It is common in estuarine waters to place fixed monitoring stations, with the advantages of easy maintenance and continuous measurements. These two features make fixed monitoring stations indispensable for understanding the optical complexity of estuarine waters and enable an improved quantification of uncertainties in satellite-derived water quality variables. However, comparing the point-scale measurements of stationary monitoring systems to time-snapshots of satellite pixels suffers from additional uncertainties related to temporal/spatial discrepancies. This research presents a method for validating satellite-derived water quality variables with the continuous measurements of a fixed monitoring station in the Ems Dollard estuary on the Dutch-German borders. The method has two steps; first, similar in-situ measurements are grouped. Second, satellite observations are upscaled to match these point measurements in time and spatial scales. The upscaling approach was based on harmonizing the probability distribution functions of satellite observations and in-situ measurements using the first and second moments. The fixed station provided a continuous record of data on suspended particulate matter (SPM) and chlorophyll-a (Chl-a) concentrations at 1 min intervals for 1 year (2016–2017). Satellite observations were provided by Sentinel-2 (MultiSpectral Instrument, S2-MSI) and Sentinel-3 (Ocean and Land Color Instrument, S3-OLCI) sensors for the same location and time of in-situ measurements. Compared to traditional validation procedures, the proposed method has improved the overall fit and produced valuable information on the ranges of goodness-of-fit measures (slope, intercept, correlation coefficient, and normalized root-mean-square deviation). The correlation coefficient between measured and derived SPM concentrations has improved from 0.16 to 0.52 for S2-MSI and 0.14 to 0.84 for S3-OLCI. For the Chl-a matchup, the improvement was from 0.26 to 0.82 and from 0.14 to 0.63 for S2-MSI and S3-OLCI, respectively. The uncertainty in the derived SPM and Chl-a concentrations was reduced by 30 and 23% for S2-SMI and by 28 and 16% for S3-OLCI. The high correlation and reduced uncertainty signify that the matchup pairs are observing the same fluctuations in the measured variable. These new goodness-of-fit measures correspond to the results of the performed sensitivity analysis, previous literature, and reflect the inherent accuracy of the applied derivation model.

Satellite data from the Climate Change Initiative (CCI) lakes project were used to examine the influence of climate on chlorophyll-a (Chl-a). Nonparametric multiplicative regression and machine learning were used to explain Chl-a concentration trend and dynamics. The main parameters of importance were seasonality, interannual variation, lake level, water temperature, the North Atlantic Oscillation, and antecedent rainfall. No evidence was found for an earlier onset of the summer phytoplankton bloom related to the earlier onset of warmer temperatures. Instead, a curvilinear relationship between Chl-a and the temperature length of season above 20°C (LOS) was found with longer periods of warmer temperature leading to blooms of shorter duration. We suggest that a longer period of warmer temperatures in the summer may result in earlier uptake of nutrients or increased calcite precipitation resulting in a shortening of the duration of phytoplankton blooms. The current scenario of increasing LOS of temperature with climate change may lead to an alteration of phytoplankton phenological cycles resulting in blooms of shorter duration in lakes where nutrients become limiting. Satellite-derived information on lake temperature and Chl-a concentration proved essential in detecting trends at appropriate resolution over time.

Under the current Anthropocene Epoch there is an urgent need to deliver high‐quality data, information and knowledge to the decision-making process for a sustainable management of environmental concerns, in particular for inland water. Most literature address the advantages brought by remote sensing (RS) techniques in operational monitoring and management of lakes. In the present work, optical RS is applied to a complex ecosystem, the turbid eutrophic shallow Lake Trasimeno (Italy). A first example of RS application addresses the use of high frequency spectroradiometric measurements collected by a WISPstation to retrieve intra-inter daily and seasonal dynamics of chlorophyll-a and phycocyanin. A second section focuses on long term trends of water quality by means of satellite data time series for the whole lake surface. Then we exploit the latest generation of hyperspectral satellite images (PRISMA and DESIS) utilizing the high spectral resolution and improving the accuracy of estimated lake water quality. Finally, high spatial resolution satellite data is used for a finer scale mapping of bottom substrates. Application of these techniques improved scientific understanding on the timing, composition and distribution of phytoplankton blooms, the role of nutrients and climate drivers as well as changes in the extent and composition of aquatic plants.

The frequency of heatwave events in Europe is increasing as a result of climate change. This can have implications for the water quality and ecological functioning of aquatic systems. We deployed three spectroradiometer WISPstations at three sites in Europe (Italy, Estonia, and Lithuania/Russia) to measure chlorophyll-a at high frequency. A heatwave in July 2019 occurred with record daily maximum temperatures over 40 °C in parts of Europe. The effects of the resulting storm that ended the heatwave were more discernable than the heatwave itself. Following the storm, chlorophyll-a concentrations increased markedly in two of the lakes and remained high for the duration of the summer while at one site concentrations increased linearly. Heatwaves and subsequent storms appeared to play an important role in structuring the phenology of the primary producers, with wider implications for lake functioning. Chlorophyll-a peaked in early September, after which a wind event dissipated concentrations until calmer conditions returned. Synoptic coordinated high frequency monitoring needs to be advanced in Europe as part of water management policy and to improve knowledge on the implications of climate change. Lakes, as dynamic ecosystems with fast moving species-succession, provide a prism to observe the scale of future change.

This study presents an assessment of PRISMA (PRecursore IperSpettrale della Missione Applicativa) for water applications, by including a general description of the mission and by focusing on the standard Level 1 (L1) and Level 2 (L2) products acquired on different aquatic systems. A preliminary analysis on the estimation of signal-to-noise ratio (SNR) from L1 PRISMA products in the visible near infrared spectra (VISNIR) is indicating values comparable to Sentinel-2 MSI from literature, apart at short wavelengths where PRISMA SNR is lower. Few examples of L2 products in terms of water reflectance are also presented to encourage the exploitation of PRISMA for aquatic ecosystem mapping. The results of this study are indicating that even if some applications might be developed with the standard L2 products, an ad-hoc processing might be necessary to include the specific requirements of atmospheric correction of water targets. Further analyses with a higher number of imagery data are however recommended to fully characterize the PRISMA products.

Lakes are integrators of environmental and climatic changes occurring within their contributing basins. Understanding the complex behavior of lakes in a changing environment is essential to effective water resource management and mitigation of climate change effects. The ESA CCI Lakes is a multi-disciplinary project (https://climate.esa.int/en/projects/lakes) combining expertise to exploit data to create the largest and longest possible consistent, global record of five lake climate variables: lake water level, extent, temperature, surface-leaving reflectance, and ice cover. The phase 1 version of the database covers 250 globally distributed lakes with temporal coverage, depending on parameter, ranging from 1992 up to 2019. The dataset is planned to expand to 2000 lakes in the second phase. The distribution of the dataset will be introduced over space and time. The potential of the dataset and in particular of data records on chlorophyll-a concentrations, is explored for Lake Trasimeno, a shallow eutrophic lake of central Italy which is a specific case study of the lakes CCI project included in the Long-Term Ecosystem Research (LTER) network. In situ measurements from LTER were used to evaluate satellite products as well as to complete the CCI data record. Meteo-climatic data were extracted to analyze the interrelationships between the trend in water parameters and climate factors. An in situ WISPstation sensor was also used to provide high frequency (every 15 minutes) information on chlorophyll-a and phycocyanin concentration for last two years. We used Artificial Intelligence (AI) and Non-Parametric Multiplicative Regression (NPMR) techniques to analyze the data. Chlorophyll-a in Lake Trasimeno was dominated by a summer bloom consistently initiating in July and typically peaking in early September and was largely predicted by the time variable - accounting for 87% of feature importance. The North Atlantic Oscillation (NAO) was the next most important variable (4% feature importance) corroborated by NPMR and shown to be largely important during early to mid-September when a positive NAO, associated with high pressure and warm sunny weather, led to an increase in chlorophyll-a concentrations. Regional climatic indices as well as the more obvious nutrient drivers of algal blooms should therefore be considered in lake management. Comparing the high frequency WISPstation data (2018-2020) with the CCI dataset allows for detailed cross validation. Interestingly some of the rapid fluctuations visible from the satellite record that may have been interpreted as noise are supported by the in situ data. In addition, utilizing the phycocyanin results from the WISPstation showed, in near real time, how cyanophytes played a key role in the sudden increases and declines in chlorophyll-a in mid to late summer. Coupling climatic indices, nutrient concentrations and near real time phycocyanin concentrations could be indispensable to the management of blooms in high value recreational lakes such as Trasimeno.

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 difference, SA, between 0.80 and 3.39; root mean square difference, RMSD, between 0.98 and 4.76 [mW m−2 sr−1 nm−1]), with slightly larger differences 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.

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 ‘day of year’ 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–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.

The EU funded “AQUAculture USEr driven operational Remote Sensing information services project” (AQUAUSERS grant number 607325) is a user driven project for the aquaculture industry that aims at providing this industry with relevant and timely information based on the most recent satellite data and innovative optical insitu measurements. The Water Insight Spectrometer (WISP-3) is a hand held instrument which can provide measurements of the optical parameters Chlorophyll-a (Chl-a), Total Suspended Matter (TSM), Coloured Dissolved Organic Matter (CDOM), and the Spectral Diffuse Attenuation Coefficient (Kd). Sampling campaigns were carried out between March 2014 and September 2015, to collect water samples at the same time as taking optical reading from the WISP-3 at an offshore aquaculture site off Sagres on the SW Portugal, operated by Finisterra Lda, one of the “users” in the project. The estimates from the WISP-3 for Chla and TSM have been compared with in-situ measurements from the water samples for these two variables, with the objective of calibrating the algorithms used by the WISP-3 for estimation of Chla and TSM. At a later stage in the project, it is expected that WISP-3 readings can be related to remote sensing products developed from the Ocean Land Coloured Instrument (OLCI) from the Sentinel-3 satellite. The key purpose of AQUAUsers is to develop, in collaboration with “users” from the aquaculture industry, a mobile phone application (app) that collates satellite information on optical water quality and temperature together with in-situ data of these variables to develop a decision support system for daily management of the aquaculture.

Citizen observations, environmental data gathered by volunteers without professional observation capabilities, have been extensively used for Finnish water quality monitoring tasks. Recently, mobile smartphones and their digital cameras have enabled more direct measurements of transparency related water quality variables with inexpensive technology suitable for volunteers. These "Secchi3000" ideas of measurement technology by viewing known targets through multiple viewing path lengths within measured water were used to develop an iQwtr measurement device for water transparency related citizen observations. Past experiences with crowdsourcing and use of in situ water transparency data with satellite observations are reviewed and future challenges outlined.

With global population expansion, the demand for high-quality protein is rising dramatically, and fish farming is gaining importance to ensure food security. Aquaculture is the fastest growing food production sector worldwide. Environmental conditions determine the growth and health of the produced species, while the production often releases large amounts of nutrients to the surrounding environment. Therefore, monitoring is needed on several levels. However, available data are often disparate, inconsistent in coverage and of unknown quality. To support the growth of efficient and sustainable aquaculture production, the FP7 AQUAUSERS project (www.aqua-users.eu) aims at providing the aquaculture industry with userrelevant and timely information based on the most up-to-date satellite data and innovative optical in situ measurements.