## 4 Discussion  
The combination of field data, high spatial resolution images and modeling shows a strong efficiency in the spatiotemporal monitoring of water quality at the reservoir scale. On the other hand, the measured values of the different proposed models showed in most cases a strong correlation with those measured in the field. Three water quality parameters were selected in this study: dissolved oxygen, nitrates and Chl-a. The choice of these parameters is based on their importance in the eutrophication of fresh or coastal water [44, 45]. The most visible phenomena are the appearance in spring and summer of the green tides in coastal marine water and the water in lakes and rivers. These manifestations correspond to an ecological imbalance linked to excessive inputs of phosphorus (including in the form of phosphate PO4\({}^{3}\)-) and nitrogen (nitrate NO\({}^{3}\)-). In fact, these inputs lead to an explosion in the development of aquatic plants, which leads to an excessive local accumulation of biomass and is the cause of various undesirable effects such as impoverishment of biodiversity, visual and olfactory nuisance, inconvenience for bathing, difficulties in water treatment (drinking water), gas emissions and colonization by algae producing toxins such as certain Cyanophyceae. Several estimation models have been developed based on the multiple stepwise regression analysis, while the choice of the suitable model was based on the largest compliance index (R\({}^{2}\)) and the smallest root mean square error (RMSE). The estimation of nitrate was done by applying the model that groups bands B1, B3 and B4 with the largest R\({}^{2}\) and the smallest RMSE among all the extracted models (R\({}^{2}\) = 0.62, RMSE = 0.16 mg/L). For the estimation of dissolved oxygen, the model chosen is the one that combines the two bands B2 and B3 (with R\({}^{2}\) = 0.56 and RMSE = 0.65 mg/L). For Chl-a, the model chosen is the one that includes the bands B5, B6 and B8 (with R2 = 0.58 and RMSE= 0.07 mg/L). The choice of the bands integrated into the model was made on the basis of a statistical study that was carried out between in situ measurements and satellite data. For chlorophyll a, a correlation was obtained between the in situ measurements of this parameter and band 5 of the Sentinel-2 sensor, which is located in the 704.1 nm spectral range. This result is in agreement with the results obtained by [PERSON] [18], who used the peak reflectance between 700 and 720 nm for the estimation of this parameter. For nitrate, this study showed that the estimation of this parameter is very efficient when using the spectral interval from 442.7 to 664.6 nm (Table 4). For the estimation of the dissolved oxygen, the results show that the spectral interval of 492.4 to 559.8 nm is more appropriate (Table 4). Another work that was carried out by [PERSON] and [PERSON] [23] has shown that one of the main advantages of Sentinel-2 over Landsat-8 is the presence of the band B5 (704.1 nm) with a spatial resolution of 20 m to determine chlorophyll absorption. Eventually, these images  
Figure 8: Obtained maps of Chl-a using best model. will be useful for many aquatic water quality monitoring applications, and they can also be combined into a virtual constellation to improve temporal coverage. In Morocco, satellite images have been widely used for modeling and spatiotemporal monitoring of several environmental phenomena, but the application of satellite images in spatiotemporal monitoring of lake water quality is still not well developed. The only study is the one carried out by [PERSON] and his collaborators in 2019 [3], which aimed to map water quality parameters using Sentinel images. Indeed, the spectral interval from 559.8 to 740.5 nm for the mapping of Chl-a, the spectral interval from 832.8 to 1373.5 nm for dissolved oxygen and the spectral interval from 442.7 to 864.7 nm for nitrate had R\({}^{2}\) indices of 0.78, 0.74 and 0.67, respectively.