LAUSR

Abstract Eutrophic reservoirs are characterized by excessive presence of plant and algal growth due to favourable environmental conditions, temperature, light and nutrients. Human activities accelerate this phenomenon and provoke dramatic changes to the aquatic ecosystems. The monitoring of water quality of these ecosystems and the study of the effects they have on the environment demand a large amount of spatial and temporal information, which is almost exclusively provided by Earth Observations (EO). This study uses a large temporal series of Sentinel-2 (S2; 2016 till 2019) images to characterize the temporal and spatial distribution of chlorophyll-a [Chl-a] in San Roque Reservoir, Cordoba Province, Argentina. A robust method that combines empirical modelling of [Chl-a] and data mining analysis is employed. Model results showed significant fit (R2 = 0.77) between [Chl-a] measured in the reservoir and the ratio between the NIR and red bands of S2. An analysis of spatio-temporal patterns demonstrated that [Chl-a] distribution in San Roque is complex and influenced by seasonal changes, aeolian forces, hydrodynamic flows, bathymetry, water levels, and pollution sources. The study also found a correlation between algae bloom events and areas with extreme levels of [Chl-a] (>850 mg/m3) in the water body. Additionally, advanced data mining tools such as slope analysis and spatial anomalies indexes, identified regions in the reservoir where water quality had improved or deteriorated. The results show the added value of using large Sentinel-2 data series to assess the concentration of Chlorophyll-a in eutrophic reservoirs over a variety of spatial and temporal scales.