Predicting water depth to limit tailings resuspension in water cover – just add water? 1

Adrian Manlagnit

25 April 2008

1 This paper was written primarily as literature review on the current research work on the resuspension of

mine wastes using water cover, a common method of limiting acid mine drainage generation. The author has submitted this paper as part of the requirements in the graduate course ENVE 5704 Topics in Environmental Engineering: Mine Waste Management (Winter 2008) at Carleton University, Ottawa, ON. For more specific discussion of materials presented, the reader is directed to the Reference section for titles of the journal articles for his/ her further research.

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Abstract

Acid mine drainage (AMD), which generates sulfuric acid and dissolved trace metals from oxidation of mine wastes exposed to water and oxygen, is one of the most serious problems facing the mining industry. Creating water cover over tailings is seen to have the potential to limit oxidation that would produce AMD with its twin benefits of limiting oxygen diffusivity and solubility. This is evidenced by reduced sulfate and metals concentrations in laboratory and field studies where tailings and waste rocks were flooded. However, the resuspension of flooded mine wastes may threaten the apparent success of water cover. This literature review looks into recent methodologies developed to predict water depth that would prevent resuspension of flooded tailings. The Linear Wave Theory continues to provide the basis of the models used in wind-wave calculations, with the Sverdup-Munk-Bretschneider (SMB) model the most commonly used in the studies reviewed. A stand-out among the current methodologies is the one predicting the ‘optimum’ water cover depth – either a depth with no resuspension or a depth allowing resuspension and related water quality conditions but within regulations. A range of 0.5 m to 2.50 m of water depth to prevent resuspension was predicted at various test sites, though resuspension may still occur due to other factors not captured by the methodologies. Studies reviewed have recommended additional research to further understand the physio-chemical nature of tailings and their combined reactions so water depth as a function of resuspension could be suitably determined.

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Table of Contents

I. Introduction ………………………………………………………………………….1

II. Predicting Water Depth to Limit Resuspension..……………………………..3

III. Further Insights – Water Cover Mechanism and Resuspension.……..…..7

IV. Discussion……………………………………………………………………..….18

V. Conclusion…………………………………………………………………………20

References

Appendices

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1

I. Introduction

One of the many serious environmental problems the mining industry worldwide

is facing today is how to control acid mine drainage (AMD). AMD is produced

when tailings and waste rocks from mining pyritic massive sulfide deposits is

exposed primarily to water and atmospheric oxygen, resulting in sulfuric acid and

dissolved trace metals. Although AMD from pyrite oxidation can be naturally

produced and disseminated, they have localized impacts and can be attenuated

by dilution and neutralizing agents from nature. Whereas mining-produced AMD,

at higher concentrations in tailings impoundments, can contribute significant

loadings of acidity and dissolved metals when released to the environment

(MEND 1998).

To limit pyritic oxidation, water cover is one of the many emerging technologies

that can potentially limit the resulting AMD production from tailings and waste

rocks. Water cover is effective in suppressing oxidants for twin reasons – the low

solubility of O2 (8.6 g/ m3 at 20oC) and low diffusivity of O2 (~2 x 10-9 m2/s) in

water compared to 1.78 x 10-5 m2/s in air. Oxygen transfer in flooded tailings by

molecular diffusion is approximately 10,000 times slower than those without

water cover (Simms, et al, 2000). Other benefits of water cover include a)

creating a reducing environment for growth of sulfate- and nitrate-reducing

microorganisms that helps in precipitation of metals dissolved as sulfides and

ammonia from reduction of nitrates, b) preventing surface erosion and dust

problems.

Water cover evolved from the disposal of tailings on natural bodies of water such

as freshwater lakes and oceans for reasons of general convenience rather than

as a control mechanism for reactive tailings in the late 1980s (MEND 1998).

Although research data have shown that the disposal of sulfide-rich tailings in

biologically-productive lakes will not lead to long-term acid generation or

excessive concentrations of dissolved trace metals in the covering water, only

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short-term impact on the ecology and biology of the lake systems (MEND 1998),

the practice became increasingly unattractive to government regulators, thus the

shift to engineered impoundments.

There are four types of water cover methods that can be employed on mine

wastes, namely, (1) the sub-aqueous or underwater disposal in natural water

bodies such as lakes and marine disposal; (2) the disposal into man-made

impoundments or reservoirs;. (3) the disposal into flooded mine workings and

open pits, and (4) a water cover built on existing waste management sites

(Mohamed, et al, 1993). The near-impossibility of obtaining permits from

government regulators, particularly in North America, to dispose tailings and

waste rocks on natural marine waters pushes the mining sector to use the fourth

type - shallow covers (up to 2 meters) - as primary method of flooding mine

wastes and control AMD. Deep water covers appears to be less attractive option

to mine operators due to concerns on the long-term stability of reservoirs from

hydrostatic pressures, the high costs of construction including efficient flood

control systems and its maintenance, and the attendant monitoring of the

structure and water quality (Yanful, et al, 2004), among others.

Shallow water covers, compared with deeper ones, can also provide the twin

benefits of limiting oxygen diffusivity and solubility, thus dampening AMD

production and metals release. Laboratory and field studies (Yanful, et al, 2000

and Simms et al, 2000) have shown that dissolution and release of trace metals

from both oxidized and pre-oxidized can be minimized by shallow water cover.

However, wind-induced waves could cause erosion and resuspension of tailings

after flooding especially if the water depth is less than 1 m (Mian and Yanful,

2003). With oxygen concentration in shallow water covers at approximately close

to the saturation point (Vigneault et al, 2001), resuspension causes tailings to

oxidize more than flooded tailings at rest as shown in the laboratory (Yanful et al,

2000; Yanful and Verma, 1998). Indeed, resuspension is one of the key problems

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affecting the treatment and operational efficiency of flooding mine tailings waste

rocks, especially those with shallow cover.

This literature review looked into different methodologies developed to date to

predict water depth and examine the results from new studies that could be

further integrated in the design of water cover to prevent resuspension of flooded

tailings.

II. Predicting Water Depth to Limit Resuspension

From the early 1980s to early 1990s, laboratory studies were conducted primarily

to measure geochemical performance of water cover and these returned positive

results, i.e. even up to 99.70% reduction in AMD generation and control of trace

metals migration via precipitation compared to the unflooded tailings. This

apparent success in terms of geochemical performance could be threatened by

resuspension – a phenomenon that was not captured in the plexiglass columns

during earlier experiments however evidenced in later field studies (Yanful, 2004,

and Adu-Wusu, et al, 2001).

The depth of the water cover – with far-reaching effects from engineering design

(total volume of water and heights of impoundments) to physical/ geochemical

performances (control of AMD generation and structural stability) to project

economics (initial capital and long-term maintenance and monitoring costs) – is

a key component of implementing this AMD treatment technology. Designing

water cover depth is based on any of the two key criteria: 1) hydrological forecast

of the probability of occurrence of a drought event or 2) the minimum water cover

depth necessary to prevent resuspension (Yanful and Simms, 1998). There are

many variables, both measured and derived, in a wave activity that could

influence water depth as well as velocity as seen on Table I.

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Table I. Wave Variables Influencing Minimum Water Depth (MEND 1998)

Process Measured Variables

Derived Variables

Output

wave activity

wind speed wind direction fetch tailings grain size tailings density

wind duration wave period wave height

minimum depth bed velocity

Until the late 1990s, studies reviewed have shown that designing the water cover

depth was based on empirically-derived models and hydrological forecasting

(statistical probability approach of measuring drought duration to determine the

size and hence, the volume and depth of an impoundment to maintain moisture

saturation of the tailings). More importantly, the linear wave theory has provided

the continued basis of these models used to determine the minimum water cover

depth that will prevent resuspension of particles submerged in water.

Linear Wave Theory

The Linear Wave Theory, as described by Yanful and Simms (1998), is used

when estimating particle resuspension and is based on this premise – the height

of the waves is small compared to the wave length and water depth. This

premise then linearizes two boundary conditions describing the wave motion: 1)

the dynamic surface boundary condition which describes the vertical component

of water velocity at the surface, and 2) the kinematic boundary condition, which is

Bernoulli’s equation for unsteady flow at the surface. Water velocities can then

be determined. The horizontal water particle velocity is particularly important as

this correlates empirically with bed velocity, bed shear stress, or the wave height

to water depth ratio in controlling resuspension and/or stability of deposited

materials.

The horizontal velocity particle, u, can be derived by the following equation, with

other variables including assuming waves being either in shallow or deep water:

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u = πH [cosh (k+z)/ sinh (kd)] cos (kx-σt) where L

k is the wave number, defined as 2π/L

σ is the wave angular frequency, defined as 2π/T

z and x are spatial coordinates (z is negative below the water surface)

d is the water depth to the bottom

H is the wave height, empirically determined from wind-wave relationships

T is period, empirically determined from wind-wave relationships

L is wavelength to be solved iteratively using the equation = gT2 tanh (2πD/L)

2π If the depth is greater than L/2 i.e. (for deep water cover), the maximum

horizontal water velocity is independent of water depth and can be obtained

using the equation u = πH exp [2πz/L).

T

For shallow water covers i.e. engineered impoundments, the velocity equation is

given by u = πH exp [L/2πd).

T

Empirical Models and their Applications

With the linear wave theory providing working foundation to assess particle

resuspension, there are several empirical models that have been developed to

determine water depth based on waves in shallow and/or deeper water. These

are the Norwegian Hydrotechnical Laboratory (NHL) model, the Sverdup-Munk-

Bretschneider (SMB) model, the Rodney and Stefan model and the University of

British Columbia (UBC) model (Lawrence et al., 1991). Please refer to Appendix

I for more detailed description of the different models and methodologies.

The results from previous studies (Hay and Company Consultants, 1996,

Mohamed, Yong, et al, 1993; Eriksson, Lindvall, et al, 2001) on designing water

cover depth using various empirical models to date are summarized in the

following table. The data on Quirke Cell 14 (Elliot Lake) and Hjerkkin (Norway)

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mine sites and, whenever available, the resulting resuspension (or lack of it) for

each sites were taken from an earlier review of water cover projects made by

Yanful and Simms in 1998.

Table II. Water Depth Predicted by Various Models at Different Sites

Minesites Tailings/ ore types

Water cover design and empirical model/ method used

Predicted minimum depth + results

Equity Silver, BC (1996)

Minerals include chalcopyrite CuFe2, tennanite (Cu,Fe,Zn,Ag)12 As4S13 and tetrahedrite (Cu,Fe,Zn,Ag)12

Sb4S13.

To have no resuspension of tailings, HAY Consultants (1996) used the work of Lawrence et al. (1991), the UBC model and Komar and Miller (1975) relating the depth of water cover required for bed stability to wave height and sediment characteristics. Using wave hindcast procedures, the over-water distances at the Equity pond, and the sediment characteristics from sampling, the minimum water cover depth for a variety of wind speeds was calculated.

The depth required at no movement of tailings is 1.4 m at 18.6 m/s wind. Observed bed form showed resuspension at depths < 1.4 m. Water quality parameters as at 1996 < provincial guidelines, could be indication of no resuspension.

Solbec-Cupra, Quebec (1993)

The tailings have 1.56% Cu, 4.5% Zn, and 0.69% Pb, 52.11 g /t Ag and 0.58 g /t Au.

To prevent resuspension, a semi-empirical method based on Sverdrup-Munk-Bretschneider method for shallow water is used to calculate the significant wave height and significant wave period. Height of water = actual wave height in the field/ experimental ratio (wave height/water height).

The minimum water above tailing obtained is 1.341m; with sand layer on top of the tailings, the height can be reduced to 0.741m.

Quirke Cell 14, Elliot Lake, ON (1995)

The tailings’ chemically composed of 82% qtz.

The water cover’s depth is to maintain saturation of the tailings in the event of a drought and aid vegetation growth. Hydrological forecasting was used.

Minimum water cover depth is 0.6 m. Due to coarse tailings and small wave fetch, resuspension was not considered a potential problem, thus was not monitored.

Stekenjokk Tailings, N. Sweden (1989)

The tailings are sulfidic and metal rich (20% S; 0.65% Zn; 0.2% Cu) and has carbonates (7% CaCO3).

To ensure the tailings were covered even in the event of a 1000-year drought, the Norwegian Hydrotechnical Laboratory (NHL) model was used.

The calculated depth varied between 0.2 - 2.2 m for fetch lengths of 0.05 -1.10 km without a sand layer, and 0.2-0.93 m with a sand layer. Wave breakers also installed. TSS <

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detection (1995). Hjerkkin, Norway (1986)

The sulfur of the tailings varied from 18 % measured in 1976 to less than 5% in 1989. Cu, Zn, and Fe in a single sample 1989 was 0.26%, 0.49 %, and 17.5 % respectively.

To prevent resuspension, the Norwegian Hydrotechnical Laboratory (NHL) model was used.

A minimum depth of 1.5 m was obtained to stop resuspension, though it was not measured later in 1995. SO4 and Zn concentrations went down and could indicate reduced particles’ suspension.

It has been shown that shallow water cover (0.6 m to 2.2.m as predicted from the

aforementioned studies) could control resuspension. The addition of sand layer

(although at a cost if implemented) in the Solbec Cupra and Stenkenjokk sites

have also shown to decrease the volume of water and hence the depth.

However, these predicted values are site-specific due to disparate physical

features (geometry, size, orientation, wind conditions, climate, etc) of the tailings

ponds, in addition to complex behavior of flooded tailings themselves.

III. Further Insights – Water Cover Mechanism and Resuspension

Resuspension as has been verified by Yang et al (2000) is a function of frictional

shear force exerted by the flow per unit area of bed or the shear stress. When

the total bed shear stress (bottom current shear stress + surface wave shear

stress) due to wind-induced wave exceeds the critical shear stresses of the

tailings, resuspension would occur (Mian et al, 2003). Formulas for stresses

(bottom wave, surface current and critical) are on Appendix II.

As described by Mian and Yanful (2003) from previous studies (Baines and

Knapp, 1965; Lick, 1986 and Yang, 2001), wind creates a shear stress at the

surface at the surface of the tailings pond, which then drives a surface drift

current in the direction of the wind and a return current near the tailings of the

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bed. For shallow waters, wave action is the dominant force in creating shear

while it is the return current in deeper waters. Figure I illustrates the process.

Figure I. Mechanism of Wind-Induced Erosion, Resuspension and Transportation of Flooded Mine Tailings (Mian and Yanful, 2003)

Resuspension at shallow areas

A similar study from previously-enumerated cases (see Table II) has been

undertaken by Yanful and Catalan in 2001. At the Heathe Steel Upper Cell

tailings area (Miramichi, NB), a field test was made using field-measured wind

conditions, tailings pond geometry, and laboratory-measured physical properties

of tailings to predict wind-driven resuspension of mine tailings. Using the

Sverdup-Munk-Bretschneider (SMB) method, wave parameters such as wave

height and time period were determined while wind-induced shear stress at the

surface of the pond and return or countercurrents shear stress to result with the

total combined bed stress were also determined. A critical depth for tailings

resuspension was predicted to be 1.18–1.34 m. The critical shear stress of the

study tailings was between 0.12 and 0.17 Pa (see Figure I) and at 10 m/s wind in

shallow water cover, resuspension occurred.

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Figure I. Shear Stress and Suspended Tailings Concentration Measured in Rotating Plume (Yanful and Catalan, 2001)

From the field sediment traps, resuspension occurs largely in areas where the

water cover depth was 1 m or less. For the Heathe Steel Upper Cell tailings, a 1-

m water cover, tailings erosion could occur if the wind speed is greater than 7.5

or 8.5 m/s based on the lower or upper bound values of the critical shear stress,

respectively, while (see Figure II) the critical wind speed increases linearly with

water cover depth, and that the rate of increase (see Figure III).

Figure II. Shear stress vs. Wind Speed for 1-m Cover (Yanful and Catalan, 2001)

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Figure III. Critical Wind Speed vs. Water Cover Depth (Yanful and Catalan, 2001)

The study has also observed that currents generated by surface shear stress

traveling in the same direction with the waves as well as the bottom return

currents could have likely transported the resuspended tailings to other locations

where the cover was deeper than 1 m.

Total bed shear depends on wind speed, wave shear

Studies by Adu-Wusu et al (2000) on shallow water cover (< 1m) at Quirke Cell

14 (Elliot Lake, ON), they have found out that wind speeds greater than 8 m/s

could create wave heights greater than 10 cm and bottom shear stresses greater

than 0.2 Pascal resulted in erosion and resuspension as the critical shear stress

of the tailings was exceeded. The SMB method was used in determining wave

height and wave period. Other important findings on shallow water cover: a)

wave contribute more significantly than current in the total shear stress (see

Figure IV); and b) total shear stress is dependent more on wind speed than water

depth in shallow water (see Figure V).

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Figure IV. Shear Stress vs. Water Depth at 8 m/s (Adu-Wusu et al, 2003)

Figure V. Total shear stress vs. Water Depth at Different Speeds (Adu-Wusu et al, 2003)

Maximum resuspension at longest fetch

Field studies by Mian and Yanful (2003) on co-disposed tailings and sludge with

shallow covers (up to 2 m) at the Heathe Steele Mines (Miramichi, NB) have also

shown that wind blowing at 8-9 m/s along the long-axis (longest fetch) of the

tailings ponds produced more resuspension and erosion as indicated by higher

total suspended solids (TSS) concentration, exceeding the federal effluent

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guidelines of 25 mg/L. The SMB method was used in determining wave height

and wave period. Figures VI also showed that water cover depth of 1 m must be

maintained to ensure TSS concentrations are below federal guidelines and that

wind speed has to exceed 9.5 m/s for the bottom sediments to get float at 1 m.

However it must be noted that the calculated TSS concentrations are higher than

those measured at the effluent since the experiment was performed using water

column and the effects of transport and deposition of sludge were not factored in.

Figure VI. Calculated TSS concentration at max wind speed and varying fetches (Mian and Yanful, 2003)

This study has also confirmed the results of studies by Adu-Wusu, et al (2000)

discussed earlier that wave-induced shear stress dominates the total bed shear

stress and that bottom return currents has negligible effects for shallow water

covers (see Figure VII).

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Figure VII. Total Shear Stresses (from Surface Drifts and Bottom Currents) for 0.5 m Water Cover Depth (Mian and Yanful, 2003)

To eliminate or allow resuspension based on optimum water depth

Samad and Yanful (2004) have proposed a methodology of predicting an

optimum water depth that would either eliminate resuspension or allow

resuspension but with TSS and sulfate concentrations within federal regulations.

The minimum water depth required is based on the condition that wind-induced

bottom shear stress would not exceed the critical shear stress for tailings

erosion. The study prescribes that the distribution of required depths in the pond

is obtained by dividing the pond into a number of grids with suitable grid spacing

and the computations are performed at each grid cell. The design wind speed

and directional distribution for a given return period is based on measured wind

data. Fetch length at each grid points are then calculated according to the

directional wind distribution. Figure VIII describes the process while details of the

equations including variables used are in Appendix III.

In the computational framework proposed by Samad and Yanful (2004), the first

cycle of computations involves finding the minimum water depth needed to

completely eliminate resuspension of the tailings using wind data and the

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measured critical shear stress. The resulting depths are presented in depth-

contour maps.

Figure VIII. Computational Flowchart for the Methodology of Predicting Optimum Water Cover Depth (Samad and Yanful, 2004)

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During the second computational cycle, specific conditions are applied to the

minimum required water depth, allowing partial tailings resuspension, resulting

with reduced depth requirement. The equivalent TSS and sulfate concentrations

at reduced water depth are then determined and plotted as distribution maps

along with depth contours.

Wave parameters such as wave heights and periods were calculated with both

the SMB and the Coastal Engineering (CEM) methods the given wind speeds,

fetch lengths in the direction of the wind, and water depths. The time necessary

to meet the fetch-limited condition in the pond is also determined prior to

calculating significant wave properties (Samad and Yanful 2004).

As proposed by two authors (Samad and Yanful 2004), sulfate concentration will

be also estimated as an oxidation product based on the principle similar to a

batch reactor, where the rate of loss of oxygen for oxidation is set equal to the

rate of accumulation of the oxidation product. Oxygen consumption for oxidation

of the bed tailings can be obtained through the diffusion law; the dissolved

oxygen concentration in a completely mixed water column, in the absence of

advection or sediment resuspension, is found through the equation:

dC/dt = D * d2C/dz2 – K*C, where C is the oxygen concentration (kg/m-3); t is time

(s); D is effective diffusion coefficient of oxygen in tailings (m2/s-1); z depth of

water in water column (m) and K is oxidation rate (s-1). The steady-state solution

of the previous equation at the tailings-water interface can be found for oxygen

mass flux, O2 flux (kg.m-2s-1) as O2 flux = dm/dt = Co√D*K*. Co is oxygen

concentration at the air-water interface (kg.m-3).

Using the rate law and reaction rate constant, the rate of sulfate production can

then be derived from the previous oxygen flux (Samad and Yanful, 2004).

However, data on oxidation of resuspended tailings in a tailings impoundment

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can be largely unavailable, thus sulfate production is derived using the batch

reactor principle and volume of tailings resuspension (Samad and Yanful, 2004).

From an earlier study, Yanful and Gautam (2001) offered a formula to find the

rate of sulfate production, SO4-2 flux (kg.m2.s-1) = dms/dt = sE, where dms/dt is the

sulfate mass flux (kg.m2.s-1); s is the sulfate production rate from the shake flask,

e.g. 1.88 mgL-1(SO4-2).day-1.g-1L

-1(tailings) for the Heathe Steel tailings, and E being

the tailings erosion rate (kg/m2).

The erosion rate E can be found using the Ariathurai-Partheniades erosion

equation E = M [(τo - τc)/ τc]n for cohesive materials, where τo is the total bed

shear stress, τc is the critical bed shear stress with units of N/m2, n is an

exponent and M is a coefficient whose values can be found through laboratory or

in-situ experiments or from large-scale observational data (Samad and Yanful

2004).

The proposed model was used to calculate, as demonstration of the model, the

required depth of water as well as the reduced depth cover and the

corresponding TSS and sulfate concentrations at the Premier Gold Project-

Tailings Storage Facility (PGP-TSF) in British Columbia. The results are as

follows:

a) Minimum depth without resuspension: 0.80 m to 2.5 m (Case 1 at maximum

wind speed of 16 m/s) and 0.80 m to 4.40m (Case 2 at maximum wind speed at

16 m/s and assumed to be along the direction of the longest axis). See Figure IX

for depth contour of the two cases.

b) Restricting minimum depths to 1.5 m and 2.0 m, sulfate concentrations were

43 mg/L and 9 mg/L, respectively. Sulfate concentration rates also decreased to

9.8 mg/L/d and 2.8 mg/L/d (1.5 m and 2.0 m, respectively), see Figure X.

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Figure IX. Contour of Minimum Depth Required, Case 1 (left) at maximum wind speed of 16m/s and Case 2 (Right) at 16 m/s wind and along max fetch length (Samad and Yanful 2004)

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Figure X. Contour of sulfate production rate (intervals in mg/L/d); (a) case 3 with 1.5 m maximum allowable water depth and (b) case 4 with 2.0 m maximum allowable water depth. (Samad and Yanful 2004)

Other highlights of the Samad and Yanful (2004) study:

1) Both TSS and sulfate concentrations and rate of production increased when

maximum wind speed coincides with maximum fetch length. This has also been

proven in previous study (Mian and Yanful 2003).

2) Unlike studies made by Catalan and Yanful (2001) that assumed minimal

contribution of bottom current shear to the total shear stress, this present study

found the opposite is true, but largely dependent on the significant wave height

(affected wind speed and fetch length) and water depth in the pond. But

generally shares the same view that at greater water depth, bottom shear stress

is greater than wave (surface) stress.

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IV. Discussion

Methodology of predicting water depth

From all the studies surveyed, the minimum depth of water cover predicted

ranged from 0.2 m to 2.5 m, however, each site is different and correlation of

parameters and conditions when determining this value would be limited. The

SMB method appears to be robust when finding for wave heights and periods

based on measured variables (wind speed, direction and fetch) especially for

waves in shallow waters, although other models (see Appendix I) have also

performed well in wind-wave calculations. The approach of employing

hydrodynamic principles have yielded reasonable estimations of values (velocity,

stresses, concentrations, etc) or ratios between predicted and those measured in

the laboratory or in the field. However, even with the existing methods use in the

design of water covers, there could still be a chance for resuspension to occur at

wind speeds and fetch larger than those used in the studies.

Recognizing the recurring problem of resuspension of tailings, the latest

methodology suggested by Samad and Yanful (2004) of predicting water depth

that would either eliminate resuspension or allow it but at desired water quality

provides greater flexibility in terms of design, construction, maintenance/

monitoring and regulatory aspects to mine operators. The method has linked the

minimum depth to desired TSS and sulfate concentrations. Although at a

preliminary stage and has not yet been used on actual design, its computational

capabilities have initially demonstrated its practicality and usefulness in coming

up with scenarios e.g. range of concentrations and production rates at different

depths. But other aspects of the method such as wave measurements, surface

drift currents, TSS concentrations and laboratory concentrations have been

validated.

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Cover design considerations

Other surveyed studies in the paper may not have directly discussed depth

prediction however they were included as they have presented new information

on resuspension at different wind and wave conditions. Of particular important

findings include 1) the maximum loadings from resuspension (TSS and sulfate

concentration and production rate) occur when steady wind blow along the

longest axis of the pond; 2) wave-induced shear stress dominates the total bed

shear stress and that bottom return currents has minor effects at shallow water

covers and 3) total shear stress is dependent more on wind speed than water

depth in shallow water. These three previously-mentioned observations could be

used in deciding the geometry, orientation and size of a tailings pond to be

designed or operated.

Physical and chemical nature of tailings

The authors of the reviewed papers have also made the following observations:

a) A more comprehensive and rigorous evaluation of sediment transport in the

tailings pond would require careful field measurements of current velocity.

Further experiments are needed to fully understand the erosion and deposition

characteristics of the sludge and tailings particles. The dependence of the

cohesive nature of tailings and sludge particles on consolidation time, water

content, temperature, clay mineral content, and salt concentrations needs to be

investigated (Mian and Yanful 2003);

b) Estimation of the production of other metals aside from sulfate contained in

mine tailings requires assessment of the kinetic reactions of the minerals. In

addition, general water balance and seasonal fluctuations in water volume in the

tailings pond may contribute to the seasonal occurrence of relatively severe

periods of water quality concerns (Samad and Yanful 2004);

c) Certain properties of mine tailings such as thixotropy, flocculation and

cementation and their interactions may influence erosion and entrainment in

more complex ways than can be explained by simple flow dynamics (Adu-Wusu,

et al, 2000).

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d) An equation or model that would incorporate the processes of cohesion, self-

consolidation, flocculation, fall velocity, tailings pond hydrology and water

balance is still needed to address resuspension problem (Mian and Yanful 2002)

IV. Conclusions

This paper has surveyed studies relating how water depth, a critical component

in implementing this treatment technology, could be predicted to prevent

resuspension of flooded tailings. Resuspension due to wind-induced waves could

trigger reoxidation of resuspended tailings and compromising water and effluent

quality. Despite existing design methods and numerous models of preventing

resuspension, the phenomenon still occurs, both on shallow and deeper waters

(>2m). Examples specifically on the prediction of water cover depth have been

shown and a depth ranging from 0.2 m to 2.5 m were obtained at different test

sites, though no correlations exist among the parameters used during their

derivations as they are site-specific. Monitoring during and after field tests have

yielded some success though resuspension would still recur at a particular time

in a given year. New insights from recent studies can be useful deciding the

geometry, orientation and size of a tailings pond to be designed or operated to

minimize wave and introduction of oxygen. A new method was also proposed

that would predict ‘optimum’ water depth – either no resuspension or allow

resuspension at desired water quality – that could provide greater flexibility to

mine operators and regulators alike.

The Linear Wave Theory continues to provide the basis of the models used in

wind-wave calculations, with the SMB model the most commonly used in the

studies reviewed. Though they have provided tools in subsequent prediction of

minimum depth, the methods developed to date may not quite capture yet other

complex inter-relationship of variables such velocity, flocculation, pond geometry,

water balance, cohesion properties, chemical concentrations, among others

within the water cover. Thus, research is still needed to further understand the

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physiochemical nature of tailings so water depth as a function of resuspension

could be determined.

There is still a dearth of data as to the long-term viability and performance of the

water cover to control AMD and release of metals to the environment, thus,

continued monitoring of sites implementing this method is needed. Water cover

to treat mine wastes is a physical and chemical processes occurring

simultaneously and is more than just adding water.

23

References

Mian, M. H and Yanful, E. (2004). Analysis of wind-driven resuspension of metal mine sludge in a tailings pond. Journal of Environmental Engineering and Science 3:119 –135. Holmstromm, H., Ljungberg, J. and Ohlander, B. 2000. The character of the suspended and dissolved phases in the water cover of the flooded mine tailings at Stekenjokk, northern Sweden. The Science of Total Environment. 247: 15 – 31. Samad, M and Yanful, E. A design approach for selecting the optimum water cover depth for subaqueous disposal of sulfide mine tailings. 2005. Canadian Geotechnical Journal. 42: 207–228. Adu-Wusu, C, Yanful, E. and Mian M. Field evidence of resuspension in a mine tailings pond. 2001. Canadian Geotechnical Journal. 38: 796–808 Simms, P. Yanful, E, St-Arnaud, L, and Aube, B. A laboratory evaluation of metal release and transport in preoxidized mine tailings. 2000. Applied Geochemistry 15: 1245±1263. Elberling, B. and Daamgard, L. Microscale measurements of oxygen diffusion and consumption in subaqueous sulfide tailings. 2001. Geochimica et Cosmochimica Acta, Vol. 65, No. 12, pp. 1897–1905. Mohamed, A, Yong, R., Caporuscio, R and Li, R. Flooding of a mine tailings site and suspension of solids – Impact and Prevention. 1994. MEND Report 2.13.2b Vigneault, B, Campbell, P, Tessier, A, and De Vitre, R. Geochemical changes in sulfidic mine tailings stored under a shallow water cover. 2001. Water Resources Vol. 35, No. 4, pp. 1066±1076, 2001. Yanful, E, Verma, A and Straatman, A. Turbulence-driven metal driven release from resuspended pyrrhotite tailings. 2000. Journal of Geotechnical and Geoenvironmental Engineering, Vol. 126, No. 12. Paper No. 20515. Peacey, V, Yanful, E, Li, M and Patterson, M. 2002. Water cover over mine tailings and sludge: field studies of water quality and resuspension. International Journal of Surface Mining, Reclamation and Environment. Vol. 16, pp. 289 – 203. Samad, M and Yanful, E. 2005. A design approach for selecting the optimum water cover depth for subaqueous disposal of sulfide mine tailings. Canadian Geotechnical Journal. 42: 207–228.

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Yanful, E, Samad, M and Mian, H. 2004. Shallow Water Cover Technology for Reactive Sulfide Tailings Management. Waste Geotechnics, pp. 42 – 52. Catalan, L and Yanful, E, St-Arnaud, L. 2000. Field assessment of metal and sulfate fluxes during flooding of pre-oxidized mine tailings. Advances in Environmental Research 4: 295 – 306. Yanful, E. and Catalan, L. Predicted and field-measured resuspension of flooded mine tailings. 2002. Journal of Environmental Engineering, Vol. 128, No. 4. Catalan, L. and Yanful, E. Sediment-trap measurements of suspended mine tailings in shallow water cover. 2002. Journal of Environmental Engineering, Vol. 128, No. 1. Mian, H and Yanful, E. 2003. Tailings erosion and resuspension in two mine tailings ponds due to wind waves. Advances in Environmental Research 7: 745–765 Hay and Company Consultants. 1996. Shallow water covers – Equity Silver Base Information on Physical Variables. MEND Project 2.11.5ab. 71 pp. Simms, P and Yanful, E. Review of water cover sites and research projects. 1997. MEND Report 2.18.1. 137 pp. Design guide for the subaqueous disposal of reactive tailings in constructed impoundments. 1998. MEND Project 2.11.9. 183 pp.

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APPENDICES Appendix I. Description of Methods to Predict Water Depth – Hydrological Forecasting and Empirical Models (Yanful and Simms 1998) Hydrological Forecasting By statistically-determining drought duration period, e.g. 100 years, along with modeling the tailings hydrology, the size of the impoundment can be known that will primarily maintain moisture saturation of tailings during worst dry season. From the hydrological model of the impoundment, the required depth of water cover can be determined. Other factors such as hydraulic conductivity of the tailings and underlying soil deposits and the surface and sub-surface hydrology must also be known. The absence of realistic weather records hinders the accuracy of the statistical analyses thus allowing for substitution from neighboring stations. Empirical Models and Methodologies Norwegian Hydrotechnical Laboratory (NHL) Approach - Norway This method use empirical methods to calculate the necessary depth of water to eliminate resuspension based on two different criteria (shear force and shear velocity). For particle sizes greater than 100 µm, a maximum shear force at which particles will resuspend, based on work by Shields (1936), is calculated. For particle sizes less than 100 µm, a maximum shear velocity is determined. Estimates of resuspension consider wind events with a 10-year return period. Wave heights and wave periods are calculated for various fetch lengths. A non-dimensional fetch (F”) is calculated using the following relationships: F” = gF/u*

2 (F is the fetch, g is the acceleration due to gravity) u* is the air shear velocity is calculated by u* = CdU10

2

Cd = (0.8 +0.065 U10)10e-3: (U10 is the wind speed at a 10 m height above the water surface and Cd, the drag coefficient at the air-water interface) The following non-dimensional parameters are then defined: H”mo = g H”mo / u*

2 where Hmo is the significant wave height T”u = gTu/ u* , where Tu is the upper wave period Td’ = gTd/ u* where Td is the duration of the wind event These non-dimensional parameters have been correlated with fetch length using data from the North Sea: T”u = gTu/ u* where K1 = 0.0506 Td’ = gTd/ u* where K2 = 0.903

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Td’ = = K3(F”)e-3 where K3 = 23 From these parameters the real significant wave heights and periods can be back calculated. The uncertainty in the above expressions is assumed to be around 10 %. The bed velocity, Ub, can be calculated from the above wave characteristics using linear wave theory. The shear force at the bottom, τb, is then calculated as: τb = 0.5fw σw Ub2 where σw is the specific mass of water, kg/m3 Ub is the maximum bottom water velocity calculated from linear wave theory, m/s, and fw is a dimensionless shear factor and can be calculated iteratively using the expression: 1/(4√fw) + log 1/(4√fw) = -0.08 + log aw/(2.5d50) where aw is the water particle amplitude at the bottom calculated from linear wave theory and d50 is the average tailings particle diameter Shear force criterion, derived from Shield’s work, which estimated critical shear force for a given particle experimentally and is given by the empirical equation: Τsh = τ σw g d50 [(ys/yw) – 1] where Τsh is the critical shear force, τ is a dimensionless shear force obtained from Shield’s experiments, g is the acceleration due to gravity, and γs and γw are the specific weights of particles and water. Then if τb > τsh resuspension occurs. However, for particles sizes smaller than 100 µm, Shield’s criterion is unreliable because the background data are sparse, and the cohesive forces between small particles is not taken into account. For particle sizes less than 100 µm a critical shear velocity criterion is used. U* the shear velocity, is calculated as U* = (τb/ρs)e0.5, where ρs is the tailings particle density Then an empirical criterion is used to assess if suspension occurs: U* > 1.7 w, where w is the settling velocity. The settling velocity of a single, spherical, and cohesionless particle is assumed to represent the average settling velocity of suspended tailings of a certain grain size. Settling velocity is obtained from the results of Rouse (1937b) who performed experiments with spherical quartz particles of density of 2.65 g/cm3. To get a homogeneous suspension over the whole water depth, the shear velocity must be 200 times the settling velocity. UBC Approach (Lawrence et al., 1991) Lawrence et al. (1991) used linear wave theory and wave hindcasting procedures to determine the depth of water cover needed to prevent the resuspension of Syncrude oil sands tailings in northeastern Alberta. A simple model was developed Ward et al. (1994) to predict the amount of wind-entrained tailings and found good agreement between the model results and measured data. As with the NHL method, the design wind speed has

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a 10-year wind speed of 1-hour duration. Wave characteristics were calculated from wind speed and fetch using empirical relationships derived by the U.S. Coastal Engineering Research Center, except that the coefficients K1, K2, and K3 were 0.0016, 0.2714, and 68.8 respectively. Assuming that the bottom wave velocities can be calculated using linear wave theory, and that the waves causing suspension are deep water waves, then Ub = 2πH/Texp(2πd/L, where H and T are the wave height and period, d is the pond depth, and L = gT2/2π, the deep water wavelength. Note that d > L/2 is assumed in the derivation of Ub. Ub must exceed some threshold velocity Ut for resuspension to occur. Lawrence et al (1991) noted that because of the thixotropic nature of tailings there will be a significant difference between the behaviour of tailings and non-cohesive particles. Sverdup-Munk-Bretschneider Method This approach also relies on empirically derived expressions relating maximum wind speed, fetch length, and wind duration to wave characteristics previously but assumes waves are shallow. The method estimates the maximum wave height. Some investigations of resuspension have used a wave height to water depth ratio as a criterion for resuspension. The maximum wave height is calculated as Hmax = (0.5lnNIW)0.5Hs, where Hs is the significant wave height obtained and NIW (Td/Tp) is the number of incident waves. Td is the duration of the wind event, and Tp is the peak energy period, both obtained empirically. To verify whether shallow wave conditions exist, the wavelength, L= gT2/2π, must be less than twice the depth of water. Rodney and Stefan (1987) Method This method estimates the shear force at the bed in shallow ponds, which is employed in two empirical equations to estimate the rate of resuspension. The rate of resuspension and the settling velocity of the particles considered are used to calculate an equilibrium concentration of suspended solids in the pond. The bed shear stress is calculated considering three different wind-induced phenomena: return currents, progressive waves, and standing waves. The shear stress on the bed from a return current for non-stratified turbulent flow is approximately 10% of the shear stress generated on the surface (Baines and Knapp, 1965), and is given by τwl = 0.1Cd ρaU10

2, where U10 is the wind speed, Cd is the drag coefficient and Cd = 0.0005 (U10< 15 m/sec and Cd = 0.0026 for U10 > 15 m/sec. ρa is the density of air ( kg/m3) The shear force from progressive waves can be calculated from the bed velocity, Ub, is τw = ρf Ub

2, where ρ is the density of water and f is the wave friction factor, for which a value of 0.004 for flow in lakes was used. The bed velocity is calculated from linear wave theory. Wave height (H) and period (T) are calculated using the following empirical equations:

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where F, g, and d are fetch length, acceleration due to gravity, and pond depth respectively.

The stress caused by standing waves is periodic over a large time scale. The wind setup, or the difference in water depth from the downwind to the upwind end of a body of water caused by wind action, is calculated using the following empirical expression: S = 3.37 x 10(e-7) U10

2F/dm, where dm is the average lake depth (m) The maximum rise above the mean water depth, dr, is given by dr = 0.57S, and the the maximum flow velocity Um is Um = dr (g/dm)1.5. The flow velocity at any time t and at any distance x from the centre of the pond for a given fetch F is U = Um x cos (πx/F) x sin (2πt/T). Then the shear due to standing waves is obtained by substituting U into the equation τwl = 0.1Cd ρaU10

2. Appendix II. Wave Shear Formulas from Linear Wave Theory (Adu-Wusu, et al 2000) The bottom shear stress can be found by τw = ½ fw ρ u2

bm, derived from ubm = πH/T [1/sinh(2πh/L)] where ubm horizontal wave velocity, h is the depth of water, wave height H and significant wave period T from the ff equations:

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where F is the fetch and UA is defined as the wind stress factor (= 0.71U1.23, where U is the wind speed in meters per second) which accounts for the nonlinear relationship between wind stress and wind speed. Also, fw (fw = 2/√Rw) is the wave friction factor, r is the fluid density, and ubm is the maximum bottom fluid velocity near the tailings bed. The wave friction factor fw is a function of the amplitude Reynolds number Rw (Rw = ubmam/v, am is the maximum displacement of the individual fluid particles from their mean position and v is the kinematic viscosity of the fluid) and the relative roughness of the boundary. The stress due to wind-induced currents can be found by

The variables zsh and zbh are evaluated as zsh = zs/h and zbh = zb/h, where zsh = 2.2 × 10–4 and zbh = 1.4 × 10–4 were used (Wu and Tsanis 1994). The variables zb and zs are characteristic heights at the bottom and surface of the water, respectively, i.e., z = 0 and z = h, and are used to characterize the thickness of the viscous sublayer, with z

30

measured from the bottom of the pond. The nondimensional depth of water is expressed as zh = z/h. rw is the density of water. The constant l characterizes the intensity of turbulence. For surface Reynolds numbers ranging from 103 to 105, l is estimated to be between 0.2 and 0.5. The friction velocity at the surface, u*s (u*s = 0.035U/0.53x√ (ρa/ ρw). Note: ρw is the density of air, and U is the wind speed (in m/s). Previous equation (τw) can be used to calculate the shear stress due to current at the bottom where z = 0. For flow over a smooth bed, under laminar flow conditions, the combined bed shear stress is simply a linear addition of the pure current and pure wave shear stresses (Whitehouse et al. 1999). Appendix III. Formula and Variables Used in the Computational Framework (Samad and Yanful 2004) For shallow- and intermediate-water waves,

where h is the water depth (m); L is the wave length (m); Hs is the significant wave height (average height of the highest one-third of waves in a wave train (m)); F is the fetch length over which wind blows (m); Ua is the wind stress factor (m·s–1) (= 0.71U1.23, where U is the wind speed (m·s–1) at 10 m elevation); g is the acceleration due to gravity (m·s–2); and Ts is the significant wave period (s).

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where H0m is the energy-based significant wave height (m) (= Hs); ua * is the shear velocity in the atmospheric boundary layer (ABL) (m·s–1); and Tp is the wave period corresponding to the spectral peak frequency (s) (≈ Ts). The analysis (CERC 2002) also defines the persistent time required for achieving the fetch-limited wave condition for a given fetch length and wind velocity. The wind duration to achieve fetch-limited condition, tF,U (s), is given (CERC 2002) by

CD is the drag coefficient: Cd = Ua

*2/U2 and Cd = 0.001 91.1 + 0.35U) The wavelength, L (m), can be calculated iteratively by L = gTs

2/ 2π x tanh (2πh/L) The small-amplitude (linear) wave theory can be applied to determine near-bottom velocity amplitude, U1m (m·s–1), and particle displacement length, am (m), corresponding to the significant wave height and period. These can be obtained as U1m= πHs/Ts (1/sinh (kh); am = U1m/ωs where k is the wave number (= 2π/L); and ωs is the wave frequency (s–1) corresponding to the significant wave period (= 2π/Ts). Maximum bed shear stress, τ0w (N·m–2), developed by oscillatory motion at the free surface, can be described by applying the quadratic friction law (Jonsson 1966).

For laminar motion, the friction factor can be obtained analytically as shown by Jonsson (1966) is fw = 2/√Rew Counter Current Flow (CCF)-induced bottom shear stress, the equation is

The total bottom stress (wave and CCF): τo = τow/2 + τoc

The surface drift velocity, Us, has components from both wind-induced surface drift (Usc) and generated wind waves (Usw) and can be obtained following Wu (1975) and Fredsøe and Diegaard (1992), respectively.