A GEOCHEMICAL MIXING MODEL APPROACH TO ATTRIBUTING SEDIMENT SOURCES FROM FOUR LAKES IN YUNNAN, CHINA AND CONNECTIONS TO HYDROLOGIC BALANCE

Attribution of sediment contaminant sources in aquatic environments remains a challenge due to the dynamics of historical sources, the potential for modern-day remobilization of legacy contamination, and the influence of hydrologic balance on both sources and remobilization. Here we demonstrate the utility of a Markov chain Monte Carlo Bayesian mixing model to reveal how sediment sources have changed over the late Pleistocene and Holocene using sediment cores from four lakes in Yunnan, China, a region with a long history of legacy contamination. We use the molar ratios of Pb/Cd and Cu/Zn to characterize potential sediment endmembers (e.g., soils, crustal material, atmospheric pollution, and coal) and calculate these same ratios for lake sediments down-core to distinguish sediment sources. Long-term variations in the proportion of metal in sediment sourced from soils at Lakes Xingyun and Dian correlate well with June insolation at 20°N, which is a dominant control on Indian Summer Monsoon strength, suggesting a connection between soil weathering and erosion and lake hydrologic balance. Model results that encompass the last 2000 years suggest that there may be some relationship between anthropogenically forced lake level fluctuations and remobilized sediment, but it is not consistent in all settings. This study demonstrates that a geochemical mixing model approach may be feasible for other locations similarly plagued by legacy contamination but will require further refinement of endmember chemistries, demonstrating that approaches aimed at mitigation and remediation must be site-specific.