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Biogeosciences An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/bg-2018-504
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-2018-504
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 03 Jan 2019

Research article | 03 Jan 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Biogeosciences (BG).

Floodwater Impact on Galveston Bay Phytoplankton Taxonomy, Pigment Composition and Photo-Physiological State following Hurricane Harvey from Field and Ocean Color (Sentinel-3A OLCI) Observations

Bingqing Liu, Eurico J. D'Sa, and Ishan D. Joshi Bingqing Liu et al.
  • Department of Oceanography and Coastal Sciences, College of the Coast and Environment, Louisiana State University, Baton Rouge, LA 70803, USA

Abstract. Phytoplankton taxonomy, pigment composition and photo-physiological state were studied in Galveston Bay (GB), Texas (USA) following the extreme flooding associated with Hurricane Harvey (August 25–29, 2017) using field and satellite ocean color observations. Percentage of chlorophyll a (Chl a) in different phytoplankton groups were determined from a semi-analytical IOP (inherent optical property) inversion algorithm. The IOP inversion algorithm revealed the dominance of freshwater species (cyanobacteria and green algae) in the bay following the hurricane passage (September 29, 2017) under low salinity conditions associated with the discharge of floodwaters into GB; 2 months after the hurricane (October 29–30, 2017), under more seasonal salinity conditions, the phytoplankton community transitioned to an increase in small sized groups such as haptophyte and prochlorophyte. Sentinel-3A OLCI-derived Chl a obtained using a red/NIR band ratio algorithm for the turbid estuarine waters was highly correlated (R2 > 0.90) to HPLC-derived Chl a concentrations. A Non-Negative Least Square (NNLS) inversion model was then applied to OLCI-derived Chl a maps of GB to obtain spatiotemporal distributions of phytoplankton diagnostic pigments; results appeared consistent with extracted phytoplankton taxonomic composition derived from the IOP inversion algorithm. OLCI-derived diagnostic pigment distributions also exhibited good agreement with HPLC measurements, with mean R2 ranging from 0.39 for violaxanthin to 0.98 for Chl a. Environmental factors (e.g. floodwaters) combined with phytoplankton taxonomy also strongly modulated phytoplankton physiology in the bay as indicated by measurements of photosynthetic parameters with a Fluorescence Induction and Relaxation (FIRe) system. Phytoplankton in well-mixed waters (mid-bay area) exhibited maximum PSII photochemical efficiency (FV/FM) and low effective absorption cross section (δPSII), while the areas adjacent to the shelf (likely nutrient-limited) showed low FV/FM and elevated values. Overall, the approach using field and ocean color data combined with inversion models allowed, for the first time, an assessment of phytoplankton response to a large hurricane-related floodwater perturbation in a turbid estuarine environment based on its taxonomy, pigment composition and physiological state.

Bingqing Liu et al.
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Bingqing Liu et al.
Bingqing Liu et al.
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Short summary
An approach using bio-optical field and ocean color (Sentinel-3A OLCI) data combined with inversion models allowed for the first time, an assessment of phytoplankton response (changes in taxonomy, pigment composition and physiological state) to a large hurricane-related floodwater perturbation in a turbid estuary. The study revealed the transition in phytoplankton community species as well as the spatiotemporal distributions of phytoplankton diagnostic pigments in the floodwater impacted bay.
An approach using bio-optical field and ocean color (Sentinel-3A OLCI) data combined with...
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