Session 4: Prediction of Impacts

Dr. Rob Bowell – SRK Consulting (UK)

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

Gas transferO2 CO2

Pit lake / wall rock interaction

Direct

precipitation

Lake evaporation

GW inflow during pit filling

Runoff from high wall

Mixing

Seepage to groundwater

Mineral precipitationand Adsorption

Static water level

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.

Generic Concepts

Source: Figure 5-3. Chapter 5. Prediction. GARD guide

Flow Diagram

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

3-Phase Approach for Assessing Baseline

Chemistry and Predicting Future Water Quality

Geological

Analytical Engineering

Management

and Mitigation Quantify Magnitude

of Impact

Define Contributing

Processes

Check List

Conceptual thinking about

the interaction of a mine with

the environment requires

tools:

• Geological

• Hydrological

• Climate

• Geochemical

characterization

• Land use

Influence of Geology on Geochemistry

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, 2009. EG fig 6. v.105, pp3-41

Key Alteration Types

Alteration – hydrothermal

Contrasting mineral

assemblage from

parent rock

Contrasting element

enrichment/depletion

Essential to characterize

Source: Stillitoe, 2009. EG fig 10. v.105, pp3-41

Hydrothermal Alteration & ABA

NP

eq kg

CaCO3/t

AP. eq kg CaCO3/t

QSP KFSP

Argillic

Silica

Propylitic

Deutric

Carbonate

UNCERTAIN ZONE

NET ACID PREDICTION

NET NEUTRAL PREDICTION

Alteration control on ABA

Chemical Zonation

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

Metal Chemistry/Mineralogical Controls

0.01

0.1

1

10

100

1000

10000

100000

0 2 4 6 8 10 12

pH (su)

(Co

+N

i+C

u+

Zn

+C

d+

Pb

)mg

/L

High sulfide-Au

Porphyry

Low sulfide-Au

Carlin-type

VMS

SEDEX

Tin veins

Younger Diagram

PUMPED DEEP

GROUND WATERS

BRINES

NET ALKALINE

NET ACID

ALKALINITY100%

ACIDITY100%

SO

100%4

2- Cl100%

-

100

60

40

20

0

0 20 40 60 80 100

80

% t

ota

l as m

g/l C

aC

O 3

%S (SO +Cl ) meq/l4

2- -

High Sulfidation

Porphyry

CarbonatePb-Zn Clay pitsLow Sulfidation

CarlinShear zone Au

Geochemical Change with Time

TIME

Mass Loadingto groundwater

Process waterBuffering

50-200 years >10,000 years

Natural attenuation capacity infoundation soils

Seepage co-mingles with groundwaterNo control other than dilution

Release of Process waterhigh pH, sulfate

Chronic seepage fromreactive tailings

Tailings seepage mixeswith groundwater

Example: Tsumeb, Namibia

Polymetallic pipe-like deposit

Precambrian age

1908-1993 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 Mt @ 4.3% Cu, 7% Pb,

• 2% Zn, 3 opt Ag, + 330 ppm

Ge,

Eh-pH Groundwaters

Upperoxide zone

SurfaceS N

Sulfide ore

Lower oxide zone

Nor

th B

reak

Fra

ctur

e Zon

e

0 1000Metre

2 4 6 8 10 12

-0.2

0

0.2

0.4

0.6

0.8

1.0

H O

H O

O

H2

2

2

2

pH

E(V

)

First oxidation zoneSecond oxidation zone

First sulfide zoneSecond sulfide zone

Mineralogy/Geochemistry, First Oxidation Zone

First oxidation zone

More resistant or

low solubility, higher pCO2

secondary minerals

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?

• 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

Background Groundwater Histogram

0

100

200

300

400

x<10 10<x<5050<x<100 x>100

Fre

qu

en

cy

.00%

20.00%

40.00%

60.00%

80.00%

100.00%

120.00%

Frequency

Cumulative %

As, µg/L Frequency Percentage

x<10 302 37.15%

10<x<50 373 45.88%

50<x<100 69 8.49%

x>100 69 8.49%

Total 813 100%

Arsenic standard of 50 µg/L

Snowpack Precipitation

Evapotranspiration Infiltration

Ground Water in

Ground Water out

Well

Recharge

WATER BUDGET EQUATION:

SWIN + RECHARGE + GWIN = SWOUT + ET + PUMPING + GWOUT

QIN = QOUT

Water Budget

Water Balance

Water Relationship to Mining Features

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

Environmental and Cultural Setting

Receptors – do they exist?

Evaluation level for water

Purpose of land and water resources in the area

Upstream issues

Ore zone

Pit Shell

Waste Waste

Overburden

Oxide zone

Transition zone

Sulfide zone

Pre Mining Conceptual Model

Unrecovered ore

Oxide zone

Transition zone

Sulfide zone

Waste rock

Ore

Tailings

Air + Water

ARDML

Sulfide mine Waste

Post Mining Conceptual Model

Groundwater Flowpath

Pit Lake Conceptual Model

Gas transferO2 CO2

Pit lake / wall rock interaction

Direct

precipitation

Lake evaporation

GW inflow during pit filling

Runoff from high wall

Mixing

Seepage to groundwater

Mineral precipitationand Adsorption

Static water level

Waste Rock/Heap Leach

Conceptual Model: Tailings

Precipitation

Evaporation

Gas Transfer

Surface

ponding

Groundwater flow

Cyanide + metals in entrained decant waters

Tailings drawdown and meteoric leaching

Interpretation of TMF Geochemistry

Bedrock

Core of Unreacted Tailings

Limit of Entrained Moisture

Limit of Oxygen Transfer

Surface of Tailings

Leached Layer

Precipitation

Evaporation

Alkalinity being removed

(net alkaline)

Geosynthetic Liner

Reaction Layer

Moves with time?

Leached of reactive components

(Net Acid)

Alkalinity being removed

(Net Alkaline)

Alkalinity has been consumed

(Net Acid)

Runoff

Bedrock

Core of Unreacted Tailings

Limit of Entrained Moisture

Limit of Oxygen Transfer

Surface of Tailings

Leached Layer

Precipitation

Evaporation

Alkalinity being removed

(net alkaline)

Geosynthetic Liner

Reaction Layer

Moves with time?

Leached of reactive components

(Net Acid)

Alkalinity being removed

(Net Alkaline)

Alkalinity has been consumed

(Net Acid)

Runoff

Bedrock

Core of Unreacted Tailings

Limit of Entrained Moisture

Limit of Oxygen Transfer

Surface of Tailings

Leached Layer

Precipitation

Evaporation

Alkalinity being removed

(net alkaline)

Geosynthetic Liner

Reaction Layer

Moves with time?

Leached of reactive components

(Net Acid)

Alkalinity being removed

(Net Alkaline)

Alkalinity has been consumed

(Net Acid)

Runoff

Mine Life Cycle

Early Exploration

Stage

Advanced

Exploration & Pre-

Feasibility Stage

Feasibility &

Development

Stage – Mine

Design

Operational Stage Monitoring and

Management

• Geoenvironmen-

tal 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

Prediction timing

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

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

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

Geochemical models

WATEQ

MINSOLV

MINTEQ

PHREEQC

GWB

PHAST

Choice, regulatory acceptance,

database value

Importance of thermodynamic database

Parameter

Observed

Value

Standard

Model

Prediction

Refined Model

Prediction

pH 6.8 7.57 7.06

Sulfate (mg/L) 419 366 424

Arsenic (mg/L) 0.96 5.33 0.83

Iron (mg/L) 0.05 0.005 0.05

Calcium (mg/L) 172 671 192

Sources: Bowell et al., 1998; Parshley et al., 2000; SRK, 2000; SRK, 2001; Bowell & Parshley, 2004

Size matters!

1012 kg in exposed pit walls

Size distribution - important

45

Degree of Saturation

46

Degree of Saturation versus GOR

47

Rfield = Rlab x SFmoist x SFsize x SFcontact x SFtemp x SFO2

Rlab = HCT leach rates

SFmoist = reduced oxidation due to low moisture

SFsize = reactivity reduction due to HCT vs field PSD

SFcontact = reduction due to unflushed mass (retained

solutes) in field vs HCT

SFtemp = rate relationship for temperature: Arrhenius

SFO2 = reactive mass reduction due to O2 diffusion

limits

Convert Laboratory data to field

scenario

Method Modified from Kempton et al., 2012

Sensitivity of inputs on results

49

Sensitivity

Scenario

Base case Sensitivities

Availability of

hydrous ferric

oxide (HFO) for

adsorption

Assumes that 25% of the potential

hydrous ferric oxide produced during

pyrite oxidation is available for solute

adsorption

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

Assumes that an average of all

humidity cell weeks is representative

of the waste rock dump weathering at

any one time.

Average of last 20 weeks of humidity cell test

data used

High sulfur

humidity cell use

Assumes that using the average of

humidity cells is representative

Average of cells replaced with high sulfur

material humidity cell only

Infiltration rate

Assumes that post closure, infiltration

into the WRD will return to catchment

baseline infiltration) while the rest

reports as surface of run-off

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..

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

Input Parameters

51

WRD cross-section parameters NAF PAF

2D cross-section dimensions

Height (m)

Width (m)

Slope Ratio

80

725

2:1

80

725

2:1

2D cross-sectional area (m2) 45200 45200

Mass of cross-section (tonnes) 34,804 34,804

Specific density of the rock (kg.m-3

) 2800 2800

Sulfur mass fraction (%) 0.07 3.80

Effective sulfur mass fraction (%) 0.014 0.76

Porosity 0.35 0.35

Intrinsic oxidation rate (kg.m-3

.s-1

) 9.10E-11 2.16E-08

Water infiltration rate (ma-1

) 0.5 0.5

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 (O2)kg -1

(air) 0.23 0.23

Prediction

52

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)

Apply to Geochemical Predictions

December 3, 2008 NWMA - Reno, NV 53

0.1 mole/m2/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 seepage

PAF seepage Groundwater

NAF seepage

PAF seepage Groundwater

NAF seepage

PAF seepage

Groundwater

pH

7.84 4-7 7.31 7.84 4-7 7.31 7.84 4-7 7.30 7.84 4-7 7.28

Alk mg/L as CaCO3

280 <1 - 30 248 280 <1 - 30 249 280 <1 - 30 244 280 <1 - 30 234

SO4 mg/L 401 147 309 401 293 316 401 731 336 401 1448 370

Na mg/L 151 1.68 116 151 3.35 116 151 8.35 116 151 16.5 117

Ca mg/L 39.0 39.3 46.8 39.0 78.6 48.6 39.0 196 54.1 39.0 387 63.2

K mg/L 208 10.2 139 208 20.3 139 208 50.6 141 208 100 143

Mg mg/L 107 2.42 75.0 107 4.84 75.1 107 12.1 75.4 107 23.9 76.0

Al mg/L 0.0026 0.0018 0.0047 0.0026 0.0016 0.0047 0.0026 0.0054 0.0050 0.0026 0.019 0.0055

As mg/L 0.0016 0.0018 0.0012 0.0016 0.0036 0.0013 0.0016 0.0090 0.0016 0.0016 0.018 0.0020

Co mg/L 0.08 0.0027 0.052 0.08 0.0054 0.052 0.08 0.014 0.053 0.08 0.027 0.053

Cr mg/L 0.09 0.0011 0.057 0.09 0.0022 0.057 0.09 0.0055 0.058 0.09 0.011 0.058

Cu mg/L 0.014 0.0039 0.0098 0.014 0.0077 0.0100 0.014 0.019 0.011 0.014 0.038 0.011

Fe mg/L 0.00033 35.7 1.78 0.00033

67.8 3.27 0.00033 144 4.67 0.00033 271 5.22

Mn mg/L 1.3E-10 0.13 0.24 1.3E-10 0.27 0.24 1.3E-10 0.67 0.26 1.3E-10 1.32 0.29

Mo mg/L 0.41 0.0042 0.27 0.41 0.0085 0.27 0.41 0.021 0.27 0.41 0.042 0.27

Ni mg/L 0.021 0.26 0.032 0.021 0.53 0.045 0.021 1.31 0.081 0.021 2.60 0.14

Pb mg/L 0.00070 0.00067 0.00054 0.00070

0.0013 0.00057 0.00070 0.0033 0.00066 0.00070 0.0066 0.00082

Sb mg/L 0.23 0.0023 0.15 0.23 0.0046 0.15 0.23 0.012 0.15 0.23 0.023 0.15

U mg/L 0.22 0.0042 0.14 0.22 0.0083 0.14 0.22 0.021 0.14 0.22 0.041 0.14

Zn mg/L 1.08 0.037 0.72 1.08 0.075 0.72 1.08 0.19 0.72 1.08 0.37 0.73

Account for Oxygen in Predictions

54

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

Groundwater

NAF seepage

PAF seepage

Groundwater

Seepage/flow (m3/yr) 252340 22324 402779 252340 22324 402779

pH 7.84 4-7 7.31 7.80 4-7 7.28

Alk mg/L as CaCO3

280 <1 - 30 248 264 <1 - 30 236

SO4 mg/L 401 147 309 1042 155 702 101101740 3275475 124405883 262866150 3450905 282835978

Na mg/L 151 1.68 116 290 2.48 200 38066954 37411 46686432 73101265 55300 80540211

Ca mg/L 39.0 39.3 46.8 62.6 39.9 62.2 9834353 877480 18859224 15800596 890370 25053767

K mg/L 208 10.2 139 286 13.2 182 52525262 226772 55844268 72127211 294857 73320969

Mg mg/L 107 2.42 75.0 169 4.24 111 27085214 54019 30212838 42631770 94633 44754093

Al mg/L 0.0026 0.0018 0.0047 0.0026 0.0015 0.0045 657 39.4 1907 645 33.5 1794

As mg/L 0.0016 0.0018 0.0012 0.011 0.0019 0.0074 400.66 40.3 499.3 2881.2 43.3 2961

Co mg/L 0.08 0.0027 0.052 0.11 0.0034 0.069 19297 60.5 21034 26651 76.7 27640

Cr mg/L 0.09 0.0011 0.057 0.25 0.0021 0.15 22136 24.5 23118 62174 45.8 62083

Cu mg/L 0.014 0.0039 0.0098 0.0096 0.0047 0.0069 3478 86.3 3941 2413 106 2777

Fe mg/L 0.00033 35.7 1.78 0.00038 35.7 1.89 84.2 795869 715330 96 795906 760430

Mn mg/L 1.3E-10 0.13 0.24 2.1E-10 0.14 0.26 3.2E-05 2980 95984 5.4E-05 3109 103449

Mo mg/L 0.41 0.0042 0.27 1.24 0.0090 0.77 103524 94.6 107916 312240 201 311506

Ni mg/L 0.021 0.26 0.032 0.13 0.25 0.10 5377 5880 13046 32453 5485 39927

Pb mg/L 0.00070 0.00067 0.00054 0.0027 0.0034 0.0019 176.6 14.9 216.5 679.7 76.6 767

Sb mg/L 0.23 0.0023 0.15 0.29 0.0022 0.18 58021 51.7 60283 73576 50.0 73343

U mg/L 0.22 0.0042 0.14 0.29 0.0048 0.18 54870 93.1 57004 73165 108 72937

Zn mg/L 1.08 0.037 0.72 0.42 0.024 0.28 271493 835 288685 105277 538 112098

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

NWMA - Reno, NV 56

NWMA - Reno, NV 57

NWMA - Reno, NV 58

NWMA - Reno, NV 59

Example: Groundwater flowpath,

Zambian pit

Conceptual Model

61

Typical Steps

in Numerical Prediction

62

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 528 -- -- -- -- --

Al 10.9 <0.2 <0.3 0.05 0.33 4,810

Cu 9.83 <0.5 0.03 0.04 0.08 1,010

Mg 574 611 161 126 14.1 7,610

pH 4.3 8.8 7.7 7.9 8 3

Se 0.001 0.12 0.054 0.02 0.0008 0.15

Sulfate 4,230 3,300 1,090 1,040 30 50,200

U 0.05 0.03 -- -- -- 0.05

Predicted chemistry:

Flood u/g workings to base of pit

UG fill Pit Lake 2550

Concentration AWQS Avian

mg/L Criteria

Al 523.4 47.1

As 0.0216 0.01 22.1

Sb 0.0003 0.006

Ba 0.0980 2 89.4

Be 0.1260 0.004

Cd 0.0489 0.005 6.23

Cr 0.1720 0.01 4.3

Cu 116.5 202.0

F 23.4 4.0 33.5

Ni 6.58 0.1 333

Pb 0.0048 0.01 16.54

Hg 0.0002 0.0005 1.93

Se 0.0028 0.05 2.15

Tl 0.0010 0.002

U 0.0026 68.8

Sulfate 6756

Predicted Pit Water Chemistry

Pit Lake 2550 Pit Lake 2765

Concentration Concentration

mg/L mg/L

pH 5.54 5.68

Al 439.8 98.0

As 0.003 0.002

Sb 0.001 0.001

Ba 0.084 0.065

Be 0.111 0.012

Cd 0.042 0.022

Cr 0.152 0.118

Cu 127.1 79.0

F 19.95 19.00

Ni 5.58 4.99

Pb 0.004 0.004

Hg 0.000 0.000

Se 0.015 0.013

Tl 0.001 0.001

U 0.079 0.068

Sulfate 5750 6000

Batch test calibration

5/19/2014 66

• 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

Example: Prediction of Backfill

chemistry North Mara, Tanzania

Option 1: Conceptual Model for PAF waste disposal

in Gena pit lake (assumes that disposed material

will be unavailable for reaction)

Option 2: Conceptual Model for PAF waste disposal

above water level in Gena Pit (assumes that disposed

material will be available for reaction)

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

Define Model Inputs

Waste Rock

Geochemistry

Potentially Acid Forming

Not Acid Forming

Geochemical Rock Inputs

Scaling of Data

1012 kg in exposed pit walls

Rfield = Rlab x SFmoist x SFsize x SFcontact x SFtemp x SFO2

Rlab = HCT leach rates

SFmoist = reduced oxidation due to low moisture

SFsize = reactivity reduction due to HCT vs field PSD

SFcontact = reduction due to unflushed mass (retained solutes)

in field vs HCT

SFtemp = rate relationship for temperature: Arrhenius

SFO2 = reactive mass reduction due to O2 diffusion limits

Convert Laboratory Data

to Field Scenario

Method Modified from Kempton et al., 2012

Geochemical Calibration

Geochemical Predictions

• Against Tanzanian standards

exposed PAF waste above water

level is not recommended-

exceedences 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

Environmental Assessment

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