Preprints
https://doi.org/10.5194/hess-2018-451
https://doi.org/10.5194/hess-2018-451
24 Oct 2018
 | 24 Oct 2018
Status: this preprint was under review for the journal HESS but the revision was not accepted.

Technical note: Snow Water Equivalence Estimation (SWEE) Algorithm from Snow Depth Time Series Using a Snow Density Model

Noriaki Ohara, Siwei He, Andrew D. Parsekian, and Thijs Kelleners

Abstract. Snow water equivalence (SWE) is typically computed from snow weight by the SNOTEL system in the US. However, a snow pillow, the main snow weight sensor used by SNOTEL, requires a large, open, flat area (at least 9 square meters) and substantial maintenance costs. This article presents the snow water equivalence estimation (SWEE) algorithm that estimates the SWE evolution merely from continuous snow depth and temperature measurements using common sensors. The key component is a depth-averaged snow density model that is available in the literature, but is underutilized. Here, we demonstrate that the snow density model can estimate mass exchanges (SWE changes due to snowfall, erosion, deposition, and snowmelt) as well as the SWE. The SWEE algorithm can potentially increase the number of snow monitoring locations because snow depth and temperature sensors are considerably more accessible and economical than snow weighing sensor.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Noriaki Ohara, Siwei He, Andrew D. Parsekian, and Thijs Kelleners
 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Noriaki Ohara, Siwei He, Andrew D. Parsekian, and Thijs Kelleners
Noriaki Ohara, Siwei He, Andrew D. Parsekian, and Thijs Kelleners

Viewed

Total article views: 2,268 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,827 386 55 2,268 84 67 69
  • HTML: 1,827
  • PDF: 386
  • XML: 55
  • Total: 2,268
  • Supplement: 84
  • BibTeX: 67
  • EndNote: 69
Views and downloads (calculated since 24 Oct 2018)
Cumulative views and downloads (calculated since 24 Oct 2018)

Viewed (geographical distribution)

Total article views: 2,009 (including HTML, PDF, and XML) Thereof 1,992 with geography defined and 17 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 14 Dec 2024
Download