Water quality impacts to surface water and groundwater receptors can be a major risk of mining operations. Managing that risk requires modelling, monitoring and management. One of the major uncertainties in developing a thorough water quality model is understanding the partitioning of seepage through a mine rock or tailings landform. Does the water report as surface water or as groundwater recharge?
A key control of this partitioning is the hydraulic conductivity (K) of geologic media underlying mine waste landforms. Similarly, hydraulic conductivity is an important control on mobilization and transport of contaminants through saturated mine rock and tailings. Hydraulic conductivity is a physical property which describes the ease with which a porous material can transmit fluid (usually water) through its pore spaces. It differs from permeability in that it is dependent on both the material and the fluid characteristics. Hydraulic conductivity is a parameter that is heavily relied on for use in numerical models to estimate travel times, velocity, and peak concentrations of contaminants of concern (COPC) reaching an environmental receptor. This article present considerations for one simple, yet effective, method to estimate in situ hydraulic conductivity and help conceptualization of water flowpaths at your site.
The reliability of hydraulic conductivity estimates is dependent on three primary factors:
1) How the tests were completed in the field
2) Estimation parameters selected during data processing
3) Appropriate interpretation by the solver
Error introduced at any of these stages may lead to under or over-estimation at the magnitude scale. Keep reading for tips to avoid these errors in your tests and improve your model results.
In situ horizontal hydraulic conductivity may be estimated in saturated deposits under confined or unconfined conditions. ‘Slug tests’ are a common and effective method to estimate in situ hydraulic conductivity in saturated zones. Other type of K tests could include pump tests, infiltration testing, or permeameter testing.
An in situ slug test begins by injecting or withdrawing a volume (typically a 1m3 solid slug) into the water column to generate an instantaneous change in pressure head. The change in displacement over time is monitored using a pressure transducer (logger). Appropriate test selection, range of logger, and reading interval of the logger is crucial to execute a reliable K test.
Some common areas where error can be introduced into the test include:
Parameter selection is dependent on which analytical solution is being used, under what conditions (confined vs. unconfined), and accuracy of physical measurements taken during execution of the test.
The most common mathematical solutions for overdamped tests include Hvorslev, Bouwer-Rice (B-R), and Kansas Geological Survey (KGS). Underdamped tests are typically solved using the Butler method. Each solution has been developed for specific aquifer properties, and care should be taken in selecting which solution to use.
To summarize some key consideration in the interpretation of K test, interpretation will be discussed in terms of B-R and KGS solutions. Assuming a test is completed in an unconfined aquifer in which the water table intersects the well screen, the B-R solution may be considered as a starting point. A filter pack correction is assumed for a porosity of 30%. Figure 2 illustrates the curve generated from the hypothetical test. Note the “double straight-line effect” which is an indication that B-R is an appropriate solution to use in this case.
Interpretation of this solution involves curve matching and feasibility assessment. When curve matching to the appropriate portion of the curve, an ideal head range between normalized head 0.2 and 0.3 m/m is typically a reasonable starting point. In the below example, the ideal head range captures later time recovery, and would not be considered the best part of the curve to fit. To assess if the estimated K value is feasible, consider what is known about the site, like lithology, groundwater flow direction, and confined/unconfined conditions.
Figure 2: B-R Example.
Created in AQTESOLV (demo version) 
Figure 3 shows an example of a reliable KGS solution in an unconfined aquifer with water level above the well screen. Curve matching in this case is typically computed by a program and involves less interpretation than the B-R solution above.
In this example, the Ss value may be used to assess the reliability of the estimate. An Ss < 1E-6 m/s may indicate an underdeveloped well or other potential issues. Adjustments can be made to initial displacement, anisotropy ratio, and/or well radius relative to borehole radius (to account for skin effects) until Ss provides a reasonable magnitude estimate. In most programs, Ss can also be forced set to a minimum value of 1E-6 m/s.
Figure 3: KGS Example
Created in AQTESOLV (demo version) 
Okane applies a comprehensive approach for developing hydrological and water quality models for greenfield and operating sites. The hydrological and water quality performance of a mine waste landform are interpreted within the context of the site-specific hydrological and hydrogeological settings, and with appropriate characterization of materials governing COPC fate and transport.
Okane takes great care in developing and interpretating numerical models that serve as powerful tools for understanding water flow and quality in mine-impacted watersheds. Hydraulic conductivity is a key input in developing quantitative estimates of water flow and quality. In the development of 2D and 3D numerical models, horizontal hydraulic conductivity is especially important as it dictates the lateral movement of water through the subsurface towards potential environmental receptors. Used in conjunction with other properties such as hydraulic gradients and COPC source and sink terms, accurate estimation of hydraulic conductivity is an important step towards developing a water quality model that informs the potential risk to water quality and effective strategies to mitigate this risk.
 Solinst. 2021. https://www.solinst.com/products/dataloggers-and-telemetry/3001-levelogger-series/ltc-levelogger/
 Sun, H., & Koch,M. 2014. Under -versus overestimation of Aquifer Hydraulic Conductivity from Slug Tests. Hamburg - Lehfeldt & Kopmann (eds)
 AQTESOLV. 2021. https://www.aqtesolv.com
Despite the global pandemic, national economies like Australia have shown resilience due in large part to the strength of the resources sector.  Despite the benefits this performance brings to investors, governments, and communities, it is the sector’s environmental, social, and governance (ESG) performance which is dominating public discourse and impacting investment decisions. License-to-operate remained the leading risk to businesses within the resource sector from 2019 to 2020. 
The reason – Inability to predictably control the impact on environmental and heritage values of the land on which we operate.
Where then, can operators focus efforts to control these impacts? From an environmental perspective, the mine features which frequently represent the largest potential source of contaminants are mined rock stockpiles (MRS) or waste rock dumps (WRD). These constructed landforms can contain significant existing contaminant loads, and have the potential to continue producing contaminants which can be mobilized; this process is generally known as metal leaching and acid rock drainage (ML/ARD) or acid and metalliferous drainage (AMD). These landforms dominate our post-mining landscapes yet their design and construction are often only undertaken with immediate operational expenditure (OPEX) in mind. It is this singular focus which compromises not only our industry’s environmental performance, but also our legacy and long-term liability.
By considering additional performance metrics such as projected seepage water quality and landform evolution during MRS / WRD design and construction, we can better understand the potential impacts of post closure liability on net present value (NPV). Understanding closure liability from an NPV perspective allows closure professionals to communicate upwards within their business and reach consensus about how full lifecycle environmental goals can be realised through smart landform engineering.
Fundamentally, limiting ML/ARD or AMD from an MRS or WRD is about managing the supply of oxygen into reactive waste, then limiting contaminant transport through surface water management and/or reduction of water through the waste (net percolation; NP). The way in which we manage or place mined rock, in combination with site-specific controls (e.g., oxygen availability, rainfall, temperature, surface water) largely drives the potential for negative impacts. Therefore, with years of research undertaken and an industry understanding of ML/ARD or AMD processes, some historically used MRS or WRD dumping and construction practices are no longer acceptable.
At Okane, we couple geochemical and hydrological modelling with mine-planning processes to evaluate a range of construction scenarios in respect to closure goals and NPV. We empower operators to make smart decisions about how legacy and liability are controlled.
Our process, rooted in the observational method, takes a site-specific approach through risk and opportunity analysis. Using Okane’s approach to integrated life of mine planning:
We present the range of options and their associated performance to our clients and stakeholders to inform decision-making and facilitate consensus building.
The landform option carried forward then becomes a fully integrated part of the mine plan, and operators no longer need to make unverified assumptions about the potential environmental impact of their MRS or WRD. Okane’s approach empowers operators to:
Okane has partnered with clients across the mining industry for 25 years and has established a clear Roadmap to Closure by managing closure performance from feasibility assessment through to relinquishment.
1 Constable, T (2020) Minerals Council Australia, accessed July 2021 https://www.minerals.org.au/news/mining-largest-contributor-australian-economy-2019-20
2 Mitchel (2020) Ernest and Young, accessed July 2021. https://www.ey.com/en_au/mining-metals/10-business-risks-facing-mining-and-metals
3 Terzaghi and Peck (1967) Soil Mechanics in Engineering Practice, 3rd Edition | Wiley
A cover system is a type of engineered barrier used to manage mine waste during operations or at mine closure. A cover system may be constructed using naturally available materials, such as locally available soils and mine waste with appropriate physical and chemical properties. However, they may also be constructed from a combination of natural and synthetic materials, with synthetic materials providing physical properties that natural materials alone cannot. A cover system’s main purpose is to provide a reclamation surface for mine waste storage facilities (e.g. waste rock dumps, tailings storage facilities) that provides a stable, reliable, and sustainable interface between the receiving environment and the mine waste (Figure 1).
Figure 1: Conceptual schematic of a cover system.
Design objectives for cover systems can vary, however common objectives are typically developed to address physical stability and chemical stability. Physical stability of a cover system is related to the overall landform design and may address concerns related to surface water management, dust and erosion control. Cover designs can also address chemical stability whereby water movement through a cover system and into stockpiles of reactive mine rock is to be minimised, leading to reductions in contaminant loadings into the receiving environment. We refer to the water movement through a cover system and into the underlying waste material as “Net Percolation”1.
Mining landscapes can be described at several scales: Region, Landscape, Landform, Landform Element and Microsite (Figure 2). A cover system design falls within the Landform Element scale and is an integral component of waste stockpile design, for example, waste rock dumps and tailings storage facilities. Therefore, integration of cover system and landform objectives is critical, and both sets of objectives must contribute towards achieving the agreed returning land use.
Figure 2: The mining landscape.
Cover system functions and types are broad, and selection depends on a site’s climate and the environmental impact(s) requiring mitigation.
There are six general cover system functions, some of which include several variations for achieving the intended function (Figure 3):
Figure 3: Cover system function; a) Reclamation/revegetation; b) erosion protection; c) store-and release and enhanced store-and-release; d) enhanced store-and-release – capillary break; e) barrier; f) saturated soil or rock.
Cover system designs may incorporate multiple functions. For example, it is very common to have reclamation/revegetation, erosion protection, and store and release cover functions coupled with a primary objective, such as minimizing contaminated seepage. In this example the cover design does not solely focus on minimising contaminated seepage but also captures the reclamation/revegetation and erosion functions providing a more robust solution. The overall solution establishes the target vegetation community and achieves acceptable erosion rates, which in turn have positive impacts to the cover systems ability to mitigate contaminated seepage.
Okane’s approach to designing cover systems for mine waste has been developed over 25 years working on mine sites spanning the globe across all climate regimes. Unlike other geotechnical consultants we integrate mine closure with mine planning to deliver optimized cover system design solutions for our clients at all mining stages. Over the years Okane has developed the following eight key factors that will ensure the success of your cover system:
Okane is the industry leading expert in cover system design and performance monitoring. Our multidisciplinary team can help you design, construct and monitor cover systems that will complement your final landform designs, and help you achieve your mine closure plans.
 International Network for Acid Protection (INAP), 2017. Global Cover System Design--Technical Guidance Document. November.
 Landform Design Institute (LDI), 2021. Mining with the end in mind: Landform design for sustainable mining. Position Paper 2021-01. March. Landform Design Institute. Delta, BC, Canada.