A reactive transport benchmark on heavy metal cycling in lake sediments

Sediments are active recipients of anthropogenic inputs, including heavy metals, but may be difficult to interpret without the use of numerical models that capture sediment-metal interactions and provide an accurate representation of the intricately coupled sedimentological, geochemical, and biological processes. The focus of this study is to present a benchmark problem on heavy metal cycling in lake sediments and to compare reactive transport models (RTMs) in their treatment of the local-scale physical and biogeochemical processes. This benchmark problem has been developed based on a previously published reactive-diffusive model of metal transport in the sediments of Lake Coeur d'Alene, Idaho. Key processes included in this model are microbial reductive dissolution of iron hydroxides (i.e., ferrihydrite), the release of sorbed metals into pore water, reaction of these metals with biogenic sulfide to form sulfide minerals, and sedimentation driving the burial of ferrihydrite and other minerals. This benchmark thus considers a multicomponent biotic reaction network with multiple terminal electron acceptors (TEAs), Fickian diffusive transport, kinetic and equilibrium mineral precipitation and dissolution, aqueous and surface complexation, as well as (optionally) sedimentation. To test the accuracy of the reactive transport problem solution, four RTMs-TOUGHREACT (TR), CrunchFlow (CF), PHREEQC, and PHT3D-have been used. Without sedimentation, all four models are able to predict similar trends of TEAs and dissolved metal concentrations, as well as mineral abundances. TR and CF are further used to compare sedimentation and compaction test cases. Results with different sedimentation rates are captured by both models, but since the codes do not use the same formulation for compaction, the results differ for this test case. Although, both TR and CF adequately capture the trends of aqueous concentrations and mineral abundances, the difference in results highlights the need to consider further the conceptual and numerical models that link transport, biogeochemical reactions, and sedimentation