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Shallow water environmental information is crucial for the study of marine ecosystems and human activities. There have been numerous satellite remote sensing studies focused on this area. However, accurate information acquisition from remote sensing data remains difficult in this region due to the complexity of the environment and the coupling between benthic reflectance and water column scattering. In this study, we developed a method to retrieve the diffuse attenuation coefficient (Kd), seafloor classification, and bathymetric maps by combining satellite laser altimetry and optical remote sensing imagery in shallow water areas. Firstly, the relationships between remote sensing reflectance (Rrs), water depth, and Kd were established based on radiative transfer theory. This method allows for the retrieval of Kd in shallow water regions, overcoming the limitations present in previous studies. Secondly, we eliminated the water column attenuation and obtained the bottom reflectance index (BRI). The BRI allowed us to determine the bottom reflectance and classify the seafloor using the Gaussian mixture model clustering method. This approach can effectively reduce the error in bathymetric inversion caused by variations in bottom reflectance. Finally, we developed a neural network model for bathymetric inversion. The model inputs consist of Rrs data and spectral shape data containing physical constraint information, aiming to achieve a robust estimation performance. We conducted the study in two experimental areas (the Bimini Islands and the Yongle Atoll) and compared the results with validation data to evaluate the algorithm performance. The results indicated an agreement between the estimated Kd and the validation data (inferred Kd490 values of 0.062 m−1 and 0.058 m−1, compared to a validation data range of 0.055–0.087 m−1 and 0.059–0.070 m−1, respectively). In addition, the seafloor classification accuracy was 86.74 % for the Yongle Atoll area. Finally, the neural network model accurately predicted the bathymetry in the two regions. The accuracy of the bathymetric maps improved significantly with seafloor classification, as indicated by reductions in root mean square error (RMSE) of 0.12 m and 0.15 m, and in mean absolute percentage error (MAPE) by 2.24 % and 5.87 %, respectively. Overall, the proposed method can be used to effectively decouple benthic and water column signals and accurately obtain Kd, bottom reflectance, and bathymetric information for shallow water environments, providing unprecedented information for assessing and monitoring ecosystems and facilitating further research.

The diffuse attenuation coefficient of photosynthetically active radiation (KdPAR) is commonly used to predict light attenuation in aquatic productivity models, but obtaining measurements of PAR to compute KdPAR is difficult. In situ calculations of KdPAR require multiple measurements of PAR through the water column, and these measurements are infeasible for real-time recording. Instead, predictive models using surface-water measurements may be used. Traditional KdPAR models are based on open-ocean habitats and rely on chlorophyll—as a proxy measurement for phytoplankton abundance—as the main predictive parameter. However, elevated suspended sediments and dissolved organic materials may also affect KdPAR values of inland water bodies and estuaries. In this study, we leverage KdPAR calculations derived from in situ light measurements collected along with surface-water-quality parameters across the Sacramento-San Joaquin River Delta in California, USA (the Delta). Sampling occurred between January of 2013 and May of 2014. We also explored regional and seasonal effects, but these did not clearly affect the model. Ultimately, the best-performing model included surface-level turbidity only (R2 = 0.91). The simplicity of the model facilitates use of KdPAR estimates for a variety of purposes throughout the Delta, including euphotic depth calculations, and as inputs to primary-productivity and habitat-suitability models. We demonstrate the model’s usability with two open-sources data sets (one spatially dense, and one temporally dense), and estimate KdPAR, euphotic depth, and primary productivity within the Delta. We provide calculations for each estimation, allowing users to easily adopt these models and apply them to their own data or with open-sourced data, which are abundant.

Marine water quality significantly impacts human livelihoods and production such as fisheries, aquaculture, and tourism. Satellite remote sensing facilitates the predictions of large-area marine water quality without the need for frequent field work and sampling. Prediction of diffuse attenuation coefficient (Kd), which describes the speed at which light decays as it travels through water, obtained from satellite-derived ocean color products can reflect the overall water quality trends. However, current models inadequately explore the complex nonlinear features of Kd, and there are difficulties in achieving accurate long-term predictions and optimal computational efficiency. This study innovatively proposes a model called Remote Sensing-Informer-based Kd Prediction (RSIKP). The proposed RSIKP is characterized by a distinctive Multi-head ProbSparse self-attention mechanism and generative decoding structure. It is designed to comprehensively and accurately capture the long-term variation characteristics of Kd in complex water environments while avoiding error accumulation, which has a significant advantage in multi-dataset experiments due to its high efficiency in long-term prediction. A multi-dataset experiment is conducted at different prediction steps, using 70 datasets corresponding to 70 study areas in Hangzhou Bay and Beibu Gulf. The results show that RSIKP outperforms the five prediction models based on Artificial Neural Networks (ANN, Convolutional Neural Networks (CNN), Gated Recurrent Unit (GRU), Long Short-Term Memory Recurrent Neural Networks (LSTM-RNN), and Long Short-Term Memory Networks (LSTM)). RSIKP captures the complex influences on Kd more effectively to achieve higher prediction accuracy compared to other models. It shows a mean improvement of 20.6%, 31.1%, and 22.9% on Mean Absolute Error (MAE), Mean Square Error (MSE), and Mean Absolute Percentage Error (MAPE). Particularly notable is its outstanding performance in the long time-series predictions of 60 days. This study develops a cost-effective and accurate method of marine water quality prediction, providing an effective prediction tool for marine water quality management. [ABSTRACT FROM AUTHOR]

The tremendous improvement for satellite remote sensing has provided mankind with the feasibility of observing large-scale ocean phenomena from space. Passive remote sensing of ocean color has delivered continuous records of ocean surface information, although there are inherent limitations to this natural light-dependent measurement. The development of spaceborne lidars breaks through the restrictions of passive techniques that are unavailable for obtaining the vertical characteristics of water column, and provides a new approach to the detection of ocean subsurface. In this study, the active spaceborne lidar ICESat-2 and passive optical satellite are fused, to establish an inversion method of lidar equation and semi-analytical model. The diffuse attenuation coefficient (kd) was estimated in various areas of the global oceans, and vertical profiles of chlorophyll-a concentration (Chla) were further obtained. The results showed that Mean Absolute Errors (MAE) of Chla derived by the proposed method with BGC-Argo data were in the range of 0.003–0.14 mg/m3, and the Mean Absolute Percentage Error (MAPE) was between 12.5 % and 26.9 %; Comparison with ocean color products indicated that R2 of Chla was in the range of 0.84–0.98, and MAE of kd was in the range of 0.004–0.021 m−1. The multiple validation approaches have demonstrated the effectiveness of water column profile detection with ICESat-2 lidar and passive satellite, which contributes to the enhanced understanding of ocean subsurface phytoplankton and their spatial or temporal variations.

The three-stream radiation transfer model is used to investigate the fluctuation in the underwater diffuse attenuation coefficient of downwelling irradiance in the polar ocean with a high solar zenith angle and different direct radiation proportions. First, the applicability of the three-stream radiation model in the polar region is validated by using 18 in situ observation data from September to October 2009 in the Beaufort Sea. Statistics show that in the absence of sea ice, the average relative errors between the simulation and observation values for 490 nm downwelling irradiance (Ed(490)) and its diffuse attenuation coefficient (Kd(490)) are 7.04% and 9.88%, respectively. At the stations surrounded by sea ice, the radiation is relatively small due to ice blocking, and the average relative errors simulated by the model reach 15.89% and 15.55%, respectively. Second, simulations with different chlorophyll concentrations and different proportions of direct radiation reveal that a high solar zenith angle has a greater impact on Kd(490) in the surface water. Kd(490) is less affected by the light field (affected by the solar zenith angle and the proportion of direct radiation) at depths greater than 30 m, and meets the linear relationship with the inherent optical parameters (the sum of the absorption coefficient and backscattering coefficient). The surface Kd(490) is still consistent with that at a depth of more than 50 meters under a high solar zenith angle, implying that the surface Kd(490) can also be considered as an inherent optical parameter at a high solar zenith angle (greater than 60 degrees). The relative error of obtaining surface Kd(490) by using the linear relationship at the 50 m layer is found to be less than 8% in the seawater with chlorophyll concentration greater than 0.05 mg m−3. The effect of the solar zenith angle and proportion of direct radiation can be ignored when measuring the diffuse attenuation coefficient in the polar region. Finally, the model can correct the ice induced fluctuation in downward irradiance, allowing for optical research of seawater beneath the ice in the polar ocean. [ABSTRACT FROM AUTHOR]

The new generation photon-counting lidar on Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) can obtain the subsurface optical properties of sea waters. Recent studies highlight the applications of deriving the lidar attenuation coefficient $K_{\mathrm {lidar}}$ and then substituting $K_{\mathrm {lidar}}$ into the bio-optical model to obtain more information of sea waters. As commonly used bio-optical models are built for the diffuse attenuation coefficient $K_{d}$ that are traditionally derived by passive ocean color sensors, whether $K_{\mathrm {lidar}}$ derived from ICESat-2 can be directly used as $K_{d}$ is a fundamental question. Given that $K_{d}$ is an apparent optical property (AOP) in the water column rather than an inherent optical property (IOP), $K_{d}$ is closely related to the zenith angle of the incident light. The zenith angle of the incident light of the sunlight is normally tens of degrees for ocean color sensors, while the maximum laser off-nadir angle is ~1.5° for the ICESat-2 lidar. To demonstrate this issue, we select hundreds of ground tracks of ICESat-2 in both open ocean and coastal sea waters and compare the derived $K_{\mathrm {lidar}}$ with their corresponding Moderate Resolution Imaging Spectroradiometer (MODIS)-derived $K_{d}$. The results indicate that the corrected results of $1.2\times K_{\mathrm {lidar}}$ , instead of the direct results of $K_{\mathrm {lidar}}$ , are more consistent with MODIS $K_{d}$. This study is of great significance to the better fusion of active lidar data and passive optical data in ocean observations. [ABSTRACT FROM AUTHOR]

Diffuse attenuation coefficient of photosynthetically available radiation (PAR), KPAR, is a key product of ocean color remote sensing. Current ocean color algorithms generally detect only the average KPAR within one optical depth, K P A R R S . Due to the marked vertical variations of KPAR, knowledge of K P A R R S is insufficient to accurately evaluate the submarine light field. By using field in situ observations, a two-step approach, based on the development of an ocean color algorithm for K P A R R S and the relationships between K P A R R S and the average KPAR from the surface down to depth Z ( K ¯ P A R Z ), was developed to remotely estimate the vertical variations in K ¯ P A R Z in the North Pacific from the MODerate-resolution Imaging Spectrometer (MODIS) imagery. The root mean square difference of log( K ¯ P A R Z ) in depths within the euphotic zone was around ±0.059 (in unit of m−1 for K ¯ P A R Z ), which corresponded to a deviation of ±15% for the estimated K ¯ P A R Z and the penetration depths of PAR. Our study may provide a promising approach to detect the vertical variations of K ¯ P A R Z and underwater PAR distributions in the North Pacific Ocean. [ABSTRACT FROM AUTHOR]

We analyze the efficacy of using a Do-It-Yourself (DIY) modular instrument to estimate the diffuse attenuation coefficient (Kd) of photosynthetically active radiation (PAR), which can be used for operational oceanography in turbid shallow waters. This parameter evaluates the water transparency, as it summarizes several water components providing an indicator for water quality. Historically, water transparency has been measured with a simple and inexpensive tool: the Secchi disk. Although it contributes a valuable index of visual water clarity, the quality of its measurements is user-dependent, and it does not enable the automatic monitoring of the water quality. For this reason, we need electronic devices to get accurate measures and facilitate long-term evaluations for water quality monitoring. This paper has two main objectives: First, to present the KduPRO, a low-cost and DIY moored instrument. The KduPRO is an evolution of the KdUINO buoy, that provides an estimation of the water transparency in coastal areas and continental waters, with an automatic quality control parameter that makes this sensor suitable for operational observing systems; and second, to provide a replicability analysis associated to the uncertainty of its Kd estimations. This instrument is based on a modular system of light sensors, independent of each other, measuring the irradiance at different depths. This study analyses the performance of the KduPRO with other reference commercial instruments, the performance between different modules of the same system and finally, a case study of measuring the water quality in Loch Leven (a lake in Scotland). The affordable cost, ease of use and measurement repeatability make this instrument a potentially valuable tool for anyone interested in monitoring water quality.

Cyanobacterial bloom accumulation and dissipation frequently occur in Lake Taihu, a typically shallow, eutrophic lake due to wind wave disturbance. However, knowledge of the driving mechanisms of cyanobacterial blooms on underwater light attenuation is still limited. In this study, we collected a high-frequency in situ monitoring of the wind field, underwater light environment, and surface water quality to elucidate how cyanobacterial bloom accumulation and dissipation affect the variations in underwater light attenuation in the littoral zone of Lake Taihu. Results showed that cyanobacterial blooms significantly increased the diffuse attenuation coefficient of ultraviolet-B (Kd(313)), ultraviolet-A (Kd(340)), and photosynthetically active radiation (Kd(PAR)); the scattering of total suspended matter (bbp(λ)); and the absorption of phytoplankton (aph(λ)) and chromophoric dissolved organic matter (CDOM, ag(λ)) (p < 0.01). The Kd(PAR) decreased quickly during the processes of bloom dissipation, but the decrease of Kd(313) and Kd(340) lagged 0.5 day. Our results suggested that cyanobacterial blooms could increase particle matters and elevated the production of autochthonous CDOM, resulting in underwater light attenuation increase. Ultraviolet radiation (UVR) and PAR attenuation both have significant responses to cyanobacterial blooms, but the response processes were distinct due to the different changes of particle and dissolved organic matters. Our study unravels the driving mechanisms of cyanobacterial blooms on underwater light attenuation, improving lake ecosystem management and protection. [ABSTRACT FROM AUTHOR]

The hydrographic and bio-optical properties of the Bering Sea shelf were analyzed based on in-situ measurements obtained during four cruises from 2007 to 2009. According to the temperature and salinity of the seawater, the spring water masses on the Bering Sea shelf were classified as the Alaskan Coast Water, Bering Sea Shelf Water, Anadyr Water, Spring Mixed Layer Water, Remnant Winter Water, and Winter Water, each of which had varying chlorophyll a concentrations. Among them, the highest chlorophyll a concentration occurred in the nutrient-rich Anadyr Water ((7.57±6.16) mg/m3 in spring). The spectrum-dependent diffuse attenuation coefficient (Kd(λ)) of the water column for downwelling irradiance was also calculated, exhibiting a decrease at 412–555 nm and then an increase within the range of 0.17–0.48 m−1 in spring. Furthermore, a strong correlation between the chlorophyll a concentration and the attenuation coefficient was found at visible wavelengths on the Bering Sea shelf. Spatially, the chlorophyll a concentration was higher on the northern shelf ((5.18±3.78) mg/m3) than on the southern shelf ((3.64±2.51) mg/m3), which was consistent with the distribution of the attenuation coefficient. Seasonally, the consumption of nutrients by blooms resulted in minimum chlorophyll a concentration ((0.78±0.51) mg/m3) and attenuation coefficient values in summer. In terms of the vertical structure, both the attenuation coefficient and the chlorophyll a concentration tended to reach maximum values at the same depth, and the depth of the maximum values increased as the surface temperature increased in summer. Moreover, an empirical model was fitted with a power function based on the correlation between the chlorophyll a concentration and the attenuation coefficient at 412–555 nm. In addition, a spectral model was constructed according to the relationship between the attenuation coefficients at 490 nm and at other wavelengths, which provides a method for estimating the bio-optical properties of the Bering Sea shelf. [ABSTRACT FROM AUTHOR]

The diffuse attenuation coefficient of photosynthetically active radiation is an important inherent optical property of the subaquatic light field. This parameter, as a measure of the transparency of the medium, is a good indicator of water quality. Degradation of the optical properties of water due to anthropogenic disturbances is a common phenomenon in freshwater ecosystems. In this study, we used four algorithm-based Landsat 8 OLI and Sentinel-2A/B MSI images to estimate the diffuse attenuation coefficient of photosynthetically active radiation in Lake Villarrica located in south-central Chile. The algorithms' estimated data from the ACOLITE module were validated with in situ measurements from six sampling stations. Seasonal and intralake variations of the light attenuation coefficient were studied. The relationship between the diffuse attenuation coefficient of photosynthetically active radiation, meteorological parameters, and an optical classification was also explored. The best results were obtained with QAA v6 KdPAR Nechad (R2 = 0.931, MBE = 0.023 m−1, RMSE = 0.088 m−1, and MAPE = 35.9%) for spring and QAA v5 Kd490 algorithms (R2 = 0.919, MBE = −0.064 m−1, RMSE = −0.09 m−1, and MAPE = 30.3%) for summer. High KdPAR values are associated with the strong wind and precipitation events suggest they are caused by sediment resuspension. Finally, an optical classification of freshwater ecosystems was proposed for this lake. The promising results of this study suggest that the combination of in situ data and observation satellites can be useful for assessing the bio-optical state of water and water quality dynamics in Chilean aquatic systems. [ABSTRACT FROM AUTHOR]

Estimates of the diffuse attenuation coefficient ( K d ) at two different wavelengths and band-integrated (PAR) were obtained using different published algorithms developed for open ocean waters spanning in type from explicit-empirical, semi-analytical and implicit-empirical and applied to data from spectral radiometers on board six different satellites (MODIS-Aqua, MODIS-Terra, VIIRS–SNPP, VIIRS-JPSS, OLCI-Sentinel 3A and OLCI-Sentinel 3B). The resultant K d s were compared to those inferred from measurements of radiometry from sensors on board autonomous profiling floats (BGC-Argo). Advantages of BGC-Argo measurements compared to ship-based ones include: 1. uniform sampling in time throughout the year, 2. large spatial coverage, and 3. lack of shading by platform. Over 5000 quality-controlled matchups between K d s derived from float and from satellite sensors were found with values ranging from 0.01 to 0.67 m − 1 . Our results show that although all three algorithm types provided similarly ranging values of K d to those of the floats, for most sensors, a given algorithm produced statistically different K d distributions from the two others. Algorithm results diverged the most for low K d (clearest waters). Algorithm biases were traced to the limitations of the datasets the algorithms were developed and trained with, as well as the neglect of sun angle in some algorithms. This study highlights: 1. the importance of using comprehensive field-based datasets (such as BGC-Argo) for algorithm development, 2. the limitation of using radiative-transfer model simulations only for algorithm development, and 3. the potential for improvement if sun angle is taken into account explicitly to improve empirical K d algorithms. Recent augmentation of profiling floats with hyper-spectral radiometers should be encouraged as they will provide additional constraints to develop algorithms for upcoming missions such as NASA's PACE and SBG and ESA's CHIME, all of which will include a hyper-spectral radiometer. [ABSTRACT FROM AUTHOR]

Underwater light availability is a crucial aspect for the ecological functioning of shallow water bodies. Light extinction from terrestrial inputs is a growing threat to these coastal habitats. The blended quasi-analytical algorithm (QAA) was extended for the derivation of colored dissolved organic matter (CDOM) absorption coefficient along with other inherent optical properties (IOPs) from satellite observations for Southeast Asian waters. The contribution of these IOPs to diffuse attenuation of light (Kd) and penetration depth (Zd) was investigated. A vulnerability assessment was performed to identify locations potentially threatened by poor light quality in Southeast Asian waters. Advection of peatland-influenced Sumatran coastal waters rich in organic matter (ag(400nm): 1.0-2.0m-1) and sediments (bbp(400nm): 0.5-1m-1) drive the spatial heterogeneity of Sunda shelf seawater. Photic zone depth, Zd(490nm), is year-round restricted to ≤5m for critically vulnerable Sumatran coastal waters (vulnerability index, VI>0.8). This critically vulnerable state is further extended towards the southern Malacca Strait, influencing the eastern Singapore Strait from June to September. The areas harbouring marine ecosystems in the shelf waters attain a higher threshold (VI=0.6-0.8), constraining the photosynthesis to depths ≤10m. A transformation of central Malacca Strait from not vulnerable (VI

Bathymetric information is critical for environmental monitoring and maintenance of marine safety. The signal received by passive optical remote sensors contains the reflectance information from the seabed, which then forms the informational basis of bathymetry; however, passive optical bathymetry models often require partial prior information. Although spaceborne active lidar has been shown to accurately detect bathymetry within narrow range of tracks, for some small islands or coastal sites, these tracks may not accurately traverse the shallow ocean area. To this end, a satellite derived bathymetry method based on ICESat-2 diffuse attenuation signal without prior information was proposed here. The diffuse attenuation coefficients of the water column were estimated according to the ICESat-2 lidar signal of deep areas near the target shallow water area, and the parameters for the bathymetry algorithm without prior depth information were obtained. Combined with the Sentinel-2 multispectral imagery, accurate large-scale bathymetric information of Zhongye Island and Reefs, Guam, and Ngau were obtained. Bathymetric data from ICESat-2 of multiple tracks were used for verification, and the results showed that the new model performed well, as mean absolute error (MAE) for the three study areas ranged 0.35–1.52 m, and root Mean square error (RMSE) fell between 0.74 and 1.89 m. In the absence of any bathymetric information, the new method can achieve higher or similar accuracy to the more commonly employed Stumpf model.

The state of water quality around Panggang Island, Seribu Islands, in recent decades experienced degradation caused by human activities. The parameters of the diffuse attenuation coefficient (Kd) is an important optical property-related attenuation of light in the water column, and its brightness. Landsat 8 data has potential to map the value of Kd(490) in regional waters in Indonesia. Landsat 8 data could provide solutions to spatial data availability of Kd(490) values in addition to Ocean Color data. The purposes of this research was to developed empirical algorithm of Landsat 8 data to derive values of Kd(490) that can be use as tools for monitoring water quality optically on a regional scale which could not be done by Ocean Color data that has spatial resolution limitation. In-situ measurement of radiometric data was done by using TriOS-RAMSES hyperspectral spectroradiometer with a range of 320 – 890 nm and spectral sampling of 3.3 nm on shallow-waters around Panggang Island. The development of Kd(490) algortihm was done by simulation on ratio of Green and Near-infrared band has great determination values with Kd(490) empirically, which that empirical algorithm can be applied on Landsat 8 data to derive its values. In addition, it is noted that the shallow-waters around Panggang Island, dominant affected by absorption of chlorophyll-a rather than scattering by suspended solids.

Increasing sediment load and deteriorating water clarity are the key challenges for many inland water bodies. The uncertainty associated with the bio-optical complexity of these water bodies limits remote-sensing approaches to monitor such fragile ecosystems. Therefore, we measured optical properties along with water quality parameters in the Chilika lagoon, the second-largest brackish water lagoon in the world. We evaluated exiting quasi-analytical algorithms (QAAs) to retrieve particle back-scattering coefficients (bbp) and diffuse attenuation coefficient (Kd) from surface remote-sensing reflectance (Rrs) data. However, existing QAAs underestimated the observed bbp and Kd values in the Chilika lagoon. Therefore, a modified inversion algorithm (MIA) using the combined features of the sixth version of QAA (QAA v6) and the IOPs inversion model of inland waters (IIMIW) is proposed and validated. Values of bbp at 665 nm and Kd at 490 nm were then used to estimate suspended particulate matter (SPM) and Secchi disk depth (ZSD), respectively. The bias for bbp and Kd was significantly reduced using MIA, which improved the accuracy of SPM and ZSD estimation. We further used MIA to retrieve bbp(665) and Kd(490) values from the Sentinel 2A/2B (S2A/S2B) multispectral instrument (MSI) Rrs data for each pixel over the Chilika lagoon to estimate SPM and ZSD respectively. Better root-mean-squared error (RMSE) value of 10.91 mg L−1 for SPM (ranging from 11.54 to 99.00 mg L−1) and 0.21 m for ZSD (ranging from 0.15 to 1.2 m) was observed when compared with in situ measurements (n = 77). The mean SPM trend from 90 different S2A/S2B MSI acquisition dates from 2017 to 2021 indicated that SPM concentration in the lagoon is closely related to wind velocity. Matching fish landing trends with SPM concentrations was also observed, which may open new opportunities to manage inland water bodies using remote-sensing observations. [ABSTRACT FROM AUTHOR]

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Summary: The aim of this study was to investigate the light transfer through sea ice with a focus on bio-optical substances both in fast ice and in the drift ice zones in the northern Baltic Sea. The measurements included snow and ice structure, spectral irradiance and photosynthetically active radiation below the sea ice. We also measured the concentrations of the three main bio-optical substances which are chlorophyll-a, suspended particulate matter, and coloured dissolved organic matter (CDOM). These bio-optical substances were determined for melted ice samples and for the underlying sea water. The present study provides the first spectral light transfer data set for drift ice in the Baltic Sea. We found high CDOM absorption values typical to the Baltic Sea waters also within sea ice. Our results showed that the transmittance through bare ice was lower for the coastal fast ice than for the drift ice sites. Bio-optical substances, in particular CDOM, modified the spectral distribution of light penetrating through the ice cover. Differences in crystal structure and the amount of gas inclusions in the ice caused variation in the light transfer. Snow cover on ice was found to be the dominant factor influencing the light field under ice, confirming previous studies. In conclusion, snow cover dominated the amount of light under the ice, but did not modify its spectral composition. CDOM in the ice absorbs strongly in the short wavelengths. As pure water absorbs most in the long wavelengths, the light transfer through ice was highest in the green (549–585 nm).

Ultraviolet (UV) radiation plays an important role in the ocean for the biogeochemical cycling through photooxidation of colored dissolved organic matter and metals. It also influences the release of trace gases into the atmosphere. Understanding interaction and climate feedback mechanisms of these processes requires global long-term monitoring of UV radiation in the ocean. Ocean color sensors provide the diffuse attenuation coefficient for downwelling solar irradiance (Kd) as an estimate for the mean light penetration depth in the surface ocean. However, Kd products for the UV spectral range are currently only indirectly inferred from measurements in the visible spectral region. We exploit the UV and visible wavelengths of the TROPOMI sensor onboard Sentinel-5P to directly infer diffuse attenuation coefficients in the UV and blue spectral range. Our approach is based on Differential Optical Absorption Spectroscopy in combination with radiative transfer modeling which has been used in earlier studies to successfully derive Kd in the blue from the vibrational Raman scattering (VRS) signal. VRS was detected in the backscattered radiances of TROPOMI-like sensors at a spectral resolution around 0.5 nm. We adapt this method for the TROPOMI sensor and more spectral regions to obtain two novel Kd products in the UV range (312.5–338.5 nm and 356.5–390 nm), additionally to the blue Kd (390–423 nm). One month of TROPOMI data show high sensitivity to retrieve VRS (fit errors

Sentinel-2 imagery is potentially ideal for providing a rapid assessment of the ecological condition of estuarine water due to its high temporal and spatial resolution and coverage. However, for optically shallow waters, the problem of isolating the effect of seabed reflectance from the influence of water properties makes it difficult to use the observed surface reflectance to monitor water quality. In this study, we adopt a methodology based on Lyzenga’s model to estimate water quality properties such as the dominant wavelength and diffuse attenuation coefficient (Kd) of shallow estuarine waters. Lyzenga models the observed reflectance (R) using four parameters: total water depth (z), sea-bed reflectance (Rb), water reflectance (Rw) and Kd. If Rb is known a priori and multiple observations of R are available from different total water depths, we show that Lyzenga’s model can be used to estimate the values of the remaining two parameters, Kd and Rw. Observations of R from different water depths can either be taken from the same image at different proximal locations in the estuary (“spatial method”) or from the same pixel observed at different tidal stages (“temporal method”), both assuming homogeneous seabed and water reflectance properties. Tests in our case study estuary show that Kd and Rw can be estimated at water depths less than 6.4 m. We also show that the proximity restriction for the reflectance correction with the temporal method limits outcomes to monthly or seasonal resolution, and the correction with the spatial method performs best at a spatial resolution of 60 m. The Kd extracted from the blue band correlates well with the observed Kd for photosynthetically active radiation (PAR) (r2 = 0.66) (although the relationship is likely to be estuary-specific). The methodology provides a foundation for future work assessing rates of primary production in shallow estuaries on large scales.

Underwater ultraviolet radiation (UVR), which plays a significant role in photobiological and photochemical processes, is one of the key factors in marine ecosystems. A new algorithm KpcaUV, based on kernel principal component analysis (KPCA) and multiple linear regression (MLR), was proposed in this study for the retrieval of the UVR diffuse attenuation coefficient Kd(λ) from remote sensing reflectance Rrs(λ) in the global ocean. KPCA can be applied in all areas that principal components analysis (PCA) can be used. More importantly, KPCA can help mapping data into high dimensions and reducing the nonlinearity between inputs and outputs, which will improve the performance and robustness of algorithms when deriving large dynamic ranges parameters. Compared with SeaUVc, which is one of the most successful Kd(λ) retrieval algorithms in UVR, the results showed that KpcaUV (with R2 : 0.970 and RMSE: 14.0%) performed similar to SeaUVc (with R2 : 0.963 and RMSE: 15.6%) when implemented with high-quality data. Nevertheless, KpcaUV was more robust and consistent than SeaUVc when implemented on the satellite images with different levels of quality control. The RMSD of SeaUVc had a significant reduction from 26.8% (QA ≥ 0.6) to 12.7% (QA = 1.0), and the RMSD of KpcaUV varied less than SeaUVc from 14.6% (QA ≥ 0.6) to 10.1% (QA = 1). Hence, considering its good nonlinear-problem-solving ability and robustness when applied to multiple satellites, KpcaUV proposed by this study can be used to obtain Kd(380) for the continuous observation of the large area. [ABSTRACT FROM AUTHOR]

The Coronavirus disease 2019 (COVID-19) pandemic halted human activities globally in multiple sectors including tourism. As a result, nations with heavy tourism, such as Belize, experienced improvements in water quality. Remote sensing technologies can detect impacts of “anthropauses” on coastal water quality. In this study, moderate resolution imaging spectroradiometer (MODIS) satellite data were employed along the Belizean coast to investigate impacts of the COVID-19 shutdown on water quality. The attenuation coefficient at 490 nm, Kd(490), was used as an indicator of water quality, with a lower Kd(490) indicating increased water clarity. Four Coastal Management Zones were characterized by marine traffic as high traffic areas (HTAs) and two as low traffic areas (LTAs). Monthly composites for two periods, 2002–2019 (baseline) and 2020 were examined for Kd(490). For months prior to the COVID-19 shutdown in Belize, there was generally no significant difference in Kd(490) (p > 0.05) between 2020 and baseline period in HTAs and LTAs. Through the shutdown, Kd was lower in 2020 at HTAs, but not for LTAs. At the LTAs, the Kd(490)s observed in 2020 were similar to previous years through October. In November, an unusually active hurricane season in 2020 was associated with decreased water clarity along the entire coast of Belize. This study provides proof of concept that satellite-based monitoring of water quality can complement in situ data and provide evidence of significant water quality improvements due to the COVID-19 shutdown, likely due to reduced marine traffic. However, these improvements were no longer observed following an active hurricane season.

Vertical variability of inherent optical properties (IOPs) affect the water quality retrievals from remote sensing data. Here, we studied the vertical variability of IOPs and simulated apparent optical properties (AOPs) in the Gulf of Finland (Baltic Sea) under three characteristic (non)stratification conditions. In the case of mixed water column, the vertical variability of optically significant constituents (OSC) and IOPs was relatively small. While in case of stratified water column the IOPs of surface layer were three times higher compared to the IOPs below the thermocline and the IOPs were strongly correlated with the physical parameters (temperature, salinity). Measurements of IOPs in stratified water column showed that the ratio of scattering (b(440)) to absorption (a(440)) changed under the thermocline (b(440)/a(440) < 1) i.e., absorption became the dominant component of attenuation under thermocline while the opposite is true for the upper layer. Simulated (from IOPs) spectral irradiance reflectance (R(λ)) and spectral diffuse attenuation coefficient (Kd(λ)) from deeper layers (below thermocline) have significantly smaller magnitude and smoother shape. This becomes relevant during upwelling events—a common process in the coastal Baltic Sea. We quantified the effect of upwelling on surface water properties using simulated AOPs. The simulated AOPs (from IOPs measurements) showed a decrease of the signal up to 68.8% and an increase of optical depth (z90(λ)) from 2.3 to 4.3 m in the green part of the spectrum in case upwelled water mass reaches the surface. In the coastal waters a vertical decrease of Kd(λ) in the PAR region (400–700 nm) by 6.8% (surface to 20 m depth) was observed, while vertical decrease of chlorophyll-a (Chl-a) and total suspended matter (TSM) was 31.7 and 42.1%, respectively. The ratio R(490)/R(560)≥0.77 indicates also the upwelled water mass. The study showed that upwelling is a process that, in addition to biological activity, horizontal transport of OSC, and temperature changes, alters the optical signal of surface water measured by a remote sensor. Knowledge about the vertical variability of IOPs and AOPs relation to upwelling can help the parametrisation of remote sensing algorithms for retrieving water quality estimates in the coastal regions.

The COVID-19 pandemic has affected the entire world and has had a devastating impact on both lives and livelihoods in India. The only way to defeat the rapid spread of COVID-19, is to shut down socio-economic activities and to maintain minimal human interaction with the implementation of a lockdown. Such lockdowns have manifested in a pollution curtailment in almost all spheres of the planet, including in marine pollution. Quantifying this decrease in pollution levels enables the scientific community to assess the contribution of anthropogenic (especially non-essential) activities to global/regional pollution levels. This paper aims to study the impact of the stringent lockdown period (phase 1 and 2) on coastal water quality along the Chennai coast of India, by analyzing suspended matter concentration (SPM), a key element of water quality and diffuse attenuation coefficient, Kd(490), using LANDSAT-8 Operational Land Imager (OLI) data. LANDSAT-8/OLI, L1TP scenes were subjected to radiometric calibration and atmospheric correction to derive surface reflectance values from raw digital numbers using ACOLITE software and a brief insight has been given for the Dark Spectrum Fitting algorithm used in ACOLITE. SPM concentration decreased by 15.48 and 37.50% in the Chennai and Ennore ports, respectively, due to minimal vessel movement and cargo handling. The stringent lockdown led to the operation of fewer thermal plant units, thus less fly ash was emanated, resulting in a 28.05% reduction in SPM levels over Ennore creek. As industrial and commercial activities subsided, the city’s water bodies became clearer than they were just a fortnight prior to the lockdown, with a reduction of 22.26% of SPM in Adyar and 33.97% in Cooum riverine estuaries. Decrease in Kd(490) showed a positive relationship with SPM and thus improved coastal water quality because of the reduction of SPM during this period. The variations in PM2.5 and PM10 concentrations were studied using National Air Quality Monitoring Programme (NAMP) data and reduced levels in particulate matter concentration (PM2.5 and PM10) for the Adyar residential area (24.38 and 28.43%) and for the Nungampakkam commercial area (36.09 and 67.18%) were observed. A significant reduction in PM2.5 concentration (45.63%) was observed in the Ennore-Manali Industrial region.

Accurate estimation of the underwater light field associated with photosynthetically available radiation (PAR) is critical to compute phytoplankton growth rate and net primary production (NPP), and to assess photo‐physiological response of phytoplankton, such as changes in cellular pigmentation. However, methods to estimate PAR used in many previous studies lack in accuracy, likely resulting in significant bias in light‐dependent products such as NPP derived from remote sensing, model simulations, or autonomous platforms. Here we propose and validate a new model for more accurate estimation of the subsurface PAR profile which uses chlorophyll concentration as its input. Validation is performed using 1,744 BGC‐Argo profiles of chlorophyll fluorescence that are calibrated with surface satellite‐derived chlorophyll concentration over their lifetime. The independent verification with the float's PAR sensors confirms the accuracy of satellite chlorophyll estimate worldwide and in the Southern Ocean in particular. Plain Language Summary: In this study, we propose a new model to compute the underwater light field available for phytoplankton growth. The model uses as its inputs the above water radiation (which can be obtained from public databases) and the subsurface distribution of chlorophyll‐a, a pigment shared by all phytoplankton that can be estimated from sensors deployed on robotic platforms and that is used by many ocean ecosystem models. We test the model accuracy using data observed by the light sensors on autonomous profiling floats and find it performs well. The comparison also highlights that estimates of surface chlorophyll concentrations from satellites are unbiased worldwide, in contrast to some published accounts. Key Points: The model takes into account the vertical change of chlorophyll and improves the estimate of the subsurface photosynthetically available radiation fieldThe model is applicable to autonomous platforms, ecosystem and biogeochemical models, and ocean color remote sensingModel comparison with independent in‐situ radiometry confirms that satellite chlorophyll‐a retrievals are unbiased worldwide [ABSTRACT FROM AUTHOR]

Light is essential for primary production and, therefore, its attenuation controls the vertical distribution of plants and phytoplankton over the water column. The diffuse attenuation of irradiance (K) is mainly governed by the attenuation by the water itself and the concentrations of optically active substances (e.g., phytoplankton, inorganic particles and colored dissolved molecules), which makes it an important parameter for eutrophication monitoring. Over the past century, Denmark has had recurrent eutrophication events, with extreme episodic cases where anoxic conditions were observed. Since the 1980’s, eutrophication in Danish waters has been monitored with regards to the diffuse attenuation coefficient of scalar irradiance (Ko) of photosynthetically active radiation (PAR, 400–700 nm), Ko(PAR). However, radiometric measurements in Denmark are difficult in winter due to low solar zenith angle and only few light hours. On top of that, radiometric measurements in the first meters of the water column are highly affected by light refraction influenced by waves, compromising the monitoring of shallow turbid waters as in Denmark. Therefore, we developed a semi-analytical model based on data to from a spectral AC instrument (AC-S, Sea-Bird Scientific) that can estimate the underwater light field and the diffuse attenuation coefficient of downwelling irradiance, Kd(PAR). We tested two distinct approaches based on equations from the literature for estimation of Kd(PAR). The results show that modeled PAR profiles follow the overall shape of in situ radiometric profiles but with smoother profiles, especially in the surface layer (2–5 m). Along with that, the method provided robust Kd(PAR) estimates, that were strongly correlated to the reference Ko(PAR) values from in situ profiles and with low root mean square error (RMSE). Thus, AC-S data can be used to estimate the underwater light field and Ko(PAR). This will make possible to retrieve Ko(PAR) in the absence of daylight and, therefore, allow for environmental monitoring outside the daylight hours, making environmental monitoring more efficient. In addition, the method provides valuable insights into the factors controlling light attenuation.

• A novel study was developed for diffuse attenuation retrieval in Amazon floodplains. • Semi-Analytical K d algorithm from Lee et al. (2013) performed well for turbid waters. • Uncertainties were lower than 22% for Sentinel-2 images in the visible bands. The modeling of underwater light field is essential for the understanding of biogeochemical processes, such as photosynthesis, carbon fluxes, and sediment transports in inland waters. Water-column light attenuation can be quantified by the diffuse attenuation coefficient of the downwelling irradiance (K d) using semi-analytical algorithms (SAA). However, the accuracy of these algorithms is currently limited in highly turbid environments, such as Amazon Floodplains, due to the SAA parametrization steps. In this study, we assessed an SAA approach for K d retrieval using a sizeable (n = 239) and diverse dataset (e.g., K d (490) ranging from almost 0 to up to 30 m−1 with mean values of 5.75 ± 3.94 m−1) in Amazon freshwater ecosystem. The main framework of this study consists of i) re-parametrization of a quasi-analytical algorithm using regional in-situ inherent optical properties (IOPs) and ii) application and validation of SAA for K d retrieval using in-situ and Sentinel-2/MSI (n = 49) derived from Remote Sensing Reflectance (R rs). Overall, the performance of the calibrated SAA was satisfactory for both in-situ and satellite R rs. The validation results with in-situ data achieved a Mean Absolute Percentage Error (MAPE) lower than 22%, Correlation Coefficient (R) > 0.80, Root Mean Square Error (RMSE) lower than 1.7 m−1, and bias between 0.73 and 1.34 for simulated visible bands of Sentinel-2/MSI (490, 560 and 660 nm) (VIS). The results using MSI imagery were similar to those of in-situ, with R > 0.9, MAPE < 20%, RMSE < 1.25 m−1, and bias between 0.98 and 1.10 for VIS bands, which illustrate the viability of this methodology for K d mapping in Amazon Floodplain Lakes. Therefore, this study demonstrates a successful application of satellite remote sensing data for the spatialization of the K d in the optically complex waters of Amazon Basin, which is essential for the ecological management of the Amazon Floodplain Lakes. [ABSTRACT FROM AUTHOR]

Solar radiation is a primary driver affecting several physical, chemical and biological processes in lake ecosystems. The attenuation of sunlight in water is directly controlled by optically active substances. Here, the seasonal and interlake heterogeneities of the diffuse attenuation coefficients (Kd(λ)) of ultraviolet radiation (UVR) and photosynthetically active radiation (PAR) were studied based on field investigations in six Yunnan Plateau lakes (i.e., Chenghai, Dianchi, Erhai, Fuxian, Lugu and Yangzong) of China, October 2014-July 2016. The results revealed that Kd(λ) generally increased with decreasing wavelength and increasing trophic state and that Kd(UVR) presented higher interlake heterogeneity than Kd(PAR). The interlake heterogeneity surpassed the seasonal heterogeneity of Kd(λ), whereas the intralake seasonal heterogeneity, which is related to the lake trophic state and solar spectrum, was obvious. Although the main factors affecting Kd(λ) were chromophoric dissolved organic matter (CDOM) and phytoplankton in general, the interlake heterogeneity was found. In eutrophic, turbid shallow Lake Dianchi, CDOM primarily affected UV-B, whereas total suspended solids (TSS) and/or phytoplankton had important effects on Kd(UV-B), Kd(UV-A) and Kd(PAR). CDOM, TSS and phytoplankton influenced the Kd(UV-B), Kd(UV-A) and Kd(PAR) in the deep mesotrophic Lake Chenghai and Lake Erhai, but the main particulate factors were different between these two lakes. In the deep, oligotrophic clear Lake Fuxian and Lake Lugu, only the significant effect of CDOM on Kd(UVR) in Lake Fuxian was detected. Additionally, the factors affecting Kd(λ) in Lake Yangzong were atypical, possibly due to the artificial addition of massive amounts of ferric chloride. [ABSTRACT FROM AUTHOR]

The composition of phytoplankton and the concentration of pigments in their cells make their absorption and specific absorption coefficients key parameters for bio-optical modeling. This study investigated whether the multispectral vertical diffuse attenuation coefficient of downward irradiance (Kd) gradients could be a good framework for accessing phytoplankton genera. In situ measurements of remote sensing reflectance (Rrs), obtained in an Amazon Floodplain Lake (Lago Grande do Curuai), were used to invert Kd, focusing on Sentinel-3/Ocean and Land Color Instrument (OLCI) sensor bands. After that, an analysis based on the organization of three-way tables (STATICO) was applied to evaluate the relationships between phytoplankton genera and Kd at different OLCI bands. Our results indicate that phytoplankton genera are organized according to their ability to use light intensity and different spectral ranges of visible light (400 to 700 nm). As the light availability changes seasonally, the structure of phytoplankton changes as well. Some genera, such as Microcystis, are adapted to low light intensity at 550–650 nm, therefore high values of Kd in this range would indicate the dominance of Microcysts. Other genera, such as Aulacoseira, are highly adapted to harvesting blue-green light with higher intensity and probably grow in lakes with lower concentrations of colored dissolved organic matter that highly absorbs blue light (405–498). These findings are an important step to describing phytoplankton communities using orbital data in tropical freshwater floodplains. Furthermore, this approach can be used with biodiversity indexes to access phytoplankton diversity in these environments.

Measuring the diffuse attenuation coefficient (Kd) allows for monitoring the water body’s environmental status. This parameter is of particular interest in water quality monitoring programs because it quantifies the presence of light and the euphotic zone’s depth. Citizen scientists can meaningfully contribute by monitoring water quality, complementing traditional methods by reducing monitoring costs and significantly improving data coverage, empowering and supporting decision-making. However, the quality of the acquisition of in situ underwater irradiance measurements has some limitations, especially in areas where stratification phenomena occur in the first meters of depth. This vertical layering introduces a gradient of properties in the vertical direction, affecting the associated Kd. To detect and characterize these variations of Kd in the water column, it needs a system of optical sensors, ideally placed in a range of a few cm, improving the low vertical accuracy. Despite that, the problem of self-shading on the instrumentation becomes critical. Here, we introduce a new concept that aims to improve the vertical accuracy of the irradiance measurements: the underwater annular irradiance (Ea). This new concept consists of measuring the irradiance in an annular-shaped distribution. We first compute the optimal annular angle that avoids self-shading and maximizes the light captured by the sensors. Second, we use different scenarios of water types, solar zenith angle, and cloud coverage to assess the robustness of the corresponding diffuse attenuation coefficient, Ka. Finally, we derive empirical functions for computing Kd from Ka. This new concept opens the possibility to a new generation of optical sensors in an annular-shaped distribution which is expected to (a) increase the vertical resolution of the irradiance measurements and (b) be easy to deploy and maintain and thus to be more suitable for citizen scientists.

Impact of satellite-derived shortwave attenuation depth and its spatial variability on the upper ocean dynamics has been studied using a numerical ocean model over the Bay of Bengal. We conducted two simulations, differing in the spatial distribution of shortwave attenuation depth for the period 2014–2015. The control run use a constant attenuation depth of 23 m (the default case for Type-I water) while the experimental run (ER) use spatially varying attenuation depths derived from daily climatology of the diffuse attenuation coefficient ( K d 490). Simulated parameters like sea surface temperature (SST) and mixed-layer depth (MLD) are sensitive to K d 490 that limits the penetration of downwelling shortwave radiation into the ocean. It has been found that K d 490 alters the upper ocean thermodynamics significantly. Validation has been performed using satellite, moored-buoy and profile data, for the year 2015. During spring, the errors in SST in the ER are reduced up to 35% at buoy location. The impact of improving shortwave attenuation depth is found to be maximum in the upper ocean (50–150 m). Error in simulated temperature at 100 m depth is reduced by 15% in the ER. MLD, barrier layer thickness, and the depth of 26 °C isotherm also show significant improvements in the ER. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The diffuse attenuation coefficient of downwelling irradiance (Kd) is an essential parameter for inland waters research by remotely sensing the water transparency. Lately, Kd semi-analytical algorithms substituted the empirical algorithms widely employed. The purpose of this research was to reparametrize a semi-analytical algorithm to estimate Kd and then apply it to a Sentinel-2 MSI time-series (2017–2019) for the Três Marias reservoir, Brazil. The results for the Kd semi-analytical reparametrization achieved good accuracies, reaching mean absolute percentage errors (MAPE) for bands B2, B3 and B4 (492, 560 and 665 nm), lower than 21% when derived from in-situ remote sensing reflectance (Rrs), while for MSI Data, a derived MAPE of 12% and 38% for B2 and B3, respectively. After the application of the algorithm to Sentinel-2 images time-series, seasonal patterns were observed in the results, showing high Kd values at 492 nm during the rainy periods, mainly in the tributary mouths, possibly due to an increase in the surface runoff and inflows and outflow rates in the reservoir watershed.

We evaluated six empirical and semianalytical models of the diffuse attenuation coefficient at 490 nm (Kd(490)) using an in situ dataset collected in the Pearl River estuary (PRE). A combined model with the most accurate performance (correlation coefficient, R2 = 0.92) was selected and applied for long-term estimation from 2003 to 2017. Physical and biological processes in the PRE over the 14-year period were investigated by applying satellite observations (MODIS/Aqua data) and season-reliant empirical orthogonal function analysis (S-EOF). In winter, the average Kd(490) was significantly higher than in the other three seasons. A slight increasing trend was observed in spring and summer, whereas a decreasing trend was observed in winter. In summer, a tongue with a relatively high Kd(490) was found in southeastern Lingdingyang Bay. In Eastern Guangdong province (GDP), the relatively higher Kd(490) value was found in autumn and winter. Based on the second mode of S-EOF, we found that the higher values in the eastern GDP extended westward and formed a distinguishable tongue in winter. The grey relational analysis revealed that chlorophyll-a concentration (Cchla) and total suspended sediment concentration (Ctsm) were two dominant contributors determining the magnitude of Kd(490) values. The Ctsm-dominated waters were generally located in coastal and estuarine turbid waters; the Cchla-dominated waters were observed in open clear ocean. The distribution of constituents-dominated area was different in the four seasons, which was affected by physical forces, including wind field, river runoff, and sea surface temperature.

The vertical distribution of irradiance in the ocean is a key input to quantify processes spanning from radiative warming, photosynthesis to photo-oxidation. Here we use a novel dataset of thousands local-noon downwelling irradiance at 490 nm (Ed(490)) and photosynthetically available radiation (PAR) profiles captured by 103 BGC-Argo floats spanning three years (from October 2012 to January 2016) in the world’s ocean, to evaluate several published algorithms and satellite products related to diffuse attenuation coefficient (Kd). Our results show: (1) MODIS-Aqua Kd(490) products derived from a blue-to-green algorithm and two semi-analytical algorithms show good consistency with the float-observed values, but the Chla-based one has overestimation in oligotrophic waters; (2) The Kd(PAR) model based on the Inherent Optical Properties (IOPs) performs well not only at sea-surface but also at depth, except for the oligotrophic waters where Kd(PAR) is underestimated below two penetration depth (2zpd), due to the model’s assumption of a homogeneous distribution of IOPs in the water column which is not true in most oligotrophic waters with deep chlorophyll-a maxima; (3) In addition, published algorithms for the 1% euphotic-layer depth and the depth of 0.415 mol photons m−2 d−1 isolume are evaluated. Algorithms based on Chla generally work well while IOPs-based ones exhibit an overestimation issue in stratified and oligotrophic waters, due to the underestimation of Kd(PAR) at depth.

Copyright of Journal of Remote Sensing is the property of Editorial Office of Journal of Remote Sensing & Science Publishing Co. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

An optical algorithm is developed for the retrieval of the downwelling diffuse attenuation coefficient $K_{d}$ (490) in the Red Sea using a comprehensive hydrolight simulated data set ($N = 5000$). We found a robust relationship between the $K_{d}$ (490) and the ratio of remote sensing reflectance $R_{\text {rs}}$ (443)/ $R_{\text {rs}}$ (555), with an excellent determination coefficient ($R^{2} = 0.999$) and a low root-mean-square error (RMSE = 0.00033). The performance of the developed algorithm is evaluated with in situ data collected in the Red Sea by comparing obatined model output with existing empirical (NASA, Morel et al., Zhang and Fell, Tiwari and Shanmugam) and semianalytical (Lee et al.) algorithms. On the used in situ data from the Red Sea, the new algorithm shows good retrievals of $K_{d}$ (490) with a low bias, and a low RMSE compared to that of the existing algorithms. For satellite application, we applied our algorithm to selected MODIS–Aqua images acquired over the Red Sea, which captured spatial features of phytoplankton blooms and physical processes (e.g., cyclonic and anticyclonic circulations) in the Red Sea. The new algorithm has the potential to improve our understanding of water transparency and photosynthetic processes that rely on the availability of solar radiation. [ABSTRACT FROM AUTHOR]

Abstract To assess the seasonal and spatial variations and long-term trends in water optical properties in Lake Fuxian, investigations based on field work in four seasons and a long-term analysis of data from 1980 to 2014 were conducted. The results show that there was no significant variation in the euphotic depth (Z eu) across the four seasons, and no significant correlations between Z eu and potential influencing factors in seasons other than summer, suggesting that the water itself may be a major factor regulating the Z eu in general. Nevertheless, significant differences in Z eu between the north region (NR) and the south region (SR) were observed in all seasonal tests except spring. This finding relates to a higher abundance of chromophoric dissolved organic matter (CDOM) in the NR due to runoff, especially in the rainy seasons (summer and autumn). CDOM and its terrigenous component had an important impact on Z eu in summer, with the highest precipitation, and impacts from suspended solids and non-algal particles were also found in the NR in summer. The Secchi disk depth in the lake decreased clearly over the years, with significantly negative correlations with the increasing permanganate index and air temperature, implying that organic contaminants (CDOM and/or phytoplankton) are important regulators of water transparency. We estimate that the combined effects of climate warming and changes in land use and land cover are also indirect regulating factors. These findings should be considered in the protection of Lake Fuxian, owing to the importance of light penetration in aquatic ecosystems. Graphical abstract Unlabelled Image [ABSTRACT FROM AUTHOR]

An important goal of coral reef science is to understand the roles played by environmental conditions in determining benthic community structure. Pursuit of this goal typically involves testing for associations between community structure and environmental conditions, and in recent years, attention has focused on temperature and seawater pH. Such analyses are helpful in projecting coral reef community structure into the future, but their efficacy depends on the extent to which changes in community structure are correctly associated with causative processes, and whether future conditions are a subset of those experienced in the past. Here, we describe variation from 2014 to 2017 in one environmental factor, photosynthetically active radiation (PAR), at 19-m depth on the reefs of St. John, US Virgin Islands, and evaluate the extent to which this factor could cause changes in benthic community structure. The transmission of downwelling surface PAR to 19-m depth (TPAR-19) varied from 2.0 to 40.0% among days, and from 4.8 to 15.8% among months within a year, and was lower and more variable in the autumn versus other seasons. Monthly TPAR-19 was inversely associated with monthly rainfall, suggesting that runoff affected seawater clarity. The monthly diffuse attenuation coefficient (Kd-PAR) varied 1.7-fold from 0.097 to 0.164 m−1 and was within the range expected for coral reefs. Given the high temporal variation in underwater light intensity, and its importance to foundational reef taxa, understanding of the response of coral reefs to temperature and pH (and other factors) will remain incomplete without closer attention to this physical environmental condition. [ABSTRACT FROM AUTHOR]

The diffuse attenuation coefficient is an indicator of light availability in the surface layer, and is used in a broad range of applications, including numerical simulations, for the parameterization of the light transmission in the water column. In this study, a new dataset of the diffuse attenuation coefficient for the Eastern Mediterranean Sea test case is developed using an existing optical dataset of 2614 beam attenuation coefficient profiles. This method introduces a way of overcoming the difficulty of measuring the diffuse attenuation coefficient in-situ by utilizing the most routinely measured variable, the beam attenuation coefficient. The proposed approach uses existing semi-analytical relationships and a neural network. The neural network, a multi-layer perceptron regression model, is trained and validated with a dataset of 29398 concurrent bio-optical in-situ measurements from the PROSOPE cruise and remotely sensed surface variables. The model is applied to the Eastern Mediterranean dataset and the results are interpolated into a gridded gap-free field, with a grid resolution of 0.0416° x 0.0416°, which is assessed and compared with a satellite-derived product, investigating their significant differences. The resulting field's mean value is slightly reduced with respect to the satellite product, showing regions of higher turbidity, with the most prominent located in the northern Aegean Sea in regions of excess colored dissolved organic matter and around mesoscale features and in the Cretan and Levantine Sea in regions of higher mesoscale activity. • A diffuse attenuation coefficient dataset was developed using a neural network. • Beam attenuation measurements were used in the neural network. • The neural network was applied in the Eastern Mediterranean Sea. • The attenuation variability in the Eastern Mediterranean was assessed. • There was variability in the difference between our product and the satellite dataset. [ABSTRACT FROM AUTHOR]

Commonly we see the diffuse attenuation coefficient of downwelling irradiance (Kd) expressed as a sum of the contributions of various constituents. We show here that, both theoretically and numerically, because Kd is an apparent optical property (AOP), this approach is not consistent with radiative transfer. We further advocate the application of models of Kd developed in past decades that are not only consistent with radiative transfer but also provide more accurate estimates, in particular for coastal turbid waters.