Date of Award
2018
Document Type
Open Access Master's Thesis
Degree Name
Master of Science in Environmental Engineering (MS)
Administrative Home Department
Department of Civil and Environmental Engineering
Advisor 1
Noel Urban
Committee Member 1
Min Wang
Committee Member 2
Cory McDonald
Abstract
To increase understanding of mercury cycling, a seasonal mass balance model was developed to predict mercury concentrations in lakes and fish. Results indicate that seasonality in mercury cycling is significant and is important for a northern latitude lake. Models, when validated, have the potential to be used as an alternative to measurements; models are relatively inexpensive and are not as time intensive. Previously published mercury models have neglected to perform a thorough validation. Model validation allows for regulators to be able to make more informed, confident decisions when using models in water quality management. It is critical to quantify uncertainty; models are often over-parameterized and constrained by few measurements. As an approach, the Markov Chain Monte Carlo (MCMC) Bayesian method was used for uncertainty analysis. The uncertainty analysis provided a better means for calibration, helpful insight on the distribution of model parameter values, and the uncertainty in model predictions.
Recommended Citation
Hendricks, Ashley, "A model to predict concentrations and uncertainty for mercury species in lakes", Open Access Master's Thesis, Michigan Technological University, 2018.
Included in
Applied Statistics Commons, Environmental Chemistry Commons, Environmental Engineering Commons, Environmental Monitoring Commons, Fresh Water Studies Commons, Natural Resources Management and Policy Commons, Numerical Analysis and Computation Commons, Ordinary Differential Equations and Applied Dynamics Commons, Other Civil and Environmental Engineering Commons