Spatial assessment of open cut coal mining progressive rehabilitation to support the monitoring of rehabilitation liabilities

Worldwide coal mining has expanded over the past few decades, though growth has recently slowed due to reduced demand, partly due to concerns around CO emissions and climate change impacts. Coal mining is also a significant driver of land disturbance in regions where economic coal seams and coal mining methods are applied, in particular open cut extraction. To address these impacts, mined landscapes are rehabilitated with the aim of making them safe, stable, non-polluting and self-sustainable to an agreed post-mining land use such as agriculture or conservation. Progressive rehabilitation is often conducted to keep the footprint of disturbance to a minimum and to ensure that ecological and/or agricultural land use production is restored as soon as possible in preference to waiting until after mine closure. Environmental regulators require methods for tracking the performance of mining companies engaging in progressive rehabilitation to evaluate the success or otherwise of their regulatory frameworks and to ensure companies meet the requirements of their environmental authorities or mining licenses. In this study, we describe a spatial method for assessing mine disturbance and rehabilitation regionally and analyse our results in terms of rehabilitation liability. We first developed a land cover classification framework for mapping mining impacts and rehabilitation that categorises land cover using a mining land cover disturbance typology. We then used the Fitzroy Basin in Australia as a case study, utilising the land cover classification scheme to map 37 open cut-coal mines, using manual interpretation of remote sensing data. By comparing the percentage area of rehabilitation with the total mine area we assessed the variability in progressive rehabilitation for the 37 mines. For example, older mines which have a history of progressive rehabilitation should have large areas and a high proportion of area rehabilitated. Finally, we calculated a range of regional rehabilitation liabilities by applying two publically available rehabilitation cost-calculators to the land cover data. We calculated the rehabilitation liability as ranging from $2.7 to $5.5 billion Australian dollars. The lower and upper bounds of the estimate reflect the uncertainty associated with the range of land use types and potential rehabilitation methods, from simple to more complex rehabilitation methods. We conclude by discussing how the methods could be used to support effective decision making by government agencies regulating and monitoring mining activities