Articles | Volume 2, issue 4
https://doi.org/10.5194/soil-2-615-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/soil-2-615-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Original research article
| 
09 Dec 2016
Original research article |
| 09 Dec 2016
Deriving pedotransfer functions for soil quartz fraction in southern France from reverse modeling
Jean-Christophe Calvet
CORRESPONDING AUTHOR
CNRM, UMR 3589 (Météo-France, CNRS), Toulouse, France
Noureddine Fritz
CNRM, UMR 3589 (Météo-France, CNRS), Toulouse, France
Christine Berne
CNRM, UMR 3589 (Météo-France, CNRS), Toulouse, France
Bruno Piguet
CNRM, UMR 3589 (Météo-France, CNRS), Toulouse, France
William Maurel
CNRM, UMR 3589 (Météo-France, CNRS), Toulouse, France
Catherine Meurey
CNRM, UMR 3589 (Météo-France, CNRS), Toulouse, France
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- An advanced change detection method for time-series soil moisture retrieval from Sentinel-1 L. Zhu et al. 10.1016/j.rse.2022.113137
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32 citations as recorded by crossref.
- Global Soil Moisture Estimation based on GPM IMERG Data using a Site Specific Adjusted Antecedent Precipitation Index T. Ramsauer & P. Marzahn 10.1080/01431161.2022.2162351
- Excluding quartz content from the estimation of saturated soil thermal conductivity: Combined use of differential effective medium theory and geometric mean method Y. Fu et al. 10.1016/j.agrformet.2023.109743
- Hybrid Methodology Using Sentinel-1/Sentinel-2 for Soil Moisture Estimation S. Nativel et al. 10.3390/rs14102434
- Soil Moisture Monitoring at Kilometer Scale: Assimilation of Sentinel-1 Products in ISBA O. Rojas-Munoz et al. 10.3390/rs15174329
- Modelling of soil solid thermal conductivity H. He et al. 10.1016/j.icheatmasstransfer.2020.104602
- A novel AMSR2 retrieval algorithm for global C-band vegetation optical depth and soil moisture (AMSR2 IB): Parameters' calibration, evaluation and inter-comparison M. Wang et al. 10.1016/j.rse.2024.114370
- Improved SMAP Soil Moisture Retrieval Using a Deep Neural Network-Based Replacement of Radiative Transfer and Roughness Model J. Lee et al. 10.1109/TGRS.2024.3489974
- A Generic First-Order Radiative Transfer Modelling Approach for the Inversion of Soil and Vegetation Parameters from Scatterometer Observations R. Quast et al. 10.3390/rs11030285
- Estimating the drainage rate from surface soil moisture drydowns: Application of DfD model to in situ soil moisture data E. Jalilvand et al. 10.1016/j.jhydrol.2018.08.035
- A review and evaluation of 39 thermal conductivity models for frozen soils H. He et al. 10.1016/j.geoderma.2020.114694
- Identification of soil-cooling rains in southern France from soil temperature and soil moisture observations S. Zhang et al. 10.5194/acp-19-5005-2019
- Pedotransfer Functions in Earth System Science: Challenges and Perspectives K. Van Looy et al. 10.1002/2017RG000581
- A cross-resolution transfer learning approach for soil moisture retrieval from Sentinel-1 using limited training samples L. Zhu et al. 10.1016/j.rse.2023.113944
- Impact of biochar addition on soil thermal properties: Modelling approach B. Usowicz et al. 10.1016/j.geoderma.2020.114574
- Are the Current Expectations for SAR Remote Sensing of Soil Moisture Using Machine Learning Overoptimistic? L. Zhu et al. 10.1109/TGRS.2025.3533927
- Normalized concept for modelling effective soil thermal conductivity from dryness to saturation H. He et al. 10.1111/ejss.12820
- Bridging spatio-temporal discontinuities in global soil moisture mapping by coupling physics in deep learning Z. Wei et al. 10.1016/j.rse.2024.114371
- Uncertainty estimation for a new exponential-filter-based long-term root-zone soil moisture dataset from Copernicus Climate Change Service (C3S) surface observations A. Pasik et al. 10.5194/gmd-16-4957-2023
- Expanding scales: Achieving prediction of van Genuchten model hydraulic parameters in deep profiles by incorporating broad in situ soil information in pedotransfer functions Y. Tong et al. 10.1016/j.jhydrol.2025.132912
- The International Soil Moisture Network: serving Earth system science for over a decade W. Dorigo et al. 10.5194/hess-25-5749-2021
- Time series soil moisture retrieval from SAR data: Multi-temporal constraints and a global validation L. Zhu et al. 10.1016/j.rse.2023.113466
- A Sensor to Monitor Soil Moisture, Salinity, and Temperature Profiles for Wireless Networks X. Chavanne & J. Frangi 10.3390/jsan13030032
- An effective medium theory-based unified model for estimating thermal conductivity of unfrozen and frozen soils H. Ji et al. 10.1016/j.catena.2024.107942
- Bias-blind and bias-aware assimilation of leaf area index into the Noah-MP land surface model over Europe S. Scherrer et al. 10.5194/hess-27-4087-2023
- Estimating the uncertainties of satellite derived soil moisture at global scale F. Gibon et al. 10.1016/j.srs.2024.100147
- Quartz contents derived from particle density measurements improve the accuracy of soil thermal conductivity estimates L. Li et al. 10.1016/j.geoderma.2023.116526
- Relative Strengths Recognition of Nine Mainstream Satellite-Based Soil Moisture Products at the Global Scale X. Min et al. 10.3390/rs14122739
- Validation and expansion of the soil moisture index for assessing soil moisture dynamics from AMSR2 brightness temperature X. Meng et al. 10.1016/j.rse.2024.114018
- Potential of Mapping Global Soil Texture Type From SMAP Soil Moisture Product: A Pilot Study L. Zhao et al. 10.1109/TGRS.2021.3119667
- An advanced change detection method for time-series soil moisture retrieval from Sentinel-1 L. Zhu et al. 10.1016/j.rse.2022.113137
- Pedotransfer Functions of Soil Thermal Conductivity for the Textural Classes Sand, Silt, and Loam A. Markert et al. 10.2136/sssaj2017.02.0062
- Estimating 500-m Resolution Soil Moisture Using Sentinel-1 and Optical Data Synergy M. Foucras et al. 10.3390/w12030866
Latest update: 02 Apr 2025
Short summary
Soil thermal conductivity in wet conditions can be retrieved together with the soil quartz content using a reverse modelling technique based on sub-hourly soil temperature observations at three depths below the soil surface.
A pedotransfer function is proposed for quartz, for the considered region in France.
Gravels have a major impact on soil thermal conductivity, and omitting the soil organic matter information tends to enhance this impact.
Soil thermal conductivity in wet conditions can be retrieved together with the soil quartz...
