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One of the major sources of pollution affecting inland and coastal waters is related to poorly treated or untreated wastewater discharge, particularly in urbanized watersheds. The excess of nutrients, organic matter, and pathogens causes an overall deterioration of water quality and impairs valuable ecosystem services. The detection of wastewater pollution is essential for the sustainable management of inland and coastal waters, and remote sensing has the capability of monitoring wastewater contamination at extended spatial scales and repeated frequencies. This study employed satellite-derived water quality indicators and spatiotemporal analysis to assess the risk of wastewater contamination in Conceição Lagoon, a coastal lagoon in Southern Brazil. Using an analytical model, three water quality indicators were derived from Level 2A Sentinel-2 MSI images: the absorption coefficients of chlorophyll-a and detritus combined with coloured dissolved organic matter, and the backscattering coefficient of suspended solids. The temporal standardized anomalies were calculated for each water quality indicator for the period of 2019–2021, and their anomalies during a known outfall event were used to evaluate spatial variation modes. The spatial mode explaining most of the variability was used to estimate weights for the water quality indicators anomalies in a linear transformation that can indicate the risk of wastewater contamination. Results showed that the wastewater spatial mode for this region was characterized by positive anomalies of backscattering coefficient of particulate matter and absorption coefficient of detritus combined with coloured dissolved organic matter, each with a relative importance of 50%. The application of this spatiotemporal analysis was formulated as the Wastewater Contamination Index. With the aid of photographic records, and additional meteorological and water quality data, the results of the index were verified for wastewater outfall events in the

Suspended Particulate Matter (SPM) plays an important role in controlling water quality, particularly in turbid estuaries. SPM may be impacted by changes in weather and climate, including potential changes in the frequency or intensity of extremes. Yet, the linkages between extreme events in wind and river discharge, and particularly the role these have on local dynamics and spatial patterns of estuarine SPM are, to date, largely unknown. This study investigates the effects that wind and river discharge have on SPM in a turbid estuary. It uses atmospherically corrected remotely sensed reflectances from Landsat-5, -7, and -8. From these data, we establish a 37-year-long time series, from 1984 to 2020, of satellite-derived SPM for the Scheldt Estuary. SPM was estimated using an algorithm applied to the near-infrared band and subsequently compared to in situ SPM data. Additionally, a time series of river discharge and wind speed were used to assess the frequency and severity of extreme events of wind speed and river discharge. In general, statistically significant but weak relationships between SPM and river discharge and between SPM and wind speed were observed. SPM correlated with river discharge and wind in large parts of the estuary, indicating the important role of these drivers in the entire estuarine system. Our study demonstrates how synoptic satellite snapshots can be combined with in situ time series of drivers, such as river discharge and wind, to capture where these drivers relate to (and likely affect) SPM within an estuary. However, our study demonstrates an inability to capture SPM during windstorms both from in situ and satellite data. We discuss the challenges and limitations of assessing the effects of extreme events from satellite and in situ SPM. We recommend the deployment of complementary moored turbidimeters for continuous observations at two strategic locations, as indicated by our spatial study, to improve the ability to capture the effects of

Turbid coastal plumes carry sediments, nutrients, and pollutants. Satellite remote sensing is an effective tool for studying water quality parameters in these turbid plumes while covering a wide range of hydrological and meteorological conditions. However, determining boundaries of turbid coastal plumes poses a challenge. Traditionally, thresholds are the approach of choice for plume detection as they are simple to implement and offer fast processing (especially important for large datasets). However, thresholds are site-specific and need to be re-adjusted for different datasets or when meteorological and hydrodynamical conditions differ. This study compares state-of-the-art threshold approaches with a novel algorithm (PLUMES) for detecting turbid coastal plumes from satellite remote sensing, tested for Patos Lagoon, Brazil. PLUMES is a semi-supervised, and spatially explicit algorithm, and does not assume a unique plume boundary. Results show that the thresholds and PLUMES approach each provide advantages and limitations. Compared with thresholds, the PLUMES algorithm can differentiate both low or high turbidity plumes from the ambient background waters and limits detection of coastal resuspension while automatically retrieving metrics of detected plumes (e.g., area, mean intensity, core location). The study highlights the potential of the PLUMES algorithm for detecting turbid coastal plumes from satellite remote sensing products, which can have significantly positive implications for coastal management. However, PLUMES, despite its demonstrated effectiveness in this study, has not yet been applied to other study sites.

Recently, there have been significant efforts in the integration of in-situ and satellite observations for effective monitoring of coastal areas (e.g., the Copernicus program of the European Space Agency). In this study, a 15-year diurnal variation of Water Constituent Concentrations (WCCs) was retrieved from multi-sensor satellite images and in-situ hyperspectral measurements using Radiative Transfer (RT) modeling in the Dutch Wadden Sea. The existing RT model 2SeaColor was inverted against time series of in-situ hyperspectral measurements of water leaving reflectances (Rrs [sr−1]) for the simultaneous retrieval of WCCs (i.e., Chlorophyll-a (Chla), Suspended Particulate Matter (SPM), Dissolved Organic Matter (CDOM)) on a daily basis between 2003 and 2018 at the NIOZ jetty station (the NJS) located in the Dutch part of the Wadden Sea. At the same time, the existing coupled atmosphere-hydro-optical RT model MOD2SEA was used for the simultaneous retrieval of WCCs from time series of multi-sensor satellite images of the MEdium Resolution Imaging Spectrometer (MERIS) onboard ENVISAT, Multispectral Instrument (MSI) onboard Sentinel-2 and Ocean and Land Colour Instrument (OLCI) onboard Sentinel-3 between 2003 and 2018 over the Dutch Wadden Sea. At the NJS, a direct comparison (Taylor diagram and statistical analysis) showed strong agreement between in-situ and satellite-derived WCC values (Chla: R2 ≥ 0.70, RMSE ≤7.5 [mg m−3]; SPM: R2 ≥ 0.72, RMSE ≤5.5 [g m−3]; CDOM absorption at 440 nm: R2 ≥ 0.67, RMSE ≤1.7 [m−1]). Next, the plausibility of the spatial variation of retrieved WCCs over the study area was evaluated by generating maps of Chla [mg m−3], SPM [g m−3], and CDOM absorption at 440 nm [m−1] from MERIS and OLCI images using the MOD2SEA model. The integration of the spatio-temporal WCC data obtained from in-situ measurements and satellite images in thi

Many coastal waters include large areas of Optically Shallow Waters (OSWs) where the sea-bottom affects above-water observations of remote sensing reflectance (Rrs [sr−1]). If not treated, the effect of bottom reflectance will interfere with the correct retrieval of Water Constituent Concentrations (WCCs) from hyperspectral and multispectral remote sensing observations. To study this phenomenon in more detail, the existing semi-infinite 2SeaColour Radiative Transfer (RT) model was modified into a finite water layer model, bounded by a diffusely reflecting surface at the sea-bottom. From simulations with the new model, called Water - Sea Bottom (WSB) model, it was observed that a ratio of spectral bands in the Near-Infrared, bands 750 nm and 900 nm, is nearly insensitive to the WCCs and increases with the shallowness of the water, and therefore can be used as a robust index to detect OSWs. The newly established Near-Infrared Bottom Effect Index (NIBEI) was applied to a series of satellite observations over the Wadden Sea during high and low tidal phases. Images from the MEdium Resolution Imaging Spectrometer (MERIS) and the Ocean and Land Colour Instrument (OLCI) were processed to retrieve WCCs of the study area. The results indicate that the sea-bottom effect in OSWs affects the accuracy of atmospheric correction and retrievals. On the other hand, applying the NIBEI to flag OSWs improves the reliability and consistency of WCCs maps. The application of proposed NIBEI on satellite images requires only Top Of Atmosphere (TOA) radiances at 750 nm and 900 nm and does not depend on atmospheric correction and ancillary local input data (e.g., bathymetry map, bottom type, empirical coefficients, in-situ measurements). As a result, the proposed NIBEI can readily be applied to detect OSWs on various ocean colour remote sensors in various shallow coastal regions.

This study aimed to investigate the capability of the two-stream radiative transfer model 2SeaColor for the simultaneous retrieval of Chlorophyll-a (Chla), Suspended Particulate Matter (SPM) and Colored Dissolved Organic Matter (CDOM) concentrations from remote sensing measurements under various conditions (i.e., solar zenith angle values (SZAs) and water turbidity levels). For this evaluation, a time series of diurnal in-situ hyperspectral measurements of remote sensing reflectance (Rrs) concurrent with in-situ measured Chla and SPM concentrations between 2008 and 2010 by the NIOZ jetty station (the NJS), located in the Dutch part of the Wadden Sea, was used. Validation of the model retrievals against in-situ measurements showed an acceptable accuracy (Chla: R2= 0.80 and RMSE = 2.98 [mg m−3]; SPM: R2= 0.89 and RMSE = 2.53 [g m−3]) with good agreement between the temporal trends of measured and retrieved concentration values over multiple years. However, the model inversion results yielded less good estimates at SZA > 60° during winter. Furthermore, the effect of the tide on the variation of daily time series of Chla and SPM concentrations was analyzed. At the particular NJS location, the tidal effects on the concentrations of SPM and Chla were found to be small. The capability of the 2SeaColor model to retrieve reliable estimates, and the favorable location of the NJS, which is little influenced by tidal phase variations, contribute to a better understanding of the long-term variability of Chla and SPM concentrations. The results of this study may support the ongoing efforts on Sentinel-3 Ocean and Land Color Instrument (OLCI) calibration and validation at the Dutch Wadden Sea.

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An accurate estimation of the chlorophyll-a (Chla) concentration is crucial for water quality monitoring and is highly desired by various government agencies and environmental groups. However, using satellite observations for Chla estimation remains problematic over coastal waters due to their optical complexity and the critical atmospheric correction. In this study, we coupled an atmospheric and a water optical model for the simultaneous atmospheric correction and retrieval of Chla in the complex waters of the Wadden Sea. This coupled model called MOD2SEA combines simulations from the MODerate resolution atmospheric TRANsmission model (MODTRAN) and the two-stream radiative transfer hydro-optical model 2SeaColor. The accuracy of the coupled MOD2SEA model was validated using a matchup data set of MERIS (MEdium Resolution Imaging SpectRometer) observations and four years of concurrent ground truth measurements (2007–2010) at the NIOZ jetty location in the Dutch part of the Wadden Sea. The results showed that MERIS-derived Chla from MOD2SEA explained the variations of measured Chla with a determination coefficient of R2 = 0.88 and a RMSE of 3.32 mg·m−3, which means a significant improvement in comparison with the standard MERIS Case 2 regional (C2R) processor. The proposed coupled model might be used to generate a time series of reliable Chla maps, which is of profound importance for the assessment of causes and consequences of long-term phenological changes of Chla in the turbid Wadden Sea area.

The Wadden Sea has undergone many changes of which some (e.g., seagrass disappearance, dredging activities) are thought to have affected the concentrations of suspended particulate matter (SPM) in these waters. Results of previous analyses of long-term variation and trends in SPM are, however, possibly biased by the fact that the data underlying these trends were not corrected for methodological changes in time. In this paper we analyze the variability of Secchi disk measurements recorded at one location in the westernmost part of the Wadden Sea during almost four decades (from 1974 to 2010). The Secchi readings were corrected for varying environmental conditions (solar zenith angle, solar irradiance and sea surface conditions) at the time of observation and then converted to a turbidity proxy that measures the attenuation of light due to suspended and dissolved materials in the water column. We tested a series of hypotheses to describe the seasonal and long-term variations of this turbidity proxy. The best statistical model assumed one common seasonal pattern within the study period and a strong variation in turbidity over the years without any apparent long-term increase or decrease in time (n = 1361; r(2) = 0.53). In addition, we found that most of the turbidity variation in this part of the Wadden Sea can be described as a function of SPM, chlorophyll-a, salinity, water temperature, the filter type used for the SPM determinations, and a still unidentified seasonal factor (n = 401; r(2) = 0.88). Comparison with annual averaged ADCP-derived SPM concentrations as determined from a ferry sailing across the Marsdiep tidal inlet (1998-2008) showed that the variability in turbidity at the sampling station was indicative for the variation in light attenuation in the westernmost part of the Wadden Sea. Because the intensity of the underwater light-field affects primary productivity, this new and consistent information on long-term variation in turbidity is of profound im

We present a method to calibrate and validate observational models that interrelate remotely sensed energy fluxes to geophysical variables of land and water surfaces. Coincident sets of remote sensing observation of visible and microwave radiations and geophysical data are assembled and subdivided into calibration (Cal) and validation (Val) data sets. Each Cal/Val pair is used to derive the coefficients (from the Cal set) and the accuracy (from the Val set) of the observation model. Combining the results from all Cal/Val pairs provides probability distributions of the model coefficients and model errors. The method is generic and demonstrated using comprehensive matchup sets from two very different disciplines: soil moisture and water quality. The results demonstrate that the method provides robust model coefficients and quantitative measure of the model uncertainty. This approach can be adopted for the calibration/validation of satellite products of land and water surfaces, and the resulting uncertainty can be used as input to data assimilation schemes.

The development of an operational water quality monitoring method based on remote sensing data requires information on the apparent and inherent optical properties of water (AOP and IOP respectively). This study was performed to determine the apparent and inherent optical properties of coastal waters of the Mahakam Delta, Kalimantan, Indonesia. Inherent optical properties (IOPs) were derived from above-water radiometric measurements and ocean color model inversion. Retrieved IOPs and measured concentrations show good agreement both for total suspended matter (TSM) and chlorophyll a (Chl a) (R2 = 0.72 and 0.80 respectively). The linear relationship between the retrieved IOPs and the measured concentrations was then used to estimate the specific inherent optical properties (SIOPs) using the basic equation of the Lambert–Beer law. The specific backscattering coefficient of TSM (View the MathML source) was found to be 0.0087 m2 g−1, and the specific absorption coefficient of Chl a (View the MathML source) was found to be 0.023 m2 g−1 in the Mahakam Delta. The estimated values of SIOP for TSM and Chl a could be considered spatially constant for the Mahakam Delta, and resulted in reliable estimates of TSM and Chl a concentrations (R2 = 0.84 and 0.85 respectively). The specific backscattering coefficient of TSM found in this study is similar to that of the Barito Estuary (in the southern part of Kalimantan) but lower than that of the Berau Estuary (in the northern part of Kalimantan), whereas the specific backscattering coefficient of Chl a is similar to that found in the Berau Estuary. This study contributes to the development of an operational method based on remote sensing data to map water constituent concentrations in the Mahakam Delta, as well as to enrich the information about the optical properties of Indonesian waters., The development of an operational water quality monitoring method based on remote sensing data requires information on the apparent and inherent optical properties of water (AOP and IOP respectively). This study was performed to determine the apparent and inherent optical properties of coastal waters of the Mahakam Delta, Kalimantan, Indonesia. Inherent optical properties (IOPs) were derived from above-water radiometric measurements and ocean color model inversion. Retrieved IOPs and measured concentrations show good agreement both for total suspended matter (TSM) and chlorophyll a (Chl a) (R2 = 0.72 and 0.80 respectively). The linear relationship between the retrieved IOPs and the measured concentrations was then used to estimate the specific inherent optical properties (SIOPs) using the basic equation of the Lambert–Beer law. The specific backscattering coefficient of TSM (View the MathML source) was found to be 0.0087 m2 g−1, and the specific absorption coefficient of Chl a (View the MathML source) was found to be 0.023 m2 g−1 in the Mahakam Delta. The estimated values of SIOP for TSM and Chl a could be considered spatially constant for the Mahakam Delta, and resulted in reliable estimates of TSM and Chl a concentrations (R2 = 0.84 and 0.85 respectively). The specific backscattering coefficient of TSM found in this study is similar to that of the Barito Estuary (in the southern part of Kalimantan) but lower than that of the Berau Estuary (in the northern part of Kalimantan), whereas the specific backscattering coefficient of Chl a is similar to that found in the Berau Estuary. This study contributes to the development of an operational method based on remote sensing data to map water constituent concentrations in the Mahakam Delta, as well as to enrich the information about the optical properties of Indonesian waters.