Articles | Volume 17, issue 4
https://doi.org/10.5194/tc-17-1457-2023
https://doi.org/10.5194/tc-17-1457-2023
Research article
 | 
05 Apr 2023
Research article |  | 05 Apr 2023

Snowmelt characterization from optical and synthetic-aperture radar observations in the La Joie Basin, British Columbia

Sara E. Darychuk, Joseph M. Shea, Brian Menounos, Anna Chesnokova, Georg Jost, and Frank Weber

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Cited articles

Barnett, T. P., Adam, J. C., and Lettenmaier, D. P.: Potential impacts of a warming climate on water availability in snow-dominated regions, Nature, 438, 303–309, 2005. 
Bernier, P. Y.: Microwave Remote Sensing of Snowpack Properties: Potential and Limitations, Hydrol. Res., 18, 1–20, https://doi.org/10.2166/nh.1987.0001, 1987. 
Darychuk, S.: Export Sentinel-1 SAR Images for Snowmelt Analysis, Github [code], https://github.com/saradarychuk/Snowmelt-Characterization-from-Sentinel-1-SAR, last access: 31 March 2023a. 
Darychuk, S.: Snow Disappearance Estimates in Glacierized Basins, Github [code], https://github.com/saradarychuk/Snowmelt-Characterization-from-Sentinel-1-SAR, last access: 31 March 2023b. 
Deems, J. S., Fassnacht, S. R., and Elder, K. J.: Fractal Distribution of Snow Depth from Lidar Data, J. Hydrometerol., 7, 285–297, 2006. 
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Short summary
We use synthetic-aperture radar (SAR) and optical observations to map snowmelt timing and duration on the watershed scale. We found that Sentinel-1 SAR time series can be used to approximate snowmelt onset over diverse terrain and land cover types, and we present a low-cost workflow for SAR processing over large, mountainous regions. Our approach provides spatially distributed observations of the snowpack necessary for model calibration and can be used to monitor snowmelt in ungauged basins.
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