Articles | Volume 27, issue 1
https://doi.org/10.5194/hess-27-21-2023
https://doi.org/10.5194/hess-27-21-2023
Research article
 | 
02 Jan 2023
Research article |  | 02 Jan 2023

Estimating spatiotemporally continuous snow water equivalent from intermittent satellite observations: an evaluation using synthetic data

Xiaoyu Ma, Dongyue Li, Yiwen Fang, Steven A. Margulis, and Dennis P. Lettenmaier

Viewed

Total article views: 1,926 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,422 442 62 1,926 107 44 44
  • HTML: 1,422
  • PDF: 442
  • XML: 62
  • Total: 1,926
  • Supplement: 107
  • BibTeX: 44
  • EndNote: 44
Views and downloads (calculated since 22 Jun 2022)
Cumulative views and downloads (calculated since 22 Jun 2022)

Viewed (geographical distribution)

Total article views: 1,926 (including HTML, PDF, and XML) Thereof 1,726 with geography defined and 200 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 12 Oct 2024
Download
Short summary
We explore satellite retrievals of snow water equivalent (SWE) along hypothetical ground tracks that would allow estimation of SWE over an entire watershed. The retrieval of SWE from satellites has proved elusive, but there are now technological options that do so along essentially one-dimensional tracks. We use machine learning (ML) algorithms as the basis for a track-to-area (TTA) transformation and show that at least one is robust enough to estimate domain-wide SWE with high accuracy.