Optical and altimetry data integration for river discharge estimation on a global scale

Rivers play a central role in the Earth’s hydrological system, acting as pathways for freshwater transport and supporting ecosystems, human societies, and economic activities. Accurate monitoring of river discharge is essential for understanding the global water cycle, managing water resources, and addressing the increasing pressures associated with climate change. Despite its importance, discharge monitoring based on in-situ measurements remains limited, with sparse and uneven coverage, particularly in remote and ungauged regions. In this context, satellite observations offer a unique opportunity to overcome these limitations by enabling large-scale and consistent estimation of river discharge across diverse environments.

This study presents an advanced framework that combines satellite observations from optical and altimetry sensors to generate a global river discharge product tailored for hydrological applications. Building on the capabilities of EUMETSAT satellite systems and Copernicus contributing missions, the framework integrates data from multiple satellite platforms to enhance information content and improve accuracy relative to single-sensor approaches. A key innovation lies in the fusion of complementary datasets (optical and altimetry), which improves both spatial and temporal resolution, especially in areas where ground-based observations are scarce or absent.

The analysis focuses on more than 300 sites distributed worldwide, covering a wide range of climatic conditions and hydrological regimes. This dataset enables an assessment of the long-term potential of satellite-derived discharge estimates for water resource management and climate impact studies. Particular emphasis is placed on evaluating the added value of the global product in ungauged basins, as well as identifying its limitations in monitoring smaller rivers, where higher spatial resolution is often required.

To ensure the robustness and transferability of the proposed framework, multiple river discharge estimation methods are systematically tested on a representative subset comprising approximately 30% of the analyzed sites. This intercomparison aims to identify the most reliable and scalable approach, which is then adopted to generate river discharge estimates for the full dataset. The outcomes of this evaluation are presented here and subsequently extended to a global-scale application.

The results highlight the strong potential of satellite-based technologies for river discharge monitoring, enabling more robust, consistent and timely information to support decision-making in the context of global environmental change.