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Coastal waters require monitoring of chlorophyll-a concentration (Chl-a) in a wide range of Chl-a from a few mg/m3 to hundreds of mg/m3, which is of interest to the fisheries industry, evaluation of climate change effects, ecological modeling and detection of Harmful Algal Blooms (HABs). Monitoring can be carried out from the Visible Infrared Imaging Radiometer Suite (VIIRS) and Ocean and Land Colour Instrument (OLCI) Ocean Color (OC) satellite sensors, which are currently on orbit and are expected to be the main operational OC sensors at least for the next decade. A Neural Network (NN) algorithm, which uses VIIRS M3-M5 reflectance bands and an I1 imaging band, was developed to estimate Chl-a in the Chesapeake Bay, for the whole range of Chl-a from clear waters in the Lower Bay to extreme bloom conditions in the Upper Bay and the Potomac River, where Chl-a can be used for bloom detection. The NN algorithm demonstrated a significant improvement in the Chl-a retrieval capabilities in comparison with other algorithms, which utilize only reflectance bands. OLCI NIR/red 709/665 nm bands red edge 2010 algorithm denoted as RE10 was also explored with several atmospheric corrections from EUMETSAT, NOAA and NASA. Good consistency between the two types of algorithms is shown for the bloom conditions and the whole range of waters in the Chesapeake Bay (with RE10 switch to OC4 for lower Chl-a) and these algorithms are recommended for the combined VIIRS-OLCI product for the estimation of Chl-a and bloom monitoring. The algorithms were expanded to the waters in Long Island Sound, demonstrating good performance.

Urban estuaries are dynamic environments that hold high ecological and economic value. Yet, their optical complexity hinders accurate satellite retrievals of important biogeochemical variables, such as chlorophyll-a (Chl-a) biomass. Approaches based on a limited number of satellite spectral bands often fail to capture seasonal transitions and sharp spatial gradients in estuarine Chl-a concentrations, inhibiting integration of satellite data into water quality monitoring and conservation programs. We propose a novel approach that utilizes the wide range of spectral information captured by the Ocean and Land Color Instrument (OLCI) to retrieve estuarine Chl-a. To validate our approach, we used measurements in Long Island Sound (LIS), a highly urbanized estuary increasingly susceptible to anthropogenic stressors and climate change. Hyperspectral remote sensing reflectance (Rrs) and Chl-a data representing the spatiotemporal diversity of LIS were used to assess the ideal atmospheric correction approach for OLCI and develop a multi-spectral multiple linear regression (MS-MLR) Chl-a algorithm. POLYMER derived Rrs proved to be the preferred atmospheric correction approach. Evaluation of MS-MLR performance in retrieving Chl-a with in situ Rrs showed good agreement with field measurements. Application to OLCI-retrieved Rrs showed significant improvement (20%-30%) in common error metrics relative to other algorithms assessed. The MS-MLR approach successfully captured seasonal cycles and spatial gradients in Chl-a concentration. Application of this method to urban estuaries and coasts enables accurate, high resolution Chl-a observations at the ecosystem scale and across a range of conditions, as needed for conservation and ecosystem management efforts.

South and Southeast Asia (SSEA) is a socially, economically and ecologically diverse region, with a rapidly growing population and accelerating industrial development, agricultural intensification using manufactured fertilizers, terrestrial landscape change, expansion of water engineering, sewage production and land conversions. Nitrogen and phosphorus are major nutrients that play an essential role in the eutrophication of inland and coastal water bodies. Eutrophic areas, when combined with appropriate coastal ocean physical conditions, can develop into hypoxic zones that result in long-term ecosystem disruption. This study addressed changes in terrestrial nitrogen and phosphorus mobilization associated with land-use transitions, fertilizer use and sewage from 2002 to 2016 in the SSEA region, with a focus on the Mekong and Krishna-Godavari watersheds. Terrestrial mobilization results from the internal production or addition of reactive, soluble and/or plant available forms of nitrogen and phosphorus. To estimate terrestrial mobilization associated with land conversion, published data were mined for estimates of land cover change effects on soil carbon, nitrogen and phosphorus pools. Data on exogenous fertilizer and sewage effluents were also compiled from the literature. From the analysis, it showed that fertilizer input was the largest source of nitrogen and phosphorus in both case study watersheds. Sewage and land conversion were not a significant source of terrestrial phosphorus mobilization in either watershed. All land conversions resulted in declines in soil carbon, ranging from 11% to 38%. Nitrogen increased, on average by 15%, in conversions of agricultural to urban land, but decreased in all other conversions. Phosphorus increased by 89% in wetland to agriculture conversions, but decreased between 2% and 24% for other land conversions. Expansion of agriculture at the expense of forest was the dominant land conversion in the Mekong watershed. Urbanization, at the expense of agriculture and forest, was the dominant land conversion in the Krishna/Godavari watershed. These results suggest that management of nutrient pollution (N and P) in SSEA will need to focus on reducing the use and/or improving the efficiency of fertilizer use along with regular consolidated monitoring in both watersheds.

Arctic landscapes are warming and becoming wetter due to changes in precipitation and the timing of snowmelt which consequently alters seasonal runoff and river discharge patterns. These changes in hydrology lead to increased mobilization and transport of terrestrial dissolved organic matter (DOM) to Arctic coastal seas where significant impacts on biogeochemical cycling can occur. Here, we present measurements of dissolved organic carbon (DOC) and chromophoric DOM (CDOM) in the Yukon River-to-Bering Sea system and two river plumes on the Alaska North Slope which flow into the Beaufort Sea. Our sampling characterized optical and biogeochemical properties of DOM during high and low river discharge periods for the Yukon River-Bering Sea system. The average DOC concentration at the multiple Yukon River mouths ranged from a high of 10.36 mg C L-1 during the ascending limb of the 2019 freshet (late May), 6.4 mg C L-1 during the descending limb of the 2019 freshet (late June), and a low of 3.86 mg C L-1 during low river discharge in August 2018. CDOM absorption coefficient at 412 nm (aCDOM(412)) averaged 8.23 m-1, 5.07 m-1, and 1.9 m-1, respectively. Several approaches to model DOC concentration based on its relationship with CDOM properties demonstrated cross-system seasonal and spatial robustness for these Arctic coastal systems despite spanning an order of magnitude decrease in DOC concentration from the lower Yukon River to the Northern Bering Sea as well as the North Slope systems. “Snapshot” fluxes of DOC and CDOM across the Yukon River Delta to Norton Sound were calculated from our measurements and modeled water fluxes forced with upstream USGS river gauge data. Our findings suggest that during high river flow, DOM reaches the delta largely unaltered by inputs or physical and biogeochemical processing and that the transformations of Yukon River DOM largely occur in the plume. However, during low summer discharge, multiple processes including local precipitation events, microbial decomposition, photochemistry, and likely others can alter the DOM properties within the lower Yukon River and Delta prior to flowing into Norton Sound.

Abstract The Arctic is experiencing rapid warming, resulting in fundamental shifts in hydrologic connectivity and carbon cycling. Dissolved organic matter (DOM) is a significant component of the Arctic and global carbon cycle, and significant perturbations to DOM cycling are expected with Arctic warming. The impact of photochemical and microbial degradation, and their interactive effects, on DOM composition and remineralization have been documented in Arctic soils and rivers. However, the role of microbes, sunlight and their interactions on Arctic DOM alteration and remineralization in the coastal ocean has not been considered, particularly during the spring freshet when DOM loads are high, photoexposure can be quite limited and residence time within river networks is low. Here, we collected DOM samples along a salinity gradient in the Yukon River delta, plume and coastal ocean during peak river discharge immediately after spring freshet and explored the role of UV exposure, microbial transformations and interactive effects on DOM quantity and composition. Our results show: (1) photochemical alteration of DOM significantly shifts processing pathways of terrestrial DOM, including increasing relative humification of DOM by microbes by > 10%; (2) microbes produce humic-like material that is not optically distinguishable from terrestrial humics; and (3) size-fractionation of the microbial community indicates a size-dependent role for DOM remineralization and humification of DOM observed through modeled PARAFAC components of fluorescent DOM, either through direct or community effects. Field observations indicate apparent conservative mixing along the salinity gradient; however, changing photochemical and microbial alteration of DOM with increasing salinity indicate changing DOM composition likely due to microbial activity. Finally, our findings show potential for rapid transformation of DOM in the coastal ocean from photochemical and microbial alteration, with microbes responsible for the majority of dissolved organic matter remineralization.

Coastal systems are hotspots of ecological, geochemical and economic activity, yet their dynamics are not accurately represented in global models. In this Review, Ward and colleagues assess the current state of coastal science and recommend approaches for including the coastal interface in predictive models.

The Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission will include a hyperspectral imaging radiometer to advance ecosystem monitoring beyond heritage retrievals of the concentration of surface chlorophyll and other traditional ocean color variables, offering potential for novel science and applications. PACE is the first NASA ocean color mission to occur under the agency’s new and evolving effort to directly engage practical end users prior to satellite launch to increase adoption of this freely available data toward societal challenges. Here we describe early efforts to engage a community of practice around marine food-related resource management, business decisions, and policy analysis. Obviously one satellite cannot meet diverse end user needs at all scales and locations, but understanding downstream needs helps in the assessment of information gaps and planning how to optimize the unique strengths of PACE data in combination with the strengths of other satellite retrievals, in situ measurements, and models. Higher spectral resolution data from PACE can be fused with information from satellites with higher spatial or temporal resolution, plus other information, to enable identification and tracking of new marine biological indicators to guide sustainable management. Accounting for the needs of applied researchers as well as non-traditional users of satellite data early in the PACE mission process will ultimately serve to broaden the base of informed users and facilitate faster adoption of the most advanced science and technology toward the challenge of mitigating food insecurity.

Water quality measures for inland and coastal waters are available as discrete samples from professional and volunteer water quality monitoring programs and higher-frequency, near-continuous data from automated in situ sensors. Water quality parameters also are estimated from model outputs and remote sensing. The integration of these data, via data assimilation, can result in a more holistic characterization of these highly dynamic ecosystems, and consequently improve water resource management. It is becoming common to see combinations of these data applied to answer relevant scientific questions. Yet, methods for scaling water quality data across regions and beyond, to provide actionable knowledge for stakeholders, have emerged only recently, particularly with the availability of satellite data now providing global coverage at high spatial resolution. In this paper, data sources and existing data integration frameworks are reviewed to give an overview of the present status and identify the gaps in existing frameworks. We propose an integration framework to provide information to user communities through the the Group on Earth Observations (GEO) AquaWatch Initiative. This aims to develop and build the global capacity and utility of water quality data, products, and information to support equitable and inclusive access for water resource management, policy and decision making.

Coastal environments are highly dynamic, and are characterized by short-term, local-scale variability in atmospheric and oceanic processes. Yet, high-frequency measurements of atmospheric composition, and particularly nitrogen dioxide (NO2) and ozone (O3) dynamics, are scarce over the ocean, introducing uncertainties in satellite retrievals of coastal ocean biogeochemistry and ecology. Combining measurements from different platforms, the Korea-US Ocean Color and Air Quality field campaign provided a unique opportunity to capture, for the first time, the strong spatial dynamics and diurnal variability in total column (TC) NO2 and O3 over the coastal waters of South Korea. Measurements were conducted using a shipboard Pandora Spectrometer Instrument specifically designed to collect accurate, high-frequency observations from a research vessel, and were combined with ground-based observations at coastal land sites, synoptic satellite imagery, and air-mass trajectory simulations to assess source contributions to atmospheric pollution over the coastal ocean. TCO3 showed only small (