An official website of the United States government
Abstract Phytoplankton growth in estuaries is regulated by a complex combination of physical factors with freshwater discharge usually playing a dominating role controlling nutrient and light availability. The role of other factors, including upwelling-generating winds, is still unclear because most estuaries are too small for upwelling to emerge. In this study, we used remotely sensed proxies of phytoplankton biomass and concentration of suspended mineral particles to compare the effect of river discharge with the effect of upwelling events associated with persistent along-channel southerly winds in the Chesapeake Bay, a large estuary where upwelling and its effects on biogeochemical dynamics have been previously reported. The surface chlorophyll-a concentrations (Chl-a) were estimated from Visible Infrared Imaging Radiometer Suite (VIIRS) satellite data using the Generalized Stacked-Constraints Model (GSCM) corrected for seasonal effects by comparing remotely sensed and field-measured data. Light limitation of phytoplankton growth was assessed from the concentration of suspended mineral particles estimated from the remotely sensed backscattering at blue (443 nm) wavelength bbp(443). The nine-year time series (2012–2020) of Chl-a and bbp(443) confirmed that a primary factor regulating phytoplankton growth in this nearshore eutrophic area is discharge from the Susquehanna River, and presumably the nutrients it delivers, with a time lag up to four months. Persistent southerly wind events (2–3 days with wind speed >4 m/s) affected the water column stratification in the central part of the bay but did not result in significant increases in remotely sensed Chl-a. Analysis of model simulations of selected upwelling-favorable wind events revealed that strong southerly winds resulted in well-defined lateral (East–West) responses but were insufficient to deliver high-nutrient water to the surface layer to support phytoplankton bloom. We conclude that, in the Chesapeake Bay, which is a large, eutrophic estuary, wind-driven upwelling of deep water plays a limited role in driving phytoplankton growth under most conditions compared with river discharge. Integr Environ Assess Manag 2022;18:921–938. © 2022 SETAC KEY POINTS River discharge is a primary factor regulating phytoplankton growth in the Chesapeake Bay. Upwelling-generating wind events were insufficient to support phytoplankton blooms. Generalized Stacked-Constraints Model (GSCM) is a useful method for processing ocean color satellite imagery in the nearshore areas.
more »
« less
Satellite Estimation of Chlorophyll-a Using Moderate Resolution Imaging Spectroradiometer (MODIS) Sensor in Shallow Coastal Water Bodies: Validation and Improvement
The size and distribution of Phytoplankton populations are indicators of the ecological status of a water body. The chlorophyll-a (Chl-a) concentration is estimated as a proxy for the distribution of phytoplankton biomass. Remote sensing is the only practical method for the synoptic assessment of Chl-a at large spatial and temporal scales. Long-term records of ocean color data from the MODIS Aqua Sensor have proven inadequate to assess Chl-a due to the lack of a robust ocean color algorithm. Chl-a estimation in shallow and coastal water bodies has been a challenge and existing operational algorithms are only suitable for deeper water bodies. In this study, the Ocean Color 3M (OC3M) derived Chl-a concentrations were compared with observed data to assess the performance of the OC3M algorithm. Subsequently, a regression analysis between in situ Chl-a and remote sensing reflectance was performed to obtain a green-red band algorithm for coastal (case 2) water. The OC3M algorithm yielded an accurate estimate of Chl-a for deep ocean (case 1) water (RMSE = 0.007, r2 = 0.518, p < 0.001), but failed to perform well in the coastal (case 2) water of Chesapeake Bay (RMSE = 23.217, r2 = 0.009, p = 0.356). The algorithm developed in this study predicted Chl-a more accurately in Chesapeake Bay (RMSE = 4.924, r2 = 0.444, p < 0.001) than the OC3M algorithm. The study indicates a maximum band ratio formulation using green and red bands could improve the satellite estimation of Chl-a in coastal waters.
more »
« less
- PAR ID:
- 10120897
- Date Published:
- Journal Name:
- Water
- Volume:
- 11
- Issue:
- 8
- ISSN:
- 2073-4441
- Page Range / eLocation ID:
- 1621
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
As harmful algae blooms are increasing in frequency and magnitude, one goal of a new generation of higher spectral resolution satellite missions is to improve the potential of satellite optical data to monitor these events. A satellite-based algorithm proposed over two decades ago was used for the first time to monitor the extent and temporal evolution of a massive bloom of the dinoflagellate Lingulodinium polyedra off Southern California during April and May 2020. The algorithm uses ultraviolet (UV) data that have only recently become available from the single ocean color sensor on the Japanese GCOM-C satellite. Dinoflagellates contain high concentrations of mycosporine-like amino acids and release colored dissolved organic matter, both of which absorb strongly in the UV part of the spectrum. Ratios <1 of remote sensing reflectance of the UV band at 380 nm to that of the blue band at 443 nm were used as an indicator of the dinoflagellate bloom. The satellite data indicated that an observed, long, and narrow nearshore band of elevated chlorophyll-a (Chl-a) concentrations, extending from northern Baja to Santa Monica Bay, was dominated by L. polyedra. In other high Chl-a regions, the ratios were >1, consistent with historical observations showing a sharp transition from dinoflagellate- to diatom-dominated waters in these areas. UV bands are thus potentially useful in the remote sensing of phytoplankton blooms but are currently available only from a single ocean color sensor. As several new satellites such as the NASA Plankton, Aerosol, Cloud, and marine Ecosystem mission will include UV bands, new algorithms using these bands are needed to enable better monitoring of blooms, especially potentially harmful algal blooms, across large spatiotemporal scales.more » « less
-
Abstract. Ocean color remote sensing is a challenging task over coastal watersdue to the complex optical properties of aerosols and hydrosols. Inorder to conduct accurate atmospheric correction, we previously implementeda joint retrieval algorithm, hereafter referred to as the Multi-Angular Polarimetric Ocean coLor (MAPOL) algorithm,to obtain the aerosol and water-leavingsignal simultaneously.The MAPOL algorithm has been validated with syntheticdata generated by a vector radiative transfer model, and good retrievalperformance has been demonstrated in terms of both aerosol and oceanwater optical properties (Gao et al., 2018).In this work we applied the algorithm to airborne polarimetricmeasurements from the Research Scanning Polarimeter (RSP) over bothopen and coastal ocean waters acquired in twofield campaigns: the Ship-Aircraft Bio-Optical Research (SABOR) in2014 and the North Atlantic Aerosols and Marine Ecosystems Study(NAAMES) in 2015 and 2016. Two different yet related bio-opticalmodels are designed for ocean water properties. One model aligns withtraditional open ocean water bio-optical models that parameterize theocean optical properties in terms of the concentration of chlorophyll a. The other is a generalized bio-optical model for coastal watersthat includes seven free parameters to describe the absorption andscattering by phytoplankton, colored dissolved organic matter, andnonalgal particles. The retrieval errors of both aerosol opticaldepth and the water-leaving radiance are evaluated. Through thecomparisons with ocean color data products from both in situmeasurements and the Moderate Resolution Imaging Spectroradiometer(MODIS), and the aerosol product from both the High SpectralResolution Lidar (HSRL) and the Aerosol Robotic Network (AERONET), the MAPOL algorithm demonstrates both flexibility and accuracy in retrievingaerosol and water-leaving radiance properties under various aerosoland ocean water conditions.more » « less
-
Abstract The incidence of vibriosis is rising globally with evidence of climate variability influencing environmental processes that support growth of pathogenicVibrio spp. The waterborne pathogen,Vibrio vulnificuscan invade wounds and has one of the highest case fatality rates in humans. The bacterium cannot be eradicated from the aquatic environment, hence climate driven environmental conditions enhancing growth and dissemination ofV.vulnificusneed to be understood to provide preemptive assessment of its presence and distribution in aquatic systems. To achieve this objective, satellite remote sensing was employed to quantify the association of sea surface temperature (SST) and chlorophyll‐a(chl‐a) in locations with reportedV.vulnificusinfections. Monthly analysis was done in two populated regions of the Gulf of Mexico—Tampa Bay, Florida, and Galveston Bay, Texas. Results indicate warm water, characterized by a 2‐month lag in SST, high concentration of phytoplankton, proxied for zooplankton using 1 month lagged chl‐avalues, was statistically linked to higher odds ofV.vulnificusinfection in the human population. Identification of climate and ecological processes thresholds is concluded to be useful for development of an heuristic prediction system designed to determine risk of infection for coastal populations.more » « less
-
Abstract Water quality monitoring is relevant for protecting the designated, or beneficial uses, of water such as drinking, aquatic life, recreation, irrigation, and food supply that support the economy, human well-being, and aquatic ecosystem health. Managing finite water resources to support these designated uses requires information on water quality so that managers can make sustainable decisions. Chlorophyll- a (chl- a , µg L −1 ) concentration can serve as a proxy for phytoplankton biomass and may be used as an indicator of increased anthropogenic nutrient stress. Satellite remote sensing may present a complement to in situ measures for assessments of water quality through the retrieval of chl- a with in-water algorithms. Validation of chl- a algorithms across US lakes improves algorithm maturity relevant for monitoring applications. This study compares performance of the Case 2 Regional Coast Colour (C2RCC) chl- a retrieval algorithm, a revised version of the Maximum-Peak Height (MPH (P) ) algorithm, and three scenarios merging these two approaches. Satellite data were retrieved from the MEdium Resolution Imaging Spectrometer (MERIS) and the Ocean and Land Colour Instrument (OLCI), while field observations were obtained from 181 lakes matched with U.S. Water Quality Portal chl- a data. The best performance based on mean absolute multiplicative error (MAE mult ) was demonstrated by the merged algorithm referred to as C 15 −M 10 (MAE mult = 1.8, bias mult = 0.97, n = 836). In the C 15 −M 10 algorithm, the MPH (P) chl- a value was retained if it was > 10 µg L −1 ; if the MPH (P) value was ≤ 10 µg L −1 , the C2RCC value was selected, as long as that value was < 15 µg L −1 . Time-series and lake-wide gradients compared against independent assessments from Lake Champlain and long-term ecological research stations in Wisconsin were used as complementary examples supporting water quality reporting requirements. Trophic state assessments for Wisconsin lakes provided examples in support of inland water quality monitoring applications. This study presents and assesses merged adaptations of chl- a algorithms previously reported independently. Additionally, it contributes to the transition of chl- a algorithm maturity by quantifying error statistics for a number of locations and times.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/w11081621
