Coastal lagoons are transitional ecosystems with complex spatial and temporal variability. Remote sensing tools are essential for monitoring and unveiling their variability. Turbidity is a water quality parameter used for studying eutrophication and sediment transport. The objective of this research is to analyze the monthly turbidity pattern in a shallow coastal lagoon along two years with different precipitation regimes. The selected study area is the Albufera de Valencia lagoon (Spain). For this purpose, we used Sentinel 2 images and in situ data from the monitoring program of the Environment General Subdivision of the regional government. We obtained Sentinel 2A and 2B images for years 2017 and 2018 and processed them with SNAP software. The results of the correlation analysis between satellite and in situ data, corroborate that the reflectance of band 5 (705 nm) is suitable for the analysis of turbidity patterns in shallow lagoons (average depth 1 m), such as the Albufera lagoon, even in eutrophic conditions. Turbidity patterns in the Albufera lagoon show a similar trend in wet and dry years, which is mainly linked to the irrigation practice of rice paddies. High turbidity periods are linked to higher water residence time and closed floodgates. However, precipitation and wind also play an important role in the spatial distribution of turbidity. During storm events, phytoplankton and sediments are discharged to the sea, if the floodgates remain open. Fortunately, the rice harvesting season, when the floodgates are open, coincides with the beginning of the rainy period. Nevertheless, this is a lucky coincidence. It is important to develop conscious management of floodgates, because having them closed during rain events can have several negative effects both for the lagoon and for the receiving coastal waters and ecosystem. Non-discharged solids may accumulate in the lagoon worsening the clogging problems, and the beaches next to the receiving coastal waters will not receive an important load of solids to nourish them.

Developing indicators to monitor environmental change in wetlands with the aid of Earth Observation Systems can help to obtain spatial data that is not feasible with in situ measures (e.g., flooding patterns). In this study, we aim to test Sentinel-2A/B images suitability for detecting small water bodies in wetlands characterized by high diversity of temporal and spatial flooding patterns using previously published indices. For this purpose, we used medium spatial resolution Sentinel-2A/B images of four representative coastal wetlands in the Valencia Region (East Spain, Mediterranean Sea), and on three different dates. To validate the results, 60 points (30 in water areas and 30 in land areas) were distributed randomly within a 20 m buffer around the border of each digitized water polygon for each date and wetland (600 in total). These polygons were mapped using as a base map orthophotos of high spatial resolution. In our study, the best performing index was the NDWI. Overall accuracy and Kappa index results were optimal for −0.30 threshold in all the studied wetlands and dates. The consistency in the results is key to provide a methodology to characterize water bodies in wetlands as generalizable as possible. Most studies developed in wetlands have focused on calculating global gain or loss of wetland area. However, inside of wetlands which hold protection figures, the main threat is not necessarily land use change, but rather water management strategies. Applying Sentinel-2A/B images to calculate the NDWI index and monitor flooded area changes will be key to analyse the consequence of these management actions.

Phytoplankton blooms are sporadic events in time and are isolated in space. This complex phenomenon is produced by a variety of both natural and anthropogenic causes. Early detection of this phenomenon, as well as the classification of a water body under conditions of bloom or non-bloom, remains an unresolved problem. This research proposes the use of Inherent Optical Properties (IOPs) in optically complex waters to detect the bloom or non-bloom state of the phytoplankton community. An IOP index is calculated from the absorption coefficients of the colored dissolved organic matter (CDOM), the phytoplankton (phy) and the detritus (d), using the wavelength (λ) 443 nm. The effectiveness of this index is tested in five bloom events in different places and with different characteristics from Mexican seas: 1. Dzilam (Caribbean Sea, Atlantic Ocean), a diatom bloom (Rhizosolenia hebetata); 2. Holbox (Caribbean Sea, Atlantic Ocean), a mixed bloom of dinoflagellates (Scrippsiella sp.) and diatoms (Chaetoceros sp.); 3. Campeche Bay in the Gulf of Mexico (Atlantic Ocean), a bloom of dinoflagellates (Karenia brevis); 4. Upper Gulf of California (UGC) (Pacific Ocean), a diatom bloom (Coscinodiscus and Pseudo-nitzschia) and 5. Todos Santos Bay, Ensenada (Pacific Ocean), a dinoflagellate bloom (Lingulodinium polyedrum). The diversity of sites show that the IOP index is a suitable method to determine the phytoplankton bloom conditions.

The baseline of a specific variable defines the average behavior of that variable and it must be built from long data series that represent its spatial and temporal variability. In coastal and marine waters, phytoplankton can produce blooms characterized by a wide range of total cells number or chlorophyll a concentration. Classifying a phytoplankton abundance increase as a bloom depends on the species, the study area and the season. The objective of this study was to define the baseline of satellite absorption coefficients in Todos Santos Bay (Baja California, Mexico) to determine the presence of phytoplankton blooms based on the satellite inherent optical properties index (satellite IOP index). Two field points were selected according to historical bloom reports. To build the baseline, the data of phytoplankton absorption coefficients ( a p h y , G I O P ) and detritus plus colored dissolved organic matter (CDOM) ( a d C D O M , G I O P ) from the generalized inherent optical property (GIOP) satellite model of the NASA moderate resolution imaging spectroradiometer (MODIS-Aqua) sensor was studied for the period 2003 to 2016. Field data taken during a phytoplankton bloom event on June 2017 was used to validate the use of satellite products. The association between field and satellite data had a significant positive correlation. The satellite baseline detected a trend change from high values to low values of the satellite IOP index since 2010. Improved wastewater treatment to waters discharged into the Bay, and increased aquaculture of filter-feeding mollusks could have been the cause. The methodology proposed in this study can be a supplementary tool for permanent in situ monitoring programs. This methodology offers several advantages: A complete spatial coverage of the specific coastal area under study, appropriate temporal resolution and a tool for building an objective baseline to detect deviation from average conditions during phytoplankton bloom events.