The monitoring of water bio-physical parameters and the management of aquatic ecosystems are crucial to cope with the current state of inland water degradation. Not only does water quality monitoring support management decision making, it also provides vital insights to better understand changing structural and functional lake processes. Remote sensing has been widely recognized as an essential integrating technique for water quality monitoring, thanks to its capabilities to utilize both historical archive data for thousands of lakes as well as near-real time observations at multiple scales. To date, most of the applications developed for inland water have been based on multispectral and mid to coarse spatial resolution satellites, while a new generation of spaceborne imaging spectroscopy is now available, and future missions are under development. This review aims to present the exploitation of data gathered from two currently orbiting hyperspectral sensors (i.e., PRISMA and DESIS) to retrieve water quality parameters across different aquatic ecosystems, encompassing deep clear lakes and river dammed reservoirs.

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.

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.