Knowledge of inland water quality and riverine inputs to oceans is fundamental for water management, environmental monitoring and for the definition of policies and planning strategies related to the sustainable use of rivers. While European Union directives aim at the conservation of inland water resources, the ground operational monitoring network is often inadequate. Rivers monitoring using Remote Sensing may complement in-situ measurements supplying continuous spatially explicit representation of parameters related to water quality and solid transport, even if the high frequency dynamics of water parameters could be not catched due to limited satellite revisit time.
Sentinel-2 and Landsat 8 satellites, equipped with MSI and OLI optical sensors whose spectral bands allow to perform a more accurate atmospheric correction, allow to develop methodologies for monitoring river color from space thanks to high spatial resolution and short revisit time.
This study present a processing chain developed to monitor water constituents in rivers using high resolution satellite images. Multitemporal analysis of Chl-a and Total Suspended Matter (TSM) bio-geophysical variables was performed for the case study of Po river (Italy) for the year 2017. Quantitative estimation of water constituents, retrieved from both Sentinel-2 and Landsat 8 satellite data, using the C2RCC and ACOLITE algorithms, were compared and main outcomes discussed. The developed processing chain can be used to create operational services for river monitoring and represent a major improvement in the identification of spatio-temporal dynamics, like solid transport, in riverine systems.