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Modelling Tools for the Prediction of Drainage Quality from Mine Wastes

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Modelling Tools for the Prediction of Drainage Quality from Mine Wastes Improving the environmental properties, utilisation potential and long-term prediction of mining wastes Edited by Päivi M. Kauppila and Timo Tarvainen Geological Survey of Finland, Bulletin 408, 27-42, 2018 MODELLING TOOLS FOR THE PREDICTION OF DRAINAGE QUALITY FROM MINE WASTES by Muhammad Muniruzzaman, Teemu Karlsson and Päivi M. Kauppila Muniruzzaman, M., Karlsson, T. & Kauppila, P. M. 2018. Modelling tools for the prediction of drainage quality from mine wastes. Geological Survey of Finland, Bulletin 408, 27–42, 7 figures and 2 tables. The weathering of mine wastes often leads to low quality drainage typically characterised by acidic pH and elevated concentrations of dissolved metals/metalloids. Therefore, prior knowledge and quantitative predictions of drainage quality is crucial during mine planning in order to properly assess the environmental impact in the vicinity of mining activity. In recent decades, a great deal of research attention has been paid to accurately predict the mine waste drainage and that has led to the development of a wide variety of predictive models with different levels of sophistication. Despite the availability of a plethora of modelling approaches and well established tools, there is still a lack of attention towards attempting a rigorous predictive modelling at the planning phase (e.g. environmental impact assess- ment) of a mine. This work presents a relatively simple predictive model that can be used at such early phase of a mine when data is very limited. The model formulation is based on reactive transport approaches that take into account water flow, gas transport and mineral weathering reactions. Furthermore, this paper also includes example case studies (both in waste rock pile and tailings systems) demonstrating the scope and capability of the presented model and how such approaches can be used effectively at potential mine sites. Keywords: Prediction, mine waste, drainage quality, AMD, predictive model, reactive trans- port modelling Geological Survey of Finland, P.O. Box 1237, FI-70211 Kuopio, Finland E-mail: [email protected] https://doi.org/10.30440/bt408.2 Editorial handling by Timo Tarvainen. Received 28.4.2018; Received in revised form 30.9.2018; Accepted 22.11.2018 27 Geological Survey of Finland, Bulletin 408 Muhammad Muniruzzaman, Teemu Karlsson and Päivi M. Kauppila 1 INTRODUCTION Management of mine wastes is a prescient issue in cess based approaches that quantitatively resolve all mining sectors since uncontrolled waste disposal the relevant physical, geochemical, microbiological, may result in liability for the operators with the risk electrochemical, and thermal processes (e.g. Steefel of financial consequences as well as reputational et al. 2015). damage (e.g. Blowes et al. 2014). Of primary concern Depending on the capabilities, typical predictive is the release of low quality drainage from the waste models in mining environmental simulations can deposits that leads to adverse effects on the envi- be categorised as geochemical models that only ronment, ecosystem, and human health (e.g. Blowes take into account the geochemical processes occur- & Jambor 1990, Blowes et al. 2014, Nordstrom et al. ring in the waste piles (e.g. Parkhurst et al. 1985, 2015). Such drainages are known to be the results Davis & Ritchie 1986, Davis & Ashenberg 1989, Ball of the weathering processes of sulphide-rich waste et al. 1987, Blowes & Jambor 1990, Allison et al. deposits under oxic environments and/or under 1991, Wolery et al. 1992, Alpers & Nordstrom 1999, the influence of microbial activities (e.g. Blowes Tempel et al. 2000, Eary et al. 2003, Ramstedt et & Ptacek 1994, Tremblay & Hogan 2000, Amos et al. 2003, Moncur et al. 2005, Gunsinger et al. 2006, al. 2015, Nordstrom et al. 2015). Therefore, it is of Nordstrom & Campbell 2014), and more sophisti- utmost importance to understand the controlling cated reactive transport models that are capable physicochemical processes leading to toxic drain- of simultaneously capturing hydrogeological pro- age in mining environments to sufficiently predict cesses, multicomponent solute and gas transport, the overall system behaviour in advance (e.g. Dold thermal processes, microbiological and electro- 2017). chemical mechanisms in addition to the geochemi- During mine planning, the estimates of the cal processes (e.g. Pruess 1991, Pantelis 1993, Steefel drainage quality are required to properly assess & Lasaga 1994, Wunderly et al. 1996, Bethke 1997, the environmental influences for the environmen- Lefebvre et al. 2001, Mayer et al. 2002, Saaltink et tal impact assessment and for the environmental al. 2002, Prommer et al. 2003, Parkhurst et al. 2005, permit application to facilitate mine planning and da Silva et al. 2009, Šimunek et al. 2012, Parkhurst to prevent negative impacts on the watersheds. & Appelo 2013, Muniruzzaman et al. 2014, Amos et The prediction of effluent quality is, neverthe- al. 2015, Lichtner et al. 2015, Muniruzzaman & Rolle less, a challenging task. This is mainly because 2016, Nordstrom & Nicholson 2017, Pedretti et al. the mineral weathering reactions responsible for 2017, Rolle et al. 2018). the mine drainage are complex and long term (e.g. Despite the diversified supply of prediction meth- Blowes & Jambor 1990, Blowes & Ptacek 1994). In ods, limited publications exist on how to approach addition, they are site-specific and depend on the the modelling in a mine planning phase for which geology and climatic conditions of each mine site, data on the mine wastes is still limited. Due to these even though the overall chemical processes are the challenges, one of the aims of the KaiHaMe project same (cf. Plumlee 1999). (Management of mining wastes) was to provide In recent decades, a wide range of prediction additional tools for predictive modelling. As a first techniques have been developed including experi- step, a review of the existing prediction methods, mental methods focusing on laboratory and field including typical laboratory and field tests, as well scale tests to characterise different properties of as numerical modelling in particular, was car- waste materials (e.g. Morin & Hutt 1994, Price ried out within this project (Muniruzzaman et al. 2009, Tripathy 2014, Parbhakar-Fox & Lottermoser 2018b). In addition to the methods, the review cov- 2015, Dold 2017), as well as numerical approaches ered aspects such as relevant processes resulting to quantitatively describe and predict the system and occurring in mine drainage, available codes for dynamics by capturing all the key processes (e.g. numerical modelling, and code and model uncer- Mayer et al. 2003, Maest et al. 2005, Amos et al. tainties, and limitations and applicability under 2015). Numerical modelling is instrumental in Nordic climate. Muniruzzaman et al. (2018b) also quantifying the overall system behaviour especially discussed the potential approaches to enhance the where coupling between multi-scale processes leads prediction accuracy by using integrated methodolo- to non-intuitive system dynamics (e.g. Steefel et gies to properly describe the multifaceted processes al. 2005). Such modelling frameworks rely on pro- occurring in mine wastes. 28 Geological Survey of Finland, Bulletin 408 Modelling tools for the prediction of drainage quality from mine wastes As a next step, this investigation focuses on the lar, the model formulation, quality of the site-spe- predictive modelling of drainage water quality from cific information, and overall modelling workflow mine waste facilities (both waste rock piles and tail- were treated from the perspective of predictions ings) by means of reactive transport modelling. The in future waste facilities. The ultimate intent of study presents examples of predictive simulations these simulations is to demonstrate the presented at three particular mine sites in Finland illustrat- model capabilities and how this tool can be used ing the specific capabilities and scope of predictive in the planning phase of a mine. The simulation modelling. These simulation examples generally outcomes suggest that numerical tools in combina- demonstrate how reactive transport modelling can tion with good quality data have a great potential be effectively used in predicting the seepage water to interpret the timing and occurrence of the future compositions from mine waste settings under dif- low quality drainages that may be harmful to the ferent conditions (e.g. environmental conditions or surrounding receptors. In the following sections, a closure scenarios). Although the presented exam- brief summary of the results of the predictive mod- ples include predictive modelling in existing sites, elling is provided and the details of the study are they can be considered representative of potential presented in a separate GTK Open File Work Report future sites where data are very limited. In particu- by Muniruzzaman et al. (2018a). 2 STUDY SITES AND DATA COLLECTION Mine waste and drainage water samples were col- and from the Särkiniemi Ni mine in Leppävirta (in lected from three mine sites around Finland for operation during 2007–2009), and tailings samples the development of predictive models. Waste rock from the Pyhäsalmi Cu-Zn mine in Pyhäjärvi (oper- samples were collected from the Kylylahti Cu-Co- ated since 1962) (Fig. 1). All the sites were metal Zn-Ni-Au mine in Polvijärvi (operated since 2012) sulphide mines. 29 Geological Survey of Finland, Bulletin 408 Muhammad Muniruzzaman, Teemu Karlsson and Päivi M. Kauppila Fig. 1. Location of
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