Can fully satellite-products-driven simple models account for snow processes in data scarce regions?

This study investigates satellite-based information driven snow accounting routines to simulate snow processes in mountainous regimes that are inherently associated with data scarcity. Simple, independent and parsimonious snow accounting routines that are fully driven by remote sensing (RS) information such as the land surface temperatures and snow-cover information along with distributed temperature index-based snow-melt models, are presented. RS based snow-cover distribution does not only provide the crucial information on areal extent of snow, but can also be a highly imperative proxy for the precipitation accumulations in these data scarce regions, as the availability and resolution of the data doesn’t depend on the mountainous terrain. These models are calibrated independently on the snow-cover distribution, can be coupled with any rainfall-runoff models to simulate “snow-processes informed” discharge and are flexible enough to be extended to a wide geographical extent. These models, in addition to simulating the snow accumulation and melt processes, also use the timing of snow appearance and disappearance. This accounting of snow can be inverted to obtain seasonal precipitation estimates in data scarce snow dominated regions, which can be a very crucial information for water resources planning. Specific results pertaining to the validation of the models in Switzerland and southern Germany (ungauged scenario) are shown.