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Linking Riparian Flow-Concentration Integration Modeling and HSPF to Predict Background Methylmercury Concentrations in Northeastern Minnesota Streams.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Linking Riparian Flow-Concentration Integration Modeling and HSPF to Predict Background Methylmercury Concentrations in Northeastern Minnesota Streams./
作者:	Rutelonis, Joseph Wes.
面頁冊數:	1 online resource (59 pages)
附註:	Source: Masters Abstracts International, Volume: 57-02.
標題:	Hydrologic sciences. -
電子資源:	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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500 $a Source: Masters Abstracts International, Volume: 57-02.
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502 $a Thesis (M.S.)--University of Minnesota, 2017.
504 $a Includes bibliographical references
520 $a 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.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
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