The Mar Menor is a Spanish coastal lagoon of great ecological and economic interest. The agricultural and tourist activities developed in the surroundings of the lagoon, together with the modifications in its channels of connection with the Mediterranean Sea, have notably affected the quality of its waters, which is altering the natural balance of the ecosystem. In this work, an analysis of the density of phytoplankton present in the lagoon between the months of May to December 2017 was carried out. The results indicate a significant increase in phytoplankton density between 2500 and 67,300 cells/mL compared to previous data of 1981 (between 10 and 500 cells/mL). Concentration of Chlorophyll-a arrives to 13 µg/L and transparency of water reduces to 1.3 m according to Secchi disk depth. The presence of Chlorophyceae, Chrysophyceae, and nanoplanktonic Cryptophyceae stands out, while species diversity drops significantly. Observing the evolution of the lagoon, we can deduce that eutrophication process could increase. To avoid this, it would be necessary to implement control measures for the use of fertilizers in nearby growing areas and to study water treatment techniques to reduce nitrogen inputs so that phytoplankton densities can decrease.

Coastal lagoons are highly productive transitional water bodies threatened by human factors and vulnerable to global climate change effects. Monitoring biophysical parameters in these ecosystems is crucial for their preservation. In this work, we used Sentinel-2 and Landsat imagery combined with in situ data to (1) develop preliminary algorithms for retrieving the Chl-a concentration and water surface temperature of six lagoons located in the Ebro Delta (NE Mediterranean Sea, Spain), and to (2) compute maps and trend lines for analysing their spatiotemporal evolution from 2015 to 2022. Our findings showed that the algorithms’ accuracy ranged from 72% to 78% and had limited potential under high Chl-a concentration regimes. Even so, they revealed the lagoons’ trophic status, usual fluctuations, and deviations of both parameters attributed to seasonal (i.e., light and temperature) and short-term physical (i.e., winds) forcing, as well as valuable spatial patterns potentially useful for conservation efforts and land use planning. Future work will focus on the acquisition of a larger in situ data sample under a range of environmental conditions to improve the algorithms’ robustness, which in turn will allow the investigation of natural and human factors controlling the dynamics of the two investigated parameters.