Monitoring snow water equivalent using the phase of RFID signals
International audience The amount of water contained in a snowpack, known as snow water equivalent (SWE), is used to anticipate the amount of snowmelt that could supply hydroelectric power plants, fill water reservoirs, or sometimes cause flooding. This work introduces a wireless, non-destructive me...
Published in: | The Cryosphere |
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Main Authors: | , , , , |
Other Authors: | , , , , , , , , , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
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HAL CCSD
2023
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Online Access: | https://hal.science/hal-04178023 https://hal.science/hal-04178023/document https://hal.science/hal-04178023/file/tc-17-3137-2023.pdf https://doi.org/10.5194/tc-17-3137-2023 |
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Institut national des sciences de l'Univers: HAL-INSU |
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English |
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[SDE]Environmental Sciences [SPI]Engineering Sciences [physics] |
spellingShingle |
[SDE]Environmental Sciences [SPI]Engineering Sciences [physics] Le Breton, Mathieu Larose, Éric Baillet, Laurent Lejeune, Yves van Herwijnen, Alec Monitoring snow water equivalent using the phase of RFID signals |
topic_facet |
[SDE]Environmental Sciences [SPI]Engineering Sciences [physics] |
description |
International audience The amount of water contained in a snowpack, known as snow water equivalent (SWE), is used to anticipate the amount of snowmelt that could supply hydroelectric power plants, fill water reservoirs, or sometimes cause flooding. This work introduces a wireless, non-destructive method for monitoring the SWE of a dry snowpack. The system is based on an array of low-cost passive radiofrequency identification (RFID) tags, placed under the snow and read at 865–868 MHz by a reader located above the snow. The SWE was deduced from the phase delay of the tag's backscattered response, which increases with the amount of snow traversed by the radiofrequency wave. Measurements taken in the laboratory, during snowfall events and over 4.5 months at the Col de Porte test field, were consistent with reference measurements of cosmic rays, precipitation and snow pits. SWE accuracy was ±18 kg m−2 throughout the season (averaged over three tags) and ±3 kg m−2 during dry snowfall events (averaged over data from two antennas and four or five tags). The overall uncertainty compared to snow weighing was ±10 % for snow density in the range 61–390 kg m−3. The main limitations observed were measurement bias caused by wet snow (biased data were discarded) and the need for phase unwrapping. The method has a number of advantages: it allows for continuous measurement (1 min sampling rate in dry snow), it can provide complementary measurement of tag temperature, it does not require the reception of external data, and it opens the way towards spatialized measurements. The results presented also demonstrate that RFID propagation-based sensing can remotely monitor the permittivity of a low-loss dielectric material with scientific-level accuracy. |
author2 |
Groupe Géolithe Institut des Sciences de la Terre (ISTerre) Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)-Université Gustave Eiffel-Université Grenoble Alpes (UGA) Centre d'Etudes de la Neige (CEN) Centre national de recherches météorologiques (CNRM) Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP) Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3) Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3) Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP) Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG ) Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Grenoble Alpes (UGA)-Météo-France-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Grenoble Alpes (UGA) SLF Institut pour l'étude de la neige et des avalanches (SLF) SLF Géolithe Innov ANR-17-LCV2-0007,GEO3I LAB,Laboratoire Innovation en Géophysique, Géomécanique, Géotechnique(2017) |
format |
Article in Journal/Newspaper |
author |
Le Breton, Mathieu Larose, Éric Baillet, Laurent Lejeune, Yves van Herwijnen, Alec |
author_facet |
Le Breton, Mathieu Larose, Éric Baillet, Laurent Lejeune, Yves van Herwijnen, Alec |
author_sort |
Le Breton, Mathieu |
title |
Monitoring snow water equivalent using the phase of RFID signals |
title_short |
Monitoring snow water equivalent using the phase of RFID signals |
title_full |
Monitoring snow water equivalent using the phase of RFID signals |
title_fullStr |
Monitoring snow water equivalent using the phase of RFID signals |
title_full_unstemmed |
Monitoring snow water equivalent using the phase of RFID signals |
title_sort |
monitoring snow water equivalent using the phase of rfid signals |
publisher |
HAL CCSD |
publishDate |
2023 |
url |
https://hal.science/hal-04178023 https://hal.science/hal-04178023/document https://hal.science/hal-04178023/file/tc-17-3137-2023.pdf https://doi.org/10.5194/tc-17-3137-2023 |
genre |
The Cryosphere |
genre_facet |
The Cryosphere |
op_source |
ISSN: 1994-0424 EISSN: 1994-0416 The Cryosphere https://hal.science/hal-04178023 The Cryosphere, 2023, 17 (8), pp.3137-3156. ⟨10.5194/tc-17-3137-2023⟩ https://tc.copernicus.org/articles/17/3137/2023/ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.5194/tc-17-3137-2023 hal-04178023 https://hal.science/hal-04178023 https://hal.science/hal-04178023/document https://hal.science/hal-04178023/file/tc-17-3137-2023.pdf doi:10.5194/tc-17-3137-2023 |
op_rights |
http://creativecommons.org/licenses/by/ info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.5194/tc-17-3137-2023 |
container_title |
The Cryosphere |
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17 |
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8 |
container_start_page |
3137 |
op_container_end_page |
3156 |
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1797571079965769728 |
spelling |
ftinsu:oai:HAL:hal-04178023v1 2024-04-28T08:40:27+00:00 Monitoring snow water equivalent using the phase of RFID signals Suivi de l'équivalent en eau du manteau neigeux, en utilisant la phase de signaux RFID Le Breton, Mathieu Larose, Éric Baillet, Laurent Lejeune, Yves van Herwijnen, Alec Groupe Géolithe Institut des Sciences de la Terre (ISTerre) Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)-Université Gustave Eiffel-Université Grenoble Alpes (UGA) Centre d'Etudes de la Neige (CEN) Centre national de recherches météorologiques (CNRM) Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP) Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3) Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3) Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP) Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG ) Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Grenoble Alpes (UGA)-Météo-France-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Grenoble Alpes (UGA) SLF Institut pour l'étude de la neige et des avalanches (SLF) SLF Géolithe Innov ANR-17-LCV2-0007,GEO3I LAB,Laboratoire Innovation en Géophysique, Géomécanique, Géotechnique(2017) 2023-08-04 https://hal.science/hal-04178023 https://hal.science/hal-04178023/document https://hal.science/hal-04178023/file/tc-17-3137-2023.pdf https://doi.org/10.5194/tc-17-3137-2023 en eng HAL CCSD Copernicus info:eu-repo/semantics/altIdentifier/doi/10.5194/tc-17-3137-2023 hal-04178023 https://hal.science/hal-04178023 https://hal.science/hal-04178023/document https://hal.science/hal-04178023/file/tc-17-3137-2023.pdf doi:10.5194/tc-17-3137-2023 http://creativecommons.org/licenses/by/ info:eu-repo/semantics/OpenAccess ISSN: 1994-0424 EISSN: 1994-0416 The Cryosphere https://hal.science/hal-04178023 The Cryosphere, 2023, 17 (8), pp.3137-3156. ⟨10.5194/tc-17-3137-2023⟩ https://tc.copernicus.org/articles/17/3137/2023/ [SDE]Environmental Sciences [SPI]Engineering Sciences [physics] info:eu-repo/semantics/article Journal articles 2023 ftinsu https://doi.org/10.5194/tc-17-3137-2023 2024-04-05T00:29:02Z International audience The amount of water contained in a snowpack, known as snow water equivalent (SWE), is used to anticipate the amount of snowmelt that could supply hydroelectric power plants, fill water reservoirs, or sometimes cause flooding. This work introduces a wireless, non-destructive method for monitoring the SWE of a dry snowpack. The system is based on an array of low-cost passive radiofrequency identification (RFID) tags, placed under the snow and read at 865–868 MHz by a reader located above the snow. The SWE was deduced from the phase delay of the tag's backscattered response, which increases with the amount of snow traversed by the radiofrequency wave. Measurements taken in the laboratory, during snowfall events and over 4.5 months at the Col de Porte test field, were consistent with reference measurements of cosmic rays, precipitation and snow pits. SWE accuracy was ±18 kg m−2 throughout the season (averaged over three tags) and ±3 kg m−2 during dry snowfall events (averaged over data from two antennas and four or five tags). The overall uncertainty compared to snow weighing was ±10 % for snow density in the range 61–390 kg m−3. The main limitations observed were measurement bias caused by wet snow (biased data were discarded) and the need for phase unwrapping. The method has a number of advantages: it allows for continuous measurement (1 min sampling rate in dry snow), it can provide complementary measurement of tag temperature, it does not require the reception of external data, and it opens the way towards spatialized measurements. The results presented also demonstrate that RFID propagation-based sensing can remotely monitor the permittivity of a low-loss dielectric material with scientific-level accuracy. Article in Journal/Newspaper The Cryosphere Institut national des sciences de l'Univers: HAL-INSU The Cryosphere 17 8 3137 3156 |