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Surface-strip coal mine rehabilitation risk assessment : the development of an integrated rehabilitation risk assessment model for use in South Africa and Australia
Thesis (PhD)--University of Pretoria, 2020.
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| Format: | Thesis |
| Language: | English |
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University of Pretoria
2020
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| _version_ | 1867613595184922624 |
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| access_status_str | Open Access |
| author2 | Truter, Wayne Frederick |
| author_browse | Truter, Wayne Frederick |
| author_facet | Truter, Wayne Frederick |
| collection | Thesis |
| dc_rights_str_mv | © 2020 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
| description | Thesis (PhD)--University of Pretoria, 2020. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/77899 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:38:38.583Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2020 |
| publishDateRange | 2020 |
| publishDateSort | 2020 |
| publisher | University of Pretoria |
| publisherStr | University of Pretoria |
| record_format | dspace |
| source_str | UPSpace — University of Pretoria Institutional Repository |
| spelling | oai:repository.up.ac.za:2263/77899 Surface-strip coal mine rehabilitation risk assessment : the development of an integrated rehabilitation risk assessment model for use in South Africa and Australia Truter, Wayne Frederick u14460752@tuks.co.za O'Connor, T.G. Weyer, Vanessa Derryn UCTD Mine closure and rehabilitation integrated multi-disciplinary risk assessment rehabilitation maturity Bayesian networks integrated models and frameworks Thesis (PhD)--University of Pretoria, 2020. Surface-strip coal mine rehabilitation planning in South Africa and Australia is immature. Rehabilitation risk assessment, despite being advocated by leading practice guidelines and in some instances by legislation, is conducted with minimum requirements often met by rehabilitation professionals. Specialist data is gathered during mine approval and for the environmental impact assessment process. However, the focus of this is toward assessing mining impacts and not for rehabilitation risk assessment. Quantitative, integrated, multi-disciplinary rehabilitation risk assessment is seldom undertaken. This thesis provides a methodology towards the development of a quantitative, integrative, multi-disciplinary rehabilitation risk assessment model. Its purpose being to 'profile' surface-strip coal mine sites, in terms of their rehabilitation risk and potential for rehabilitation failure, from the outset of mine operations, with adjustments possible progressively during mine operations. The methodology was developed by first reviewing techniques suitable for the development of the model, as well as techniques developed by others. Bayesian networks (BN) were found to be the most suited. A R2AIN framework was then provided as a process towards developing several BN risk event models that can amalgamate to form a synthesis rehabilitation risk assessment model. A case study soil compaction BN model was used to demonstrate the framework in South Africa and Australia. The case study showed that it is possible to integrate and quantify rehabilitation risk, and most importantly to segregate risk into discrete contributing multidisciplines for analysis. Risk percentages can be calculated per multi-discipline, per mine phase, per site, to aid site risk ‘profiling’. It is recommended that further risk event BN models be prioritised for development and that a rehabilitation risk assessment model be developed to synthesise these into one model. This will require continuous improvements in the method, to build confidence, including extensive risk event and synthesis BN model evaluation and testing; improved BN input node states and values; and simplification of the conditional probability table construction method. Adaptation to other mining types, development activities and other regions should be investigated, as well as spatial linkages to geographic information systems. This research contribution improves upfront mine rehabilitation planning and decision making, providing improved tools and techniques than what currently exist. Geography, Geoinformatics and Meteorology PhD Unrestricted 2020-12-29T11:51:07Z 2020-12-29T11:51:07Z 2020/05/06 2020 Thesis Weyer, VD 2020, Surface-strip coal mine rehabilitation risk assessment : the development of an integrated rehabilitation risk assessment model for use in South Africa and Australia, PhD Thesis, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/77899> A2020 http://hdl.handle.net/2263/77899 en © 2020 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria |
| spellingShingle | UCTD Mine closure and rehabilitation integrated multi-disciplinary risk assessment rehabilitation maturity Bayesian networks integrated models and frameworks Surface-strip coal mine rehabilitation risk assessment : the development of an integrated rehabilitation risk assessment model for use in South Africa and Australia |
| title | Surface-strip coal mine rehabilitation risk assessment : the development of an integrated rehabilitation risk assessment model for use in South Africa and Australia |
| title_full | Surface-strip coal mine rehabilitation risk assessment : the development of an integrated rehabilitation risk assessment model for use in South Africa and Australia |
| title_fullStr | Surface-strip coal mine rehabilitation risk assessment : the development of an integrated rehabilitation risk assessment model for use in South Africa and Australia |
| title_full_unstemmed | Surface-strip coal mine rehabilitation risk assessment : the development of an integrated rehabilitation risk assessment model for use in South Africa and Australia |
| title_short | Surface-strip coal mine rehabilitation risk assessment : the development of an integrated rehabilitation risk assessment model for use in South Africa and Australia |
| title_sort | surface strip coal mine rehabilitation risk assessment the development of an integrated rehabilitation risk assessment model for use in south africa and australia |
| topic | UCTD Mine closure and rehabilitation integrated multi-disciplinary risk assessment rehabilitation maturity Bayesian networks integrated models and frameworks |
| url | http://hdl.handle.net/2263/77899 |