Predicting dissolved organic carbon concentration in a dynamic salt marsh creek via machine learning-Reference-Cited by-同舟云学术

Predicting dissolved organic carbon concentration in a dynamic salt marsh creek via machine learning

Published:2020-12-25 Issue:2 Volume:19 Page:81-95
ISSN:1541-5856
Container-title:Limnology and Oceanography: Methods
language:en
Short-container-title:Limnol Oceanogr Methods

Author:

Codden Christina J.¹²^ORCID,Snauffer Andrew M.³⁴,Mueller Amy V.¹³^ORCID,Edwards Catherine R.⁵,Thompson Megan⁵⁶,Tait Zachary⁵⁷,Stubbins Aron¹³⁸^ORCID

Affiliation:

1. Marine and Environmental Science Department Northeastern University Boston Massachusetts USA

2. Present address: Tufts Medical Center Boston Massachusetts USA

3. Civil and Environmental Engineering Department Northeastern University Boston Massachusetts USA

4. Present address: Ocean Networks Canada Victoria British Columbia Canada

5. Department of Marine Sciences Skidaway Institute of Oceanography, University of Georgia Savannah Georgia USA

6. Present address: Memorial Health University Medical Center Savannah Georgia USA

7. Present address: Lange Energy and Drives Engineering Savannah Georgia USA

8. Chemistry and Chemical Biology Department Northeastern University Boston Massachusetts USA

Publisher

Wiley

Subject

Ocean Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/lom3.10406

Reference53 articles.

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2. Linking CDOM spectral absorption to dissolved organic carbon concentrations and loadings in boreal estuaries

3. Seasonal dynamics of dissolved, particulate and microbial components of a tidal saltmarsh-dominated estuary under contrasting levels of freshwater discharge

4. Transport and fate of river discharge on the continental shelf of the southeastern United States;Blanton J. O.;J. Geophys. Res. Oceans,1983

5. Transport and retention of a conservative tracer in an isolated creek–marsh system

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