Articles | Volume 10, issue 2
https://doi.org/10.5194/soil-10-655-2024
https://doi.org/10.5194/soil-10-655-2024
Original research article
 | 
20 Sep 2024
Original research article |  | 20 Sep 2024

Depth extrapolation of field-scale soil moisture time series derived with cosmic-ray neutron sensing (CRNS) using the soil moisture analytical relationship (SMAR) model

Daniel Rasche, Theresa Blume, and Andreas Güntner

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-170', Anonymous Referee #1, 26 Feb 2024
  • RC2: 'Comment on egusphere-2024-170', Anonymous Referee #2, 02 Apr 2024

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
ED: Reconsider after major revisions (11 May 2024) by David Dunkerley
AR by Daniel Rasche on behalf of the Authors (02 Jul 2024)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (08 Jul 2024) by David Dunkerley
ED: Publish as is (08 Jul 2024) by Rémi Cardinael (Executive editor)
AR by Daniel Rasche on behalf of the Authors (15 Jul 2024)  Author's response   Manuscript 
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Short summary
Soil moisture measurements at the field scale are highly beneficial for numerous (soil) hydrological applications. Cosmic-ray neutron sensing (CRNS) allows for the non-invasive monitoring of field-scale soil moisture across several hectares but only for the first few tens of centimetres of the soil. In this study, we modify and test a simple modeling approach to extrapolate CRNS-derived surface soil moisture information down to 450 cm depth and compare calibrated and uncalibrated model results.