Monday, May 2, 2022 10am to 1pm
About this Event
"Development of numerical models to predict cycling of mercury and salt in freshwater"
University of California, Merced
Salinity and mercury concentrations are increasing due to anthropogenic activity and threaten ecosystem services of water bodies. Improved basic knowledge and advanced tools are important to reconcile ecosystem services with management of multiple water quality parameters. It is still difficult to identify main drivers for elevated salinity at a specific site and there are gaps in our basic understanding of mercury cycling. This research focused on development and application of numerical models to improve our understanding of salinity and mercury cycling and provide tools to plan management measures. The aim of the first chapter was to continue development of a module for seasonally managed wetlands as part of a real-time forecasting model. Models that adequately simulate salinity in managed wetlands are still under development. Revising water sources, inflow time series, and model variables greatly improved model performance by better representing the extensive reuse and recirculation within the simulated wetlands. Adequate simulation of conservative water quality parameters such as salinity is a pre-requisite to simulate mercury. The second chapter focused on critically reviewing published kinetic rate constants and applying them to a reaction-transport model. Mercury exists in multiple chemical forms and methylmercury (MeHg) is the most toxic form. Two important variables that determine MeHg concentrations are the rate of MeHg production and degradation. The critical review informs selection of rate constants from literature and provides a tool to assess rate constants. In the third chapter a kinetic-thermodynamic model was applied to field data to assess the effect of environmental conditions on MeHg concentrations. A novel rate formulation was developed to simulate kinetic precipitation of Hg minerals depending on sulfide and organic matter concentrations. The addition of the rate greatly improved simulation of MeHg under a range of environmental conditions resulting in improved model robustness. Overall, numerical models proofed valuable to identify knowledge gaps, improve basic understanding, and provide management support.
Stefanie Helmrich received a B.Sc. in Water Management in 2011 and a M.Sc. in Water Management in 2014 from Technical University of Dresden, Germany. She joined the Environmental Systems Graduate Group at UC Merced in 2016. While attending UC Merced, she was awarded the ES Bobcat Fellowship in 2016 and 2017, the Delta Science Fellowship in 2018, and the Southern California Edison Fellowship in 2019. Her research focuses on conceptualizing and quantifying cycling of inorganic contaminants.
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