Articles | Volume 16, issue 1
https://doi.org/10.5194/tc-16-43-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-16-43-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 Jan 2022
Research article |
| 06 Jan 2022
| 06 Jan 2022
Mapping liquid water content in snow at the millimeter scale: an intercomparison of mixed-phase optical property models using hyperspectral imaging and in situ measurements
Christopher Donahue
CORRESPONDING AUTHOR
Department of Civil Engineering, Montana State University, Bozeman,
MT 59717, USA
S. McKenzie Skiles
Department of Geography, University of Utah, Salt Lake City, UT 84112, USA
Kevin Hammonds
Department of Civil Engineering, Montana State University, Bozeman,
MT 59717, USA
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Cited
18 citations as recorded by crossref.
- Towards a Model of Snow Accretion for Autonomous Vehicles M. Carvalho et al. 10.3390/atmos15050548
- A novel method to visualize liquid distribution in snow: superimposition of MRI and X-ray CT images S. Yamaguchi et al. 10.1017/aog.2023.77
- Evaluation and Optimization of Snow Albedo Scheme in Noah‐MP Land Surface Model Using In Situ Spectral Observations in the Colorado Rockies R. Abolafia‐Rosenzweig et al. 10.1029/2022MS003141
- A Phase-Field Model for Wet Snow Metamorphism A. Moure & X. Fu 10.1021/acs.cgd.4c00539
- Mapping surface hoar from near-infrared texture in a laboratory J. Dillon et al. 10.5194/tc-18-2557-2024
- A Review of the Hydrologic Response Mechanisms During Mountain Rain-on-Snow W. Brandt et al. 10.3389/feart.2022.791760
- Laboratory Observations of Preferential Flow Paths in Snow Using Upward-Looking Polarimetric Radar and Hyperspectral Imaging C. Donahue & K. Hammonds 10.3390/rs14102297
- Retrieval of snow layer and melt pond properties on Arctic sea ice from airborne imaging spectrometer observations S. Rosenburg et al. 10.5194/amt-16-3915-2023
- UAV hyperspectral imaging for multiscale assessment of Landsat 9 snow grain size and albedo S. Skiles et al. 10.3389/frsen.2022.1038287
- Bridging the gap between airborne and spaceborne imaging spectroscopy for mountain glacier surface property retrievals C. Donahue et al. 10.1016/j.rse.2023.113849
- Unlocking the potential of melting calorimetry: a field protocol for liquid water content measurement in snow R. Barella et al. 10.5194/tc-18-5323-2024
- Watershed memory amplified the Oroville rain-on-snow flood of February 2017 K. Haleakala et al. 10.1093/pnasnexus/pgac295
- A method for imaging water transport in soil–snow systems with neutron radiography M. Lombardo et al. 10.1017/aog.2023.65
- Smartphone-based measurements of the optical properties of snow M. Allgaier & B. Smith 10.1364/AO.457976
- Retrieval of snow liquid water content from radiative transfer model, field data and PRISMA satellite data C. Ravasio et al. 10.1016/j.rse.2024.114268
- Computationally Efficient Retrieval of Snow Surface Properties From Spaceborne Imaging Spectroscopy Measurements Through Dimensionality Reduction Using k-Means Spectral Clustering B. Wilder et al. 10.1109/JSTARS.2024.3386834
- A cold laboratory hyperspectral imaging system to map grain size and ice layer distributions in firn cores I. McDowell et al. 10.5194/tc-18-1925-2024
- Improved snow property retrievals by solving for topography in the inversion of at-sensor radiance measurements B. Wilder et al. 10.5194/tc-18-5015-2024
18 citations as recorded by crossref.
- Towards a Model of Snow Accretion for Autonomous Vehicles M. Carvalho et al. 10.3390/atmos15050548
- A novel method to visualize liquid distribution in snow: superimposition of MRI and X-ray CT images S. Yamaguchi et al. 10.1017/aog.2023.77
- Evaluation and Optimization of Snow Albedo Scheme in Noah‐MP Land Surface Model Using In Situ Spectral Observations in the Colorado Rockies R. Abolafia‐Rosenzweig et al. 10.1029/2022MS003141
- A Phase-Field Model for Wet Snow Metamorphism A. Moure & X. Fu 10.1021/acs.cgd.4c00539
- Mapping surface hoar from near-infrared texture in a laboratory J. Dillon et al. 10.5194/tc-18-2557-2024
- A Review of the Hydrologic Response Mechanisms During Mountain Rain-on-Snow W. Brandt et al. 10.3389/feart.2022.791760
- Laboratory Observations of Preferential Flow Paths in Snow Using Upward-Looking Polarimetric Radar and Hyperspectral Imaging C. Donahue & K. Hammonds 10.3390/rs14102297
- Retrieval of snow layer and melt pond properties on Arctic sea ice from airborne imaging spectrometer observations S. Rosenburg et al. 10.5194/amt-16-3915-2023
- UAV hyperspectral imaging for multiscale assessment of Landsat 9 snow grain size and albedo S. Skiles et al. 10.3389/frsen.2022.1038287
- Bridging the gap between airborne and spaceborne imaging spectroscopy for mountain glacier surface property retrievals C. Donahue et al. 10.1016/j.rse.2023.113849
- Unlocking the potential of melting calorimetry: a field protocol for liquid water content measurement in snow R. Barella et al. 10.5194/tc-18-5323-2024
- Watershed memory amplified the Oroville rain-on-snow flood of February 2017 K. Haleakala et al. 10.1093/pnasnexus/pgac295
- A method for imaging water transport in soil–snow systems with neutron radiography M. Lombardo et al. 10.1017/aog.2023.65
- Smartphone-based measurements of the optical properties of snow M. Allgaier & B. Smith 10.1364/AO.457976
- Retrieval of snow liquid water content from radiative transfer model, field data and PRISMA satellite data C. Ravasio et al. 10.1016/j.rse.2024.114268
- Computationally Efficient Retrieval of Snow Surface Properties From Spaceborne Imaging Spectroscopy Measurements Through Dimensionality Reduction Using k-Means Spectral Clustering B. Wilder et al. 10.1109/JSTARS.2024.3386834
- A cold laboratory hyperspectral imaging system to map grain size and ice layer distributions in firn cores I. McDowell et al. 10.5194/tc-18-1925-2024
- Improved snow property retrievals by solving for topography in the inversion of at-sensor radiance measurements B. Wilder et al. 10.5194/tc-18-5015-2024
Latest update: 13 Dec 2024
Short summary
The amount of water within a snowpack is important information for predicting snowmelt and wet-snow avalanches. From within a controlled laboratory, the optimal method for measuring liquid water content (LWC) at the snow surface or along a snow pit profile using near-infrared imagery was determined. As snow samples melted, multiple models to represent wet-snow reflectance were assessed against a more established LWC instrument. The best model represents snow as separate spheres of ice and water.
The amount of water within a snowpack is important information for predicting snowmelt and...
