Eastern Mineral and Environmental Resources Science Center
Performing a mineral environmental assessment over a broad region would require an ability to estimate baseline water quality conditions in mineralized watersheds having little or no available water chemistry data. Knowledge of baseline (premining) water quality is essential in order to assess the potential environmental impacts of future mining. A wide range of geologic, physiographic, hydrologic, climatologic, and ecologic variables potentially control the natural generation of low-pH, metal-rich surface water and groundwater (ARD) in mineralized watersheds. Theoretically, one should be able to identify the relative significance of all variables using physical and chemical first principals in the form of numerical models – this is in fact the focus of Subtask 2.8. However, no numerical model can represent an entire watershed geochemical system with sufficient thoroughness to incorporate all of these variables. An alternate approach is to empirically derive the relative importance of different variables by analyzing existing water chemistry data from many different mineralized watersheds. For example, comparing observed water chemistry in multiple watersheds with similar mineral deposit types, alteration, and bedrock geology, but different physiographic and geomorphic characteristics would help determine the importance of certain physiographic and geomorphic variables. Relationships between watershed variables and water chemistry derived through such systematic comparisons constitute an empirical model. The purpose of this subtask is to develop such empirical models, and in doing so identify a limited number of "super variables" of primary importance in predicting the occurrence of ARD on the watershed scale. Knowledge of these super variables would be critical in successfully performing a mineral environmental assessment because data are typically scarce, particularly over broad regions, demanding that efforts be focused on the acquisition of only the most essential data coverages.
The objective of this subtask is to empirically derive the relative importance of different watershed variables (geologic, physiographic, hydrologic, climatic, and ecological) in controlling water chemistry in mineralized watersheds using existing water chemistry data. This will be done through a series of statistically-based comparisons between watershed variables and observed water chemistry utilizing both a water-chemistry database and a GIS-based approach. An attempt will be made identify "super variables" of primary importance predicting the occurrence of acid-rock drainage.
Database construction will continue and work will be performed using the database to identify important watershed variables controlling water chemistry. The GIS-based approach will be used to identity important watershed variables controlling water chemistry in the Upper Animas River basin. Composition of a draft report on the results of this subtask will begin.
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