Using Multitemporal Sentinel-1 imagery for wet snow dynamics characterization in Mediterranean mountain catchments: a case study in Sierra Nevada, Spain

Monitoring snowmelt dynamics in mountainous catchments  is essential for comprehending downstream water release, streamflow response and consequently, for a better management of water resources at the catchment scale.  In a consolidated snowpack when external inputs become positive, the snow turns into wet snow and the melting phase begins. This change modifies the dielectric constant of the snowpack which can be detected remotely using information in the microwave region of the electromagnetic spectrum. Sentinel-1 (S-1) synthetic-aperture radar (SAR) has emerged as a widely utilized technique for this purpose due to its frequent acquisitions and all-weather capability. 

This study seeks to, first, explore the capabilities of C-band S-1 SAR imagery, which has been demonstrated in previous studies in other regions such as the Alps, in capturing multi-seasonal snowmelt dynamics and, second to linked these wet-dynamics to changes in streamflow response over Mediterranean mountain areas . The study was carried out at two scales: plot and catchment: At the plot scale, the Refugio Poqueira experimental site, which is located at 2500 m a.s.l. was chosen. At the catchment scale, the headwaters of the Poqueria River, which is a  snow-driven catchment  located in the southern face of Sierra Nevada, was selected. Four hydrological years with high hydroclimatic variability, from 2016-2017 to 2019-2020, were used in the study to capture the heterogeneity of the area. 

The general change detection approach for identifying wet snow was adapted for these regions, utilizing the average S-1 SAR image from the preceding summer as  reference imagery and employing a threshold of −3.00 dB for discriminating wet snow. This adaptation was validated using Landsat images as a reference dataset, yielding a general accuracy of 0.79. The local scale analysis demonstrates that S-1 SAR imagery was  able to capture four types of melting cycles including the well-known main melting event during the spring season. The other three melting cycles are linked to the Mediterranean mountains climate and can occur throughout the hydrological year. When applied at the catchment scale, distributed melting-runoff onset maps were developed to enhance understanding of the spatiotemporal evolution of melting dynamics. Finally, a linear correlation between melting dynamics and streamflow was established for prolonged melting cycles, with a determination coefficient (R2) ranging from 0.62 to 0.83 and an average delay of approximately 21 days between melting onset and streamflow peak.

Acknowledgments: This work has been funded by the project PID2021-12323SNB-I00, HYPOMED—“Incorporating hydrological uncertainty and risk analysis to the operation of hydropower facilities in Mediterranean mountain watersheds”.