Chevrel, S, Croukamp, L, Bourguignon, A & Cottard, F 2008, 'A Remote-Sensing and GIS-Based Integrated Approach for Risk-Based Prioritization of Gold Tailings Facilities — Witwatersrand, South Africa', in AB Fourie, M Tibbett, I Weiersbye & P Dye (eds), Mine Closure 2008: Proceedings of the Third International Seminar on Mine Closure
, Australian Centre for Geomechanics, Perth, pp. 639-650, https://doi.org/10.36487/ACG_repo/852_59
The Witwatersrand gold field, located in the vicinity of Johannesburg, has been mined for more than a
century. The Witwatersrand Mining Basin is covered with an excess of 400 km² of covered tailings heaps,
thus affecting a considerable area and large watersheds. Tailings dams, waste rocks and derelict lands can
lead to regional environmental problems and disseminate potentially toxic materials into the environment.
This paper describes a collaborative project between the South African Council for Geoscience (CGS) and
the French Bureau de Recherches Géologiques et Minières (BRGM) Geological Surveys, on an Earth
Observation and GIS-based integrated methodology for rapid spatial screening and source characterization
of hazards associated with gold slime dam features at the local to the regional scale in the Witwatersrand
The following was performed: (i) a visual interpretation of land-use over time from satellite images, which
shows the growing urbanization in the West and East Rand, as well as tailings dams-reclamation, in
particular in the East Rand; (ii) a land-cover digital classification based on validated image spectra from
multi-spectral ASTER imagery, with a focus on potential surface water contamination; and (iii) a simplified
and Preliminary Risk Assessment (PRA), combining a number of information layers in a GIS, to rank the
tailing dams waste facilities and identify the sites requiring remedial actions or water/soil usage restrictions.
The GIS analysis is based on several data layers, including satellite images, digital elevation models
(DEMs), topographic maps, airborne radiometric images, geotechnical maps, groundwater depths,
boreholes, sinkholes and land cover. It uses a score-based ranking approach for each of the three
components of the pollutant source – pathway – receptor pollutant model. The final product is presented in
the form of maps that break down the final risk level related to the site, or the source classification, into
three categories: (i) sites at ‘high risk’, corresponding to sites requiring remedial works, land-use
restrictions or further detailed investigations; (ii) sites only requiring monitoring and for which it might be
necessary to draw up land-use restrictions as well as investigate and monitor sites with uncertain conditions;
and (iii) so-called ‘low-risk’ sites not requiring particular actions.
Boardman, J.W., Kruse, F.A. and Green, R.O. (1995) Mapping target signatures via partial unmixing of AVIRIS data:
in Summaries, Fifth JPL Airborne Earth Science Workshop, JPL Publication 95-1, 1, pp. 23-26.
Boardman, J.W. and Kruse, F.A. (1994) Automated spectral analysis: A geologic example using AVIRIS data, north
Grapevine Mountains, Nevada in Proceedings, 10th Thematic Conference on Geologic Remote Sensing,
Environmental Research Institute of Michigan, Ann Arbor, MI, pp. I407-I418.
Chevrel, S. (2004) Contribution of very high spatial and/or spectral resolution remote sensing in GIS-based
environmental hazard assessment of mining environments, keynote presentation at the 12th Australasian Remote
Sensing and Photogrammetry Conference, 18-22 October 2004, Fremantle, Australia (CD-ROM).
Chevrel, S. and Coetzee, H. (2000) A new tool for assessing the environmental impact of mining activities. Application
to the surface and groundwater sensitivity analysis of the West Rand area, Gauteng, South Africa. Proceedings
(CD-ROM) of the 28th International Symposium on Remote Sensing of Environment, Cape Town, South Africa,
27-31 March 2000, Paper RN 5.12.
Coetzee, H. (2008) Acquisition, processing and enhancement of multi-channel radiometric data collected with ultralight
aircraft mounted detectors. University of the Witwatersrand, Johannesburg. PhD Thesis, 357 p.
Cudahy, T. (2002) Mapping the Earth with ASTER, ASTER Workshop, Annual Meeting of the Geological Remote
Sensing Group, London, December 2002.
Cushman-Roisin, B. (undated) Environmental Fluid Mechanics, Thayer School of Engineering, Dartmouth College
Hanover, New Hampshire 03755,
Gentile, A.R., Quercia, F., Vecchio, A., Falconi, M., Schamann, M., Tarvainen, T. and Fons, J. (2005) Towards an EEA
Europe-wide assessment of areas under risk for soil contamination, Volume V. Objectives and Methodology,
European Environment Agency, 23 p. (
Robb, L.J. and Robb, V.M. (1998) Gold in the Witwatersrand Basin. The Mineral Resources of South Africa, sixth
edition, M. Wilson and C. Anhaeusser (eds), Pretoria, Council for Geoscience, pp. 294-349.
Wilson, M.G.C. and Anhaeusser, C.R. (eds) (1998) The Mineral Resources of South Africa: Handbook, Council for
Geoscience, 16, 740 p.
Winde, F. (2006) Impacts of gold-mining activities on water availability and quality in the Wonderfonteinspruit
catchment. An assessment of sources, pathways, mechanisms and risks of current and potential future pollution
of water and sediments in gold-mining areas of the Wonderfonteinspruit catchment, H. Coetzee. Pretoria, Water
Research Commission, pp. 13-34.
Wymer, D.G. (2001) The impact of gold mining on radioactivity in water and foodstuffs. Conference on
environmentally responsible mining in South Africa. Chamber of Mines of South Africa. Muldersdrift, 1,