Early warning systems are needed because e.g the floods may develop rapidly and can cause remarkable harm for mining processes as well as high costs and technical problems for the companies that are forced to handle the excess water. To enable the predictive use of water balance calculations a predictive control strategy is needed. This predictive control then allows for adjusting the water balance in advance to be able to better handle e.g. the upcoming flood situations. The project needs to test the solution as well as predictive control practices with the selected pilot customers. Mining companies need methods to manage and separate contact and non-contact water fractions to minimize raw water and water storage demand as well as to reduce flow rate and improve quality of mine water effluents discharged to receiving water bodies.
Currently, there are not any such early warning systems or water balance models of mine site water systems available that allow the stakeholders to sustainably manage and control mine site water resources. Circulation of water back to process requires that impurities are removed or their content in water is reduced.
We will integrate the hydro-meteorological forecasts, real-time monitoring data as well as the channel, basin and groundwater models with a mine site specific process control solution to automatically control the amount of water in the mine site. The solution can also be utilized without the control solution to create scenarios that indicate the effect of the forecasted data on the water amount in the mine site. The project will also aim to evaluate optimal techniques to improve the amount and the quality of circulated water, to understand the chemistry of the streams to be circulated (potential modelling case) and to evaluate the potential treatment techniques e.g mechanical techniques, membrane technologies, chemical removal through precipitation, flocculation or flotation, etc.). This WP will utilize the data from previous Green Mining projects (PUMI, Closedure, Arsenal, Miniman).