 NWMA - Reno, NV 56

57 NWMA - Reno, NV 57

58 NWMA - Reno, NV 58

59 NWMA - Reno, NV 59

60 Example: Groundwater flowpath, Zambian pit

61 61 Conceptual Model

62 62 Typical Steps in Numerical Prediction

63 Input Water Chemistry Sample (mg/l) Shaft Pit sump BF-2 BF-3 CON- E3 PLS Date 10/98 9/99 10/99 10/99 1/99 1/99 Acidity Al 10.9 <0.2 < ,810 Cu 9.83 < ,010 Mg ,610 ph Se Sulfate 4,230 3,300 1,090 1, ,200 U

64 Predicted chemistry: Flood u/g workings to base of pit UG fill Concentration AWQS Avian mg/l Criteria Al As Sb Ba Be Cd Cr Cu F Ni Pb Hg Se Tl U Sulfate 6756 P

65 Predicted Pit Water Chemistry Pit Lake 2550 Pit Lake 2765 Concentration Concentration mg/l mg/l ph Al As Sb Ba Be Cd Cr Cu F Ni Pb Hg Se Tl U Sulfate

66 5/19/ Batch test calibration

Example: Prediction of Backfill chemistry North Mara, Tanzania North Mara Mine has Potentially Acid Generating Waste that is highly reactive During High

2 mg/l Need to capture acidic runoff or limit oxidation of sulfides Option of using former pit as a storage area Currently pit has a lake What is the best

67 Example: Prediction of Backfill chemistry North Mara, Tanzania North Mara Mine has Potentially Acid Generating Waste that is highly reactive During High Rain storm events significant change in runoff chemistry from dumps o ph ~ 3.5 o Sulfate ~ 770 mg/l o Iron ~ 26 mg/l o Arsenic ~ 2 mg/l o Apluminium ~ 1.2 mg/l Need to capture acidic runoff or limit oxidation of sulfides Option of using former pit as a storage area Currently pit has a lake What is the best option o Dry storage above water level o Placement in the pit lake ie have a water oxygen barrier Can Geochemical modelling aid engineering/management decision making

68 Option 1: Conceptual Model for PAF waste disposal in Gena pit lake (assumes that disposed material will be unavailable for reaction)

69 Option 2: Conceptual Model for PAF waste disposal above water level in Gena Pit (assumes that disposed material will be available for reaction)

laboratory conditions Scaling Climate data Precipitation chemistry Lake chemistry and

70 Define Model Inputs Water Balance Groundwater flow and chemistry Surface water chemistry Rock leachate chemistry Leaching chemistry Geology Physical differences between field and laboratory conditions Scaling Climate data Precipitation chemistry Lake chemistry and volume Attenuation Mineralogy of wallrock/precipitates to determine potential saturated phases

71 Waste Rock Geochemistry Not Acid Forming Potentially Acid Forming

72 Geochemical Rock Inputs

73 Scaling of Data kg in exposed pit walls

74 Convert Laboratory Data to Field Scenario R field = R lab x SF moist x SF size x SF contact x SF temp x SF O2 R lab = HCT leach rates SF moist = reduced oxidation due to low moisture SF size = reactivity reduction due to HCT vs field PSD SF contact = reduction due to unflushed mass (retained solutes) in field vs HCT SF temp = rate relationship for temperature: Arrhenius SF O2 = reactive mass reduction due to O 2 diffusion limits Method Modified from Kempton et al., 2012

75 Geochemical Calibration

76 Geochemical Predictions

term exposure to As for birds Main control- high groundwater dilution Predicted precipitation of goethite and

77 Environmental Assessment Against Tanzanian standards exposed PAF waste above water level is not recommendedexceedences for ph and As Using a US BLM type SLRA approach only issue for wildlife is low ph and long term exposure to As for birds Main control- high groundwater dilution Predicted precipitation of goethite and jarosite (ie SI>0) Predict high levels of attenuation of As(V) species onto goethite Placement of PAF in lake shows no geochemical impacts

78 Take Home Points Prediction of mine water chemistry requires; Good site knowledge of geology, hydrogeology and mineralogy Good hydrogeological modelling Understand purpose for model Knowledge of all contributing geochemical sources Knowledge of attenuation processes Geochemical models require good database Cognisant of sensitivities in model Assess finite components Assess uncertainty in model

Prediction of Source Term Leachate Quality from Waste Rock Dumps: A Case Study from an Iron Ore Deposit in Northern Sweden

Proceedings IMWA 06, Freiberg/Germany Drebenstedt, Carsten, Paul, Michael (eds.) Mining Meets Water Conflicts and Solutions Prediction of Source Term Leachate Quality from Waste Rock Dumps: A Case Study