Open Cut » Environment
This report describes the technologies for exploring management strategies, assessing risk and addressing the challenges of both excess and insufficient water on mine sites under extreme climate variability. This is achieved through the use of a climate-driven, hierarchical system model (C-HSM) of a mine water system embedded within an optimisation scheme capable of examining the feasibility of optimal pathways for managing water on sites.
The report set the research context with an investigation into the mine site flooding risks. Flooding of mining pits has the potential to be the largest and most critical impact on a mine. A spatial framework for the assessment of regional flood risk for the mining area was developed. The approach presented in this study couples analytical hierarchy process-based multi-criteria decision making techniques with GIS. Incorporating GIS enhances the visualisation capability and increases the assessment efficiency.
The report also addresses the needs for climate and landscape data collections. The project investigated a number of data sources for case studies, and explained the techniques used to capture rainfall forecast data through down-scaling the Predictive Ocean Atmosphere Model for Australia (POAMA) seasonal forecasts and setting environmental discharging conditions.
The basis of the research is the development of a C-HSM, which helps to focus on the interaction and adaptation to extreme climate variability. Based on the C-HSM, this report demonstrates how a process-based water management simulation model is built and calibrated. A multi-objective optimisation framework was used to calibrate the 16 mine models against a number of calibration objectives and assess the performance of each mine. Model features related to rainfall and evaporation, storage dynamics of the worked water stores and unregulated annual discharges in the 16 mine sites were then analysed. Future work includes the exploration of water-sharing strategies in the 16 coalmines.
The report also presents the site-based evaluation of mine water management. This work has provided a solution to help identify more sustainable mine water management practices. The solution includes a conceptual framework for forming a decision hierarchy, an evaluation method for assessing mine water management practices and a sensitivity analysis that takes account of the preferences of stakeholders or managers. The solution was applied to a case study of the evaluation of sustainable water management practices in 16 mines located in the Bowen Basin in Queensland. The evaluation results illustrate the usefulness of the proposed solution. A sensitivity analysis was performed according to preference weights of stakeholders or managers. Some measures are provided for assessing sensitivity of strategy ranking outcomes if the weight of an indicator changes. Finally, some advice is given to improve mine water management in some mines.
Key lessons learnt from this project include the following:
· Simulation tools alone are not enough to explore satisfactory strategies for managing a mine water system. A combination of multi-objective optimisers seems to be a necessity to seek solutions of dealing with potentially conflicting multiple objectives. Mine water management can be based on water use process-based simulation that reflects the trade-offs among water security for production, cost of water use, raw water use per unit of product and unregulated discharge, as well as risks associated with water quantity and quality in worked stores. Multi-objective optimisation can be used to explore management strategies that meet the requirements from multiple aspects.
· When exploring management measures for discharge, water quality and quantity must be managed in an integrated fashion. Precise, long-term climate predictions seem impossible. Reliable or robust strategy options under a set of possible future climates are promising.
· Compared with observed rainfall data, the POAMA rainfall predictions exhibit relatively large errors, especially during the Queensland floods in 2010-11. Long-term (e.g. three months), precise rainfall prediction is extremely difficult. The unreliable predictions mean that the proposed MPC cannot fully depend on the prediction information. A setpoint is therefore determined to force the system to discharge if the water level is high in the worked water store, so the controller uses any permitted 'opportunity' to discharge excess water to avoid punishment. In fact, if the predictions are accurate enough, a new optimisation could be used to keep more water in the worked water store (and the setpoint does not need to be followed).
· Water management strategies need to be personalised site by site. The coalmine sites in the Bowen Basin vary in their development, geographical characteristics, guiding policies, local environment and water supply conditions. The variability also suggests that comparing these sites based on simple statistics is not feasible. A framework that can offer a method to comprehensively evaluate mine water management is required. The criteria and indicators of the decision hierarchy can be changed according to preferences. The stakeholders or managers can also adjust the local weights of criteria or indicators to evaluate the sustainability of mine water management. Then they can improve their management schemes according to analytical results.
· One of our major findings is that mines are able to avoid or reduce unregulated discharges and maintain water supply for production if reliable and accurate information on the quality and quantity of the mine-affected waters and environmental water is available, so that timely actions can be taken based on recommendations from the decision-support system. The key challenges faced by mine water managers are caused by the lack of timely and reliable information, in addition to their inability to process all the information once it is available. For example, the quality and quantity of the mine-affected water that could be discharged is determined by the water quality and stream flow rate at a designated gauge station. Relevant data is often unavailable due to the remoteness of the station, especially during a flooding period when timely data is urgently needed.
An e-newsletter has also been published for this project, highlighting its significance for the industry.