Uncontrolled discharge of Acid Rock Drainage (ARD) from Mount Morgan mine site accumulated over time poses significant environmental risk on the Dee River downstream. This paper investigates and flow dynamics and the ARD dispersion and dilution along the Dee River for a number of dam-break scenarios, especially to estimate the extent of downstream reduction in concentration in extreme weather conditions. Hydrologic data of Dee River was analysed and a detailed 1-D hydraulic river model was set up using Danish Hydraulic Institute, Mike 11, to simulate the contaminant transport of ARD. Simulation results of different weather condition assessed to be used as resource to proposed management options to minimise the risk of uncontrolled discharge into natural waterways. Results indicate that if dam break occur in a dry to medium season there is a risk of contamination of the downstream catchment. However if dam fails in a medium to wet season downstream concentration will be diluted to minimum 1.8 PSU

McCombe, C.

Tarakemeh, N.

Yu, B.

Zhang, H.

N. Tarakemeh

H. Zhang

B. Yu

C. Mccombe

CiteSeerX

Impacts of uncontrolled discharge of acid rock drainage from Mount Morgan Minesite on Dee River

University of Queensland eSpace

16th Australasian Fluid Mechanics Conference 
Crown Plaza, Gold Coast, Australia 
2-7 December 2007 
 
Impacts of uncontrolled discharge of acid rock drainage from Mount Morgan Minesite on 
Dee River 
 
N. Tarakemeh1, H. Zhang1, B. Yu1, and C. McCombe2 
1Griffith School of Engineering, Griffith University, QLD 4215, Australia and 2Dept Natural Resource and Mining, 
Rockhampton, Australia 
  
 
Abstract 
Uncontrolled discharge of Acid Rock Drainage (ARD) from 
Mount Morgan mine site accumulated over time poses significant 
environmental risk on the Dee River downstream. This paper 
investigates and flow dynamics and the ARD dispersion and 
dilution along the Dee River for a number of dam-break 
scenarios, especially to estimate the extent of downstream 
reduction in concentration in extreme weather conditions. 
Hydrologic data of Dee River was analysed and a detailed 1-D 
hydraulic river model was set up using Danish Hydraulic 
Institute, Mike 11, to simulate the contaminant transport of ARD. 
Simulation results of different weather condition assessed to be 
used as resource to proposed management options to minimise 
the risk of uncontrolled discharge into natural waterways. Results 
indicate that if dam break occur in a dry to medium season there 
is a risk of contamination of the downstream catchment. 
However if dam fails in a medium to wet season downstream 
concentration will be diluted to minimum 1.8 PSU.  
 
Introduction  
Mount Morgan Mine, one of the largest Gold Mines in 
Australia, located in central Queensland was significant in 
the context of Australian gold mining history. Gold was 
extracted for about a hundred years, and the mine closed 
down in 1981.  Acid rock drainage (ARD) is the key 
environmental concern at the mine site, as it poses 
significant adverse environmental risk to downstream 
catchments, the Dee, Don and Dawson Rivers. ARD 
results from the oxidised sulfide minerals in rocksand soils 
being mobilised by water moving over or through the 
sulfide minerals. This sulfidic waste material were dumped 
across a large area, including the slopes of relatively steep 
hills in the upper reaches of the Dee River catchment, 
which has facilitated its oxidisation and transport off site. 
The total area disturbed by mining activities covers about 
270 ha. Sulfide minerals have been exposed to weathering 
for more than 100 years in some parts of the mine.  
The Dee River is a part of Fitzroy River catchment, which 
flows to the east coast of the continent. Inadequate mine 
management practices of the past left the Dee River in a 
poor state, where PH is as low as 2.8 and is associate with 
high metal concentration, recorded in the Dee River next 
to the minesite during periods of low flow. While there is 
no recent evidence of acidic flows extending beyond the 
Dee River catchment into Don, Dawson or Fitzroy Rivers, 
there are oral reports of acidic flows extending into the 
Dawson River when mine was still working. Water quality 
in Dee River network deteriorated over time due to ARD 
seepage form Open Cut Pit known as one of the source 
points, NR&M (2003) [4]. In 2000, as a part of 
rehabilitation planning for this site, NR&M engaged EWL 
Sciences Pty Ltd (Jones, 2001) [7] to undertake a 
contaminant source study where Dee River has been 
monitored.  Rehabilitation Plans aimed to improve water 
quality downstream and enable greater usage of water 
resources by preventing overflows from the Open Cut Pit 
which could carry additional contaminant to the Dee 
River. NR& M (2003) [4]  Gauging stations monitor flow 
volume (or discharge) and water quality (PH, 
Conductivity) along Dee River from Kenbula ( upstream ) 
to Rannes ( downstream).  
The impact of dam failure and discharge of acidic flow to 
the river need to be assessed. In earlier studies, several 
numerical models have been developed for the purposes of 
simulating hydraulics, sediment behaviour, and water 
quality components in rivers. Wei Zenga (2003) [12] 
introduce a new model–STAND (Sediment-Transport-
Associated Nutrient Dynamics)–for simulating stream 
flow, sediment transport, and the interactions of sediment 
with other attributes of water quality. In contrast to other 
models, STAND employs a fully dynamic basis for 
quantifying sediment transport, thus distinguishing it from 
the well-known HEC-6 model. 
Water quality modelling in river systems, MARS (Model 
for Australian River Systems) has been developed by 
Musavi Jahromi (1996) [11]. The MARS-HD module is 
based on flow continuity and momentum equations. The 
MARS-AD module is established using a method known 
as “Quadratic Upstream Interpolation with Convective 
Kinematics and Estimated Streaming Terms” 
(QUICKEST). 
Todd (2004) [9] compared HEC-RAS and MIKE11 
Unsteady Flow Modelling for the Tillamook Valley. He 
discussed specifically the differences in computation of the 
channel roughness. His work shows that the computed 
difference in water surface elevation between the MIKE11 
resistance radius and the HEC-RAS hydraulic radius can 
be accounted for by adjusting the Manning’s. 
MIKE 11 has been selected to model ARD transport in 
Dee River as it is an industry standard for simulating flow 
and water level, water quality. Flexibility and speed 
ensure efficient modelling applications for all aspects of 
river engineering. In-built parameter optimization tools 
facilitate efficient model calibration and provide 
uncertainty assessment of results.  
 The main objectives of this study is to  
 To analyse hydrologic data and set up a hydraulic 
model to simulate the transport of ARD in Dee 
river.  
786
 To investigate the extent of ARD dispersion and 
dilution along the Dee River in extreme weather 
conditions.  
 
Methodology 
 
MIKE 11 is a general river modeling system developed by DHI. 
It is the most advanced and comprehensive of its type today. 
MIKE 11 has become industry standard in many countries, 
including Australia, New Zealand and Bangladesh and in many 
European countries (Danish Hydraulic Institute). MIKE 11 
contains modules for run-off simulations, hydrodynamics, flood 
forecasting, transport and dilution of dissolved substances, 
sediment transport, and river morphology as well as various 
water quality processes. 
 
 Conceptual Basis and Model Setup 
 
1- Hydrodynamic Module 
The hydrodynamic module (HD), which is the core of MIKE 11, 
includes an implicit, finite difference computation of unsteady 
flows in rivers and estuaries. The formulations can be applied to 
branched and looped networks and quasi two-dimensional flow 
simulation on flood plains. The computational scheme is 
applicable to vertically homogeneous flow conditions ranging 
from steep river flows to tidally influenced estuaries. Both 
subcritical and supercritical flow can be described by means of a 
numerical scheme, which adapts according to the local flow 
conditions. The complete nonlinear equations of open channel 
flow (Saint-Venant), DHI Mike 11 manual (2003)[5], can be 
solved numerically between all grid points at specified time 
intervals for given boundary conditions. The MIKE11 model has 
three different equations for determining the hydraulic radius in 
the above equation; the “resistance radius” (R*) (the default 
method) or one of two different hydraulic radius (Rh) equations, 
which uses either an “effective flow area” or a “total flow area”. 
“Resistance radius” has been selected for this model. 
 
2-  Advection-Dispersion Module 
The Advection-Dispersion module (AD), the advection-
dispersion (AD) module is based on the one-dimensional 
equation of conservation of mass of a dissolved or suspended 
material, i.e. the advection-dispersion equation. The module 
requires output from the hydrodynamic module, in time and 
space, in terms of discharge and water level, cross-sectional area 
and hydraulic radius. The Advection-Dispersion Equation is 
solved numerically using an implicit finite difference scheme 
which, in principle, is unconditionally stable and has negligible 
numerical dispersion. The one-dimensional (vertically and 
laterally integrated) equation for the conservation of mass of a 
substance in a solution, i.e. the one-dimensional advection-
dispersion equation reads: 
 
 where C : concentration 
D : dispersion coefficient 
A : cross-sectional area 
K : linear decay coefficient 
C2 : source/sink concentration 
q : lateral inflow 
x : space coordinate 
t : time coordinate 
Climate and hydrologic data around the Mt Morgan mine site 
analysed to define a set of appropriate upstream inflow 
conditions.  Lateral freshwater inflow downstream from the mine 
site will be estimated to determine the extent of dilution that is 
likely to occur.  A 1-D water quality model, DHI Mike 11, set up 
to simulate the contaminant transport process of ARD as a result 
of dispersion and lateral inflows.  Hydrologic scenarios and ARD 
discharge scenarios developed in collaboration with the NRM 
staff to represent a range of hydrologic conditions, including 
those during extreme events. 
  
Data and Method 
 
Relevant data was extracted from the records at gauging stations. 
These included: 
 flood peak discharges, for use in flood frequency 
estimation 
 rating curve, for use in calibration of the hydraulic 
model 
 flow velocities, for use in calibration and test of the 
hydraulic model 
 
Recorded flood hydrograph in February 2003 use as input to the 
hydraulic model. Figure 1, shows the flow in various location of 
the river for flood event on February 2003. Survey data is a 
critical input to the assessment with the hydraulic model. Details 
of the survey have been supplied by NR&M. 
-10
190
390
590
790
990
1190
1390
1590
1790
4/02/2003
6/02/2003
8/02/2003
10/02/2003
12/02/2003
14/02/2003
16/02/2003
Time
Fl
ow
 (m
3/
s)
 
Rannes
Wura
Fletcher
Kenbula
Dairy
 
Figure 1: Actual Data for Dee River on Flood Event in 2003. 
 
The ANZECC (2000) [1] guidelines provide trigger values for 
three ecosystem conditions, with a different level of protection 
recommended for each condition. Trigger values in the guidelines 
are concentrations of a chemical that, if exceeded, have the 
potential to cause problem(s) and so trigger a management 
response (ANZECC 2000)  
A detailed 1-D model, DHI Mike 11, has been set up to simulate 
the contaminant transport process of ARD as a result of 
advection and lateral inflows.  
In Hydrodynamic stage, Cross-sections of the river were 
provided for a reach from Kenbula Gauging Station to Rannes. 
Cross sections are 20 to 25 metres width which became wider in 
downstream. Typical depth is 5 - 10 metres. Plane coordinates 
entered in Cross section Editor for the left/right end of the cross 
sections spaced 5 km along the river. As resistance radius is 
applied, the levels selected according to variations in section flow 
width. Upstream of the river is narrow and become wider at Don 
River confluence. River runs at the slope of 12% to the south. 
 
The bed resistance has been selected Manning's n = 0.05, 
between three resistance type options in Mike 11:  
1. Manning's M (unit: m1/3/s, typical range: 10-100)  
2. Manning's n (reciprocal of Manning's M, typical range: 
0.010-0.100)  
3. Chezy number.  
 Wind effect has not considered in this simulation.  
 
Results and discussion 
 
A detailed 1-D model, DHI Mike 11, has been set up to simulate 
the contaminant transport process of ARD as a result of 
advection and lateral inflows.  
787
 
Model Validation: 
 
Dee River modeled for a flood event in Feb. 2003.To validates 
the model result, Available data from Wura gauging station is 
compared with Mike 11 HD, AD result. In Figure 2 Mike 11 
hydraulic result for flood event in 2003 is compared with actual 
flow data for Wura. In Figure 3 Mike 11 advection-dispersion 
result for flood event in 2003 is compared with actual salinity 
data for Wura. To adjust the result and get the most consistent 
result model runs with different Manning value and dispersion 
coefficient. After calibration of the model, simulation result is in 
reasonable agreement with the monitoring data.  
Mean square error for HD graph that compare Wura actual daily 
mean flow data and MIKE 11 result is 16%. Mean square error 
for AD graph that compares Wura actual EC data and MIKE 11 
result shows 9 %. 
This inconsistency results from insufficient data due to limited 
number of raw cross section data only at gauging stations. A 
number of cross section data have been changed in order to 
increase the model stability. Dee River bed is narrow in upstream 
and become wider in Rannes. Another explanation of this 
discrepancy is due to Dispersion coefficient and Manning Value 
which are not mathematical values and they might be chosen not 
exactly according to natural case. 
  
-100
0
100
200
300
400
500
600
700
800
900
29-
Jan-03
3-Feb-
03
8-Feb-
03
13-
Feb-03
18-
Feb-03
23-
Feb-03
28-
Feb-03
5-Mar-
03
10-
Mar-03
Time
Fl
ow
  (
m
3/
s)
Mike 11
Actual
 
Figure 2: Mike 11 HD Result and Actual Result for Wura: 25 
KM 
 
AD Wura
-0.2
0
0.2
0.4
0.6
0.8
1
1/0
2/2
0 0
3
8/0
2 /2
0 0
3
15
/02
/2 0
03
22
/02
/2 0
03
1/0
3/ 2
0 0
3
8/0
3 /2
0 0
3
15
/03
/2 0
03
22
/03
/2 0
03
29
/03
/2 0
03
Time
S
al
in
ity
 (m
ill
im
ho
s/
cm
)
Atcual
Mike 11
 
Figure 3: Mike 11 AD Result and Actual Result for Wura: 25 
KM 
 
 
 
 
 Scenarios Testing 
 
Three scenarios in different weather condition have been defined 
to assess the impact of Dam failure on downstream 
concentration. 
 
1- Dry Season Dam Failure with full storage:  
 
This scenario is expected to be the worst case scenario. Minimum 
flow is assumed for the Dee River, Dairy Creek, Fletcher Creek 
and Don River. Dam failure would lead to a rise in water level by 
less that 300 mm (Department of Natural Resource and Mining, 
Mine Pit Failure Impact Assessment Report, 2003) [4] is about 
150 m3/s. 
The initial conditions and boundary conditions are set based on 
assumptions and results from reviewing available data. For 
details of boundary set up refer to table 1. 
Results indicate that the salinity will be reduced from 13 PSU to 
12.67 downstream of the river. (refer to Figure 4) 
Boundary 
Description  
Boundary 
Type 
Chainage Inflow 
(m3/s) 
Salinity 
(PSU) 
open inflow 0 1 1 
source point inflow 1000 1 0 
source point  inflow 5000 150  13 
source point inflow 22000 1 0 
source point inflow 73000 1 0 
open Water 
level 
79000 0.5 1 
Table1: Boundary input data (MIKE11)  
 
 
12.6
12.65
12.7
12.75
12.8
12.85
12.9
12.95
13
13.05
0 20000 40000 60000 80000
Distance (m)
Sa
lin
ity
 (P
SU
)
Salinity , Dry
Scenario
 
Figure 4: Salinity (PSU) vs. Distance (m) 
 
  
2- Wet Season ( Intermediate flow ) Dam Failure with full 
storage 
 
In this scenario dam failure occurs in an intermediate flow in Dee 
River, and with minimum to medium inflows from other 
tributaries fed into the Dee River. Result shows that acidic water 
will be diluted to 8 PSU. According to Australian and New 
Zealand (ANZECC) Guidelines for Fresh and Marine Water 
Quality 2000 (Ref), there is a risk of ARD transport to the 
downstream and contamination of the whole catchment.  
The initial conditions and boundary conditions are set based on 
assumptions and results from reviewing available data. For 
details of boundary set up refer to table 2. 
Results indicate that the salinity will be reduced from 13 PSU to 
8 (PSU) downstream of the river. (refer to Figure 5) 
 
Boundary 
Description  
Boundary 
Type 
Chainage Inflow 
(m3/s) 
Salinity 
open inflow 0 75 1 
source point inflow 1000 10 0 
source point  inflow 5000 150 (3 
days) 
13 
source point inflow 22000 10 0 
source point inflow 73000 10 0 
open Water 
level 
79000 0.5 1 
Table2: Boundary input data (MIKE11) 
 
 
 
 
 
 
 
788
78
9
10
11
12
13
14
5000 25000 45000 65000 85000
Distance
S
al
in
ity
 (P
S
U)
Salinity vs. Distance, Wet 1
 
Figure 5: Salinity (PSU) vs. Distance (m) 
 
3- Wet Season (Flood Event) Dam Failure  
 
In this scenario dam will fail during a flood event while flooding 
occurs throughout the Dee River catchments and its tributaries.  
Peak flow values from Flood Frequency Analysis were used as 
boundary data. Result shows downstream concentration will be 
diluted to 1.8 PSU as a result of dispersion and dilution. There is 
no risk of pollution transport to downstream catchments. Figure 6 
shows the reslut for the salinity reduction along the river.  
The initial condition and boundary condition is set based on 
assumptions and results from reviewing available data. For 
details of boundary set up (refer to table 3) 
Results indicate that the salinity will be reduced from 13 PSU to 
1.8 (PSU) downstream of the river. (refer to Figure 6) 
 
Boundary 
Description  
Boundary 
Type 
Chainage Inflow 
(m3/s) 
Salinity 
open inflow 0 75 1 
source point inflow 1000 100 0 
source point  inflow 5000 150 (3 
days) 
13 
source point inflow 22000 150 0 
source point inflow 73000 900 0 
open Water 
level 
79000 0.5 1 
Table3: Boundary input data (MIKE11) 
 
Flood event
0
2
4
6
8
10
12
14
5000 15000 25000 35000 45000 55000 65000 75000 85000
Distance (m)
Sa
lin
ity
 (P
SU
)
Salinity vs Distance
Flood
 
Figure 6: Salinity (PSU) vs. Distance (m) 
 
 
Conclusion 
This paper investigates the impacts of dam failure and acidic 
water runoff into Dee River at different weather conditions. For 
this reason a detailed 1-D Mike 11 has been set up to simulate 
ARD transport along Dee River and calculate the concentration 
of downstream river as a result of dilution and dispersion. Result 
indicates that if dam fails in an instance that river has the 
minimum to medium flow, there is a risk of contamination of 
downstream catchments. But if Dam fails in a medium to wet 
season downstream concentration will be diluted to safe margin 
based on ANZECC 2000. The main concern would be when dam 
failure occurs during dry season that the river and other tributary 
fed into river have minimum flow.   
 
 
 
References 
  
[1] ANZECC (2000), Australian and New Zealand Guidelines for 
Fresh and Marine Water Quality, The National Water Quality 
Management Strategy. 
 
[2]Department of Natural Resources and Mines, Mount Morgan 
Mine Rehabilitation Project, 
 
[3] Dam Number 4,5,6 Dee River, Inspection Report, Draft, April 
2003  
 
[4] Department of Natural Resources and Mines, Rehabilitation 
Plan for Mount Morgan Mine, November 2003  
 
[5] DHI Software, 2003 ‘Mike 11 a Modeling System for River 
and Channels’ user Guide and  Reference Manual. 
 
[6]Haworth, L. (1975). Pollution of the Dee River resulting from 
mining at Mount Morgan, Department of Local Government 
Queensland. 
 
[7] Jones, D. R. (1996),  Impacts on the Dee River at Medium 
Flow by Discharges from the Mt Morgan Mine, CSIRO Minesite 
Rehabilitation Research Program. 
 
[8] Kellogg Brown and Root Pty Ltd. September 2003. Mt 
Morgan – Dee River Dams: Final failure impact assessment, 
Kellogg Brown and Root Pty Ltd, Toowong, Queensland 
 
[9] Todd H (2004), “Comparison of HEC-RAS and MIKE11 
Unsteady Flow Modeling for the Tillamook Valley” World 
Water Congress  
 
[10] Markham A and Dobos S. September 2003. Department of 
Natural Resources and Mines, Mount Morgan Mine 
Rehabilitation Project: Contaminant Sources in the Dee River, 
Hydrobiology Pty Ltd in association with Dobos and Associates 
Pty Ltd, Milton, Queensland 
 
[11] Musavi-Jahromi, (1996) Water Quality Modelling of River 
Systems, University of Wollongong - 1996 - University of 
Wollongong 
 
[12] Wei Zenga,*, M.B. Beckb,28 February 2003, STAND, a 
dynamic model for sediment transport and water quality 
  
 
 
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Impacts of uncontrolled discharge of acid rock drainage from Mount Morgan Minesite on Dee River

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