TY - JOUR
T1 - Regional measurements and spatial/temporal analysis of CDOM in 10,000+ optically variable Minnesota lakes using Landsat 8 imagery
AU - Olmanson, Leif G.
AU - Page, Benjamin P.
AU - Finlay, Jacques C.
AU - Brezonik, Patrick L.
AU - Bauer, Marvin E.
AU - Griffin, Claire G.
AU - Hozalski, Raymond M.
N1 - Publisher Copyright:
© 2018 Elsevier B.V.
PY - 2020/7/1
Y1 - 2020/7/1
N2 - Information on colored dissolved organic matter (CDOM) is essential for understanding and managing lakes but is often not available, especially in lake-rich regions where concentrations are often highly variable in time and space. We developed remote sensing methods that can use both Landsat and Sentinel satellite imagery to provide census-level CDOM measurements across the state of Minnesota, USA, a lake-rich landscape with highly varied lake, watershed, and climatic conditions. We evaluated the error of satellite derived CDOM resulting from two atmospheric correction methods with in situ data, and found that both provided substantial improvements over previous methods. We applied CDOM models to 2015 and 2016 Landsat 8 OLI imagery to create 2015 and 2016 Minnesota statewide CDOM maps (reported as absorption coefficients at 440 nm, a440) and used those maps to conduct a geospatial analysis at the ecoregion level. Large differences in a440 among ecoregions were related to predominant land cover/use; lakes in ecoregions with large areas of wetland and forest had significantly higher CDOM levels than lakes in agricultural ecoregions. We compared regional lake CDOM levels between two years with strongly contrasting precipitation (close-to-normal precipitation year in 2015 and much wetter conditions with large storm events in 2016). CDOM levels of lakes in agricultural ecoregions tended to decrease between 2015 and 2016, probably because of dilution by rainfall, and 7% of lakes in these areas decreased in a440 by ≥3 m- 1. In two ecoregions with high forest and wetlands cover, a440 increased by >3 m- 1 in 28 and 31% of the lakes, probably due to enhanced transport of CDOM from forested wetlands. With appropriate model tuning and validation, the approach we describe could be extended to other regions, providing a method for frequent and comprehensive measurements of CDOM, a dynamic and important variable in surface waters.
AB - Information on colored dissolved organic matter (CDOM) is essential for understanding and managing lakes but is often not available, especially in lake-rich regions where concentrations are often highly variable in time and space. We developed remote sensing methods that can use both Landsat and Sentinel satellite imagery to provide census-level CDOM measurements across the state of Minnesota, USA, a lake-rich landscape with highly varied lake, watershed, and climatic conditions. We evaluated the error of satellite derived CDOM resulting from two atmospheric correction methods with in situ data, and found that both provided substantial improvements over previous methods. We applied CDOM models to 2015 and 2016 Landsat 8 OLI imagery to create 2015 and 2016 Minnesota statewide CDOM maps (reported as absorption coefficients at 440 nm, a440) and used those maps to conduct a geospatial analysis at the ecoregion level. Large differences in a440 among ecoregions were related to predominant land cover/use; lakes in ecoregions with large areas of wetland and forest had significantly higher CDOM levels than lakes in agricultural ecoregions. We compared regional lake CDOM levels between two years with strongly contrasting precipitation (close-to-normal precipitation year in 2015 and much wetter conditions with large storm events in 2016). CDOM levels of lakes in agricultural ecoregions tended to decrease between 2015 and 2016, probably because of dilution by rainfall, and 7% of lakes in these areas decreased in a440 by ≥3 m- 1. In two ecoregions with high forest and wetlands cover, a440 increased by >3 m- 1 in 28 and 31% of the lakes, probably due to enhanced transport of CDOM from forested wetlands. With appropriate model tuning and validation, the approach we describe could be extended to other regions, providing a method for frequent and comprehensive measurements of CDOM, a dynamic and important variable in surface waters.
KW - Atmospheric correction
KW - Inland waters
KW - Lake management
KW - Satellite remote sensing
KW - Water color
KW - Water quality monitoring
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U2 - 10.1016/j.scitotenv.2020.138141
DO - 10.1016/j.scitotenv.2020.138141
M3 - Article
C2 - 32247976
AN - SCOPUS:85082706529
SN - 0048-9697
VL - 724
JO - Science of the Total Environment
JF - Science of the Total Environment
M1 - 138141
ER -