Designing Landscapes for the Future

  • September 1, 2020

Okane Consultants mine closure

Designing Landscapes for the Future

Erosion of landforms and waste containment facilities is one of the biggest environmental challenges for mining companies. High erosion rates can lead to degradation of cover systems, exposure of reactive mineral waste, acid and metalliferous drainage (AMD) and sub-optimal vegetation outcomes. However, rehabilitation projects are now benefiting from modern technologies and a better understanding of future performance.

In an era where technology such as unmanned aerial vehicles (UAV’s) or drones and terrestrial laser scanners (TLS’s) have made it possible to gather landform scale data within minutes, a shift in best practice landform assessment and design is inevitable. These technologies are now capturing data at unprecedented resolutions, recording details of the landform surface, and providing timelines of rehabilitation performance.

These technologies provide the ability to capture comprehensive landform information in less time and at lower costs than traditional approaches. The geo-referenced outputs provide sub-centimetre topographic survey and mapping capabilities, with such high-resolution aerial imagery that a golf-ball sized feature of interest can be revealed.

Leveraging Drones and Lasers

Traditional landform assessment techniques typically use transect sampling; a repeatable method based on established scientific methods for assessing rehabilitation progress. These methods are labour-intensive, costly, and do not provide the resolution required to confidently extrapolate results to an entire waste landform. Mine waste landforms often cover hundreds of hectares, contain numerous waste classes, have different combinations of geometry, aspect, and placement methods, therefore, homogeneity at a landform scale is rarely observed.

Modern instruments are extremely well-suited for erosional stability assessments due to their accuracy allowing for calculation of many fundamental metrics, including the eroded volume of an erosion feature (Figure1). They are also well suited for vegetation mapping and can be used to identify healthy (and stressed) vegetation using various colour filters in cameras making it possible to quantify vegetation metrics such as plant cover, landscape stem densities (stem/ha), biomass, and litter over entire landforms.

Rill erosion of a cover system on a mined rock stockpile landform.

Figure 1: Rill erosion of a cover system on a mined rock stockpile landform.

Capturing landscape scale erosion and vegetation metrics using new technologies has made it possible to assess landform performance by accurately quantifying parameters such as:

  • Stability trends, and rate of armouring;
  • Sediment loads and transport;
  • Critical failure points;
  • Criticality of various embankment length and gradient combinations;
  • Effectiveness of surface treatments such as contouring ripping and compaction;
  • Plant community development;
  • The effect of vegetation on erosion and sediment loss; and
  • Plant community comparisons between rehabilitated and natural analogue sites.

These metrics tell us how the landform has performed, however, the biggest opportunity is not in the monitoring/retroactive assessments, but rather obtained through predictive and validated assessments to provide confidence in design (i.e. using data to engineer success).

Predicting Future Landform Evolution

A trial landform embankment surveyed using a TLS is shown below (Figure 2). The image crudely visualises the extremely high-resolution data, a cloud of millions of discrete georeferenced points, each in true colour, and of sub-centimetre spatial accuracy.

Trial landform embankment surveyed using a terrestrial laser scanner (TLS).

Figure 2: Trial landform embankment surveyed using a terrestrial laser scanner (TLS).

This baseline data was collected as part of closure planning studies to contain potentially acid forming (PAF) waste. Over time this baseline will allow Okane to compare and monitor the smallest of changes to surface topography after, or during successive wet seasons. Temporal storm patterns collected by the landform weather station records the depth and intensity of rainfall, allowing for assessment of flow regimes, erosive energy and shear stress on surface materials. Subsequent surveys of the surface will record the impacts of individual storm and seasonal events.

Okane uses these correlations of energy and erosion to provide the fundamental relationships required to develop predictive landform evolution models. Once calibrated to rainfall events of various size and intensity, the models can be used for predictive design. Performance can be assessed for longer timeframes, at various geometries and under specific hydrological conditions. Over time, the calibrated model can be refined and optimised for clients to predict landform evolution at operational and closure timescales. Okane can then provide clients with final landform designs that do not rely on monitoring but provide confidence that design objectives will be met.

The use of traditional techniques to assess erosional stability and vegetation remain useful tools for gathering baseline data, however, due the point scale nature of these assessments they are difficult to extrapolate to a whole landform. In an era where drones and TLS’s have made it possible to gather high resolution landscape data, a shift in best practice to assess erosional stability and vegetation on large landforms has occurred. However, simply gathering high volumes of data does not ensure attainment of closure objectives. Okane leverages its multidisciplinary experts in unsaturated hydrogeology, integrated rehabilitation and revegetation, and landform design and evolution modelling to couple plant-soil interaction with landscape scale data to deliver realistic and optimised closure solutions for clients globally. Assessment of landscape scale erosion and vegetation features offer more integrated and comprehensive approaches to landform rehabilitation and mine closure.

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