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The monitoring of rivers is not the primary objective of the Sentinel-3 mission. The first satellite of the constellation was launched in February 2016 and so far no study has investigated the joint use of altimeter, near-infrared and thermal sensors for discharge estimation. Nevertheless, similar sensors onboard other platforms have showed their ability to estimate river discharge also in scarcely gauged areas. The advantage of altimetry lies in the observation of water surface elevation, which can be proficiently used in approaches based on rating curve, empirical formulae or hydraulic modeling. Even though their use is limited, near-infrared sensors are successfully used to detect the variability of river discharge thanks to their high capacity to discriminate water from land. Thermal sensors are nearly completely unused, but the unique study that uses the difference in temperature of the river water between day and night for the estimation of water level, encourages its use for river discharge assessment as well. To improve the estimation of river discharge and foster studies that are aimed at monitoring ungauged rivers, the combination of the sensors is considered a viable path. The aim of this manuscript is to review these studies to show the limitations and the potentials of each sensor onboard the Sentinel-3 satellite and to investigate the added value of using these three sensors co-located on the same platform for river discharge monitoring. [ABSTRACT FROM AUTHOR]

• Altimetry water level data are used to set-up an up-to-date river discharge dataset. • A trend analysis extended up to the more recent period has been carried out. • An upward trend has been observed in West Africa for the period 1990–2019. Changes in the frequency and magnitude of extreme hydrological events (floods and droughts) are one of the most significance consequences of the climate change and their monitoring is therefore essential in many fields. However, the number of the global in situ discharge measurements has been declining since the eighties and the global supply of available data is often restricted in many parts of world. All these reasons have fostered in the last decades the exploitation of new technologies, such as satellite data, in the estimation of river discharge. In this study, satellite altimetry water level data are used to set-up a consistent and up-to-date river discharge dataset by means of rating curves for different sites across the world. Long continuous river discharge time series so obtained are used to perform a trend analysis on extreme hydrological events. Specifically, peak-over threshold values are extracted from the discharge time series, as proxy variables of independent extreme events, and the trend analysis is then carried out to identify changes in the magnitude of extreme events. The analysis permits to identify areas of the world prone to floods, like the West Africa, or drought so that appropriate actions for disaster risk mitigation and continuous improvement in disaster preparedness, response and recovery practices can be adopted. [ABSTRACT FROM AUTHOR]

Knowledge of the freshwater dynamic and volumes on a global scale is an essential information for climate studies and, at local level, for water resources management and flood risk mitigation.Although the ground hydrological monitoring network is quite widespread throughout the world, many sites are still not monitored due to problems related to cost issues, political aspects and inaccessibility of the areas. Lack of information, besides being harmful to the knowledge of the hydrological processes, is a deterrent also for the operative aspects, i.e. early warning system, contributing to worsen the already difficult living condition of many countries, especially developing countries (i.e. in Asia and Africa).Satellite remote sensing demonstrated to be a reliable support together with in-situ measurements for the estimation of river discharge. Radar altimeter and near infrared sensors independently showed their effectiveness providing estimates of river discharge with good accuracy. Moreover, the merging between the two sources of satellite data, radar altimeter and near infrared sensors, has also demonstrated to be the best solution for the monitoring of river discharge. Previous studies, showed the feasibility only for two test sites in the Niger (Nigeria) and Po (Italy) rivers, but the encouraging results suggest that the methodology can be successfully applied at global scale. To this scope, we used the water level measurements derived by satellite radar altimetry and made available on different platforms (Hydroweb, Theia, River & Lake, HydroSat, Dahiti). For the near infrared sensors, we used the Google Earth Engine to process long time series of MODIS product at 500 m and daily resolution and derive the signal proxy of river discharge. Artificial Neural Network (ANN) has been used to merge the information coming from altimetry and near infrared sensors, by using the ground observed discharges for thirty sites sampled across the world. Following the hydrological similarity, we tried to estimate river discharge for other ungauged sites by using the ANN trained for gauged sites. The results confirm the capability of the integration of different satellite sensors to provide useful estimates of the river discharge also where the data is scarce or completely missing. [ABSTRACT FROM AUTHOR]