Sentinel-2 high-resolution data for river discharge monitoring

River monitoring is an open issue due to many intrinsic problems of the ground monitoring network. Over the last few decades, the role of satellite sensors in river discharge estimation is significantly increased thanks to the strong growth in technologies and applications. Focusing on daily river discharge measurements, a non-linear regression model has been used to link the near-infrared (NIR) reflectance ratio between a dry and a wet pixel around the section of a river to the ground measurements of river discharge. The use of medium-resolution satellite data, such as those from MODIS sensors, enables to monitor high and low flows in medium-sized catchments (<100,000 km2), thanks to satellite frequent revisit time and wide spatial coverage. However, such sensors are not suitable to provide information for medium-narrow rivers (< 250 m wide), nor to study river features and patterns that are averaged within a single pixel. Here, we investigated the use of Sentinel-2 NIR reflectances to support the hypothesis that a higher spatial resolution, i.e. 10 m, is able to better identify the wet pixels, more related to the river dynamics, with obvious advantages for river discharge estimation compared to the medium resolution sensors (e.g., MODIS at 250 m). Moreover, it also allows both a finer distinction between vegetation, soil and water and the characterization of water turbidity in the river area. A new formulation enriched by the sediment component is proposed together with a first step toward an uncalibrated procedure to select the wet pixels. Google Earth Engine (GEE) platform has been employed for the data analysis, allowing to avoid the download of big amounts of data, fostering the reproducibility of the analysis in different locations. The accuracy of the river discharges derived from Sentinel-2 reflectances is evaluated against the in-situ observations from selected gauging stations along two Italian rivers, Po and Tiber. The results confirm the good performances obtained with high-resolution images over the Po River, with average Nash-Sutcliffe efficiency ranging between 0.39 and 0.56 for the different configurations adopted. Relatively worse results were obtained over the Tiber River where the Nash-Sutcliffe efficiency ranged between 0.2 and 0.61, due to an issue on the registration of Sentinel-2 images.

Automated summary

River monitoring is a challenging issue, but the use of satellite sensors, such as those from Sentinel-2, has greatly improved river discharge estimation. This study investigates the potential of Sentinel-2 NIR reflectances in improving river discharge estimation and evaluates its accuracy using in-situ observations from Italian rivers. The results demonstrate the effectiveness of high-resolution images in estimating river discharges.