A risk-based approach to mine-site rehabilitation: use of Bayesian Belief Network Modelling to manage dispersive soil and spoil

Ghahramani, Afshin ORCID: https://orcid.org/0000-0002-9648-4606 and Bennett, John McLean and Ali, Aram ORCID: https://orcid.org/0000-0003-2986-9220 and Reardon-Smith, Kathryn and Dale, Glenn and Roberton, Stirling D. and Raine, Steven (2021) A risk-based approach to mine-site rehabilitation: use of Bayesian Belief Network Modelling to manage dispersive soil and spoil. Sustainability, 13 (20):11267. pp. 1-23.

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Abstract

Dispersive spoil/soil management is a major environmental and economic challenge for active coal mines as well as sustainable mine closure across the globe. To explore and design a framework for managing dispersive spoil, considering the complexities as well as data availability, this paper has developed a Bayesian Belief Network (BBN)-a probabilistic predictive framework to support practical and cost-effective decisions for the management of dispersive spoil. This approach enabled incorporation of expert knowledge where data were insufficient for modelling purposes. The performance of the model was validated using field data from actively managed mine sites and found to be consistent in the prediction of soil erosion and ground cover. Agreement between predicted soil erosion probability and field observations was greater than 74%, and greater than 70% for ground cover protection. The model performance was further noticeably improved by calibration of Conditional Probability Tables (CPTs). This demonstrates the value of the BBN modelling approach, whereby the use of currently best-available data can provide a practical result, with the capacity for significant model improvement over time as more (targeted) data come to hand.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Faculty/School / Institute/Centre: Current - Institute for Life Sciences and the Environment - Centre for Sustainable Agricultural Systems (1 Aug 2018 -)
Faculty/School / Institute/Centre: Current - Institute for Life Sciences and the Environment - Centre for Applied Climate Sciences (1 Aug 2018 -)
Date Deposited: 21 Oct 2021 04:44
Last Modified: 10 Nov 2021 01:40
Uncontrolled Keywords: mine rehabilitation; predictive probabilistic modelling; environmental risk; soil erosion; adaptive decision-making
Fields of Research (2008): 04 Earth Sciences > 0406 Physical Geography and Environmental Geoscience > 040608 Surfacewater Hydrology
05 Environmental Sciences > 0502 Environmental Science and Management > 050207 Environmental Rehabilitation (excl. Bioremediation)
05 Environmental Sciences > 0503 Soil Sciences > 050305 Soil Physics
05 Environmental Sciences > 0502 Environmental Science and Management > 050299 Environmental Science and Management not elsewhere classified
05 Environmental Sciences > 0503 Soil Sciences > 050302 Land Capability and Soil Degradation
Fields of Research (2020): 41 ENVIRONMENTAL SCIENCES > 4106 Soil sciences > 410605 Soil physics
41 ENVIRONMENTAL SCIENCES > 4104 Environmental management > 410405 Environmental rehabilitation and restoration
41 ENVIRONMENTAL SCIENCES > 4106 Soil sciences > 410601 Land capability and soil productivity
37 EARTH SCIENCES > 3707 Hydrology > 370704 Surface water hydrology
Socio-Economic Objectives (2008): D Environment > 96 Environment > 9606 Environmental and Natural Resource Evaluation > 960604 Environmental Management Systems
Socio-Economic Objectives (2020): 18 ENVIRONMENTAL MANAGEMENT > 1899 Other environmental management > 189999 Other environmental management not elsewhere classified
Identification Number or DOI: https://doi.org/10.3390/su132011267
URI: http://eprints.usq.edu.au/id/eprint/43956

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