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Optical approaches to examining the dynamics of dissolved organic carbon in optically complex inland waters

Bibliographic Data

ID15547368
AuthorsGuangjia Jiang (Chinese Academy of Sciences, corresponding author), Ronghua Ma (0000-0002-4485-4636, Chinese Academy of Sciences), Steven Loiselle (0000-0001-7414-0389, University of Siena), Steven A Loiselle, Hongtao Duan (0000-0002-1985-2292, Chinese Academy of Sciences)
Year2012
Volume7
Issue3
Pages034014-034014
Publication date2012-08-16
Open AccessYes
TypeARTICLE
VenueEnvironmental Research Letters (JOURNAL)
Journal identifiersISSN: 1748-9326 • E-ISSN: 1748-9326
PublisherIOP Publishing (PUBLISHER • GB)
DOI10.1088/1748-9326/7/3/034014
OpenAlexW2010435023
LanguageEN
Citations received1
References cited25

Optical approaches were developed to examine the relationship between the optically active and the optically inactive fractions of dissolved organic carbon in inland waters. A multiple linear regression model was developed on the basis of an extensive dataset from Taihu Lake, and validated employing data from another large shallow eutrophic lake (Chaohu Lake) in southern China. The model was used to estimate the concentration of dissolved organic matter (n = 191) using the absorption characteristics of its chromophoric fraction with a high correlation coefficient (R-2 = 0.62) and a low root mean squared error (RMSE = 9.67%). This intra-ecosystem validity allows us to improve our understanding of carbon dynamics using optical remote sensing approaches for these optically complex lakes, where multiple sources and sinks of dissolved organic matter were present

Carbon fibers · Dissolved organic carbon · Optically active · Total organic carbon · Chemistry · Environmental Science · Marine and coastal ecosystems · Materials Science · Water Quality Monitoring and Analysis · Water Quality Monitoring Technologies · Environmental Chemistry · Geology · Oceanography · Organic Chemistry

  • Variability of particulate organic carbon in inland waters observed from Modis Aqua imagery

    Open Access•Hongtao Duan, Lian Feng et al.•Environmental Research Letters•2014

Citations per year0.08
Citation span2014 - 2014 (1)
Highly citedNo

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