Model Calculations of Total Maximum Daily Loads of Mercury for Drainage Lakes1
Authors:
- 8 October 2008
- journal article
- Published by Wiley in Jawra Journal of the American Water Resources Association
- Vol. 44 (5) , 1295-1307
Abstract
Abstract: The Watershed Analysis Risk Management Framework watershed model was enhanced to simulate the transport and fate of mercury and to calculate the fish mercury concentrations (FMC) attained by fish through the food web. The model was applied to Western Lake Superior Basin of Minnesota, which has many peat lands and lakes. Topographic, land use, and soil data were used to set up the model. Meteorology and precipitation chemistry data from nearby monitoring stations were compiled to drive the model. Simulated flow and mercury concentrations for several stream stations were comparable to available data. The model was used to perform mercury total maximum daily load calculations for two contrasting drainage lakes (Wild Rice Lake and Whiteface Reservoir). The model results for wet deposition, dry deposition, evasion, watershed yield, and soil sequestration of mercury were comparable with available actual data. The model predicted lake ice cover from November to April and weak stratification in summer, typical of shallow lakes in cold regions. The simulated sulfate decrease and methylmercury increase near the lake bottom in late summer are caused by sulfate reduction and mercury methylation that occur in the surficial sediment. Simulated FMC were within the range of observed values and the R2 of correlation between the simulated and observed FMC was 0.77. Under the 1989‐2004 base condition, the average simulated FMC of four‐year‐old walleye was 0.31 μg/g for Whiteface Reservoir and 0.15 μg/g for Wild Rice Lake. The FMC criterion in Minnesota is 0.2 μg/g. Wild Rice Lake already meets this criterion without any load reduction. The model showed that a 65% reduction in atmospheric mercury deposition will not, by itself, allow Whiteface Reservoir to meet the criterion in 15 years. Additional best management practices will be needed to reduce 50% of the watershed input.Keywords
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