Colored Dissolved Organic Matter Absorption Research Articles

Spatial and seasonal variability of chlorophyll-a, total suspended matter, and colored dissolved organic matter in the Sundarban mangrove forest using earth observation and field data

The Sundarbans, the world's largest mangrove forest, confronts potential threats from various anthropogenic activities leading to degradation of its aquatic ecosystem. To examine the current status of the aquatic ecosystem, this study aimed to evaluate the spatial and seasonal fluctuation of three principal water quality attributes namely Chlorophyll-a (Chl-a), Total Suspended Matter (TSM), and Colored Dissolved Organic Matter (CDOM) in the complex tidal river systems of the Sundarban mangroves forest using earth observation and in-situ data. A set of two bio-optical algorithms, Ocean color-2 (OC-2) and Ocean color-3 (OC-3), were applied to measure Chl-a concentration, Green/NIR and the Red/NIR band ratio algorithms were used for TSM and the Case-2 Regional Coast Color (C2RCC) processor in the SNAP software was applied to obtain CDOM concentration in study area. A total of 50 in-situ samples were collected during post-monsoon and pre-monsoon to validate the results. Our results clearly demonstrated seasonal variability with higher Chl-a concentrations in post-monsoon than pre-monsoon. This was due to the OC-2 algorithm which produced better results with R2 = 0.73, RMSE = 0.27 for post-monsoon and R2 = 0.55, RMSE = 0.32 for pre-monsoon. Whilst, TSM concentration performed the best with R2 = 0.77; RMSE = 15.82 and R2 = 0.65; RMSE = 33.96 in post-monsoon and pre-monsoon according to the Green/NIR band ratio method. The nearshore and narrow waterway regions had the highest concentrations of TSM and Chl-a, whereas the offshore regions had the lowest. Strong association were observed between the in-situ and satellite derive absorption coefficient, aCDOM (m−1). The R2 for a CDOM during pre-monsoon was 0.65 and throughout the post-monsoon, it was 0.74. Pre-monsoon concentrations were found to be higher due to marine sources and higher wind speeds, possibly due to sediment resuspension. This kind of baseline evaluation will help to detect threats, direct preventive measures for the protection of biodiversity, and deepen our knowledge of these distinct ecosystems. The results will help develop flexible management and preservation plans that can adjust to both natural and man-made changes.

Exploring the interplay between phytoplankton taxonomy, pigments, and optical properties in Ratnagiri coastal waters using a multi-parameter approach

This study presents a comprehensive analysis of phytoplankton diversity and optical properties in the coastal waters of Ratnagiri, India. Ratnagiri, located on the southern coast of Maharashtra, is one of the major centre for fishing activities in India as well as a developing hub for industrial activities. Given its ecological significance and the pressures it faces, the coastal waters of Ratnagiri present a valuable case for studying phytoplankton dynamics and their light absorption properties. We integrated parameters like phytoplankton taxonomy, pigment composition, Coloured Dissolved Organic Matter (CDOM), and phytoplankton absorption characteristics to give a comprehensive view of the phytoplankton community and its optical environment. Phytoplankton samples from Ratnagiri were analyzed with microscopy and high-performance liquid chromatography (HPLC) for taxonomy and pigment profiling, while CDOM and absorption properties were measured using spectrophotometry. Our findings reveal more or less spatial uniformity in phytoplankton composition (Pielou's Evenness Index (J’) ranged between 0.84 and 0.9), with significant diversity (Shannon Diversity Index (H’) ranged from 3.7 to 4.19) within the phytoplankton community. Pigment analysis revealed key marker pigments associated with various phytoplankton classes including bacillariophytes (diatoms), chlorophytes, cyanophytes, haptophytes and cryptophytes, providing insights into community structure. Concurrently, CDOM absorption coefficient (aCDOM (440)) that ranged between 0.08 and 0.3 m−1 indicated varying levels of dissolved organic matter, influencing light absorption and availability within the water column. The phytoplankton absorption data highlighted the specific wavelengths most affected by phytoplankton presence, notably those contributed by diatoms and cyanophytes, providing insights into the optical properties of Ratnagiri's coastal waters. This integrative approach underscores the importance of considering multiple parameters to accurately assess phytoplankton dynamics and their impact on the aquatic environment. The results contribute to a better understanding of the ecological processes governing coastal waters in Ratnagiri and offer valuable information for future monitoring and management efforts.

Remote-sensing monitoring of colored dissolved organic matter in the Arctic Ocean

In the Arctic Ocean, variations in the colored dissolved organic matter (CDOM) have important value and significance. This study proposed and evaluated a novel method by combining the Google Earth Engine with a multilayer back-propagation neural network to retrieve CDOM concentration. This model performed well on the testing data and independent validation data (R2 = 0.76, RMSE = 0.37 m−1, MAPD = 35.43 %), and it was applied to Moderate Resolution Imaging Spectroradiometer (MODIS) images. The CDOM distribution in the Arctic Ocean and its main sea areas was first depicted during the ice-free period from 2002 to 2021, with average CDOM concentration in the range of 0.25 and 0.31 m−1. High CDOM concentration appeared in coastal areas affected by rivers on the Siberian side. The CDOM concentration was highly correlated with salinity (r = −0.92) and discharge (r > 0.68), while melting sea ice diluted seawater and CDOM concentration.

Driving factors of colored dissolved organic matter dynamics across a complex urbanized estuary

The role of estuaries in sourcing and transforming dissolved organic matter - the largest reservoir of organic carbon in the ocean - still presents many unknowns for coastal biogeochemical cycles, and is further complicated by increasing human pressures and a changing climate. Here, we examined the major drivers of colored dissolved organic matter (CDOM) dynamics in Long Island Sound (LIS), a heavily urbanized estuary of National Significance with a storied water quality past. A comprehensive new optical dataset, including measurements of CDOM absorption and fluorescence signatures, was integrated with biological and hydrological measurements to capture the spatiotemporal heterogeneities of LIS, including its urban-to-rural gradient, dynamic river mouths, and blue carbon ecosystems across seasons, following episodic storm events, and over five years. Results reveal longitudinal gradients in both DOM amount and quality. While carbon-rich and humic terrigenous DOM was dominant in the heavily riverine-influenced Central to Eastern LIS, an uncoupling between CDOM absorption (aCDOM) and dissolved organic carbon (DOC) concentration in Western LIS, and a stronger correlation with Chlorophyll-a, indicated increased autochthonous CDOM production. Closer to the New York City urban core, aCDOM was highly correlated to turbidity, consistent with increased wastewater influences. Fluorescence PARAFAC analysis provided strong evidence for seasonal processing of CDOM in LIS, related to increased summertime photochemical degradation of humic-like components and shoulder-season microbial processing. Riverine CDOM export was influenced by discharge amount, residence time, and coastal wetlands acting as additional sources of strongly humic and aromatic organic matter. These measurements allowed us to assess how hydrologic, biological, and anthropogenic processes impact DOM dynamics and, subsequently, biogeochemical variability and trophic status in this complex urbanized estuary, with implications for water quality management and policy. Results discussed here are applicable beyond LIS, as urbanized estuaries globally face similar hydrological and anthropogenic forcings.

Estimation of Dissolved Organic Carbon Using Sentinel-2 in the Eutrophic Lake Ebinur, China

Dissolved organic carbon (DOC) in lakes, as a regulatory agent and light-absorbing compound, is a key component of the global carbon cycling in lacustrine ecosystems. Hence, continuous monitoring of the DOC concentration in arid regions is extremely important. This study utilizes the QAA-CDOM semi-analytical model, which has good accuracy in retrieving the CDOM (colored dissolved organic matter) concentration of Lake Ebinur. We chose to invert the CDOM time-series data from May to October during the 2018–2022 period. A DOC estimation model was then established using the linear regression approach based on the CDOM inversion data and the field DOC measurements. In general, the DOC concentration in Lake Ebinur exhibited an increasing trend from 2018 to 2022, typically lower in May and higher in June. When comparing the average values of DOC in Lake Ebinur for the same months across different years, it can be observed that the month of September exhibits the greatest variability, whereas June shows the least variability. In sum, this study successfully retrieved CDOM concentrations for a saline lake within an arid region and developed a DOC estimation model, thereby providing a reference for investigating carbon cycling in typical lakes of arid areas.

Improving Colored Dissolved Organic Matter (CDOM) Retrievals by Sentinel2-MSI Data through a Total Suspended Matter (TSM)-Driven Classification: The Case of Pertusillo Lake (Southern Italy)

Colored dissolved organic matter (CDOM) is a significant constituent of aquatic systems and biogeochemical cycles. Satellite CDOM retrievals are challenging in inland waters, due to overlapped absorption properties of bio-optical parameters, like Total Suspended Matter (TSM). In this framework, we defined an accurate CDOM model using Sentinel2-MSI (S2-MSI) data in Pertusillo Lake (Southern Italy) adopting a classification scheme based on satellite TSM data. Empirical relationships were established between the CDOM absorption coefficient, aCDOM (440), and reflectance band ratios using ground-based measurements. The Green-to-Red (B3/B4 and B3/B5) and Red-to-Blue (B4/B2 and B5/B2) band ratios showed good relationships (R2 ≥ 0.75), which were further improved according to sub-region division (R2 up to 0.93). The best accuracy of B3/B4 in the match-ups between S2-MSI-derived and in situ band ratios proved the exportability on S2-MSI data of two B3/B4-based aCDOM (440) models, namely the fixed (for the whole PL) and the switching one (according to sub-region division). Although they both exhibited good agreements in aCDOM (440) retrievals (R2 ≥ 0.69), the switching model showed the highest accuracy (RMSE of 0.0155 m−1). Finally, the identification of areas exposed to different TSM patterns can assist with refining the calibration/validation procedures to achieve more accurate aCDOM (440) retrievals.

Tracing Atlantic water transit times in the Arctic Ocean: Coupling reprocessing-derived 236U and colored dissolved organic matter to distinguish different pathways

The Fram Strait is a key region for investigating the exchange of Atlantic water with the Arctic Ocean. Uranium-236 (236U) from the two European nuclear reprocessing plants (NRPs) at La Hague and Sellafield provides a unique fingerprint in Atlantic water which can be used for studying its circulation patterns in the Arctic Ocean. And NRPs-derived 236U (236UNRPs) can be identified by its 233U/236U signature. In this study, we use colored dissolved organic matter (CDOM) absorption to constrain the selection of three Atlantic branch waters that carried different inputs of 236UNRPs in Fram Strait. This can potentially provide better estimates of transit times of Atlantic waters in the Arctic Ocean. High CDOM levels (a350≥0.35 m−1) in Fram Strait reflect the passage of Atlantic water transported to the Arctic by the Norwegian Coastal Current (NCC) and its extension and subsequently along the Siberian continental slope and shelf where the Ob, Yenisei and Lena rivers supply terrestrial organic matter with significantly high CDOM content. Conversely, low CDOM water represents Atlantic water that has remained off the shelf. Based on CDOM absorption, potential temperature (Θ), potential density (σΘ) and 236U concentration, the path of a given body of Atlantic water could be inferred and an appropriate NRPs input function constrained so that transit times could be estimated. Our results indicate that Arctic High CDOM Water (a350≥0.35 m−1) sourced from the NCC and Barents Sea Branch Water (BSBW) in the Barents Sea Opening has an average of 7–27 yrs transit time in the upper ∼200 m of the western shelf of the Fram Strait. Atlantic Low CDOM Water (a350<0.35 m−1, Θ>2°C) sourced from the Fram Strait Branch Water (FSBW) has a short pathway from the eastern Fram Strait. Arctic Low CDOM / High 236U Water (a350<0.35 m−1, Θ≤2°C, σΘ≤27.97 or 236U concentration ≥15 × 106 atom/L) sourced from the BSBW and the FSBW has an average of 22–28 yrs transit time. These findings demonstrate how combining measurements of CDOM with 236UNRPs can improve the robustness in estimation of transit times of different Atlantic water pathways in the Arctic Ocean. There are limited ways to empirically derive estimates and the values provided offer unique data for comparison with estimates from regional circulation models.

Nunataryuk field campaigns: understanding the origin and fate of terrestrial organic matter in the coastal waters of the Mackenzie Delta region

Abstract. Climate warming and related drivers of soil thermal change in the Arctic are expected to modify the distribution and dynamics of carbon contained in perennially frozen grounds. Thawing of permafrost in the Mackenzie River watershed of northwestern Canada, coupled with increases in river discharge and coastal erosion, triggers the release of terrestrial organic matter (OMt) from the largest Arctic drainage basin in North America into the Arctic Ocean. While this process is ongoing and its rate is accelerating, the fate of the newly mobilized organic matter as it transits from the watershed through the delta and into the marine system remains poorly understood. In the framework of the European Horizon 2020 Nunataryuk programme, and as part of the Work Package 4 (WP4) Coastal Waters theme, four field expeditions were conducted in the Mackenzie Delta region and southern Beaufort Sea from April to September 2019. The temporal sampling design allowed the survey of ambient conditions in the coastal waters under full ice cover prior to the spring freshet, during ice breakup in summer, and anterior to the freeze-up period in fall. To capture the fluvial–marine transition zone, and with distinct challenges related to shallow waters and changing seasonal and meteorological conditions, the field sampling was conducted in close partnership with members of the communities of Aklavik, Inuvik and Tuktoyaktuk, using several platforms, namely helicopters, snowmobiles, and small boats. Water column profiles of physical and optical variables were measured in situ, while surface water, groundwater, and sediment samples were collected and preserved for the determination of the composition and sources of OMt, including particulate and dissolved organic carbon (POC and DOC), and colored dissolved organic matter (CDOM), as well as a suite of physical, chemical, and biological variables. Here we present an overview of the standardized datasets, including hydrographic profiles, remote sensing reflectance, temperature and salinity, particle absorption, nutrients, dissolved organic carbon, particulate organic carbon, particulate organic nitrogen, CDOM absorption, fluorescent dissolved organic matter intensity, suspended particulate matter, total particulate carbon, total particulate nitrogen, stable water isotopes, radon in water, bacterial abundance, and a string of phytoplankton pigments including total chlorophyll. Datasets and related metadata can be found in Juhls et al. (2021) (https://doi.org/10.1594/PANGAEA.937587).

Plume dispersion from the Nelson and Hayes rivers into Hudson Bay using satellite remote sensing of CDOM and suspended sediment

Change in the dispersion pattern of Arctic river plumes due to climate change and hydroelectric regulation is challenging to monitor, calling for synoptic and continuous observation using satellite remote sensing. Algorithms for colored dissolved organic matter (CDOM) and total suspended solids (TSS) were applied to moderate resolution imaging spectroradiometer (MODIS) imagery to study Nelson and Hayes river plume dispersion into southwestern Hudson Bay, employing quantile regressions to capture dispersion variability along a freshwater–marine gradient. MODIS-derived CDOM and TSS quantile concentrations (Q0.05–Q0.95) decreased exponentially with distance from the Nelson River mouth. The Q0.95 asymptote marked the offshore extent of the river plume and was used to determine the marine and river water fractions of surface water in southwestern Hudson Bay. At about 125 km from the Nelson River mouth, CDOM was reduced by 75% of its river mouth values. Owing to the significant co-variability between CDOM dilution and river discharge, a 0.25 river water fraction was estimated at this distance, which varied by ±35 km during flood and ebb flows. Anti-cyclonic winds transported the river plume along the 54° azimuth towards central Hudson Bay, while cyclonic winds propagated the plume eastward along the south shore. Particle settling in the coastal waters and resuspension events from mudflats and/or bank erosion caused non-significant relationships between TSS and river discharge. This non-conservative behavior renders TSS a less useful optical tracer of Nelson and Hayes river water in southwestern Hudson Bay. The novel quantile regression approach for defining boundaries of river water dilution in transitional waters may provide helpful information for coastal management on a spatial scale of tens to hundreds of kilometers, ranging from near real-time monitoring to seasonal and multi-year studies.

Parameterization of Light Absorption of Phytoplankton, Non-Algal Particles and Coloured Dissolved Organic Matter in the Atlantic Region of the Southern Ocean (Austral Summer of 2020)

Climate affects the characteristics of the Southern Ocean ecosystem, including bio-optical properties. Remote sensing is a suitable approach for monitoring a rapidly changing ecosystem. Correct remote assessment can be implemented based on a regional satellite algorithm, which requires parameterization of light absorption by all optically active components. The aim of this study is to analyse variability in total chlorophyll a concentration (TChl-a), light absorption by phytoplankton, non-algal particles (NAP), coloured dissolved organic matter (CDOM), and coloured detrital matter (CDM = CDOM+NAP), to parameterize absorption by all components. Bio-optical properties were measured in the austral summer of 2020 according to NASA Protocols (2018). High variability (1–2 orders of magnitude) in TChl-a, absorption of phytoplankton, NAP, CDOM, and CDM was revealed. High variability in both CDOM absorption (uncorrelated with TChl-a) and CDOM share in total non-water absorption, resulting in a shift from phytoplankton to CDOM dominance, caused approximately twofold chlorophyll underestimation by global bio-optical algorithms. The light absorption of phytoplankton (for the visible domain in 1 nm steps), NAP, CDOM, and CDM were parametrized. Relationships between the spectral slope coefficient (SCDOM/SCDM) and CDOM (CDM) absorption were revealed. These results can be useful for the development of regional algorithms for Chl-a, CDM, and CDOM monitoring in the Southern Ocean.

Clarifying water clarity: A call to use metrics best suited to corresponding research and management goals in aquatic ecosystems

Clarifying water clarity: A call to use metrics best suited to corresponding research and management goals in aquatic ecosystems

Application of airborne hyperspectral imagery to retrieve spatiotemporal CDOM distribution using machine learning in a reservoir

• A CDOM absorption coefficient was selected from seven reference wavelengths. • The optimal combinations of R rs wavelengths were determined by random forest. • The optimal random forest model with CDOM absorption coefficient was revealed. • Spatiotemporal distribution and characteristics of CDOM were confirmed. • Results can be used to reveal temporal and spatial variation in CDOM distributions. Colored dissolved organic matter (CDOM) in inland waters is used as a proxy to estimate dissolved organic carbon (DOC) and may be a key indicator of water quality and nutrient enrichment. CDOM is optically active fraction of DOC so that remote sensing techniques can remotely monitor CDOM with wide spatial coverage. However, to effectively retrieve CDOM using optical algorithms, it may be critical to select the absorption coefficient at an appropriate wavelength as an output variable and to optimize input reflectance wavelengths. In this study, we constructed a CDOM retrieval model using airborne hyperspectral reflectance data and a machine learning model such as random forest. We evaluated the best combination of input wavelength bands and the CDOM absorption coefficient at various wavelengths. Seven sampling events for airborne hyperspectral imagery and CDOM absorption coefficient data from 350 nm to 440 nm over two years (2016–2017) were used, and the collected data helped train and validate the random forest model in a freshwater reservoir. An absorption coefficient of 355 nm was selected to best represent the CDOM concentration. The random forest exhibited the best performance for CDOM estimation with an R 2 of 0.85, Nash-Sutcliffe efficiency of 0.77, and percent bias of 3.88, by using a combination of three reflectance bands: 475, 497, and 660 nm. The results show that our model can be utilized to construct a CDOM retrieving algorithm and evaluate its spatiotemporal variation across a reservoir.

Spectral Light Absorption Coefficient of Particles and Colored Dissolved Organic Matter in the Sea of Azov

The research was carried out based on the results of measuring the concentration of chlorophyll-a (TChl-a), spectral coefficient of light absorption by phytoplankton, non-algal particles (NAP) and colored dissolved organic matter (CDOM) in the southern part of the Sea of Azov in different seasons from 2016 to 2020. New data for the Sea of Azov on the variability of the spectral coefficient of light absorption by all optically active components have been obtained. A high (more than an order of magnitude) variability of all studied parameters was shown. The seasonal dynamics of TChl-a shows maxima in winter and summer. A relationship between the phytoplankton absorption and TChl-a has been revealed, which is described by a power function. Significant seasonal differences (two or more times) between the coefficients in the equation for parametrization of light absorption by phytoplankton were revealed. The NAP and CDOM light absorption were parametrized, the ranges of variability of the absorption coefficient and the exponential slope were revealed, and their seasonal dynamics was shown. Annual variability of absorption coefficient of NAP and CDOM was opposite to the annual cycle of TChl-a. The NAP and CDOM absorption coefficients increased after phytoplankton blooms, when TChl-a decreased. The relative contribution of phytoplankton, NAP, and CDOM to the total absorption by particles and dissolved matter at 440 nm varied significantly over the year. The share of phytoplankton was maximum in winter and summer, while in spring and autumn the maximum contribution to absorption was made by CDOM and NAP.

Understanding the changes of optically active substances (OACs) in Hulun Lake in the past 35 years and its indication to the degradation of aquatic ecology

Lake eutrophication and ecological degradation are among the most serious environmental problems in the world and identifying changes in key water quality parameters and associated drivers is critical for lake management. Optically active substances (OACs) are important water quality indicators that affect lake water ecology and evaluate lake eutrophication. Climate change and human activities are important factors driving the changes of OACs in lakes. Understanding how and why OACs varies in long-term trend in response to different influencing factors and its driving mechanism is needed to understand. In this study, based on the Landsat series satellite data, this study investigated the historical changes of OACs in Hulun Lake, quantitatively explained the response relationship of OACs to meteorological, hydrological and human activity elements, and discussed their indicative role in the degradation of water ecology. The results showed that during 1986–2020, OACs had obvious periodic changes; from 1986 to 1999, Chla, CDOM and TSM are relatively stable at lower values; during 2000–2009, the concentration of total suspended matter (TSM) and coloured dissolved organic matter (CDOM) increased, and the concentration of chlorophyll a (Chla) decreased; during 2010–2020 The annual TSM and CDOM concentration decreased, and the Chla concentration increased. The results showed that among the hydrometeorological and anthropogenic variables selected to explain changes in the OAC, gross domestic product (GDP) is the key factor influencing changes in the OACs, explaining 39.3%, 71.8% and 60.6% of the changes in Chla, CDOM and TSM, respectively. Air temperature (AT) can explain 24.0% of the variation in Chla, evapotranspiration (Eva) can explain 19.1% and 5.52% of the variation in CDOM and TSM, and precipitation (P) can explain 13.8% and 7.5% of the variation in Chla and TSM. Water level is an important pathway affecting OACs in Hulun Lake, explaining 50.7% of the variation in CDOM, 48.0% of the variation in TSM and 23.1% of the variation in Chla. Warming and drought in the Hulun Lake basin and human activities ultimately lead to changes in OACs. Finally, a pattern diagram to assess the degree of ecological degradation of lake was proposed. This study has substantial implications to monitor and assess the ecological degradation status of lake and maintain the sustainable development of lakes in cold and arid regions.

Remote sensing of tropical riverine water quality using sentinel-2 MSI and field observations

Monitoring the water quality as well as assessing its ecological status, both in coastal and inland environments, are essential tasks and pose serious environmental challenges. Although both field measurements and observations from permanent measuring stations may be available, the advent of modern remote sensors, such as MSI (MultiSpectral Instrument), on board the Sentinel-2 satellite, has made it possible to obtain inland biogeochemical products at high spatial (10 m) and temporal (5-days) resolutions. However, validating Sentinel-2 derived water quality estimations in tropical riverine and costal water is an ongoing effort.This study presents one of the first attempts to locally adapt and validate the C2RCC atmospheric processor for the inversion of IOPs to water quality parameters of productive tropical riverine waters in South East Asia using a time series of 65 Sentinel-2 MSI images from 2018 to 2021. We developed locally adapted relationships between C2X-Nets-derived inherent optical properties (IOPs) and surface reflectances with field observations of chl-a concentration, colored dissolved organic matter (CDOM), turbidity, transparency, and in situ reflectance spectra. Results have been validated against 3-years long time series of observations collected at six monitoring stations of the Metropolitan Waterworks Authority (MWA) of Thailand covering approximately 130 km-long stretch of the Chao Phraya river.Locally adapted C2X-Net processor showed good performances in predicting the chl-a concentrations, turbidity and Secchi disk depth. However, relatively low performance was noted for C2X-Nets processor in predicting CDOM absorption. During the period 2018–2021, the temporal trends of chl-a concentration and turbidity showed a clear seasonal pattern with peak turbidity values in the wet seasons. Spatial pattern of retrieved water quality products showed a noticeable change in correspondence with the built-up area of Bangkok. Even if elevated chl-a concentrations have been generally observed all year around, highest peaks have been observed in the dry and at beginning of the wet seasons.To the best knowledge of the authors, our findings firstly demonstrated the integration potential of C2RCC and satellite-retrieved water quality estimations into existing national water quality monitoring network in the context of water resources management and decision-making in the tropical Southeast Asian countries.

Spatial variation in diatom abundance and composition in Biwase Bay and Hamanaka Bay (Eastern Hokkaido, Japan), with reference to environmental features.

This study aims to examine the spatial variation of diatom abundance and composition along the nearshore areas of Biwase Bay and Hamanaka Bay, eastern Hokkaido. Terrestrial input via Kiritappu Wetland is expected to affect variation and composition differently depending on the position of the two bays. We conducted an oceanographic survey in June 2014 to measure seawater temperature, salinity, colored dissolved organic matter (CDOM) absorption, nutrient concentrations, and total and size-fractionated chlorophyll (Chl) a concentration at 11 stations of the shallowest (<5 m) parts of the bays. These were grouped into four areas (Areas 1 and 2 in Biwase Bay, and Areas 3 and 4 in Hamanaka Bay) based on the distance of the location from the wetland outlet (nearest in Area 1 to the farthest in Area 4). Diatoms are the major primary producers in the water column. Therefore, we also determined genus level cell abundance and diversity of diatoms to compare similarity among areas. Sea surface temperature was the lowest at Area 4, whereas sea surface salinity was the lowest at Area 1. The contribution of CDOM absorption, an indicator of wetland-influenced river discharge, and silica concentration was highest at Area 1. Total amount of nitrite and nitrate concentrations was the highest at Area 4. Total amount of Chl a concentration was also lowest in Area 1. Our size-fractionated Chl a results revealed that while the size composition of phytoplankton varied among areas, micro-sized (>10 µm) phytoplankton were predominant in Area 4. Finally, diatom composition at the genus level differed greatly among areas. Pennate diatoms were predominant in Areas 1 and 2, but centric diatoms dominated in Areas 3 and 4. Our results suggested great spatial variability in oceanographic conditions among areas, with less influence of wetland and more influence of Coastal Oyashio Water based on distance from the wetland outlet. Diatom composition showed geographical division between Biwase and Hamanaka Bays.

Natural versus anthropogenic controls on the dissolved organic matter chemistry in lakes across China: Insights from optical and molecular level analyses

Dissolved organic matter (DOM) plays an essential role in the global carbon biogeochemical cycle for aquatic ecosystems. The complexity of DOM compounds contributes to the accurate monitoring of its sources and compositions from large-scale patterns to microscopic molecular groups. Here, this study demonstrates the diverse sources and compositions for humic-rich lakes and protein-rich lakes for large-scale regions across China with the linkage to optical components and molecular high-resolution mass spectrometry properties. The total fluorescence intensity of colored DOM (CDOM) for humic-rich lake regions (0.176 Raman unit; R.U.) is significantly (p<0.05) higher than that of the protein-rich lake region (0.084 R.U.). The combined percentages of CDOM absorption variance explained by the anthropogenic and climatic variables across the five lake regions of Northeastern lake region (NLR), Yungui Plateau lake region (YGR), Inner Mongolia-Xinjiang lake region (MXR), Eastern lake region (ELR), and Tibetan-Qinghai Plateau lake region (TQR) were 86.25%, 82.57%, 80.23%, 88.55%, and 87.72% respectively. The averaged relative intensity percentages of CHOS and CHONS formulas from humic-rich lakes (90.831‰, 10.561‰) were significantly higher than that from the protein-like lakes (47.484‰, 5.638‰), respectively. The more complex molecular composition with higher aromaticity occurred in the humic-rich lakes than in the protein-rich lakes. The increasing anthropogenic effects would significantly enhance the sources, transformation, and biodegradation of terrestrial DOM and link to the greenhouse gas emission and the carbon cycle in inland waters.

Empirical Remote Sensing Algorithms to Retrieve SPM and CDOM in Québec Coastal Waters

In most coastal waters, riverine inputs of suspended particulate matter (SPM) and colored dissolved organic matter (CDOM) are the primary optically active constituents. Moderate- and high-resolution satellite optical sensors, such as the Operational Land Imager (OLI) on Landsat-8 and the MultiSpectral Instrument (MSI) on Sentinel-2, offer a synoptic view at high spatial resolution (10–30 m) with weekly revisits allowing the study of coastal dynamics (e.g., river plumes and sediment re-suspension events). Accurate estimations of CDOM and SPM from space require regionally tuned bio-optical algorithms. Using an in situ dataset of CDOM, SPM, and optical properties (both apparent and inherent) from various field campaigns carried out in the coastal waters of the estuary and Gulf of St. Lawrence (EGSL) and eastern James Bay (JB) (N = 347), we developed regional algorithms for OLI and MSI sensors. We found that CDOM absorption at 440 nm [ag (440)] can be retrieved using the red-to-green band ratio for both EGSL and JB. In contrast, the SPM algorithm required regional adjustments due to significant differences in mass-specific inherent optical properties. Finally, the application of regional algorithms to satellite images from OLI and MSI indicated that the atmospheric correction (AC) algorithm C2RCC gives the most accurate remote-sensing reflectance (Rrs) absolute values. However, the ACOLITE algorithm gives the best results for CDOM estimation (almost null bias; median symmetric accuracy of 45% and R2 of 0.78) as it preserved the Rrs spectral shape, while tending to yield positively bias SPM (88%). We conclude that the choice of the algorithm depends on the parameter of interest.

Spatial Distribution of Colored Dissolved Organic Matter in the Western Arctic Ocean

Optical properties of colored dissolved organic matter (CDOM) were investigated along a latitudinal transect (67°–77° N) in upper water (&lt;80 m depth) of the western Arctic Ocean. The absorption coefficient at 280 nm was 0.48–1.25 m−1, with the average for the oligotrophic basin area (1.04 ± 0.08 m−1) being slightly higher than that of the productive shelf area (0.95 ± 0.16 m−1), implying a decoupling effect between CDOM concentration and biological productivity in the western Arctic Ocean. The spectral slope coefficient S270–350 was negatively correlated with salinity, indicating that DOM molecular weight increases with salinity, and may be affected by melt-water input. Four fluorescent components were identified by excitation emission matrices elaborated by parallel factor analysis, including three humic-like (C1, C3, and C4) components and one protein-like (C2) component. Significant increases in concentrations of terrestrially derived humic-like C3 and C4 components with salinity were observed in the basin, mainly controlled by the physical mixing of surface fresh water and subsurface inflowing Pacific Ocean water. Terrestrial material carried by Pacific inflow is thus an important factor affecting the distribution of CDOM fluorescence components. The C3 and C4 fluorescence components may be useful as tracers of Pacific water in the western Arctic Ocean.

A New Algorithm for Simultaneous Retrieval of Aerosols and Marine Parameters

We present an algorithm for simultaneous retrieval of aerosol and marine parameters in coastal waters. The algorithm is based on a radiative transfer forward model for a coupled atmosphere-ocean system, which is used to train a radial basis function neural network (RBF-NN) to obtain a fast and accurate method to compute radiances at the top of the atmosphere (TOA) for given aerosol and marine input parameters. The inverse modelling algorithm employs multidimensional unconstrained non-linear optimization to retrieve three marine parameters (concentrations of chlorophyll and mineral particles, as well as absorption by coloured dissolved organic matter (CDOM)), and two aerosol parameters (aerosol fine-mode fraction and aerosol volume fraction). We validated the retrieval algorithm using synthetic data and found it, for both low and high sun, to predict each of the five parameters accurately, both with and without white noise added to the top of the atmosphere (TOA) radiances. When varying the solar zenith angle (SZA) and retraining the RBF-NN without noise added to the TOA radiance, we found the algorithm to predict the CDOM absorption, chlorophyll concentration, mineral concentration, aerosol fine-mode fraction, and aerosol volume fraction with correlation coefficients greater than 0.72, 0.73, 0.93, 0.67, and 0.87, respectively, for 45∘≤ SZA ≤ 75∘. By adding white Gaussian noise to the TOA radiances with varying values of the signal-to-noise-ratio (SNR), we found the retrieval algorithm to predict CDOM absorption, chlorophyll concentration, mineral concentration, aerosol fine-mode fraction, and aerosol volume fraction well with correlation coefficients greater than 0.77, 0.75, 0.91, 0.81, and 0.86, respectively, for high sun and SNR ≥ 95.