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The ESA CCI Lakes is a multi-disciplinary project (https://climate.esa.int/en/projects/lakes/) to exploit satellite data to create the largest and longest possible consistent, global record of lake climate variables: lake water level, extent, temperature, surface-leaving reflectance, and ice cover. The first version of the database includes 250 globally distributed lakes with temporal coverage ranging, depending on the variable, from 1992 up to 2019. The dataset is now growing to 2000 lakes and by next November the new version of satellite products will be accessible. In this study the potential of the dataset is being explored for different case studies (i.e. Mendota, Erken, Balaton, Iseo, Garda, Trasimeno, and Peipsi) as part of the Long-Term Ecosystem Research (LTER) network. Satellite products of chlorophyll-a, turbidity and lake surface temperature from 2002 to 2019 are compared and integrated with the corresponding in situ data in the LTER dataset. Time-series of satellite data are then explored to examine trends in the context of key meteo-climatic variables.

A coupled 3D hydrodynamic-ecological model was applied to the Santa Marta Coastal Area (SMCA, Colombian Caribbean) to provide insights into the role of external stressors (e.g. wastewater outfall and upwelling) on the water quality and benthic - pelagic coupling. The model was calibrated and validated based on benthic metabolic measurements, satellite-derived chlorophyll-a (Chl-a) and sea surface temperature (SST) maps, field and literature water quality data. The model was able to reproduce the complex dynamics and fast transitions of temperature, nutrients, and phytoplankton, including the stratification and mixing periods during the non-upwelling (NUPW) and upwelling (UPW) seasons. Wide and fast changes in the temperatures and the highly flushed environment prevented excess phytoplankton growth and nutrient accumulation in the benthic and pelagic compartments. The model proved to be a reliable research tool to analyze the interactive effects of upwelling and untreated wastewater on the functioning of a tropical bay.

Following more than two decades of research and developments made possible through various proof-of-concept hyperspectral remote sensing missions, it has been anticipated that hyperspectral imaging would enhance the accuracy of remotely sensed in-water products. This study investigates such expected improvements and demonstrates the utility of hyperspectral radiometric measurements for the retrieval of near-surface phytoplankton properties(1), i.e., phytoplankton absorption spectra (a(ph)) and biomass evaluated through examining the concentration of chlorophyll-a (Chla). Using hyperspectral data (409-800 nm at similar to 5 nm resolution) and a class of neural networks known as Mixture Density Networks (MDN) (Pahlevan et al., 2020), we show that the median error in a(ph) retrievals is reduced two-to-three times (N = 722) compared to that from heritage ocean color algorithms. The median error associated with our a(ph) retrieval across all the visible bands varies between 20 and 30%. Similarly, Chla retrievals exhibit significant improvements (i.e., more than two times; N = 1902), with respect to existing algorithms that rely on select spectral bands. Using an independent matchup dataset acquired near-concurrently with the acquisition of the Hyperspectral Imager for the Coastal Ocean (HICO) images, the models are found to perform well, but at reduced levels due to uncertainties in the atmospheric correction. The mapped spatial distribution of Chla maps and a(ph) spectra for selected HICO swaths further solidify MDNs as promising machine-learning models that have the potential to generate highly accurate aquatic remote sensing products in inland and coastal waters. For a(ph) retrieval to improve further, two immediate research avenues are recommended: a) the network architecture requires additional optimization to enable a simultaneous retrieval of multiple in-water parameters (e.g., a(ph), Chla, absorption by colored dissolved organic matter), and b) the training dataset should be extended to enhance model generalizability. This feasibility analysis using MDNs provides strong evidence that high-quality, global hyperspectral data will open new pathways toward a better understanding of biodiversity in aquatic ecosystems.

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.

The interaction between microbial communities and benthic algae as nitrogen (N) regulators in poorly illuminated sediments is scarcely investigated in the literature. The role of sediments as sources or sinks of N was analyzed in spring and summer in sandy and muddy sediments in a turbid freshwater estuary, the Curonian Lagoon, Lithuania. Seasonality in this ecosystem is strongly marked by phytoplankton community succession with diatoms dominating in spring and cyanobacteria dominating in summer. Fluxes of dissolved gas and inorganic N and rates of denitrification of water column nitrate (Dw) and of nitrate produced by nitrification (Dn) and sedimentary features, including the macromolecular quality of organic matter (OM), were measured. Shallow/sandy sites had benthic diatoms, while at deep/muddy sites, settled pelagic microalgae were found. The OM in surface sediments was always higher at muddy than at sandy sites, and biochemical analyses revealed that at muddy sites the OM nutritional value changed seasonally. In spring, sandy sediments were net autotrophic and retained N, while muddy sediments were net heterotrophic and displayed higher rates of denitrification, mostly sustained by Dw. In summer, benthic oxygen demand increased dramatically, whereas denitrification, mostly sustained by Dn, decreased in muddy and remained unchanged in sandy sediments. The ratio between denitrification and oxygen demand was significantly lower in sandy compared with muddy sediments and in summer compared with spring. Muddy sediments displayed seasonally distinct biochemical composition with a larger fraction of lipids coinciding with cyanobacteria blooms and a seasonal switch from inorganic N sink to source. Sandy sediments had similar composition in both seasons and retained inorganic N also in summer. Nitrogen uptake by microphytobenthos at sandy sites always exceeded the amount loss via denitrification, and benthic diatoms appeared to inhibit denitrification, even in the dark and under conditions of elevated N availability. In spring, denitrification attenuated N delivery from the estuary to the coastal area by nearly 35%. In summer, denitrification was comparable (~100%) with the much lower N export from the watershed, but N loss was probably offset by large rates of N-fixation.

Climate change has increased the temperature and altered the mixing regime of high-value lakes in the sub-alpine region of Northern Italy. Remote sensing of chlorophyll-a can help provide a time-series to allow an assessment of the ecological implications of this. Non-parametric multiplicative regression (NPMR) was used to visualize and understand the changes that have occurred between 2003–2018 in lakes Garda, Como, Iseo and Maggiore. In all four deep sub-alpine lakes there has been a disruption from a traditional pattern of a significant spring chlorophyll-a peak followed by a clear water phase and summer/autumn peaks. This was replaced after 2010–2012, with lower spring peaks and a tendency for annual maxima to occur in summer. There was a tendency for this switch to be interspersed by a two-year period of low chlorophyll-a, which seemed to extend until 2018 for Lake Garda. Variables that were significant in NPMR included time, air temperature, wind speed, cloud cover, winter temperature and winter values for the North Atlantic Oscillation and Eastern Atlantic pattern. The change from spring to summer chlorophyll-a maxima, relatively sudden in an ecological context, could be interpreted as a regime shift. The cause is probably cascading effects from increased winter temperatures, reduced winter mixing and altered nutrient dynamics. Future trends will depend on climate change and inter-decadal climate drivers.

Lake water quality monitoring has the potential to be improved through integrating detailed spatial information from new generation remote sensing satellites with high frequency observations from in situ optical sensors (WISPstation). We applied this approach for Lake Trasimeno with the aim of increasing knowledge of phytoplankton dynamics at different temporal and spatial scales. High frequency chlorophyll-a data from the WISPstation was modeled using non-parametric multiplicative regression. The &lsquo, day of year&rsquo, was the most important factor, reflecting the seasonal progression of a phytoplankton bloom from July to September. In addition, weather factors such as the east&ndash, west wind component were also significant in predicting phytoplankton seasonal and diurnal patterns. Sentinel 3-OLCI and Sentinel 2-MSI satellites delivered 42 images in 2018 that successfully mapped the spatial and seasonal change in chlorophyll-a. The potential influence of localized inflows in contributing to increased chlorophyll-a in mid-summer was visualized. The satellite data also allowed an estimation of quality status at a much finer scale than traditional manual methods. Good correspondence was found with manually collected field data but more significantly, the greatly increased spatial and temporal resolution provided by satellite and WISPstation sensors clearly offers an unprecedented resource in the research and management of aquatic resources.

This study focuses on the use of satellite remote sensing to map coastal erosion vulnerability in two Italian sites: Pianosa Island (Tuscany) and Piscinas (Sardinia). For both areas we focused on the land/water transitional ecosystem, with the aim of identifying potential coastal erosion phenomena and to demonstrate the role of benthic habitats in preserving the value of coastal environments. The method made use of ancillary and multispectral satellite data from 2016 to 2018. For this study, the first 7 bands of the VIS-NIR region of Sentinel-2 were used, all reprocessed at the spatial resolution of 10 m. The TOA (Top of Atmosphere) radiance products were atmospherically corrected and processed using the Sen2Coral add-on-tool and the BOMBER code (Bio-Optical Model-Based tool for Estimating water quality and bottom properties from Remote sensing images). Maps of marine substrates and bathymetry were obtained and revealed their influence on the coastal dynamics. Then, in case of Piscinas, SAR images (COSMO SkyMed and Sentinel-1B) were added to the analyses. COSMO-SkyMed allowed us to identify the coastline and to obtain qualitative indicators about the absence/presence of changes in coastal dune system, the most relevant terrestrial element of the site. Sentinel-1B supported, by adopting an inversion process scheme, the analysis of the wave state impacting the coast. By merging the satellite products, the coastal erosion vulnerability maps have been generated based on substrate type in shallow waters and sand volume variation on land: rocky bottoms and stable meadows of phanerogams seemed preserving the coast, while the substrate characterized by a loss of phanerogams and a decrease in sand volumes might be considered more vulnerable. The results confirm that the coast of Pianosa is not suffering from coastal erosion, while the vulnerability maps of Piscinas seem to be closely linked to episodic events so that the Piscinas dune system might be considered safe from coastal erosion processes

Lakes are key indicators of local and regional water¬shed changes, making them useful for detecting Earth's response to climate change (Adrian et al., 2009). Specifically, variables such as lake surface temperature, water level and extent, ice cover and lake colour are recognized by the Global Climate Observing System (GCOS) as Essential Climate Variables (ECVs) because they contribute critically to the characterization of Earth's climate (Woolway et al., 2020). Lakes are already responding rapidly to climate change. Some of the most pervasive and concerning physical consequences of climate change on lakes are the loss of ice cover (Sharma et al. 2019), changes in evaporation and water budgets (Rodell et al., 2018; Wang et al., 2018), warming surface water temperature (O'Reilly et al., 2015) and alterations in mixing regimes (Woolway and Merchant, 2019). Variations in temperature and precipitation can profoundly affect the hydrological functioning of the lake and its catchment. Together with changes in ice formation, lake level and hydrogeochemistry the effect on lake ecological functioning can be significant (Adger et al., 2007; Cisneros et al., 2014). The thermal structure of the lake can be strengthened by an increase in temperature leading to deoxygenation and an alteration of nutrient cycling that in some case exerts a stronger control than trophic status (Rogora et al., 2018). Lakes are of significant interest to the scientific community, local to national governments, industries and the wider public. A range of scientific disciplines including hydrology, limnology, climatology, biogeochemistry and geodesy are interested in the distribution and functioning of the millions of lakes (from small ponds to inland seas) from the local to the global scale. Future efforts investigating lake responses to climate change need to be grounded in sustainable, systematic, multivariate observations for a consistent set of lakes. One effort in this direction is the ongoing European Space Agency Climate Change Initiative for Lakes (CCI Lakes), which coordinates a range of remote- sensing techniques to address the lake ECVs identified by the GCOS (Woolway et al., 2020). An important aspect of efforts such as CCI Lakes is that they focus on maximizing the benefit of legacy Earth observations made over the past decades, as well as developing better observational capabilities from current and prospective missions (Woolway et al., 2020). The overarching objective of the Lakes_cci project is to produce and validate a consistent data set of the variables grouped under the Lakes ECV. This includes aiming for the longest period of combined satellite observations by designing and operating processing chains, designed to be ultimately feature in a sustainable production system. The Lakes_cci develops products for the following five thematic climate variables: oLake Water Level (LWL): a proxy fundamental to understand the balance between water inputs and water loss and their connection with regional and global climate changes. oLake Water Extent (LWE): a proxy for change in glacial regions (lake expansion) and drought in many arid environments, water extent relates to local climate for the cooling effect that water bodies provide. oLake Surface Water temperature (LSWT): correlated with regional air temperatures and a proxy for mixing regimes, driving biogeochemical cycling and seasonality. oLake Ice Cover (LIC): freeze-up in autumn and advancing break-up in spring are proxies for gradually changing climate patterns and seasonality. oLake Water-Leaving Reflectance (LWLR): a direct indicator of biogeochemical processes and habitats in the visible part of the water column (e.g. seasonal phytoplankton biomass fluctuations), and an indicator of the frequency of extreme events (peak terrestrial run-off, changing mixing conditions). In this context, Lakes_cci represents a unique framework to provide consistent and homogenous data to the multiple communities of lake scientists. The project actively engages with this community to assess the utility and future improvement of Lakes_cci products. Following the end of the first year of the project, a first version of the dataset is now available on the suite of parameters from 2002 to 2019, with some parameters extending further back to 1992, on an initial set of 250 lakes distributed globally. The validation of each individual thematic variables is based on direct comparison between remote sensing products and in situ data or other remoting sensing datasets. A following step is the analysis of the consistency between these variables through five use cases (Greenland lakes; large lakes; Danube river-lake-lagoon; Long Term Ecosystem Research (LTER) sites; brownification in Scandinavian lakes). Data generated in the Lakes_cci project is derived from data from multiple sensors and multiple satellites. LWL estimation is based on altimeters data gathered from 7 satellites (e.g. Poseidon, ENVISAT, Sentinel-3). LWE estimation is based on 8 sensors both SAR an optical onboard on different satellites (e.g. Landsat, Sentinel, ERS 1). The same typologies were used for LIC detection (e.g. Terra/Aqua, Sentinel-1). LSWT retrieval is based on 5 satellite observations (e.g. Metop A/B, Terra). LWLR data for the retrieval of chlorophyll-a and turbidity is based on optical data measured by 5 satellites (e.g. ENVISAT, Aqua, Sentinel-3). A consequence of this diversity of products is that temporal and spatial resolutions as well as data availably of each component are not currently the same. Nevertheless, a first-order harmonization of the thematic variables is ensured in each NetCDF file which contains all information available for each product. The uncertainty and data quality level estimation for each product is also included in the Lakes_cci climate data records and is available for the users. The Lakes_cci products are open public and easy to access so that it definitely presents an opportunity for lake scientists and climate modellers worldwide to perform studies for which the five lakes variables present an important dataset. In this conference we will present the project overview and progress with a focus on the preliminary results of the 5 ECVs at global level and in particular regions.

This deliverable aims at defining the details of the products and service to be developed in close cooperation with large user groups, including the DANUBIUS European research infrastructure, GEO AquaWatch/Blue Planet, Lagoons for Life and end-users in regional case studies. The deliverable also includes a detailed description of the case studies that will be considered as exemplars in the project

Gli obiettivi del lavoro sono: i) la creazione di opportune catene di processamento delle immagini Sentinel-2 e Sentinel-3 per la stima della concentrazione di Clorofilla-a (Chl-a); ii) la conversione delle riflettanze ottenute dalla WISPstation in concentrazioni di Chl-a; iii) l'analisi dei prodotti ottenuti nel 2018 per il monitoraggio delle dinamiche spazio-temporali del fitoplancton e la valutazione dello stato di qualità delle acque del lago Trasimeno sulla base della Water Framework Directive (WFD).

International audience; The importance of lake water surface temperature has long been highlighted for ecological and hydrological studies as well as for water quality management. In the absence of regular field observations, satellite remote sensing has been recognized as a cost-effective way to monitor water surface temperature on large spatial and temporal scales. The thermal infrared sensors (TIRS) onboard of Landsat satellites (since 1984) are adequate tools for monitoring surface temperature of small to medium sized lakes with a biweekly frequency, as well as for performing retrospective analysis. Nonetheless, the satellite data have to deal with effects due to the atmosphere so that several approaches to correct for atmospheric contributions have been proposed. Among these are: (i) the radiative transfer equation (RTE); (ii) a single-channel algorithm that depends on water vapor content and emissivity (SC1); (iii) its improved version including air temperature (SC2); and (iv) a mono-window (MW) algorithm that requires emissivity, atmospheric transmissivity, and effective mean atmospheric temperature. We aim to evaluate these four approaches in a river dammed reservoir with a size of 12 km² using data gathered from the band 10 of the TIRS onboard of Landsat 8. Satellite-derived temperatures were then compared to in situ data acquired from thermistors at the time of Landsat 8 overpasses. All approaches showed a good performance, with the SC1 algorithm yielding the lowest root mean square error (0.73 K), followed by the SC2 method (0.89 K), the RTE (0.94 K), and then the MW algorithm (1.23 K). Based on the validation results, we then applied the SC1 algorithm to Landsat 4, 5, and 8 thermal data (1984 to 2018) to extend data series to past years. These data do not reveal any warming trend of the reservoir surface temperature. The results of this study also confirm how the 100-m spatial resolution of TIRS is valuable as an additional source of data to field-based monitoring.

This paper describes a procedure to perform spatio-temporal analysis of river plume dispersion in prodelta areas by multi-temporal Landsat-8-derived products for identifying zones sensitive to water discharge and for providing geostatistical patterns of turbidity linked to different meteo-marine forcings. In particular, we characterized the temporal and spatial variability of turbidity and sea surface temperature (SST) in the Po River prodelta (Northern Adriatic Sea, Italy) during the period 2013–2016. To perform this analysis, a two-pronged processing methodology was implemented and the resulting outputs were analysed through a series of statistical tools. A pixel-based spatial correlation analysis was carried out by comparing temporal curves of turbidity and SST hypercubes with in situ time series of wind speed and water discharge, providing correlation coefficient maps. A geostatistical analysis was performed to determine the spatial dependency of the turbidity datasets per each satellite image, providing maps of correlation and variograms. The results show a linear correlation between water discharge and turbidity variations in the points more affected by the buoyant plumes and along the southern coast of Po River delta. Better inverse correlation was found between turbidity and SST during floods rather than other periods. The correlation maps of wind speed with turbidity show different spatial patterns depending on local or basin-scale wind effects. Variogram maps identify different spatial anisotropy structures of turbidity in response to ambient conditions (i.e. strong Bora or Scirocco winds, floods). Since the implemented processing methodology is based on open source software and free satellite data, it represents a promising tool for the monitoring of maritime ecosystems and to address water quality analyses and the investigations of sediment dynamics in estuarine and coastal waters.

For effective lakes’ management, high-frequent water quality data on a synoptic scale are essential. The aim of this study is to test the suitability of the latest generation of satellite sensors to provide information on lake water quality parameters for the five largest Italian subalpine lakes. In situ data of phytoplankton composition, chlorophyll-a (chl-a) concentration and water reflectance were used in synergy with satellite observations to map some algal blooms in 2016. Chl-a concentration maps were derived from satellite data by applying a bio-optical model to satellite data, previously corrected for atmospheric effects. Results were compared with in situ data, showing good agreement. The shape and magnitude of water reflectance from different satellite data were consistent. Output chl-a concentration maps, show the distribution within each lake during blooming events, suggesting a synoptic view is required for these events monitoring. Maps show the dynamic of bloom events with concentration increasing from 2 up to 7 mg m−3 and dropping again to initial value in less than 20 days. Latest generation sensors were shown to be valuable tools for lakes monitoring, thanks to frequent, free of charge data availability over long time periods.

Inland and coastal waterbodies are critical components of the global biosphere. Timely monitoring is necessary to enhance our understanding of their functions, the drivers impacting on these functions and to deliver more effective management. The ability to observe waterbodies from space has led to Earth observation (EO) becoming established as an important source of information on water quality and ecosystem condition. However, progress toward a globally valid EO approach is still largely hampered by inconsistences over temporally and spatially variable in-water optical conditions. In this study, a comprehensive dataset from more than 250 aquatic systems, representing a wide range of conditions, was analyzed in order to develop a typology of optical water types (OWTs) for inland and coastal waters. We introduce a novel approach for clustering in situ hyperspectral water reflectance measurements (n = 4045) from multiple sources based on a functional data analysis. The resulting classification algorithm identified 13 spectrally distinct clusters of measurements in inland waters, and a further nine clusters from the marine environment. The distinction and characterization of OWTs was supported by the availability of a wide range of coincident data on biogeochemical and inherent optical properties from inland waters. Phylogenetic trees based on the shapes of cluster means were constructed to identify similarities among the derived clusters with respect to spectral diversity. This typification provides a valuable framework for a globally applicable EO scheme and the design of future EO missions.

A temporally and spatially detailed historical (1985-2018) analysis of cyanobacteria blooms was performed in the Curonian Lagoon (Lithuania, Russia), the largest coastal lagoon in the Baltic Sea. Satellite data allowed the mapping of cyanobacteria surface accumulations, so-called "scums", and of chlorophyll-a concentration. The 34-year time series shows a tendency towards later occurrence (October-November) of the cyanobacteria scum presence, whereas the period of its onset (June-July) remains relatively constant. The periods when scums are present, "hot moments", have been consistently increasing in duration since 2008. The differences in the starting, ending and annual duration of cyanobacteria blooms have been significantly altered by hydro-meteorological conditions (river discharge, water temperature, and wind conditions) and their year-round patterns. The most important environmental factors that determined the temporal changes of the scum presence and area were the standing stock of cyanobacteria and the ambient wind conditions. The "hotspots", the areas where the blooms most likely occur, were distributed in the south-southwestern and central parts of the lagoon. The least affected areas were the northern part, which is connected to the coastal waters of the Baltic Sea, and the Nemunas River delta region. The longstanding, well-established spatial patterns of cyanobacteria blooms were linked to hydrodynamic features, namely water renewal time and current patterns, and to potential nutrient sources that included muddy sediments and the locations of colonies of piscivorous birds. Our findings confirmed that the annual and seasonal variations of cyanobacteria blooms and their regulation are a complex issue due to interactions between multiple factors over spatially and temporally broad scales. Despite great progress in the prevention and control of eutrophication and cyanobacteria blooms, the lagoon is still considered to be in a poor ecological status. This work provides a new and missing understanding on the spatial and temporal extent of cyanobacteria blooms and the factors that govern them. Such an understanding can help in planning management strategies, forecasting the magnitude and severity of blooms under changing nutrient loads and potential climate scenarios.

[White paper] Water quality metrics derived from satellite observation can complement conventional water sampling, particularly to achieve much improved spatialand temporal coverage of medium (several square kilometres) and largerwaterbodies. Thus, it has the potential to enhance confidence in WFDecological status classification, firstly by quantifying elements of environmental status that are currently not or under-reported by Member States, such as the frequency, onset, duration and extent of phytoplankton blooms. Second,confidence in ecological status assessment would improve with increasedrepresentativeness of the natural diversity of waterbodies that aremonitored, their inter-annual variability and water quality trends within largerwaterbodies. Moreover, using standardised approaches, it would allow better comparison and standardization of water quality assessment across Member States, facilitating the management of transboundary waters in particular. Finally, by increasing spatial and temporal coverage, satellite observation is expected to enhance the effectiveness of the Programme of Measures (PoM) through early detection of deterioration, improving knowledge of the potentialextent of an impact, improving monitoring of the effectiveness of PoMs and providing information to support more strategic in situ sampling. The European Union and European Space Agency currently boast the mostadvanced suite of satellite-based instruments designed to observe optical water quality. The Copernicus framework of sensors and services has hadsignificant investment in recent years. Therefore, the vast majority of the costassociated with satellite-based monitoring of surface waters has already been invested. To promote and support the use of satellite-based water quality metrics in WFD statutory monitoring and reporting activities, we make the following recommendations, particularly in light of the ongoing revision of the WFD: Recognition of satellite observation as an assessment method in the context of the revision of the Water Framework Directive. Explicit encouragement to use satellite-based monitoring to complement national and statutory monitoring and reporting, such as already exercised by a limited number of countries (examplesin this paper) and available from existing academic, governmental and private sector capabilities, will provide a clear signal to Member States that its use is supported. In particular, satellite products that enhance confidence in the classification of phytoplankton biomass (typically measured by chlorophyll-a) by vastly improving spatial and temporal coverage should be considered, since these are already highly mature and can support quality elements that have thus far been considered too costly to include using conventional methods, such as assessing the frequency and intensity of algal blooms in lakes and coastal waters. Create a satellite observation expert group to harmonise metrics across countries and advise member states on best practises. The satellite observation expert group will: ensure harmonisation of the applicable satellite observation methods and their comparability with nationally-approved and intercalibrated methods; establish guidelines on how observation uncertainties should be reported; andensure close collaboration with the Water Framework Directive Common ImplementationStrategy working group on ecological status (WG ECOSTAT). An expert group advising on bestpractise is necessary because satellite-based observation capabilities continue to improve overtime whereas water quality management relies on stable and transparent methodologies. The expert group should work towards self-certification in the industry, including representationfrom the downstream Earth observation service sector, and be led by an independent researchand policy advisory body (such as the Joint Research Centre). Reference the use of satellite-based Earth observation metrics in the Reporting Guidance (Annex 5) of the revised Water Framework Directive. Particular reference to the use of satellite-derived water quality indicators in assessing phytoplankton biomass (by proxy of chlorophyll-a) and the frequency and intensity ofphytoplankton blooms in Annex 5 as well as national and international standards will ensurethe provision of monitoring data of equivalent scientific quality and comparability. Convene a conference for EC, Member States, WFD authorities to agree onrecommendations of common practices and reporting standards when using satellitebasedwater quality metrics to support the Water Framework Directive. Provide an opportunity for policy makers to recognise and proactively support the use of already available satellite-based Earth observation derived metrics and capitalise on alreadyestablished networks of national Earth observation scientists applying relevant derived metricsto the Water Framework Directive requirements.

An intercomparison of radiance and irradiance ocean color radiometers (The Second Laboratory Comparison Exercise—LCE-2) was organized within the frame of the European Space Agency funded project Fiducial Reference Measurements for Satellite Ocean Color (FRM4SOC) May 8−13, 2017 at Tartu Observatory, Estonia. LCE-2 consisted of three sub-tasks: 1) SI-traceable radiometric calibration of all the participating radiance and irradiance radiometers at the Tartu Observatory just before the comparisons; 2) Indoor intercomparison using stable radiance and irradiance sources in controlled environment; and 3) Outdoor intercomparison of natural radiation sources over terrestrial water surface. The aim of the experiment was to provide one link in the chain of traceability from field measurements of water reflectance to the uniform SI-traceable calibration, and after calibration to verify whether different instruments measuring the same object provide results consistent within the expected uncertainty limits. This paper describes the activities and results of the first two phases of LCE-2: the SI-traceable radiometric calibration and indoor intercomparison, the results of outdoor experiment are presented in a related paper of the same journal issue. The indoor experiment of the LCE-2 has proven that uniform calibration just before the use of radiometers is highly effective. Distinct radiometers from different manufacturers operated by different scientists can yield quite close radiance and irradiance results (standard deviation s < 1%) under defined conditions. This holds when measuring stable lamp-based targets under stationary laboratory conditions with all the radiometers uniformly calibrated against the same standards just prior to the experiment. In addition, some unification of measurement and data processing must be settled. Uncertainty of radiance and irradiance measurement under these conditions largely consists of the sensor’s calibration uncertainty and of the spread of results obtained by individual sensors measuring the same object.

The relationship between invasive plant functional traits and their invasiveness is still the subject of scientific investigation, and the backgrounds of transition from non-native to invasive species in ecosystems are therefore poorly understood. Furthermore, our current knowledge on species invasiveness is heavily biased toward terrestrial species; we know much less about the influence of allochthonous plant traits on their invasiveness in aquatic ecosystems. We studied physiological and ecological traits of two introduced and three native macrophyte species in the Mantua lakes system (northern Italy). We compared their photophysiology, pigment content, leaf reflectance, and phenology in order to assess how the invasive Nelumbo nucifera and Ludwigia hexapetala perform compared to native species, Nuphar lutea, Nymphaea alba, and Trapa natans. We found L. hexapetala to have higher photosynthetic efficiency and able to tolerate higher light intensities than N. nucifera and the native species especially at extreme weather conditions (prolonged exposure to high light and higher temperatures). Chlorophyll a and b, and carotenoid contents of both allochthonous species was substantially higher than that of the native plants suggesting adaptive response to the ecosystem of Mantua lakes system. Higher variability of recorded data in invasive species also was observed. These observations suggest advanced photosynthetic efficiency of the invasive species, especially L. hexapetala, resulting in faster growth rates and higher productivity. This was supported by the evaluation of seasonal dynamics mapped from satellite remote sensing data. This study provides empirical evidence for the relationship between specific plant physiological traits and invasiveness of aquatic plant species, highlighting the importance of trait studies in predicting ecosystem-level impacts of invasive plant species.

An intercomparison of radiance and irradiance ocean color radiometers (the second laboratory comparison exercise—LCE-2) was organized within the frame of the European Space Agency funded project Fiducial Reference Measurements for Satellite Ocean Color (FRM4SOC) May 8–13, 2017 at Tartu Observatory, Estonia. LCE-2 consisted of three sub-tasks: (1) SI-traceable radiometric calibration of all the participating radiance and irradiance radiometers at the Tartu Observatory just before the comparisons; (2) indoor, laboratory intercomparison using stable radiance and irradiance sources in a controlled environment; (3) outdoor, field intercomparison of natural radiation sources over a natural water surface. The aim of the experiment was to provide a link in the chain of traceability from field measurements of water reflectance to the uniform SI-traceable calibration, and after calibration to verify whether different instruments measuring the same object provide results consistent within the expected uncertainty limits. This paper describes the third phase of LCE-2: The results of the field experiment. The calibration of radiometers and laboratory comparison experiment are presented in a related paper of the same journal issue. Compared to the laboratory comparison, the field intercomparison has demonstrated substantially larger variability between freshly calibrated sensors, because the targets and environmental conditions during radiometric calibration were different, both spectrally and spatially. Major differences were found for radiance sensors measuring a sunlit water target at viewing zenith angle of 139° because of the different fields of view. Major differences were found for irradiance sensors because of imperfect cosine response of diffusers. Variability between individual radiometers did depend significantly also on the type of the sensor and on the specific measurement target. Uniform SI traceable radiometric calibration ensuring fairly good consistency for indoor, laboratory measurements is insufficient for outdoor, field measurements, mainly due to the different angular variability of illumination. More stringent specifications and individual testing of radiometers for all relevant systematic effects (temperature, nonlinearity, spectral stray light, etc.) are needed to reduce biases between instruments and better quantify measurement uncertainties.

We mapped the extent of submerged aquatic vegetation (SAV) of Lake Iseo (Northern Italy, over the 2015&ndash, 2017 period based on satellite data (Sentinel 2 A-B) and in-situ measurements, the objective was to investigate its spatiotemporal variability. We focused on the southern sector of the lake, the location of the shallowest littorals and the most developed macrophyte communities, mainly dominated by Vallisneria spiralis and Najas marina. The method made use of both in-situ measurements and satellite data (22 Sentinel 2 A-B images) that were atmospherically corrected with 6SV code and processed with the BOMBER (Bio-Optical Model-Based tool for Estimating water quality and bottom properties from Remote sensing images). This modeling system was used to estimate the different substrate coverage (bare sediment, dense stands of macrophytes with high albedo, and sparse stand of macrophytes with low albedo). The presented results substantiate the existence of striking inter- and intra-annual variations in the spatial-cover patterns of SAV. Intense uprooting phenomena were also detected, mainly affecting V. spiralis, a species generally considered a highly plastic pioneer taxon. In this context, remote sensing emerges as a very reliable tool for mapping SAV with satisfactory accuracy by offering new perspectives for expanding our comprehension of lacustrine macrophyte dynamics and overcoming some limitations associated with traditional field surveys.

Lakes are good sentinels of the effects of climate change due to their global distribution and the capability of their physical, chemical, and biological properties to respond rapidly to climate-related changes. Water quality status of inland waters can be detected at high spatial-temporal scales by means of Earth Observation (EO) data. In this study, EO satellite data acquired from optical sensors (Envisat-MERIS, Sentinel2-MSI and Sentinel3-OLCI) were used for acquiring timely, frequent synoptic information of the four most important Italian subalpine lakes (Maggiore, Como, Iseo, Garda) over 15 years. Maps of chlorophyll-a (Chl-a), a proxy of the lake trophic state, were retrieved and used to evaluate changes in the water quality status of these ecosystems from 2003 to 2018. Imagery was processed using appropriate atmospheric correction codes to obtain remote sensing reflectance (C2R for MERIS, 6SV for MSI, Polymer for OLCI), and bio-optical models were applied to retrieve Chl-a concentration. The chain products (Rrs and Chl-a) were validated against field data. The Chl-a time series were analyzed in relation to physical and meteorological (water and air temperature) data. The median value of the Chl-a time series range between 1.03 and 1.52 mg m-3, with a seasonal variability particularly evident during spring and autumn. Chl-a concentration showed a slight tendency to increase during the 15 years analyzed, in particular for Iseo and Maggiore lakes (median annual Sen slope 0.109 and 0.111 mg m-3, respectively). This increase in trophic status is related to an increase in water and air temperature in the lakes of the Alpine region. A recent study indicated an increased temperature for subalpine lakes as 0.032 °C yr-1 during summer and an annual average rate of 0.017 °C yr-1.

The complex aquatic ecosystems, such as lakes, are characterized by a high level of hourly and daily dynamic due to the rapid growth / decrease of phytoplankton, and to the variation of the total Suspended Solids due for example to the re-suspension of the bottom caused by winds. To this variability is added the variability also the spatial one. Satellite images have the advantage of being able to respond well to the understanding of spatial variability and temporal variability during the days but not able to explore the hourly temporal variability. For this reason, within the H2020 - EOMORES project we are integrating the use of water quality products obtained from Sentinel-2 and Sentinel-3 images with Remote Sensing Reflectance (Rrs) measurements obtained from spectroradiometers mounted on platforms and / or on floating buoys that allow continuous measurements during the day and for several consecutive days.

During the last eight years, airborne hyperspectral data were acquired over aquatic ecosystems with APEX, under the umbrella of EU FP7 funding (EUFAR and INFORM projects). APEX images were collected over shallow freshwater and coastal ecosystems, characterized by joint presence of phytoplankton in high concentrations and macrophytes, namely: Mantua lakes system (Italy), on 21 September 2011 and on 27 September 2014 (5 flight lines, 5 m resolution); Lake Hídvégi (Hungary), on 19 July 2014 (3 flight lines, 5 m resolution); and Curonian Lagoon (Lithuania), on 1 and 2 September 2016 (24 flight lines, 3 m resolution). Synchronous to airborne acquisitions, radiometric and eco-limnological parameters characterizing the three study sites were collected in situ in order to validate the APEX data and to calibrate reflectance-based models for mapping the biodiversity and abundance of primary producers. Semi-empirical and bio-optical models were applied to APEX derived surface reflectance images for estimating phytoplankton pigments concentration, such as Chlorophyll-a (Chl-a) and Phycocyanin (PC), and macrophyte coverage and traits. We derived detailed maps of Chl-a concentration as proxy of phytoplankton abundance and dominant phytoplankton functional type, being Diatoms or Cryptophytes/Cyanobacteria (Giardino et al., 2018). In addition, phytoplankton spatial patchiness was assessed and related to hydrodynamic features of Mantua lakes system (Pinardi et al., 2015), and multi-temporal analysis revealed lake areas characterized by strong Chl-a variation dynamics (Bresciani et al., 2017). Ecosystem-scale maps of macrophyte morphological traits, in terms of biomass and density, were produced (Villa et al., 2017), and coexistence and interactions between phytoplankton and macrophytes were investigated (Bolpagni et al., 2014). Our main aim is to aggregate all these results for demonstrating the high potential of airborne hyperspectral imaging platforms in providing high resolution, detailed and reliable information on different primary producers in complex aquatic ecosystems.

The twin satellites Sentinel-3 (S3A/B) with Ocean and Land Colour Imager (OLCI) sensors, with a spatial resolution of 300 m, and a revisiting time of 1–2 days, and the twin satellites Sentinel-2 (S2A/B) with MultiSpectral Instrument (MSI) instrument, with a spatial resolution up to 10 m, offer a special opportunity to monitor at both small and large scale, phytoplankton phenology and variation at small time (OLCI) and at small spatial scale (MSI). The aim of this study was to contribute to further testing on MSI imagery, for retrieving chlorophyll-a (chl-a) concentration, proxy of phytoplankton abundance, in inland waters. Since OLCI has higher revisiting frequency and multiple matchups with MSI, it was also examined as a surrogate for MSI. A common image-processing scheme for both sensors was applied in the two large Italian lakes Garda (oligo-mesotrophic) and Trasimeno (eutrophic). Results showed good performances, both in retrieving atmospherically corrected Remote Sensing Reflectance, and, from this last derived, chl-a concentration maps. Very good accordance was assessed between simultaneous OLCI and MSI derived chl-a maps, both in terms of magnitude, and spatial distribution, despite the fact variations in concentration at small scale were better retrieved by MSI imagery.

Providing relatively fine spatial resolution multispectral data, Landsat-8, Landsat-7 (L8 and L7, respectively) and Sentinel-2 (S2) from 2013 to 2018 have been used in this study for enabling high-frequency monitoring of water quality of two small (the smaller with an area of 1.6 km2) freshwater dammed reservoirs. Located in Sardinia (Italy) and Crete (Greek), respectively, Mulargia and Aposelemis represent vital resources to supply drinking water in downstream valleys. A total of 400 cloud-free satellite images were turned into information on water quality by using an image processing chain implementing physically based methods for retrieving chlorophyll-a concentration (Chl-a), turbidity, Secchi disk depth (SDD) and surface water temperature. These estimates have been successfully validated (the lower Pearson correlation r was 0.88 for Chl-a) with 23 match-ups of in situ and satellite data. Results of the multi-temporal analyses showed a decrease of SDD due to the increase of Chl-a in Aposelemis or an increase of turbidity in Mulargia. For both freshwater reservoirs, the satellite-derived trophic state index assigned both lakes to mesotrophic conditions. The results finally suggested the effectiveness of S2 and Landsat in increasing, for the latest investigated years, the frequency of observations.

The relatively high spatial resolution, short revisit time and red-edge spectral band (705 nm) of the ESA Sentinel-2 Multi Spectral Imager makes this sensor attractive for monitoring water quality of coastal and inland waters. Reliable atmospheric correction is essential to support routine retrieval of optically active substance concentration from water-leaving reflectance. In this study, six publicly available atmospheric correction algorithms (Acolite, C2RCC, iCOR, l2gen, Polymer and Sen2Cor) are evaluated against above-water optical in situ measurements, within a robust methodology, in two optically diverse coastal regions (Baltic Sea, Western Channel) and from 13 inland waterbodies from 5 European countries with a range of optical properties. The total number of match-ups identified for each algorithm ranged from 1059 to 1668 with 521 match-ups common to all algorithms. These in situ and MSI match-ups were used to generate statistics describing the performance of each algorithm for each respective region and a combined dataset. All ACs tested showed high uncertainties, in many cases >100% in the red and >1000% in the near-infra red bands. Polymer and C2RCC achieved the lowest root mean square differences (~0.0016 sr−1) and mean absolute differences (~40–60% in blue/green bands) across the different datasets. Retrieval of blue-green and NIR-red band ratios indicate that further work on AC algorithms is required to reproduce the spectral shape in the red and NIR bands needed to accurately retrieve the chlorophyll-a concentration in turbid waters.

A time series of multi-spectral optical satellite data covering three years (2016-2018), acquired from the satellites of the Sentinel-2 constellation managed by the European Space Agency (ESA) and the EU Copernicus program, with cloud cover above 50% on Lake Mezzola were discarded has been gathered and processed. In addition, hydrological and meteorological parameters (temperature, incoming radiation, precipitation and water level) were retrieved from sampling stations located nearby the study area, and an in situ survey has been carried out (26 September 2018) for documenting the macrophyte conditions in the southern portion of the lake in terms of species presence, density, phenological stage, and traces of impact. The analysis of time series of Sentinel-2 derived maps have shown that both submerged and riparian macrophyte communities of Lake Mezzola and Pian di Spagna wetland were impacted by increased turbidity and sediment transport due to the August 2017 landslide events. Submerged vegetation of the southern part of the lake has exhibited a decrement in 2018, compared to previous years, in terms of total area covered and plant density, together with some signs of shifts in community composition in the littoral area. Riparian helophytes instead have shown evidence of stress during the growing season following the landslide, translated into a delay in green-up for 2018 season, i.e. reaching WAVI = 0.3, varying between 10 and 40 days compared to previous years. Although last year has shown and unusually cold early Spring in North of Italy, the late development of riparian reed beds in 2018 is not attributable only to this weather anomaly, since terrestrial reeds of Pian di Spagna wetland did not show the same growth delay from time series of WAVI scores.

Our main objectives were to map the distribution of SAV in the southern part of the Lake Iseo (a deep subalpine lake in Northern Italy) in the period 2015-2017, and to evaluate its spatiotemporal variations and the possible factors of change. Specifically, we focused our attention to the bathymetric layer between 0 and 10 m of depth dominated by Vallisneria spiralis, Najas marina and Ceratophyllum demersum. To the aim 17 Sentinel-2A/B images, at 10m spatial resolution, were atmospherically corrected through the radiative transfer code 6SV to produce the Remote Sensing Reflectance (RRS) that were then used as input of the code BOMBER (Bio-Optical Model-Based tool for Estimating water quality and bottom properties from Remote sensing images) for estimating the substrate type and coverage. The results show that the southern part of Lake Iseo is characterized by significant coverage of SAV: between 0 and 5 meters deep there are the major coverings, which decrease with increasing depth, moreover the spatial analysis has shown that close to the coast there are mainly sparse macrophytes, while dense macrophytes are usually located between 10 and 50 meters from the coast line. The temporal analysis showed a decrease in the area of SAV between 2015 and 2017, equal to 19% of the rate of coverage of the bottom. Decrease that is also confirmed by the presence of floating macrophyte stands on the surface of water.

[object Object]Satellite remote estimates of phycocyanin (PC) have become valuable for monitoring the quality of inland waters affected by harmful cyanobacterial blooms. In this study, we developed an algorithm for mapping turbidity as a proxy of PC content through Landsat 8 Operational Land Imager (OLI) data and in situ measurements. The chosen study site is Karaoun Reservoir, in Lebanon, a hypereutrophic freshwater body where turbidity is mostly driven by cyanobacteria. Satellite images were corrected for atmospheric effects with the 6S (Second Simulation of the Satellite Signal in the Solar Spectrum) code which proved to be more accurate than the DOS (Dark Object Subtraction) approach with R = 0.98 and R = 0.5, respectively. A strong relationship was found between turbidity and PC measurements (R = 0.92, R2 = 0.86), as well as between turbidity and the ratio of band 5 to band 4 of the OLI (R = 0.88, R2 = 0.77). Results reveal a promising performance of the algorithm for predicting PC concentrations with high correlations determined through simple linear regression analysis for both the calibration (R = 0.92, R2 = 0.85) and validation (R = 0.88, R2 = 0.78) periods. An application of the approach to a set of historical Landsat images revealed a time series of cyanobacterial bloom occurrence with high variation in surface area at the study site. The algorithm is considered to be suitable for retrieving cyanobacteria in highly eutrophic waters dominated by cyanobacteria where turbidity is mostly a function of the latter. This approach will improve monitoring cyanobacterial blooms on a spatial and timely basis.

An intercomparison of radiance and irradiance ocean color radiometers (the second laboratory comparison exercise--LCE-2) was organized within the frame of the European Space Agency funded project Fiducial Reference Measurements for Satellite Ocean Color (FRM4SOC) May 8-13, 2017 at Tartu Observatory, Estonia. LCE-2 consisted of three sub-tasks: (1) SI-traceable radiometric calibration of all the participating radiance and irradiance radiometers at the Tartu Observatory just before the comparisons; (2) indoor, laboratory intercomparison using stable radiance and irradiance sources in a controlled environment; (3) outdoor, field intercomparison of natural radiation sources over a natural water surface. The aim of the experiment was to provide a link in the chain of traceability from field measurements of water reflectance to the uniform SI-traceable calibration, and after calibration to verify whether different instruments measuring the same object provide results consistent within the expected uncertainty limits. This paper describes the third phase of LCE-2: The results of the field experiment. The calibration of radiometers and laboratory comparison experiment are presented in a related paper of the same journal issue [1]. Compared to the laboratory comparison, the field intercomparison has demonstrated substantially larger variability between freshly calibrated sensors, because the targets and environmental conditions during radiometric calibration were different, both spectrally and spatially. Major differences were found for radiance sensors measuring a sunlit water target at viewing zenith angle of 139° because of the different fields of view. Major differences were found for irradiance sensors because of imperfect cosine response of diffusers. Variability between individual radiometers did depend significantly also on the type of the sensor and on the specific measurement target. Uniform SI traceable radiometric calibration ensuring fairly good consistency for indoor, laboratory measurements is insufficient for outdoor, field measurements, mainly due to the different angular variability of illumination. More stringent specifications and individual testing of radiometers for all relevant systematic effects (temperature, nonlinearity, spectral stray light, etc.) are needed to reduce biases between instruments and better quantify measurement uncertainties.

L'obiettivo principale del progetto Interreg Italia-Svizzera SIMILE (Sistema Informativo per il Monitoraggio Integrato dei Laghi insubrici e dei loro Ecosistemi) è quello di supportare la presa di decisioni e la definizione di politiche di gestione dei laghi insubrici tramite un sistema informativo avanzato basato su dati provenienti da sistemi di monitoraggio innovativi.

Imaging spectrometry of non-oceanic aquatic ecosystems has been in development since the late 1980s when the first airborne hyperspectral sensors were deployed over lakes. Most water quality management applications were, however, developed using multispectral mid-spatial resolution satellites or coarse spatial resolution ocean colour satellites till now. This situation is about to change with a suite of upcoming imaging spectrometers being deployed from experimental satellites or from the International Space Station. We review the science of developing applications for inland and coastal aquatic ecosystems that often are a mixture of optically shallow and optically deep waters, with gradients of clear to turbid and oligotrophic to hypertrophic productive waters and with varying bottom visibility with and without macrophytes, macro-algae, benthic micro-algae or corals. As the spaceborne, airborne and in situ optical sensors become increasingly available and appropriate for aquatic ecosystem detection, monitoring and assessment, the science-based applications will need to be further developed to an operational level. The Earth Observation-derived information products will range from more accurate estimates of turbidity and transparency measures, chlorophyll, suspended matter and coloured dissolved organic matter concentration, to more sophisticated products such as particle size distributions, phytoplankton functional types or distinguishing sources of suspended and coloured dissolved matter, estimating water depth and mapping types of heterogeneous substrates. We provide an overview of past science, current state of the art and future directions so that early career scientists as well as aquatic ecosystem managers and associated industry groups may be prepared for the imminent deluge of imaging spectrometry data.

Lakes are inestimable renewable natural resources that are under significant pressure by human activities. Monitoring lakes regularly is necessary to understand their dynamics and the drivers of these dynamics to support effective management. Remote sensing by satellite sensors offers a significant opportunity to increase the spatiotemporal coverage of environmental monitoring programs for inland waters. Lake color is a water quality attribute that can be remotely sensed and is independent of the sensor specifications and water type. In this study we used the Multispectral Imager (MSI) on two Sentinel-2 satellites to determine the color of water of 170 Italian lakes during two periods in 2017. Overall, most of the lakes appeared blue in spring and green-yellow in late summer, and in particular, we confirm a blue-water status of the largest lakes in the subalpine ecoregion. The color and its seasonality are consistent with characteristics determined by geomorphology and primary drivers of water quality. This suggests that information about the color of the lakes can contribute to synoptic assessments of the trophic status of lakes. Further ongoing research efforts are focused to extend the mapping over multiple years.

Climate change has increased the temperature and altered the mixing regime of high-value lakes in the subalpine region of Northern Italy. Remote sensing of chlorophyll-a can help provide a time series to allow an assessment of the ecological implications of this. Non-parametric multiplicative regression (NPMR) was used to visualize and understand the changes that have occurred between 2003–2018 in Lakes Garda, Como, Iseo, and Maggiore. In all four deep subalpine lakes, there has been a disruption from a traditional pattern of a significant spring chlorophyll-a peak followed by a clear water phase and summer/autumn peaks. This was replaced after 2010–2012, with lower spring peaks and a tendency for annual maxima to occur in summer. There was a tendency for this switch to be interspersed by a two-year period of low chlorophyll-a. Variables that were significant in NPMR included time, air temperature, total phosphorus, winter temperature, and winter values for the North Atlantic Oscillation. The change from spring to summer chlorophyll-a maxima, relatively sudden in an ecological context, could be interpreted as a regime shift. The cause was probably cascading effects from increased winter temperatures, reduced winter mixing, and altered nutrient dynamics. Future trends will depend on climate change and inter-decadal climate drivers.

A first synoptic and trans-domain overview of plankton dynamics was conducted across the aquatic sites belonging to the Italian Long-Term Ecological Research Network (LTER-Italy). Based on published studies, checked and complemented with unpublished information, we investigated phytoplankton and zooplankton annual dynamics and long-term changes across domains: from the large subalpine lakes to mountain lakes and artificial lakes, from lagoons to marine coastal ecosystems. This study permitted identifying common and unique environmental drivers and ecological functional processes controlling seasonal and long-term temporal course. The most relevant patterns of plankton seasonal succession were revealed, showing that the driving factors were nutrient availability, stratification regime, and freshwater inflow. Phytoplankton and mesozooplankton displayed a wide interannual variability at most sites. Unidirectional or linear long-term trends were rarely detected but all sites were impacted across the years by at least one, but in many case several major stressor(s): nutrient inputs, meteo-climatic variability at the local and regional scale, and direct human activities at specific sites. Different climatic and anthropic forcings frequently co-occurred, whereby the responses of plankton communities were the result of this environmental complexity. Overall, the LTER investigations are providing an unparalleled framework of knowledge to evaluate changes in the aquatic pelagic systems and management options.

This study presents a first assessment of the Top-Of-Atmosphere (TOA) radiances measured in the visible and near-infrared (VNIR) wavelengths from PRISMA (PRecursore IperSpettrale della Missione Applicativa), the new hyperspectral satellite sensor of the Italian Space Agency in orbit since March 2019. In particular, the radiometrically calibrated PRISMA Level 1 TOA radiances were compared to the TOA radiances simulated with a radiative transfer code, starting from in situ measurements of water reflectance. In situ data were obtained from a set of fixed position autonomous radiometers covering a wide range of water types, encompassing coastal and inland waters. A total of nine match-ups between PRISMA and in situ measurements distributed from July 2019 to June 2020 were analysed. Recognising the role of Sentinel-2 for inland and coastal waters applications, the TOA radiances measured from concurrent Sentinel-2 observations were added to the comparison. The results overall demonstrated that PRISMA VNIR sensor is providing TOA radiances with the same magnitude and shape of those in situ simulated (spectral angle dierence, SA, between 0.80 and 3.39; root mean square dierence, RMSD, between 0.98 and 4.76 [mW m􀀀2 sr􀀀1 nm􀀀1]), with slightly larger dierences at shorter wavelengths. The PRISMA TOA radiances were also found very similar to Sentinel-2 data (RMSD < 3.78 [mW m􀀀2 sr􀀀1 nm􀀀1]), and encourage a synergic use of both sensors for aquatic applications. Further analyses with a higher number of match-ups between PRISMA, in situ and Sentinel-2 data are however recommended to fully characterize the on-orbit calibration of PRISMA for its exploitation in aquatic ecosystem mapping.

Monitoring freshwater and wetland systems and their response to stressors of natural or anthropogenic origin is critical for ecosystem conservation.A multi-temporal set of 87 images acquired by Sentinel-2 satellites over three years (2016-2018) provided quantitative information for assessing the temporal evolution of key ecosystem variables in the perialpine Lake Mezzola (northern Italy), which was suffered from the impacts of a massive landslide that took place upstream of the lake basin in summer 2017.Sentinel-2 derived products revealed an increase in lake turbidity triggered by the landslide that amounted to twice the average values scored in the years preceding and following the event. Hotspots of turbidity within the lake were in particular highlighted. Moreover both submerged and riparian vegetation showed harmful impacts due to sediment deposition. A partial loss of submerged macrophyte cover was found, with delayed growth and a possible community shift in favor of species adapted to inorganic substrates. Satellite-derived seasonal dynamics showed that exceptional sediment load can overwrite climatic factors in controlling phenology of riparian reed beds, resulting in two consecutive years with shorter than normal growing season, and roughly 20% drop in productivity according to spectral proxies: compared to 2016, senescence came earlier by around 20 days on average in 2017 season, and green-up was delayed by up to 50 days (20 days, on average) in 2018, following the landslide.The approach presented could be easily implemented for continuous monitoring of similar ecosystems subject to external pressures with periods of high sediment loads.

Earth Observation (EO) is a cost-effective tool for obtaining spatial information on the water quality status and processes taking place in seas and lakes. In particular, recent and expected advances in EO technology broaden the perspectives of monitoring toward the identification and quantification of plankton groups including cyanobacteria. The capability to detect cyanobacteria bloom is important because they can develop toxins hence presenting a range of amenity, water quality and treatment problems, as well as hazards to human health and ecological equilibrium. The problem is especially acute in the Baltic Sea where cyanobacterial blooms occur every summer covering areas of more than 100.000 km2 and washing upon beaches during the summer holiday season. With respect to lakes, they frequently exhibit cyanobacterial blooms, with an increasing occurrence presumably in correlation with eutrophication and climate change, which has resulted in economic loss and considerable public interest in this phenomenon. In such a frame, CYAN IS-WAS, aims to develop regional algorithms for detecting cyanobacterial blooms from both satellite and airborne data, and thence use those algorithms for mapping cyanobacteria during time, and thence try to derive the main environmental/ecological variables which cause the development of cyanobacteria. The cooperation activities are carried out by sharing EO data, methods and by performing joint field campaigns. The project involves training of PhD and MSc students of both countries for giving them experience in EO data analysis. The project is divulgated throughout a series of events, including scientific symposium/workshop and with scientific publications in ISI journals. The exploitation of EO data allowed us to identify the occurrence, blooming, persistence and degradation of cyanobacteria communities in selected Swedish and Italian aquatic ecosystems. The main scientific findings are:  an extremely high variability in cyanobacteria optical properties was found, thus enhancing the great importance of tuning the EO based algorithms depending on study area features;  hyperspectral images, appropriately corrected, calibrated and validated, enabled the mapping of cyanobacteria blooms; some advantage of using radar data was also demonstrated for mapping abundant blooms in presence of clouds;  comparative studies on marine (Baltic vs. north Adriatic) and freshwater (Vänern vs. subalpine deep lakes, Trasimeno and Mantova) have been accomplished thanks to joint field campaign and satellite images analysis;  Nitrogen limitation in summer in the Baltic Sea proper is a decisive factor contributing to the development of blooms of filamentous cyanobacteria occurring during summer; EO work in the NW Baltic Sea has shown that we can derive chlorophyll concentrations in Baltic Sea coastal waters reliably from MERIS data (Hervey et al. 2013);  the amount of suspended solids transported by Po river (but also by other secondary rivers as Adige and Tagliamento) into the north Adriatic Sea, reduces the available light that can be used by phytoplankton component hence also hindering the growth of cyanobacteria

Phytoplankton blooms in internal water bodies are an unpleasant sight that often emerges on top like a layer of foam containing high concentrations of toxins (scum event). Monitoring the concentration of algae and the occurrence of scum in lakes and lagoons has become a topic of interest for management and science. Optical remote sensing is a validated tool but unfortunately it is highly hindered by clouds. For regions with frequent cloud cover, such as the Baltic region, this means loss of data, which limits the purpose of sensing to spatially and temporally characterize any scum for a comprehensive ecological analysis. The aim of this paper is to investigate whether the use of synthetic aperture radar (SAR) images can compensate for the weaknesses of optical images for cyanobacteria bloom monitoring purposes in the event of cloudy skies. A &ldquo, ready to use&rdquo, approach to detect cyanobacteria bloom in the Curonian Lagoon based on the level 2 ocean product of Sentinel-1 images is proposed. This method is empirically validated for the images of summer/autumn 2018 of the Curonian Lagoon.

Thanks to the improved spatial and temporal resolution of new generation Earth Observation missions, such as Landsat 8 and Sentinel-2, the potential of remote sensing techniques in mapping land surface phenology of terrestrial biomes can now be tested in inland water systems.We assessed the capabilities of dense time series of medium resolution satellite data to deliver quantitative information about macrophyte phenology metrics, focusing on three temperate European shallow lakes with connected wetlands, located in Italy, France and Romania.Leaf area index (LAI) maps for floating and emergent macrophyte growth forms were derived from semi-empirical regression modelling based on the best performing spectral index, with an error level around 0.11 m2 m-2. Phenology metrics were computed from LAI time series using TIMESAT code and used to analyse macrophyte seasonal dynamics in terms of spatial patterns and species-dependent variability. Peculiar patterns of autochthonous and allochthonous species seasonality across the three study areas were related to the environmental characteristics of each area in terms of ecological and hydrological conditions.In addition, the influence of satellite dataset characteristics – i.e. cloud cover thresholding, temporal resolution and missing acquisitions – on phenology timing metrics retrieval was assessed. Results have shown that with full resolution (5-day revisit) time series, cloud cover can bias phenology timing metrics by less than 2 days, and that reducing temporal resolution to 15 days (similar to Landsat revisit) still allows for mapping the start and peak of macrophyte growth with an error level around 2–3 days.

Farming of shellfish and seaweeds is a tested tool for mitigating eutrophication consequences in coastal environments, however as many other marine economic activities it should be a subject of marine spatial planning for designating suitable sites. The present study proposes site selection framework for provisional zebra mussel farming in a eutrophic lagoon ecosystem, aimed primarily at remediation purposes. GIS-based multi-criteria approach was applied, combining data from empirical maps, numerical models and remote sensing to estimate suitability parameters. Site selection and prioritisation of suitable areas considered 15 environmental and socio-economic criteria, which contributed to 4 optimisation models (settlement, growth and survival of mussels, environmental and socio-economic) and 3 predefined scenarios representing provisional goals of mussel cultivation: spat production, biomass production and bioremediation. The relative importance of each criterion was assessed utilizing the Analytical Hierarchy Process. Site suitability index was calculated and the final result of the site selection analysis was summarized for 3 scenarios and overall suitability map. Four suitability classes (unsuitable, least, moderately and most suitable) were applied, and 3 most suitable zones for provisional zebra mussel cultivation with 12 candidate sites were selected accordingly. The integrated approach presented in this study can be adjusted for designating zebra mussel farming sites in other estuarine lagoon ecosystems, or cultivation of other mussel species for bioremediation purposes. The analytical framework and the workflow designed in this study are also adoptable for addressing other aquaculture-related spatial planning issues.