Seasonal variation of suspended sediment and its relationship with turbidity in Cam - Nam Trieu estuary, Hai Phong (Vietnam)

We analyzed the seasonal variation of suspended sediment and its relationship with Turbidity in Cam - Nam Trieu estuary based on data measured during three different seasons: Early wet season (May 2015), wet season (September 2015) and dry season (January 2016). The results highlighted the seasonal variation of suspended particle matter (SPM) concentrations with river flow. The average SPM concentration was highest during the dry season, with 62.95 mg/L. They were not significantly different between the early wet and wet seasons, with 59.65 mg/L and 50.94 mg/L, respectively. This study also demonstrated a strong dependence between SPM and Turbidity in the study area. The coefficients of determination varied from 0.867 to 0.971 (linear relationship), and from 0.95 to 0.991 (proportional relationship). Therefore, turbidity can be used to estimate SPM concentration. However, this relationship changed markedly with the seasons, and hence when determining SPM concentration, seasonal factors must be considered.

Remote Retrieval of Suspended Particulate Matter in Inland Waters: Image-Based or Physical Atmospheric Correction Models?

The objective of this paper was to compare the limits of three image-based atmospheric correction models (top of the atmosphere (ToA), dark object subtraction (DOS), and cosine of the sun zenith angle (COST)), and three physical models (atmospheric correction for flat terrain (ATCOR), fast line-of-sight atmospheric analysis of spectral hypercubes (FLAASH)), and ACOLITE) for retrieving suspended particulate matter (SPM) concentrations in inland water bodies using Landsat imagery. For SPM concentration estimates, all possible combinations of 2-band normalized ratios (2bNR) were computed, and a stepwise regression was applied. The correlation analysis allowed highlighting that the red/blue 2bNR was the best spectral index to retrieve SPM concentrations in the case of image-based models, while the red/green 2bNR was the best in the case of physical models. Contrary to expectations, image-based atmospheric models outperformed the accuracy of physical models. The cross-validation results underlined the good performance of the DOS and COST models, with R2 > 0.83, NASH-criterion (Nash) > 0.83, bias = −0.01 mg/L, and RMSE < 0.27 mg/L. This outperformance was confirmed using blind test validation data, with an R2 > 0.86 and Nash > 0.58 for the DOS and COST models. The challenges and limitations involved in the remote monitoring of SPM spatial distribution in turbid productive waters using satellite data are discussed at the end of the paper.

Optical Classification of Lower Amazon Waters Based on In Situ Data and Sentinel-3 Ocean and Land Color Instrument Imagery

Optical water types (OWTs) were identified from an in situ dataset of concomitant biogeochemical and optical parameters acquired in the Amazon River and its tributaries, in the Lower Amazon region, at different hydrological conditions from 2014 to 2017. A seasonal bio-optical characterization was performed. The k-means classification was applied to the in situ normalized reflectance spectra (rn(λ)), allowing the identification of four OWTs. An optical index method was also applied to the rn(λ) defining the thresholds of the OWTs. Next, level-3 Sentinel-3 Ocean and Land Color Instrument images representative of the seasonal discharge conditions were classified using the identified in situ OWTs as reference. The differences between Amazon River and clearwater tributary OWTs were dependent on the hydrological dynamics of the Amazon River, also showing a strong seasonal variability. Each OWT was associated with a specific bio-optical and biogeochemical environment assessed from the corresponding absorption coefficient values of colored dissolved organic matter (aCDOM) and particulate matter (ap), chlorophyll-a and suspended particulate matter (SPM) concentrations, and aCDOM/ap ratio. The rising water season presented a unique OWT with high SPM concentration and high relative contribution of ap to total absorption compared to the other OWTs. This bio-optical characterization of Lower Amazon River waters represents a first step for developing remote sensing inversion models adjusted to the optical complexity of this region.

Evolution of the long-term and estuary-scale phytoplankton patterns in the Scheldt estuary: the disappearance of net growth in the brackish region

Estuaries often show regions in which Chlorophyll-a (Chl-a) accumulates. The location and magnitude corresponding to such accumulation result from a complex interplay between processes such as river flushing, salinity, nutrients, phytoplankton grazing, and the light climate in the water column. Of particular interest is the long-term evolution of the estuary-scale Chl-a distribution in the Scheldt estuary (Belgium/Netherlands) in spring. From 2004–2007, we observed a limited spring-bloom in the brackish region. This bloom intensified in 2008–2014 and disappeared after 2015. This long-term evolution in Chl-a has been linked to simultaneous long-term trends in the suspended particulate matter (SPM) distribution and the improvement of the water quality, which affects grazing of Chl-a by zooplankton. However, this hypothesis has not been systematically investigated. In this paper, we apply two approaches to test this hypothesis. In the first approach, we analyze long-term in situ observations covering the full estuary. These observations include the SPM concentration, zooplankton abundance, and other variables affecting the Chl-a concentration, and show a long-term estuary-scale evolution in not only the SPM distribution but also in zooplankton abundance, freshwater discharge, and maximum photosynthetic rate. In the second approach, we apply a model approach supported by these observations to determine which of the changed conditions may explain the observed change in Chl-a. Our results suggest that a change in SPM alone cannot explain the Chl-a observations. Instead, mortality rate and grazing by zooplankton mainly explains the long-term estuary-scale evolution of Chl-a in spring. Our results highlight that insight into the zooplankton dynamics is essential to understand the phytoplankton (cf. Chl-a) dynamics in the Scheldt estuary.

The CMEMS High Resolution Coastal Service

&lt;p&gt;High-quality satellite-based ocean colour products can provide valuable support and insights in management and monitoring of coastal ecosystems. Today&amp;#8217;s availability of Earth Observation (EO) data is unprecedented including traditional medium resolution ocean colour systems (e.g. SeaWiFS, MODIS-AQUA, MERIS, Sentinel-3/OLCI), high resolution land sensors (e.g. Sentinel-2/MSI, Landsat-8/OLI, Pleiades) and geostationary satellites (e.g. SEVIRI). Each of these sensors offers specific advantages in terms of spatial, temporal or radiometric characteristics.&lt;/p&gt;&lt;p&gt;As a new production unit, the high resolution coastal service will be integrated in CMEMS. It offers 12 different products which are covered within the Ocean Colour Thematic Assembly Centre (OCTAC). The products can be categorized in two groups: 1) near real time (NRT) and Multi-Year near real time (MYNRT). The products are generated the coastal waters (20km stripe for the coastline) for all European Seas and are provided in 100m spatial resolution. All products are based on Sentinel-2 MSI data. The primary OCTAC variable from which it is virtually possible to derive all the geophysical and transparency products is the spectral Remote Sensing Reflectance (RRS). This, together with the Particulate Backscatter Coefficient (BBP), constitute the category of the optics products. The spectral BBP product is generated from the RRS products using a quasi-analytical algorithm. The transparency products include turbidity (TUR) and Suspended Particulate Matter (SPM) concentration. They are retrieved through the application of automated switching algorithms to the RRS spectra adapted to varying water conditions. The geophysical product consists of the Chlorophyll-a concentration (CHL) retrieved via a multi-algorithm approach with optimized quality flagging. The NRT products are generally provided withing 24 hours after end of the acquisition day, while monthly averaged products are provided few days after end of the respective month. A third group of products are daily gap-filled products which are provided once in a quarter. Validation of the variables has been performed by match-up analysis with in situ data as well as by comparison of the high resolution products with the well established Low Resolution CMEMS Ocean Colour products. The products will be introduced in the CMEMS service by May 2021. We will present the products themselves as well as the validation results for the different variables. The known limitations will be reported in order to provide a full picture of the new service.&lt;/p&gt;

Hydrological variability and suspended particulate matter in the middle river Niger bassin

&lt;p&gt;In the Sahel, climate variability and high population growth have led to changes in surface conditions that resulted in increased runoff coefficients and discharge in the major Sahelian rivers. The mid reaches of the Niger river have experienced significant increases in the Red flood, or local flood, that occurs during the rainy season between June and September, relative to Black flood, or Guinean flood that arrives in Niamey from December onwards.&lt;br&gt;The objective of this work was to characterize suspended particulate matter (SPM) during the Red and Black floods in the Niamey area and analyse their spatio-temporal dynamics. Two approaches are used : the first one consists of regular in-situ measurements of SPM concentration and in their physical and mineral characterization by electron microscopy; the second is based on monitoring water color by both in-situ and satellite (Sentinel 2) radiometric measurements.&lt;br&gt;SPM are characterized by very fine particles (with a major mode around 0.1-0.2 micrometers) mainly composed by kaolinites (iron oxides are also observed during the Red flood). This, combined with the very high levels of SPM concentration reached during the rainy season, results in very high values of reflectance in the visible end infrared bands. Radiometric measurements in the nir band by both the in-situ SKYE sensor and the Sentinel2 sensor are found to be significantly correlated to in-situ SPM, allowing efficient monitoring of SPM concentration in time and space.&lt;br&gt;SPM-discharge curves, reveal a complex relationship : SPM increases very rapidly at the beginning of the rainy season when soils are washed out after the long dry period, reaching a peak before the first discharge peak (Red flood). SPM continues to decrease during the second discharge peak (Black flood) from December to February, providing a distinct and unique signature. Analysis of satellite data allowed identifying the main sources of SPM and to quantify the significant contribution of the right bank river tributaries to sediments in the middle Niger river bassin. This contribution may further increase in the context of global changes (climate and anthropogenic) with important consequences on sediment transport but also on water quality and bacterial concentration which are strongly influenced by high SPM.&lt;/p&gt;

Consistency of Suspended Particulate Matter Concentration in Turbid Water Retrieved from Sentinel-2 MSI and Landsat-8 OLI Sensors

Research on the consistency of suspended particulate matter (SPM) concentration retrieved from multisource satellite sensors can serve as long-time monitoring of water quality. To explore the influence of the atmospheric correction (AC) algorithm and the retrieval model on the consistency of the SPM concentration values, Landsat 8 Operational Land Imager (OLI) and Sentinel 2 MultiSpectral Imager (MSI) images acquired on the same day are used to compare the remote sensing reflectance (Rrs) SPM retrieval values in two high-turbidity lakes. An SPM retrieval model for Shengjin Lake is established based on field measurements and applied to OLI and MSI images: two SPM concentration products are highly consistent (R2 = 0.93, Root Mean Squared Error (RMSE) = 20.67 mg/L, Mean Absolute Percentage Error (MAPE) = 6.59%), and the desired results are also obtained in Chaohu Lake. Among the four AC algorithms (Management Unit of the North Seas Mathematical Models (MUMM), Atmospheric Correction for OLI’lite’(ACOLITE), Second Simulation of Satellite Signal in the Solar Spectrum (6S), Landsat 8 Surface Reflectance Code & Sen2cor (LaSRC & Sen2cor)), the two Rrs products, as well as the final SPM concentration products retrieved from OLI and MSI images, have the best consistency when using the MUMM algorithm in SeaWIFS Data Analyst System (SeaDAS) software. The consistency of SPM concentration values retrieved from OLI and MSI images using the same model or same form of models is significantly better than that retrieved by applying the optimal models with different forms.

The impact of wildfires on the Lake Skadar/Shkodra environment

Every year wildfires bring damages to the environment of Montenegro, and, in particular, to the Lake Skadar/Shkodra environment. Wildfires are caused by dry and hot weather which is established yearly from July to September, and is likely linked to the regional climate change. In this study we used high resolution optical imagery (OLI Landsat-8 and MSI Sentinel-2A, -2B) to analyze concentrations of suspended particulate matter and chlorophyll-a in Lakes Skadar/Shkodra and Šas in order to understand the potential impact of wildfires on the lake ecosystem. The surface of burnt areas was calculated for different regions around Lakes Skadar/Shkodra and Šas. Our data showed that SPM values in lake water increase during wildfire. The highest SPM value was observed in the area around the mouth of the left branch of River Morača where the largest areas affected by fires were observed. The SPM concentration in water of Lakes Skadar/Shkodra and Šas generally decreased after rainstorms. The need for implementation of a comprehensive fire management program that includes monitoring of impact of fires on aquatic ecosystems and their biota is emphasized.

Using remote sensing and numerical modelling to quantify a turbidity discharge event in Lake Garda

We investigate the effect of the Adige-Garda spillway opening on the 03/03/2020 on Lake Garda using numerical modelling and maps of Suspended Particulate Matter (SPM) concentration. SPM maps are obtained from Sentinel-2 images processed using the BOMBER bio-optical model. Three satellite images are examined: 28/02/2020, 04/03/2020 and 07/03/2020. Maps indicate a significant increase in SPM concentrations, especially in the northern part of the lake close to the hydraulic tunnel outlet. Results are consistent with the modelled flow field. Remote sensing effectively captures the event’s spatial and temporal variation, while numerical modelling explains and corroborates the observed patterns.