Henna Punkkinen, Markku Juvankoski, Tommi Kaartinen, Jutta Laine-Ylijoki, Elina Merta, Ulla-Maija Mroueh, Jarno Mäkinen, Emma Niemeläinen & Margareta Wahlström, VTT Technical Research Centre of Finland Ltd, P.O. Box 1000, FI-02044 VTT, Finland.


Dynamic modelling is a useful tool when aiming at solving behaviour of a certain system over time. It may also provide valuable information when studying systems having feedback loops as well as oscillating systems. (Maest et al. 2005) Dynamic models, such as GoldSim, allow naturally occurring integration of different variables with their respective variability functions. This kind of approach is especially good when modelling the system’s sensitivity to extreme events or its behaviour against the changes in the treatment system that can cause progressive drifting of some variables, such as water quality (Julien et al. 2005).

Description of the technology

GoldSim, developed by the GoldSim Technology Group is an icon-based general purpose simulation software for dynamic modelling of complex systems (GoldSim Technology Group 2014a). GoldSim offers a visual simulation environment with a large number of different modelling capabilities, e.g. both logical and discrete events can be modelled (Mueller 2013). GoldSim provides the features and flexibility to simulate almost any process related to business, engineering and environmental applications (GoldSim Technology Group 2014a).

Although in general dynamic modelling is not extensively used in mine water management yet (Griffiths et al. 2008), GoldSim is perhaps the most common software used in mine water balance calculations internationally. GoldSim is very adjustable to the needs of the user, which may be one of the reasons for its popularity. It allows user to create models of mine systems to optimize operations and water and waste management and to predict future behaviour and factors having greatest influence on the water balance.

GoldSim is a potential choice to be used in mine-specific and site wide modelling as it allows the integration of multiple data streams and the integration of water quality and water balance information (GoldSim Technology Group 2014a). For example, the codes used in hydrogeochemical modelling, surface and groundwater flow modelling as well as in geotechnical simulations (HSC Sim, PHREEQC, TOUGHREACT, etc.) or at least their dynamic output can be linked into GoldSim to build an integrated, site wide and mine-specific simulation tool. GoldSim is also the most important Monte Carlo simulation software solution for analyzing uncertainties and it is able to express model uncertainties explicitly (GoldSim Technology Group 2014a).

Appropriate applications

GoldSim is well-known to the mining industry and in environmental applications and has a large group of users (Mueller 2013), as the model characteristics are suitable for mining related modelling (GoldSim Technology Group 2014a). GoldSim can be used to address a broad range of issues related to mine water management, for example, to sustain different water management scenarios, carry out uncertainty and sensitivity analyses, simulate mass balance water qualities, and design site’s infrastructure (Janowicz 2011). In addition, mining companies also use GoldSim in assessing transportation of contaminants, environmental impacts, different closure options, and performance of process operations. Management and logistics of mine materials also benefit from GoldSim simulations. (GoldSim Technology Group 2014a)

GoldSim has many advantages over conventional spreadsheet based models for building complex, quantitative models, as certain limitations arise when spreadsheets are used for modelling dynamic processes and many quantitative modelling tasks (Janowicz 2011, GoldSim Technology Group 2014a). GoldSim also differs from system dynamic softwares that are based on stocks and flows and demonstrate the feedback structures of the system (such as STELLA, Vensim, and Powersim). Although similarities exist between GoldSim and these system dynamics softwares, GoldSim is able to provide more realistic simulation data of complex systems and their future performance. (GoldSim Technology Group 2014a) According to GoldSim Technology Group (2014a) and Janowicz (2011) GoldSim differs from many other modelling approaches due to the following characteristics:

  • The modelling capabilities of GoldSim are very versatile. A wider selection of model objects exist in GoldSim compared to other dynamic softwares, which makes GoldSim-based models logical and their structure more transparent. The transparency and robustness of GoldSim models is also better than with spreadsheets. GoldSim takes into account the concept of time and is thus better suited to simulate complex dynamic systems that evolve over time than the spreadsheets (GoldSim Technology Group 2014a).
  • GoldSim model is very flexible. By using the same base model, it is possible, for example, to perform both deterministic and probabilistic simulations, alternate simulation periods, model varying time-dependent conditions (such as process water sources and sump operations) over the mine life cycle, and incorporate water quantities and qualities. (Janowicz 2011)
  • Almost all real-world systems are influenced by uncertainties as well as stochastic processes and events, and predictive modelling must be able to handle these features. Spreadsheets, for example, are not able to naturally handle uncertainties and random events. GoldSim has the ability to explicitly represent such aspects as the software was especially developed to understand uncertainty factors and stochastic mechanisms (GoldSim Technology Group 2014a). Thus GoldSim is able to clearly express uncertainty issues related to water management systems (Janowicz 2011).
  • The occurrence and consequences of discrete events in continuous systems can be successfully modelled using GoldSim (GoldSim Technology Group 2014a).
  • Other modelling alternatives may not be dimensionally aware. I.e., they do not understand different types of units or dimensions which also make them sensitive to errors. GoldSim understands all types of units and performs dimensional consistency checks and unit conversions automatically. (GoldSim Technology Group 2014a)
  • GoldSim uses specialized extension modules (such as contaminant transport module, reliability module and financial module) that are able to address systems that cannot be sufficiently modelled using the stocks and flows (GoldSim Technology Group 2014a).
  • GoldSim can interact with a large group of external file formats, such as Microsoft Excel (Janowicz 2011). GoldSim works seamlessly with spreadsheet models and information can be dynamically passed to and from spreadsheets during the modelling process (GoldSim Technology Group 2014a).
  • GoldSim can ease the interpretation of complex spreadsheet models (GoldSim Technology Group 2014a).
  • The accessibility and ease of use is better in GoldSim as there is a free version available (GoldSim Player) with limited functionalities, allowing anyone to view and run models created by authorized users (GoldSim Technology Group 2014a).

However, spreadsheets can be more suitable than GoldSim in assembling large data amounts quickly and making calculations in a single view (GoldSim Technology Group 2014a).


GoldSim model can be delivered as a self-contained GoldSim Player file which is operable by the freely distributable GoldSim Player executable. The intention of the Player file is to be intuitive for the end-user, report needed results and to allow for any anticipated changes in numerical input terms. A limited number of options can be provided that reflect different water management strategies, but not all real-world possibilities can be incorporated into these options without the quantitative definition of the management options. Models created using GoldSim Authoring tools allow to create custom interfaces or dashboards into these Player files. Buttons, input fields, sliders and result displays can be included into these interfaces. Embed text, tool-tips and graphics can also be included into the dashboard to provide instructions on the model use. (GoldSim Technology Group 2014b)

The contaminant transport module of GoldSim enables simulation of different chemical processes such as solubilities and partitioning. These processes are simple, easily configurable and flexible, but cannot be used to illustrate complete reaction paths because additional chemical relationships may be required to simulate complex hydrochemical systems. Complex chemical processes of chemical equilibrium and aqueous speciation can be modelled by integrating dynamic link library (DLL) element of GoldSim with PHREEQC (Figure 1). (Eary 2007)

Figure1. The integration of PHREEQC into GoldSim (Figure © Juhani Korkealaakso/VTT).

Usher et al. (2010) present an approach that can be used to connect empirical and theoretical geochemistry. In their work they link site-specific mine waste characterisation results and mine water balances together to predict the quality of mine water derived from waste sources. Geochemical responses from on-site monitoring, kinetic field tests and laboratory results have been linked to PHREEQC to recognize the main geochemical processes occurring at the site. Based on the data from static geochemical tests to populate the models, defined geochemical generation rates, geochemical properties of the site and water balance of the mine site, the role of GoldSim is to realise the conceptual understanding of different aspects and build a framework to provide water quality projections on a mine scale. (Usher et al. 2010)

Dynamic models differ in cost and complexity. At least in 2005 GoldSim was the most extensive modelling environment available but at the same time also the most expensive modelling code. (Maest et al. 2005) The flexibility of a general-purpose simulator and highly-graphical probabilistic simulation environment are combined in GoldSim. The graphical, object-orientated and hierarchical structure of GoldSim, the use of modules and subsystems that are linked together along with other specialized programming options enable the development of highly complex models that are yet easily interpretative (GoldSim Technology Group 2014a). Also more intuitive representation of the water management units and their operations can be developed (Janowicz 2011). Graphically GoldSim models mix visual and mathematical symbols (Ford 2010). GoldSim entails certain pre-coded objects that can be used in water balance applications (Nalecki & Gowan 2008). Furthermore, the software contains object types which can be coded and customized by the user depending on the specific modelling needs (Nalecki & Gowan 2008, GoldSim Technology Group 2014a).


Eary, T. 2007. Linking GoldSim with the PHREEQC Geochemical Model with a Dynamic Link Library Element. GoldSim 2007 User Conference, San Francisco.

Ford, A. 2010. Modeling the Environment (2nd Edition). Island Press, Washington D.C., 380 p.

GoldSim Technology Group 2014a. GoldSim Home Page. visited: 13.6.2014. Available at:

GoldSim Technology Group 2014b. GoldSim Dashboard Authoring Module. User’s Guide. Page visited: 13.5.2015. Available at:

Griffiths, J., Connely, R. & Harding, W. 2008. The importance of a good Mine Water Balance and the benefit of early data collection. Mining Magazine, July 2008. Page visited: 16.5.2014. Available at:

Haanpää, K.-M. 2013. Vesitaseista. Kaivokset vastuunkantajina – Koulutusseminaari 10 – 11.10.2013, Oulu. (in Finnish).

Janowicz, J. R. 2011. Guidance Document on Water and Mass Balance Models for the Mining Industry. Yukon Government, Environment. December 19, 2011.

Julien M.R., Gowan, M., Nalecki, P. & Kissiova, M 2005. Water balance and its integration in mine operation through the use of real-world systems modelling tools. 2005 Symposium Mines and the Environment, Rouyn-Noranda, Quebec, Canada.

Maest, A.S., Kuipers, J.R., Travers, C.L., and Atkins, D.A., 2005. Predicting Water Quality at Hardrock Mines: Methods and Models, Uncertainties, and State-of-the-Art. Kuipers & Associates and Buka Environmental.

Mueller, S. 2013. Mine Water Management -From Pre-feasibility to Closure. Mine Water Management and Treatment. Kuopio, Finland 24.9.2013.

Nalecki, P. & Gowan, M. 2008. Mine Water Management – Dynamic, Probabilistic Modelling Approach. In: Rapantova, N. & Hrkal, Z. (Eds.) Mine Water and the Environment, Ostrava (VSB – Technical University of Ostrava), 533-536. ”10th International Mine Water Association Congress“, Karlsbad, Czech Republic 2008.

Usher, B., Strand, R., Strachotta, C. and Jackson, J. 2010. Linking fundamental geochemistry and empirical observations for water quality predictions using GoldSim “Mine Water and Innovative Thinking”, IMWA 2010. Sydney.