Spatio-temporal dynamics of inherent optical properties in oligotrophic northern Gulf of Mexico estuaries

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Ike Sari Astuti, Deepak R. Mishra, Sachidananda Mishra, Blake Schaeffer

2018 Continental Shelf Research Vol. 166 Article Cited by 8

Abstract

Coastal and estuarine ecosystems provide numerous economic and environmental benefits to society. However, increasing anthropogenic activities and developmental pressure may stress these areas and hamper their ecosystem services. Satellite remote sensing could be used as a tool for monitoring water quality parameters, including inherent optical properties (IOP) in coastal regions. Spatio-temporal information on IOP variability will help in understanding the dynamics of the water quality of estuaries. The objective of this research was to develop a novel hybrid model by combining and parameterizing existing quasi analytical and semi-analytical algorithms to estimate IOPs in four oligotrophic northern Gulf of Mexico Florida estuaries. The hybrid model was applied to above surface remote sensing reflectance data representing the Medium Resolution Imaging Spectrometer (MERIS) and Sentinel-3's Ocean and Land Colour Instrument (OCLI) bands. The hybrid model produced a root means squared error (RMSE) of 0.32 m−1 (13.95% NRMSE) for total absorption (at), 0.21 m−1 (7.61% NRMSE) for detritus-gelbstoff absorption (adg), and 0.09 m−1 (22.77% NRMSE) for phytoplankton pigment absorption (aphi). Results showed that absorption by detritus and gelbstoff (adg) dominates the water in these estuaries. Monthly IOP variability in 2010 revealed that compared to other estuaries, magnitudes of IOPs was the highest in Pensacola Bay and therefore the highest attenuation. Findings also indicated that river discharge and precipitation predominantly govern the IOP variations in all four estuaries, showing an increase in IOP values following the high flow period. The hybrid model improved IOP retrieval in these low chlorophyll-a (Chl-a) estuaries where the existing spectral decomposition models did not perform satisfactorily. © 2018 Elsevier Ltd

Affiliations

Center for Geospatial Research, Dept. of Geography, University of Georgia, 30602, GA, United States; Dept. of Geography, State University of Malang, 65145, Indonesia; National Center for Coastal and Ocean Science, National Oceanic and Atmospheric Administration (NOAA), 20910, MD, United States; Environmental Protection Agency, Research Triangle Park, 27711, NC, United States