Publication Date:
2023-08-29
Description:
The monitoring and forecasting of the liquid water content (LWC) is of paramount importance in many hydrological fields, from operational avalanche forecasting to hydropower production and flood prediction. Remote sensing offers observations of the snowpack physical properties. For instance, Sentinel-1 satellites provide C-band synthetic aperture radar (SAR) data at high temporal and spatial resolutions, which can detect the presence of wet snow. On the other side, many snow models were built in literature with the purpose of simulating the snowpack mass dynamics in space and time (see e.g., Crocus, SNOWPACK, and HyS model).The present work aims at assessing the potential of satellite products, compared to models’ snow estimates, in detecting LWC. In particular, the comparison is led among (1) Sentinel-1 based wet-snow products, (2) HSAF products, from the processing of Earth observation satellites data, and (3) LWC simulations from HyS model, a temperature-index model. The case study is the Mallero basin, a middle-size alpine basin, whose flow regime is strongly influenced by snow melting and glacier ablation in spring and summer seasons. The comparison shows a good agreement between Sentinel-1 products and HyS simulations. The short period of mismatches between the two outputs are analyzed to identify the physical processes that the model is not able to reproduce. On the other side, HSAF data, with their coarse resolution, just provide a qualitative overview of the snow mantle status, over a middle-size basin. Moreover, such products are also limited by the effect of cloud covering.
Language:
English
Type:
info:eu-repo/semantics/conferenceObject
Permalink