A satellite-based approach for estimating runoff and river discharge in the Pan-Arctic region from 2003 to 2022

These datasets provide two novel, satellite-based hydrological records for the Pan-Arctic continental region, covering the period from 2003 to 2022. Addressing the critical challenge of data scarcity in high-latitude environments, they include both spatially distributed daily gridded runoff (at 0.25° resolution) and daily river discharge estimates across 41 gauging stations. The estimates were generated using an adapted version of the STREAM (Satellite-based Runoff Evaluation and Mapping) model, which integrates multi-source Earth Observation data—including GPM IMERG precipitation, ESA CCI soil moisture and snow cover, and GRACE/GRACE-FO Terrestrial Water Storage Anomalies—into a coherent hydrological framework. This approach allows for the consistent estimation of freshwater fluxes even in ungauged basins where ground observations are absent. The reliability of the datasets is underpinned by rigorous testing. The model was calibrated on the 15 largest and best-monitored Arctic basins, achieving high performance with a median Kling-Gupta Efficiency (KGE) of 0.83. To extend the estimates to ungauged regions, a climatic regionalization approach was applied and subsequently validated against 26 independent gauging stations, maintaining acceptable accuracy with a median KGE of 0.51. These datasets, which estimate a cumulative freshwater flux of 4760 ± 619 km³ yr⁻¹, provide a basis for investigating Pan-Arctic freshwater trends, supporting both large-scale hydrological modeling and climate change analysis. Details on the dataset development and on their performance assessment can be found in the related manuscript: Leopardi, F., Dari, J., Saltalippi, C., Brocca, L., Volden, E., Fernández-Prieto, D., Saemian, P., Sneeuw, N., Tourian, M.J., Camici, S., 2026. A satellite-based approach for estimating runoff and river discharge in the Pan-Arctic region from 2003 to 2022. Remote Sensing of Environment 338, 115353. https://doi.org/10.1016/j.rse.2026.115353 If you use this dataset, please consider citing both the dataset and the related paper. Acknowledgements: European Space Agency, ESA, funded the research through the STREAM-NEXT Project (EO Science for Society Permanently Open Call 4000126745/19/I-NB-CCN2)