8. Sustainable water management
• Optimisation:
– Impact on downstream water resources
– Impact on environment
– Beneficial end uses
– Social impact
– Ongoing management costs
– Mine operations
• Unlikely to be a “walk-away” solution
9. Outline
• Mine life stages
• Conceptual model
• Water balances
• Water quality modelling
• Validation
• AMCER Protocol
10. Phases of mine life
Island Copper Lake
British Columbia, Canada
Photo: T. Fischer
11. Exploration No solution: reassess?
data, decision:
Mine feasible
1. Collate any
General existing site data 1. Mine plan,
conceptual history
model
2. Site-specific
conceptual model
WQ
modelling 3. Quantify/predict likely
tools WQ evolution
Flow chart of mine
4. Assess potential environmental 4. Scenario testing:
impact and end uses - prevention possible?
WQ - remediation possible?
water assessment
“poor” - backfilling feasible?
WQ good/ - downstream mitigation?
impact acceptable
5. Design and begin data collection program
6. Document all data, calculations
(+assumptions), sampling plan
7. As input data collected, update
predictions
Goal: pit lake with
8. As external and internal validation data beneficial end uses or
collected, test prediction; acceptable impact for
if necessary, improve minimum cost
19. Exploration No solution: reassess?
data, decision:
Mine feasible
1. Collate any
General existing site data 1. Mine plan,
conceptual history
model
2. Site-specific
conceptual model
WQ
modelling 3. Quantify/predict likely
tools WQ evolution
Flow chart of mine
4. Assess potential environmental 4. Scenario testing:
impact and end uses - prevention possible?
WQ - remediation possible?
water assessment
“poor” - backfilling feasible?
WQ good/ - downstream mitigation?
impact acceptable
5. Design and begin data collection program
6. Document all data, calculations
(+assumptions), sampling plan
7. As input data collected, update
predictions
Goal: pit lake with
8. As external and internal validation data beneficial end uses or
collected, test prediction; acceptable impact for
if necessary, improve minimum cost
27. Effect of wind sheltering on stratification
DYRESM - 100% surface wind speed
DYRESM - 10% surface wind speed
28. Exploration No solution: reassess?
data, decision:
Mine feasible
1. Collate any
General existing site data 1. Mine plan,
conceptual history
model
2. Site-specific
conceptual model
WQ
modelling 3. Quantify/predict likely
tools WQ evolution
Flow chart of mine
4. Assess potential environmental 4. Scenario testing:
impact and end uses - prevention possible?
WQ - remediation possible?
water assessment
“poor” - backfilling feasible?
WQ good/ - downstream mitigation?
impact acceptable
5. Design and begin data collection program
6. Document all data, calculations
(+assumptions), sampling plan
7. As input data collected, update
predictions
Goal: pit lake with
8. As external and internal validation data beneficial end uses or
collected, test prediction; acceptable impact for
if necessary, improve minimum cost
31. Surface inflow assumptions
CAEDYM - Fe(III) and Fe(II) – CAEDYM - Fe(III) and Fe(II) –
assuming 100% seepage through assuming 10% seepage through
black shale black shale
32. During Filling Monitoring
• Geochemical characterisation of mine void and
surrounds, to determine changes in contaminant release
• Changing pit bathymetry
• On-site meteorological forcing
• Establish current and predicted mass balances
• On-site water column sensor chains
• Water quality sampling
33. Mass balances - inflows
Island Copper Lake
British Columbia, Canada
Photo: T. Fischer
36. Lake Kepwari
Collie, Australia
river diversion
LDS data, Oct 2003-May 2005
2003-
37. Post-filling Monitoring
• Geochemical characterisation of local mineralogy
• Geochemical characterisation of source waters
• On-site meteorological forcing
• Establish current and predicted mass balances
• On-site water column sensor chains
• Water quality sampling
48. Exploration No solution: reassess?
data, decision:
Mine feasible
1. Collate any
General existing site data 1. Mine plan,
conceptual history
model
2. Site-specific
conceptual model
WQ
modelling 3. Quantify/predict likely
tools WQ evolution
Flow chart of mine
4. Assess potential environmental 4. Scenario testing:
impact and end uses - prevention possible?
WQ - remediation possible?
water assessment
“poor” - backfilling feasible?
WQ good/ - downstream mitigation?
impact acceptable
5. Design and begin data collection program
6. Document all data, calculations
(+assumptions), sampling plan
7. As input data collected, update
predictions
Goal: pit lake with
8. As external and internal validation data beneficial end uses or
collected, test prediction; acceptable impact for
if necessary, improve minimum cost
49. The team The funding
Team leaders Carolyn Oldham Australian Research
Greg Ivey Council
Jason Plumb, CSIRO ACMER
Research Assoc.BibhashNath Centre for Sustainable
Ursula Salmon Mine Lakes
Matt Hipsey, CWR State Government of
Geoff Wake Western Australia
PhD students Deborah Read Wesfarmers Premier Coal
Huynh Pham Griffin Coal
Masters students Anita Huber Sons of Gwalia
Alisa Krasnostein Collie Shire Council
Honours students Emma Craven University of Western
Peter Chapman Australia
Tung Nguyen
ManuellaSusanto
Alice Turnbull
Tom Zdun
Aaron Brunt