Building Better Water Balance Models for Tailings and Mine Rock Stockpiles

Posted by  Jason Lillywhite

We are pleased to share insights from a recent presentation by Tony Zheng (University of Alberta Geotechnical Centre / OKane Consultants), Rebecca Hurtubise (AECOM), and Nicholas Beier (University of Alberta Geotechnical Centre).  This work was presented at the 2024 GoldSim User Conference. Their work focuses on building better water balance models for tailings and mine rock stockpiles, addressing critical challenges in mining operations.

In this blog post, you'll discover how physics-based models developed in GoldSim can provide insights into water balance, acid rock drainage (ARD) risks, and effective closure strategies. These advanced modeling techniques offer actionable knowledge to improve mine closure practices and ensure long-term environmental sustainability.

Read on to explore their innovative approaches and practical applications in the field of mining hydrology and geotechnical engineering.

Introduction

Seepage from tailings and mine rock stockpiles typically constitutes a small percentage of the overall site-wide water balance in mining operations. However, its disproportionate effect on water quality due to acid rock drainage (ARD) underscores the importance of effective modeling. Many site-wide water balance models for the permitting stage rely on simplified, empirical assumptions about the hydrology of these structures. This article presents examples of physics-based models built in GoldSim, focusing on how these approaches can offer more accurate insights into water balance, ARD risks, and closure strategies.

Context and Challenges

Mining operations often leave behind tailings and mine rock stockpiles, which pose unique environmental and operational risks. Effectively managing these risks requires a nuanced understanding of their hydrology, long-term physical and geochemical behavior, and potential environmental impacts.

Waste Rock

Metal leaching and ARD often occur when sulfide minerals in waste rock are exposed to oxygen and water. This reaction produces sulfuric acid, which leaches metals into surrounding water systems, impacting ecosystems and complicating reclamation efforts. Key challenges include:

• Delayed Onset: ARD may take decades to manifest, complicating efforts to predict and mitigate its effects.
• Integrated Planning: Closure plans often lack coordination with operational decisions, reducing their effectiveness in addressing ARD.
• Perpetual Maintenance: Infrastructure used to manage ARD deteriorates over time, requiring continuous maintenance.

Figure 1 - Metal leaching flow paths (source: Herasymuik, 1996)

 

Tailings Management

Tailings, due to their fine particles and weak structural strength, present additional challenges:

• Settlement: Tailings settlement affects landform stability and contaminant transport.
• Structural Weakness: Risks of liquefaction and dam instability require robust safety measures.
• Pre-deposition Limitations: Limited readiness of pre-deposition treatment technologies complicates risk management.

Addressing these challenges demands advanced modeling techniques to predict and manage hydrological and geotechnical behaviors effectively.

Advancements in Modeling Techniques

Traditional site-wide water balance models often oversimplify hydrological processes, leading to inaccuracies in long-term predictions. Physics-based and semi-empirical models developed in GoldSim provide a balance between complexity and usability, offering a detailed yet practical approach to addressing these challenges.

Intermediate Models in GoldSim

Intermediate models, as proposed by Zheng, Hurtubise, and Beier, leverage GoldSim’s dynamic simulation capabilities to bridge the gap between traditional numerical models and conceptual site-wide frameworks. These models integrate:

• Physics-Based Approaches: Capturing dominant material properties and mechanisms.
• Sensitivity Analysis: Allowing thorough testing of key parameters.
• Stakeholder Communication: Using GoldSim Player to present results effectively.

Figure 2 - Modeling Scope (Source: Zheng and Beier, 2018)

 

Case Studies Highlight Practical Applications

Case 1: Tailings Settlement

Simulating tailings settlement involves modeling water and solute transport using finite difference methods in GoldSim. This approach captures advection, diffusion, and temporal changes to predict water content and contaminant distribution. The resulting model informs:

• Landform Stability Assessments: Predicting how settlement impacts structural integrity.
• Contaminant Transport Risks: Identifying potential pathways for ARD development.

Figure 3 - Solute Transport Equation Implemented in GoldSim (Source: Zheng and Beier, 2021)

This physics-based modeling enables long-term planning for safer, more sustainable tailings management.

Case 2: Unsaturated Flow in Cover Systems and Mine Rock Stockpiles

Unsaturated flow modeling focuses on water movement through covers and waste rock to predict ARD onset.

Figure 4 - Unsaturated Flow in Cover Systems (Source: Zheng and Beier, 2021)

Using GoldSim, moisture pathways are modeled dynamically across multiple layers, capturing key interactions such as:

• Infiltration and Evaporation Dynamics: Simulating water fluxes under varying environmental and climatic conditions.
• Layered Feedback Mechanisms: Representing soil water retention and inter-layer flow. 

Figure 5 – GoldSim implementation of unsaturated flow in cover systems (Source: Zheng and Beier, 2021)

These models aid in designing covers that reduce water infiltration and minimize ARD risks over the long term.

Case 3: Strategic Waste Rock Management

Managing mine rock stockpiles involves techniques like classifying and separating waste rocks into potentially acid generating (PAG) and non-acid generating (NAG) materials (i.e. Separation), strategic placement sequencing of PAG and NAG materials (i.e.Layering) and using NAG materials to fully isolate PAG materials (i.e. Encapsulation).

• PAG Separation: Stacking acid-generating and non-acid-generating materials separately.
• Layering: Alternating PAG and NAG materials to slow oxygen and water infiltration.
• Encapsulation: Fully isolating PAG materials within NAG layers for maximum protection.

Figure 6 - Layering Options (Source: Hurtubise, 2022)

In GoldSim, this methodology is implemented using modular containers that encapsulate the logic for each lift and layer. A central Water Balance Container integrates flow and area calculations, ensuring scalability and clarity in modeling ARD risks.

Figure 7 - GoldSim Implementation (Source: Zheng and Beier, 2021)

Case 4: Tailings Dewatering Technology Evaluation

GoldSim is used to evaluate the impact of cross-flow filtration technology on reclamation and closure in the long-term. The cross-flow filtration technology involves physical processes like particle settling, cake formation, and filtrate water extraction. These processes are captured in GoldSim through:

• Interconnected Containers: Representing sequential dewatering stages.
• Semi-Empirical Formulations: Incorporating cross-flow dynamics and re-suspension effects.

Figure 8 - Semi-empirical dewatering formulation (source: Beier et al, 2020)

This approach evaluates the efficiency of dewatering technologies, supporting operational decisions and environmental compliance.

 

Key Findings

The case studies demonstrate how physics-based models in GoldSim address complex challenges in mining operations. These models offer:

• Improved Predictions: More accurate assessments of settlement, ARD risks, and dewatering efficiency.
• Informed Decision-Making: Enhanced clarity for designing mitigation strategies and closure plans.
• Flexibility: Modular designs that adapt to various site conditions and scenarios.

While intermediate models face may face challenges in stakeholder acceptance and complexity management, clear guidelines and classification schemes can improve accessibility and usability.

Conclusion

The application of intermediate models in GoldSim represents a significant advancement in mining water balance water quality modeling. By combining robust scientific methodologies with practical applications, these models address critical environmental and operational challenges. They enable modelers to design more effective mitigation strategies, improve sustainability, and ensure long-term safety in mining reclamation efforts.

For more details, consult the referenced studies by Zheng, Hurtubise, and Beier, or explore GoldSim’s capabilities further to determine if it suits your project’s needs.

References

Badiozamani, M.M., and Beier, N. 2022. Estimating the Potential Differential Settlement of a Tailings Deposit Based on Consolidation Properties Heterogeneity, Applied Sciences.

Beier, N., Zheng, X., and Sego, D. 2020. Development of an oil sands tailings management simulation model. Environmental Geotechnics: 1–15.

CEMA. 2012. End Pit Lakes Guidance Document.

Herasymuik, G.M. 1996. Hydrogeology of a sulphide waste rock dump. M.Sc. Thesis.

Hurtubise, R.R. 2022. Development of a Waste Rock Simulation Model Including Placement Techniques to Minimize Environmental Impacts of Acid Rock Drainage. M.Sc. Thesis.

Zheng, T., and Beier, N.A. 2018. System Dynamics Approach to Tailings Management Simulation, Tailings and Mine Waste Conference, Keystone, Colorado.

Zheng, T., and Beier, N. 2021. Simulation of Water Storage in a Reclamation Cover Incorporating Tailings Consolidation. Environmental Geotechnics: 1–12.