Enhancing Snow Dynamics Monitoring in the Moroccan High Atlas Using Combined Optical and Microwave Satellite Observations

The seasonal dynamics of snow in Morocco's High Atlas Mountains play a crucial role in the region's water supply, particularly through snowmelt runoff and groundwater recharge in a semi-arid context. Snowmelt provides a significant amount of water to surface and groundwater reservoirs, especially during the summer when precipitation is very rare. However, monitoring snow cover and melt processes in this region remains difficult due to complex topography, high spatial variability, frequent cloud cover in winter, and limited in situ observations. To this end, in this study, we examine the synergistic use of optical and microwave satellite data to improve the monitoring of snow dynamics in the High Atlas.

Optical observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) provide high temporal resolution estimates of snow cover extent, but they are limited by cloud contamination and variable illumination conditions in mountainous terrain. To overcome these limitations, microwave observations from the Sentinel-1 and the Global Microwave Imager (GMI)/Tropical Microwave Imager (TMI) are integrated. The combined optical-microwave framework enables us to improve the temporal continuity and robustness of dynamic snow retrievals, allowing for better characterization of snow accumulation and melt phases across elevation gradients in the High Atlas Mountains, under both clear and cloudy conditions.

The results show that the multi-sensor approach significantly improved the temporal continuity and reliability of snow dynamics monitoring compared to single-sensor approaches. The integration of microwave data allowed for consistent identification of accumulation and melt events, particularly during cloudy periods when MODIS data are not available. In particular, it allowed for better detection of rapid snow events that are often missed by optical data alone and also reduced uncertainty in estimates of snow cover duration, which is essential for assessments of water availability in the High Atlas Mountains. Overall, the approach developed here offers significant potential for improving hydrological modeling and quantifying the contribution of snowmelt to water reservoir storage in semi-arid mountainous regions where data are scarce.