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Measuring snow liquid water content with low-cost GPS receivers.
Koch, Franziska; Prasch, Monika; Schmid, Lino; Schweizer, Jürg; Mauser, Wolfram.
Afiliação
  • Koch F; Department of Geography, Ludwig-Maximilians-Universität München, Luisenstr. 37, Munich 80333, Germany. franziska.koch@lmu.de.
  • Prasch M; Department of Geography, Ludwig-Maximilians-Universität München, Luisenstr. 37, Munich 80333, Germany. m.prasch@lmu.de.
  • Schmid L; WSL Institute for Snow and Avalanche Research SLF, Flüelastr. 11, 7260 Davos Dorf, Switzerland. lino.schmid@slf.ch.
  • Schweizer J; WSL Institute for Snow and Avalanche Research SLF, Flüelastr. 11, 7260 Davos Dorf, Switzerland. schweizer@slf.ch.
  • Mauser W; Department of Geography, Ludwig-Maximilians-Universität München, Luisenstr. 37, Munich 80333, Germany. w.mauser@lmu.de.
Sensors (Basel) ; 14(11): 20975-99, 2014 Nov 06.
Article em En | MEDLINE | ID: mdl-25384007
The amount of liquid water in snow characterizes the wetness of a snowpack. Its temporal evolution plays an important role for wet-snow avalanche prediction, as well as the onset of meltwater release and water availability estimations within a river basin. However, it is still a challenge and a not yet satisfyingly solved issue to measure the liquid water content (LWC) in snow with conventional in situ and remote sensing techniques. We propose a new approach based on the attenuation of microwave radiation in the L-band emitted by the satellites of the Global Positioning System (GPS). For this purpose, we performed a continuous low-cost GPS measurement experiment at the Weissfluhjoch test site in Switzerland, during the snow melt period in 2013. As a measure of signal strength, we analyzed the carrier-to-noise power density ratio (C/N0) and developed a procedure to normalize these data. The bulk volumetric LWC was determined based on assumptions for attenuation, reflection and refraction of radiation in wet snow. The onset of melt, as well as daily melt-freeze cycles were clearly detected. The temporal evolution of the LWC was closely related to the meteorological and snow-hydrological data. Due to its non-destructive setup, its cost-efficiency and global availability, this approach has the potential to be implemented in distributed sensor networks for avalanche prediction or basin-wide melt onset measurements.

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Health_economic_evaluation Idioma: En Revista: Sensors (Basel) Ano de publicação: 2014 Tipo de documento: Article País de afiliação: Alemanha

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Health_economic_evaluation Idioma: En Revista: Sensors (Basel) Ano de publicação: 2014 Tipo de documento: Article País de afiliação: Alemanha