Hydrological Modelling Of Snow Cover In The Large Upper Po River Basin: Winter 2004 Results And Validation With Snow Cover Estimation From Satellite
Price
Free (open access)
Transaction
Volume
89
Pages
10
Published
2006
Size
998 kb
Paper DOI
10.2495/GEO060301
Copyright
WIT Press
Author(s)
D. Rabuffetti, A. Salandin & R. Cremonini
Abstract
The study of the hydrological budget of mountainous river basins requires the understanding of the annual cycle of snow accumulation and melting. In fact a deep knowledge of snow cover distribution and dynamic offers several possibilities to improve water resource management and exploitation. The implemented model reproduces an energetic budget of the snowy mantle at small scales using DEM resolution. The use of a distributed model accounts for the high time-space variability of meteorological factors, such as precipitation, air temperature and solar radiation, whose fields at soil level are reconstructed from spot measurements through interpolation procedures based on the topography of the river basin. The modelled variables are the snow water equivalent (SWE) and the discharge generated by the snowmelt while the mechanics of the snowy mantle like thickness and density are not considered. At the same time the simplified degree day method, that uses only air temperature as an index to melt is also implemented and compared. The propagation of melting water inside the snowy mantle is modelled through the conceptual linear reservoir approach; the outflow from snowy mantle is propagated as superficial run-off to the closing section of the river basin through the Muskingum-Cunge hydrological model. The basin of the river Po closed at the section of Ponte Becca is studied in the simulation; it covers a surface of approximately 38000 km2. The simulation ranges from winter 2004 to spring 2005. The modelled snow cover over the catchment is compared with estimation from satellite, derived using the Normalized Difference Snow Index (NDSI), concurring to the validation of the model. Keywords: snow, energy budget, degree day, satellite images, model validation.
Keywords
snow, energy budget, degree day, satellite images, model validation.