Superconducting Gravimeter Observations Show That a Satellite-Derived Snow Depth Image Improves the Simulation of the Snow Water Equivalent Evolution in a High Alpine Site

The lack of accurate information on the spatiotemporal variations of snow water equivalent (SWE) in mountain catchments remains a key problem in snow hydrology and water resources management. This is partly because there is no sensor to measure SWE beyond local scale. At Mt. Zugspitze, Germany, a su...

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Detalles Bibliográficos
Autores: Koch, Franziska, Gascoin, Simon, Achmüller, K., Schattan, Paul, Wetzel, Karl-Friedrich, Deschamps-Berger, César, Lehning, Michael, Rehm, Till, Schulz, Karsten, Voigt, Christian
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2024
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/378911
Acceso en línea:http://hdl.handle.net/10261/378911
https://api.elsevier.com/content/abstract/scopus_id/85212586039
Access Level:acceso abierto
Palabra clave:Mountain hydrology
Satellite-derived snow depth image
Snow water equivalent
Snowpack modeling
Cryo-hydro-gravimetry
Snow cover distribution
Descripción
Sumario:The lack of accurate information on the spatiotemporal variations of snow water equivalent (SWE) in mountain catchments remains a key problem in snow hydrology and water resources management. This is partly because there is no sensor to measure SWE beyond local scale. At Mt. Zugspitze, Germany, a superconducting gravimeter senses the gravity effect of the seasonal snow, reflecting the temporal evolution of SWE in a few kilometers scale radius. We used this new observation to evaluate two configurations of the Alpine3D distributed snow model. In the default run, the model was forced with meteorological station data. In the second run, we applied precipitation correction based on an 8 m resolution snow depth image derived from satellite observations (Pléiades). The snow depth image strongly improved the simulation of the snowpack gravity effect during the melt season. This result suggests that satellite observations can enhance SWE analyses in mountains with limited infrastructure.