## 5 Conclusions  
Our results have demonstrated the potential of remote sensing techniques to differentiate POM and PIM and thus map out the composition of suspended particles, in order to provide their spatial and temporal variations. It is important to determine the composition of TSM in the study area given that the transparency of the water is fundamentally influenced by the suspended solids, sometimes the mineral fraction rather than the organic one. In this work, with statistical significance for continental waters, 10 indices are proposed for the estimation of TSM, 10 indices for the estimation of the POM and one index for the estimation of PIM, found from data obtained in very different water bodies. Results show that the use of a single band (R\({}_{705}\) for TSM and PIM determination and R\({}_{783}\) for POM determination) can provide a robust and sensitive algorithm for these variables. The correlations presented by the use of the single band algorithms were R\({}^{2}\) = 0.7918 for TSM algorithm, R\({}^{2}\) = 0.5785 for POM algorithm and R\({}^{2}\) = 0.6302 for PIM algorithm. The normalized errors presented by these algorithms were 10.3% for TSM algorithm, 14.8% for POM algorithm and 12.2% for PIM algorithm. The single band selected algorithms have been verified after application in Sentinel-2 images and in water bodies is viable. The C2 RCC processor provides acceptable automatic results regarding TSM determination and could be an alternative to using specific algorithms. Wind speed, rainfall, human activities or soil type can affect TSM, POM and PIM changes. In future studies, a comprehensive analysis of multiple factors surrounding water bodies would be necessary to determine possible trends in variation. In particular, the application of similar sensors or more advanced sensors would assist in constructing consistent and more complete satellite-derived time series data. In order to deepen the range of application of the algorithms developed, it would be convenient to extend the investigation to a larger number of water bodies with different trophic status (lakes, ponds, reservoirs, marshes, etc.). Conceptualization and methodology, B.A., X.-S.-P., A.R.-V. and J.D. ; Data curation, P.U., X.S.-P., E.V. and B.A. ; Formal analysis, J.M.S. and E.V. ; Funding acquisition, J.M. ; Project administration, J.D. ; Writing--original draft, B.A. ; Writing--review & editing, all authors; Supervision, X.S.-P., E.V., J.D., A.R.-V. and J.M.S. All authors have read and agreed to the published version of the manuscript. This research was partially funded by the European Union-ERDF and the Ministry of Science and Innovation and the State Research Agency of Spain under project RTI2018-09865-BC51 (FLEX3L4-Advanced Products L3 and L4 for the FLEX-S3 mission) and partially funded by the GENERALITAT VALENCIANA postdoc research grant (X.S.-P) APOSTD/2020/134, the project SEQUARMON (Sentinel quality reservoirs monitoring). **Informed Consent Statement**: Not applicable. **Data Availability Statement**: The data presented in this study are available on request from the corresponding author. **Acknowledgments**: The authors acknowledge the Ebro Basin Authority for the reports to monitoring reservoirs water quality between 2016 to 2019. **Conflicts of Interest**: The authors declare no conflict of interest. **Appendix A**  
**Table A1. Summary of sampled water bodies. Abbreviations: lat. : latitude; lon. : longitude. **