The snow plays a crucial role for many human activities. It is like a water tower that stocks the water during winter and releases it downstream during the melting season.
“How much snow is in that watershed? Is the snow condition potentially dangerous? When will it melt?”
This is the key question that water managers and public officers are asking during winter time. The answer to this question may not only help to plan industrial production, for example for hydro-power players, but also to address water resources balances at regional or national scale.
The current approach in snow monitoring is based on snow measurements, like in-situ snow gauges. These stations, however, cannot cover all areas and basins. For these reasons, during Winter and Spring, several measurement campaigns are organized on selected basins to increase the number of measurements.
Despite its numerosity, in-situ measurements provide only point-wise information and thus need to be spatially interpolated. The common approach is to use statistical models seeking a correlation with morphological features, with a final correction through the snow covered area derived by satellite images.
Despite its popularity, this approach is subject to some drawbacks:
Waterjade exploits a new technology built upon a physically-based approach. Each point of the basin is assigned its topographical characteristics in terms of elevation, slope and aspect in order to account for the shadowing effect typical of the complex morphology. Then a specifically designed snow model derives the snow evolution by solving the mass and energy conservation equations on the snow pack.
This allows to distinguish the physical processes commanding snow evolution (accumulation, compaction and melting) and eventually to estimate snow depth and snow water equivalent.
The advantages of this technology are:
