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

This study presents daily, long-term (2003−2022) satellite-based estimates of river discharge and gridded runoff at 0.25° × 0.25° spatial resolution across the continental Pan-Arctic region. Satellite observations of precipitation from the Integrated Multi-satellite Retrievals (IMERG) for Global Precipitation Measurement (GPM), soil moisture and snow cover fraction from the European Space Agency's Climate Change Initiative (ESA CCI), and Terrestrial Water Storage Anomalies from satellite gravimetry are integrated into a conceptual hydrological model, STREAM, specifically adapted to simulate the hydrological regime of Pan-Arctic regions. The model is calibrated and validated using data from the 15 largest and best-monitored Arctic basins. It demonstrates high performance in reproducing daily river discharge observations, with a median Kling-Gupta Efficiency (KGE) of 0.83. To extend the model to ungauged regions, a regionalization approach based on similarities in basin climatic attributes is proposed, enabling the transfer of calibrated STREAM model parameters. When validated over 26 independent gauging stations, the regionalized river discharge estimates maintained acceptable accuracy, with a median KGE of 0.51. Using this framework, STREAM is applied across the continental Pan-Arctic region covering an area of 16.5 × 106 km2. The resulting spatially and temporally consistent runoff dataset, which can be used to complement more detailed process-based model estimates, enables the quantification of freshwater fluxes to the Arctic Ocean, estimated at 4760 ± 619 km3 yr−1. The results highlight the potential of satellite observations—particularly GRACE data—in supporting large-scale hydrological modelling and in reconstructing the Arctic freshwater cycle in data-scarce environments.