Abstract ID: 3.8239 | Accepted as Poster | Poster | TBA | TBA

Mountain socio-ecosystems are under increasing pressure from anthropogenic forcings (warming, precipitation change and nutrient inputs). Understanding and projecting the consequences of these changes for local biodiversity and downstream water resources, requires to be able to model transfer of energy and water by vertical and lateral fluxes. The determination of these water paths is particularly challenging in mountain terrains, where small scale snow, topographic and geomorphological processes drive hydrology. Conceptual and semi-distributed hydrological models fail to represent the complexity of these water paths and land surface model often neglect lateral fluxes, making both approaches limited in studying trajectories of mountain socio-ecosystems.
To overcome these limitations, we applied the data-intensive and calibration-light critical zone model ParFlow-CLM3.5, to a highly instrumented alpine catchment (6.2 km², 1950-3100 m.a.s.l) near the Lautaret Pass, in the French Alps. Specific efforts were directed toward the representation and definition of small-scale snow hydrological processes, modifying significantly the timing, amount, and location of water fluxes above and below the surface.
Limitations of the initial snow scheme were overcome by refining the snow/rain transition dependencies on meteorological factors, by improving the snow albedo aging routine, by accounting for Saharan dust events and by selecting relevant spatial distribution methods for meteorological forcings. The snow/rain transition was evaluated with a disdrometer. Meteorological forcings are distributed based on topography (slope effect on radiation and windspeed, shading, reillumination by longwave radiation), altitude (precipitation, temperature and humidity gradients), and remote sensing measurements (snow redistribution).
In this presentation we will focus on these snow scheme improvements, and the ability of the model to represent the dynamic of the snow cover during the season at decametric resolution. This will be evaluated spatially with drone, Sentinel-2, and Pleiades images (snow height, snow cover), locally with albedo, snow height and Snow Water Equivalent, and hydrologically with streamflow observations. Further on, this work aims to show that distributed and physics-based hydrological modelling is feasible over complex alpine terrain, with reduced field data needs, and to provide a reproducible framework.