SYNOPTIC SAMPLING AND PRINCIPAL COMPONENTS ANALYSIS TO IDENTIFY SOURCES OF WATER AND METALS TO AN ACID MINE DRAINAGE STREAM

Contaminated drainage from historical and contemporary hard rock mining activities is recognised as one of the most pressing global water quality issues. Typically, contaminated drainage has multiple sources across a mineralised watershed and is often diffuse in nature. Consequently, effective remediation requires an accurate and detailed assessment of spatial patterns of contamination at the watershed-scale. The synoptic mass balance approach for quantifying contaminant sources and loading has been used extensively within the USA as part of the USGS Abandoned Mine Lands Initiative. Patterns in the chemical characteristics of water inflows can be used to fingerprint the distinct geochemical signals of mined and unmined areas within a watershed. Principal components analysis (PCA) is a powerful statistical method for determining chemical similarity or distinction between spatially dense synoptic samples. In this study, a combined synoptic sampling and principal components analysis approach is adopted in Lion Creek, a mineralised watershed receiving acid mine drainage in Colorado, USA. The objectives of this research are: (i) to quantify the impacts of mining activity on stream water quality; (ii) to quantify the spatial pattern of constituent loading; and (iii) to identify inflow sources most responsible for observed changes in stream chemistry and constituent loading.