Articles | Volume 20, issue 9
https://doi.org/10.5194/hess-20-3859-2016
© 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/hess-20-3859-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
19 Sep 2016
Research article |
| 19 Sep 2016
Incorporation of globally available datasets into the roving cosmic-ray neutron probe method for estimating field-scale soil water content
William Alexander Avery
School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
Catherine Finkenbiner
School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
Trenton E. Franz
CORRESPONDING AUTHOR
School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
Tiejun Wang
School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
Anthony L. Nguy-Robertson
School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
Andrew Suyker
School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
Timothy Arkebauer
School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
Francisco Muñoz-Arriola
School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
Biological Systems Engineering, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
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Cited
34 citations as recorded by crossref.
- Mapping soil moisture with the OPtical TRApezoid Model (OPTRAM) based on long-term MODIS observations E. Babaeian et al. 10.1016/j.rse.2018.04.029
- Effect of Biomass Water Dynamics in Cosmic-Ray Neutron Sensor Observations: A Long-Term Analysis of Maize–Soybean Rotation in Nebraska T. Morris et al. 10.3390/s24134094
- Practical Data Products From Cosmic-Ray Neutron Sensing for Hydrological Applications T. Franz et al. 10.3389/frwa.2020.00009
- Synergies for Soil Moisture Retrieval Across Scales From Airborne Polarimetric SAR, Cosmic Ray Neutron Roving, and an In Situ Sensor Network B. Fersch et al. 10.1029/2018WR023337
- A profile shape correction to reduce the vertical sensitivity of cosmic‐ray neutron sensing of soil moisture L. Scheiffele et al. 10.1002/vzj2.20083
- Making sense of cosmic-ray soil moisture measurements and eddy covariance data with regard to crop water use and field water balance E. Wang et al. 10.1016/j.agwat.2018.04.017
- Cosmic‐ray Neutron Rover Surveys of Field Soil Moisture and the Influence of Roads M. Schrön et al. 10.1029/2017WR021719
- Calibration and Validation of the Cosmic Ray Neutron Rover for Soil Water Mapping within Two South African Land Classes T. Vather et al. 10.3390/hydrology6030065
- Characterization of the Coherence Between Soil Moisture and Precipitation at Regional Scales D. Wu et al. 10.1029/2020JD034340
- Effects of Biomass and Soil Water Content Distribution on Cosmic Ray Neutron Probe Measurement Q. Wang et al. 10.3390/w15152766
- On the Information Content of Cosmic‐Ray Neutron Data in the Inverse Estimation of Soil Hydraulic Properties G. Brunetti et al. 10.2136/vzj2018.06.0123
- Evaluation of a cosmic-ray neutron sensor network for improved land surface model prediction R. Baatz et al. 10.5194/hess-21-2509-2017
- Deterministic chaotic dynamics in soil moisture across Nebraska C. Di et al. 10.1016/j.jhydrol.2019.124048
- Focus on the nonlinear infiltration process in deep vadose zone Y. He et al. 10.1016/j.earscirev.2024.104719
- Field Testing of Gamma-Spectroscopy Method for Soil Water Content Estimation in an Agricultural Field S. Becker et al. 10.3390/s24072223
- Spatial patterns of soil moisture from two regional monitoring networks in the United States T. Wang et al. 10.1016/j.jhydrol.2017.07.035
- Evaluating controls of soil properties and climatic conditions on the use of an exponential filter for converting near surface to root zone soil moisture contents T. Wang et al. 10.1016/j.jhydrol.2017.03.055
- Cosmic Ray Neutron Sensing for Simultaneous Soil Water Content and Biomass Quantification in Drought Conditions J. Jakobi et al. 10.1029/2018WR022692
- On the use of the critical event concept for quantifying soil moisture dynamics T. Wang et al. 10.1016/j.geoderma.2018.08.013
- Investigation of controls on the regional soil moisture spatiotemporal patterns across different climate zones D. Wu et al. 10.1016/j.scitotenv.2020.138214
- Comparison of environmental controls on soil moisture spatial patterns at mesoscales: Observational evidence from two regions in China T. Wang et al. 10.1016/j.geoderma.2020.114451
- Comment on Dong and Ochsner (2018): “Soil Texture Often Exerts Stronger Influence Than Precipitation on Mesoscale Soil Moisture Patterns” J. Jakobi et al. 10.1029/2020WR027790
- Multiscale soil moisture estimates using static and roving cosmic-ray soil moisture sensors D. McJannet et al. 10.5194/hess-21-6049-2017
- Response characteristics of the resistivity and water content during the imbibition process in remolded coal without gas J. Yue et al. 10.1002/ese3.452
- Uncertainty, sensitivity and improvements in soil moisture estimation with cosmic-ray neutron sensing G. Baroni et al. 10.1016/j.jhydrol.2018.07.053
- The Applicability of the Cosmic Ray Neutron Sensor to Simultaneously Monitor Soil Water Content and Biomass in an Acacia mearnsii Forest T. Vather et al. 10.3390/hydrology7030048
- Technical Note: Revisiting the general calibration of cosmic-ray neutron sensors to estimate soil water content M. Heistermann et al. 10.5194/hess-28-989-2024
- Error Estimation for Soil Moisture Measurements With Cosmic Ray Neutron Sensing and Implications for Rover Surveys J. Jakobi et al. 10.3389/frwa.2020.00010
- Status and Perspectives on the Cosmic‐Ray Neutron Method for Soil Moisture Estimation and Other Environmental Science Applications M. Andreasen et al. 10.2136/vzj2017.04.0086
- Soil Texture Often Exerts a Stronger Influence Than Precipitation on Mesoscale Soil Moisture Patterns J. Dong & T. Ochsner 10.1002/2017WR021692
- Evaluating the impacts of environmental factors on soil moisture temporal dynamics at different time scales Q. Chai et al. 10.2166/wcc.2020.011
- Toward Large‐Scale Soil Moisture Monitoring Using Rail‐Based Cosmic Ray Neutron Sensing D. Altdorff et al. 10.1029/2022WR033514
- Cosmic-Ray neutron Sensor PYthon tool (crspy 1.2.1): an open-source tool for the processing of cosmic-ray neutron and soil moisture data D. Power et al. 10.5194/gmd-14-7287-2021
- Evaluating climate and soil effects on regional soil moisture spatial variability using EOFs T. Wang et al. 10.1002/2017WR020642
34 citations as recorded by crossref.
- Mapping soil moisture with the OPtical TRApezoid Model (OPTRAM) based on long-term MODIS observations E. Babaeian et al. 10.1016/j.rse.2018.04.029
- Effect of Biomass Water Dynamics in Cosmic-Ray Neutron Sensor Observations: A Long-Term Analysis of Maize–Soybean Rotation in Nebraska T. Morris et al. 10.3390/s24134094
- Practical Data Products From Cosmic-Ray Neutron Sensing for Hydrological Applications T. Franz et al. 10.3389/frwa.2020.00009
- Synergies for Soil Moisture Retrieval Across Scales From Airborne Polarimetric SAR, Cosmic Ray Neutron Roving, and an In Situ Sensor Network B. Fersch et al. 10.1029/2018WR023337
- A profile shape correction to reduce the vertical sensitivity of cosmic‐ray neutron sensing of soil moisture L. Scheiffele et al. 10.1002/vzj2.20083
- Making sense of cosmic-ray soil moisture measurements and eddy covariance data with regard to crop water use and field water balance E. Wang et al. 10.1016/j.agwat.2018.04.017
- Cosmic‐ray Neutron Rover Surveys of Field Soil Moisture and the Influence of Roads M. Schrön et al. 10.1029/2017WR021719
- Calibration and Validation of the Cosmic Ray Neutron Rover for Soil Water Mapping within Two South African Land Classes T. Vather et al. 10.3390/hydrology6030065
- Characterization of the Coherence Between Soil Moisture and Precipitation at Regional Scales D. Wu et al. 10.1029/2020JD034340
- Effects of Biomass and Soil Water Content Distribution on Cosmic Ray Neutron Probe Measurement Q. Wang et al. 10.3390/w15152766
- On the Information Content of Cosmic‐Ray Neutron Data in the Inverse Estimation of Soil Hydraulic Properties G. Brunetti et al. 10.2136/vzj2018.06.0123
- Evaluation of a cosmic-ray neutron sensor network for improved land surface model prediction R. Baatz et al. 10.5194/hess-21-2509-2017
- Deterministic chaotic dynamics in soil moisture across Nebraska C. Di et al. 10.1016/j.jhydrol.2019.124048
- Focus on the nonlinear infiltration process in deep vadose zone Y. He et al. 10.1016/j.earscirev.2024.104719
- Field Testing of Gamma-Spectroscopy Method for Soil Water Content Estimation in an Agricultural Field S. Becker et al. 10.3390/s24072223
- Spatial patterns of soil moisture from two regional monitoring networks in the United States T. Wang et al. 10.1016/j.jhydrol.2017.07.035
- Evaluating controls of soil properties and climatic conditions on the use of an exponential filter for converting near surface to root zone soil moisture contents T. Wang et al. 10.1016/j.jhydrol.2017.03.055
- Cosmic Ray Neutron Sensing for Simultaneous Soil Water Content and Biomass Quantification in Drought Conditions J. Jakobi et al. 10.1029/2018WR022692
- On the use of the critical event concept for quantifying soil moisture dynamics T. Wang et al. 10.1016/j.geoderma.2018.08.013
- Investigation of controls on the regional soil moisture spatiotemporal patterns across different climate zones D. Wu et al. 10.1016/j.scitotenv.2020.138214
- Comparison of environmental controls on soil moisture spatial patterns at mesoscales: Observational evidence from two regions in China T. Wang et al. 10.1016/j.geoderma.2020.114451
- Comment on Dong and Ochsner (2018): “Soil Texture Often Exerts Stronger Influence Than Precipitation on Mesoscale Soil Moisture Patterns” J. Jakobi et al. 10.1029/2020WR027790
- Multiscale soil moisture estimates using static and roving cosmic-ray soil moisture sensors D. McJannet et al. 10.5194/hess-21-6049-2017
- Response characteristics of the resistivity and water content during the imbibition process in remolded coal without gas J. Yue et al. 10.1002/ese3.452
- Uncertainty, sensitivity and improvements in soil moisture estimation with cosmic-ray neutron sensing G. Baroni et al. 10.1016/j.jhydrol.2018.07.053
- The Applicability of the Cosmic Ray Neutron Sensor to Simultaneously Monitor Soil Water Content and Biomass in an Acacia mearnsii Forest T. Vather et al. 10.3390/hydrology7030048
- Technical Note: Revisiting the general calibration of cosmic-ray neutron sensors to estimate soil water content M. Heistermann et al. 10.5194/hess-28-989-2024
- Error Estimation for Soil Moisture Measurements With Cosmic Ray Neutron Sensing and Implications for Rover Surveys J. Jakobi et al. 10.3389/frwa.2020.00010
- Status and Perspectives on the Cosmic‐Ray Neutron Method for Soil Moisture Estimation and Other Environmental Science Applications M. Andreasen et al. 10.2136/vzj2017.04.0086
- Soil Texture Often Exerts a Stronger Influence Than Precipitation on Mesoscale Soil Moisture Patterns J. Dong & T. Ochsner 10.1002/2017WR021692
- Evaluating the impacts of environmental factors on soil moisture temporal dynamics at different time scales Q. Chai et al. 10.2166/wcc.2020.011
- Toward Large‐Scale Soil Moisture Monitoring Using Rail‐Based Cosmic Ray Neutron Sensing D. Altdorff et al. 10.1029/2022WR033514
- Cosmic-Ray neutron Sensor PYthon tool (crspy 1.2.1): an open-source tool for the processing of cosmic-ray neutron and soil moisture data D. Power et al. 10.5194/gmd-14-7287-2021
- Evaluating climate and soil effects on regional soil moisture spatial variability using EOFs T. Wang et al. 10.1002/2017WR020642
Latest update: 19 Nov 2024
Short summary
Here we present a strategy to use globally available datasets in the calibration function used to convert observed moderated neutron counts into volumetric soil water content. While local sampling protocols are well documented for fixed probes, the use of roving probes presents new calibration challenges. With over 200 fixed probes and 10 roving probes in use globally, we anticipate this paper will serve as a keystone for the growing cosmic-ray neutron probe and hydrologic community.
Here we present a strategy to use globally available datasets in the calibration function used...
