PREDICTION AND MANAGEMENT OF PIT LAKE WATER QUALITY: PRELIMINARY FINDINGS OF THE ADTI-MMS PIT LAKE WORKBOOK

The water quality of lakes that result from open-pit mining of precious-metal and coal resources can potentially have negative effects on ecosystems and water resources for centuries after mine closure. Over the last two decades, environmental consultants and other researchers have produced a considerable volume of literature aimed at predicting the water quality of pit lakes in advance of open-pit mining. These predictions are used by environmental regulators and mine managers to make decisions regarding mine permit approval, mine closure strategies, and potential post-mining site uses to achieve sustainable development objectives set by the mining industry. A volunteer group of representatives from regional and federal agencies, the mining industry, academia, and consultancy firms, known as the Acid Drainage Technology Initiative, Metal Mining Sector (ADTI-MMS, http://www.unr.edu/mines/adti/), has prepared a technical document intended to provide a thorough description of the current understanding of pit lakes and best-practice management approaches for predicting, influencing, and remediating pit lake water quality. The Pit Lake Workbook will be one of six chapters in the Handbook of Technologies for Management of Metal Mine and Metallurgical Process Drainage which is being considered for publication by the Society for Mining, Metallurgy, and Exploration (SME). The workbook contains manuscripts by 31 researchers from the United States, Australia, Canada, and Germany which are organized into seven sections addressing regulatory requirements, characterization, conceptual models, sampling & monitoring, predictive models (i.e. climatological, hydrological, limnological, and geochemical), remediation, post-mining uses, and current data gaps & best practices. This presentation will address the preliminary findings of the Pit Lake Workbook with an emphasis on current data gaps and contemporary best practices for the prediction of pit lake water quality.