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Linking Riparian Flow-Concentration ...
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University of Minnesota.
Linking Riparian Flow-Concentration Integration Modeling and HSPF to Predict Background Methylmercury Concentrations in Northeastern Minnesota Streams.
Record Type:
Language materials, manuscript : Monograph/item
Title/Author:
Linking Riparian Flow-Concentration Integration Modeling and HSPF to Predict Background Methylmercury Concentrations in Northeastern Minnesota Streams./
Author:
Rutelonis, Joseph Wes.
Description:
1 online resource (59 pages)
Notes:
Source: Masters Abstracts International, Volume: 57-02.
Subject:
Hydrologic sciences. -
Online resource:
click for full text (PQDT)
ISBN:
9780355418576
Linking Riparian Flow-Concentration Integration Modeling and HSPF to Predict Background Methylmercury Concentrations in Northeastern Minnesota Streams.
Rutelonis, Joseph Wes.
Linking Riparian Flow-Concentration Integration Modeling and HSPF to Predict Background Methylmercury Concentrations in Northeastern Minnesota Streams.
- 1 online resource (59 pages)
Source: Masters Abstracts International, Volume: 57-02.
Thesis (M.S.)--University of Minnesota, 2017.
Includes bibliographical references
The St. Louis River Watershed in Northeastern Minnesota has been studied extensively to determine the degree to which sulfate loading from the Mesabi Iron Range affects microbial methylation and bioaccumulation of mercury. Recent studies have identified natural processes unrelated to mining, most often in non-mining portions of the region, as the primary source of methylmercury loading to the river. Here, we further evaluate those contributions by interpreting water chemistry (DOC, THg, MeHg and Fe) from seven St. Louis River tributaries and three main channel sampling sites with the Riparian Flow-Concentration Integration Model (RIM) which was developed for interpretation of stream chemistry in boreal streams in Sweden. This model assumes that riparian wetland soil, the last substrate that porewater encounters before becoming river water, controls the chemistry of local groundwater recharging the river. In locations that contain mixed mining and non-mining contributions, a watershed model (Hydrologic Simulation Program -- Fortran: HSPF) was used to estimate the relative groundwater and point source contributions. The RIM approach with soil temperature incorporated as a time-varying parameter is more physically based compared to regression-based methods that have been used previously to interpret stream loads in the region. The comparison of Nash-Sutcliffe model efficiency calculations for both RIM and regression-based models indicate that RIM offers a significant improvement in model predictive power. Since stream flow and temperature are the main drivers, RIM reduces the necessity for widespread, repetitive methylmercury sampling efforts to estimate methylmercury loads.
Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018
Mode of access: World Wide Web
ISBN: 9780355418576Subjects--Topical Terms:
1179176
Hydrologic sciences.
Index Terms--Genre/Form:
554714
Electronic books.
Linking Riparian Flow-Concentration Integration Modeling and HSPF to Predict Background Methylmercury Concentrations in Northeastern Minnesota Streams.
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Linking Riparian Flow-Concentration Integration Modeling and HSPF to Predict Background Methylmercury Concentrations in Northeastern Minnesota Streams.
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The St. Louis River Watershed in Northeastern Minnesota has been studied extensively to determine the degree to which sulfate loading from the Mesabi Iron Range affects microbial methylation and bioaccumulation of mercury. Recent studies have identified natural processes unrelated to mining, most often in non-mining portions of the region, as the primary source of methylmercury loading to the river. Here, we further evaluate those contributions by interpreting water chemistry (DOC, THg, MeHg and Fe) from seven St. Louis River tributaries and three main channel sampling sites with the Riparian Flow-Concentration Integration Model (RIM) which was developed for interpretation of stream chemistry in boreal streams in Sweden. This model assumes that riparian wetland soil, the last substrate that porewater encounters before becoming river water, controls the chemistry of local groundwater recharging the river. In locations that contain mixed mining and non-mining contributions, a watershed model (Hydrologic Simulation Program -- Fortran: HSPF) was used to estimate the relative groundwater and point source contributions. The RIM approach with soil temperature incorporated as a time-varying parameter is more physically based compared to regression-based methods that have been used previously to interpret stream loads in the region. The comparison of Nash-Sutcliffe model efficiency calculations for both RIM and regression-based models indicate that RIM offers a significant improvement in model predictive power. Since stream flow and temperature are the main drivers, RIM reduces the necessity for widespread, repetitive methylmercury sampling efforts to estimate methylmercury loads.
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click for full text (PQDT)
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