Articles | Volume 17, issue 4
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


Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on tc-2022-89', Carlo Marin, 24 Jun 2022
    • AC1: 'Reply on RC1', Sara Darychuk, 15 Sep 2022
  • RC2: 'Comment on tc-2022-89', Giacomo Bertoldi, 22 Aug 2022
    • AC2: 'Reply on RC2', Sara Darychuk, 23 Sep 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Reconsider after major revisions (further review by editor and referees) (04 Oct 2022) by Kang Yang
AR by Sara Darychuk on behalf of the Authors (11 Nov 2022)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (21 Nov 2022) by Kang Yang
RR by Carlo Marin (03 Dec 2022)
RR by Anonymous Referee #3 (10 Feb 2023)
ED: Publish subject to technical corrections (16 Feb 2023) by Kang Yang
AR by Sara Darychuk on behalf of the Authors (24 Feb 2023)  Author's response   Manuscript 
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.