UNDERSTANDING GEOCHEMICAL REACTIONS IN PERIGLACIAL/SUBGLACIAL ENVIRONMENT BY INVERSE MODELING OF WEST GREENLAND GLACIAL MELTWATER USING PHREEQCI

Biogeochemical processes in subglacial environments are critical to our understanding of terrestrial chemical denudation and global biogeochemical cycles in glacierized environments. This work studies possible periglacial/subglacial weathering reactions using inverse modeling based on the chemical composition of bulk glacial meltwater from two regions of the western Greenland Ice Sheet (Thule, 76°N, 68°W, and Kangerlussuaq, 67°N, 50°W). PHREEQCi, a computer-based speciation mass-balance model, solves a series of chemical reactions simultaneously based on the input parameters of supraglacial meltwater as inflow and bulk meltwater as outflow, as well as being constrained by local mineralogy. This study demonstrates that PHREEQCi is an informative model for generating a range of weathering scenarios that could account for the observed changes in water chemistry between the supraglacial and bulk meltwater over the ablation season. The most likely weathering scenario is organic carbon oxidation and sulfide oxidation by dissolved O₂ coupled with carbonate dissolution and incongruent silicate dissolution; this is consistent with existing abiotic geochemical weathering model results. CO₂-driven dissolution is not important in subglacial environments because atmospheric CO₂ was not required under any weathering scenarios. The feasibility of anoxic weathering, which is hypothesized to be present in subglacial environments, was also tested at the Kangerlussuaq study site. For this scenario, the model demonstrates that methanogenesis can account for the bulk meltwater evolution by reducing organic carbon to methane. This study provides a suite of possible geochemical weathering reactions for interpreting water quality in the periglacial/subglacial environments. Inverse modeling typically does not provide a unique solution and additional constraints such as primary and secondary minerals are helpful to select the most likely weathering scenario.