Field testing of the universal calibration function for determination of soil moisture with cosmic-ray neutrons

2014 ◽  
Vol 50 (6) ◽  
pp. 5235-5248 ◽  
Author(s):  
David McJannet ◽  
Trenton Franz ◽  
Aaron Hawdon ◽  
Dave Boadle ◽  
Brett Baker ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Cosmic Ray ◽  
Field Testing ◽  
Calibration Function ◽  
Universal Calibration

scholarly journals A universal calibration function for determination of soil moisture with cosmic-ray neutrons

2012 ◽  
Vol 9 (9) ◽  
pp. 10303-10322 ◽  
Author(s):  
T. E. Franz ◽  
M. Zreda ◽  
R. Rosolem ◽  
T. P. A. Ferre
Keyword(s):  
Soil Moisture ◽  
Water Distribution ◽  
Neutron Transport ◽  
Cosmic Ray ◽  
Urban Environments ◽  
Calibration Function ◽  
Transport Code ◽  
Probe Site ◽  
Universal Calibration

Abstract. A cosmic-ray soil moisture probe is usually calibrated locally using soil samples collected within its support volume. But such calibration may be difficult or impractical, for example when soil contains stones, in presence of bedrock outcrops, in urban environments, or when the probe is used as a rover. Here we use the neutron transport code MCNPx with observed soil chemistries and pore water distribution to derive a universal calibration function to be used in such environments. Comparisons with independent soil moisture measurements at one cosmic-ray probe site and, separately, at thirty-five sites, show that the universal calibration function explains more than 75% of the total variation within each dataset, permitting accurate isolation of the soil moisture signal from the measured neutron signal.

scholarly journals A universal calibration function for determination of soil moisture with cosmic-ray neutrons

2013 ◽  
Vol 17 (2) ◽  
pp. 453-460 ◽  
Author(s):  
T. E. Franz ◽  
M. Zreda ◽  
R. Rosolem ◽  
T. P. A. Ferre
Keyword(s):  
Soil Moisture ◽  
Pore Water ◽  
Water Distribution ◽  
Neutron Transport ◽  
Cosmic Ray ◽  
The Other ◽  
Calibration Function ◽  
Neutron Intensity ◽  
Intensity Measurements ◽  
Universal Calibration

Abstract. A cosmic-ray soil moisture probe is usually calibrated locally using soil samples collected within its support volume. But such calibration may be difficult or impractical, for example when soil contains stones, in presence of bedrock outcrops, in urban environments, or when the probe is used as a rover. Here we use the neutron transport code MCNPx with observed soil chemistries and pore water distribution to derive a universal calibration function that can be used in such environments. Reasonable estimates of pore water content can be made from neutron intensity measurements and by using measurements of the other hydrogen pools (water vapor, soil lattice water, soil organic carbon, and biomass). Comparisons with independent soil moisture measurements at one cosmic-ray probe site and, separately, at 35 sites, show that the universal calibration function explains more than 79% of the total variability within each dataset, permitting accurate isolation of the soil moisture signal from the measured neutron intensity signal. In addition the framework allows for any of the other hydrogen pools to be separated from the neutron intensity measurements, which may be useful for estimating changes in biomass, biomass water, or exchangeable water in complex environments.

scholarly journals Use of cosmic ray neutron sensors for soil moisture monitoring in forests

2015 ◽  
Vol 12 (9) ◽  
pp. 9813-9864 ◽  
Author(s):  
I. Heidbüchel ◽  
A. Güntner ◽  
T. Blume
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Cosmic Ray ◽  
Soil Samples ◽  
Calibration Function ◽  
Neutron Sensors ◽  
Hydrogen Mass

Abstract. Cosmic ray neutron sensors (CRS) are a promising technique to measure soil moisture at intermediate scales. To convert neutron counts to average volumetric soil water content a simple calibration function can be used (the N0-calibration of Desilets et al., 2010). This calibration function is based on soil water content derived directly from soil samples taken within the footprint of the sensor. We installed a CRS in a mixed forest in the lowlands of north-eastern Germany and calibrated it 10 times throughout one calendar year. Each calibration with the N0-calibration function resulted in a different CRS soil moisture time series, with deviations of up to 0.12 m3 m-3 for individual values of soil water content. Also, many of the calibration efforts resulted in time series that could not be matched with independent in situ measurements of soil water content. We therefore suggest a new calibration function with a different shape that can vary from one location to another. A two-point calibration proved to be adequate to correctly define the shape of the new calibration function if the calibration points were taken during both dry and wet conditions covering at least 50 % of the total range of soil moisture. The best results were obtained when the soil samples used for calibration were linearly weighted as a function of depth in the soil profile and non-linearly weighted as a function of distance from the CRS, and when the depth-specific amount of soil organic matter and lattice water content was explicitly considered. The annual cycle of tree foliation was found to be a negligible factor for calibration because the variable hydrogen mass in the leaves was small compared to the hydrogen mass changes by soil moisture variations. Finally, we provide a best practice calibration guide for CRS in forested environments.

scholarly journals Use of cosmic-ray neutron sensors for soil moisture monitoring in forests

2016 ◽  
Vol 20 (3) ◽  
pp. 1269-1288 ◽  
Author(s):  
Ingo Heidbüchel ◽  
Andreas Güntner ◽  
Theresa Blume
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Cosmic Ray ◽  
Soil Samples ◽  
Calibration Function ◽  
Total Range ◽  
Hydrogen Mass

Abstract. Measuring soil moisture with cosmic-ray neutrons is a promising technique for intermediate spatial scales. To convert neutron counts to average volumetric soil water content a simple calibration function can be used (the N0-calibration of Desilets et al., 2010). The calibration is based on soil water content derived directly from soil samples taken within the footprint of the sensor. We installed a cosmic-ray neutron sensor (CRS) in a mixed forest in the lowlands of north-eastern Germany and calibrated it 10 times throughout one calendar year. Each calibration with the N0-calibration function resulted in a different CRS soil moisture time series, with deviations of up to 0.1 m3 m−3 (24 % of the total range) for individual values of soil water content. Also, many of the calibration efforts resulted in time series that could not be matched with independent in situ measurements of soil water content. We therefore suggest a modified calibration function with a different shape that can vary from one location to another. A two-point calibration was found to effectively define the shape of the modified calibration function if the calibration points were taken during both dry and wet conditions spanning at least half of the total range of soil moisture. The best results were obtained when the soil samples used for calibration were linearly weighted as a function of depth in the soil profile and nonlinearly weighted as a function of distance from the CRS, and when the depth-specific amount of soil organic matter and lattice water content was explicitly considered. The annual cycle of tree foliation was found to be a negligible factor for calibration because the variable hydrogen mass in the leaves was small compared to the hydrogen mass changes by soil moisture variations. As a final point, we provide a calibration guide for a CRS in forested environments.

THE DETERMINATION OF SOIL MOISTURE BY EXTRACTION AND GAS CHROMATOGRAPHY

Soil Science ◽  
1974 ◽  
Vol 117 (2) ◽  
pp. 120-123 ◽  
Author(s):  
E. L. MEREK ◽  
G. C. CARLE
Keyword(s):  
Gas Chromatography ◽  
Soil Moisture

Moisture and humidity dependence of the above-ground cosmic-ray neutron intensity revised

2021 ◽  
Author(s):  
Markus Köhli ◽  
Jannis Weimar ◽  
Benjamin Fersch ◽  
Roland Baatz ◽  
Martin Schrön ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Soil Moisture ◽  
Count Rate ◽  
Cosmic Ray ◽  
Mathematical Treatment ◽  
Specific Response ◽  
Parameter Equation ◽  
Neutron Count ◽  
Dry Conditions ◽  
Humidity Dependence

<p>The novel method of Cosmic-ray neutron sensing (CRNS) allows non-invasive soil moisture measurements at a hectometer scaled footprint. Up to now, the conversion of soil moisture to a detectable neutron count rate relies mainly on the equation presented by Desilets et al. (2010). While in general a hyperbolic expression can be derived from theoretical considerations, their empiric parameterisation needs to be revised for two reasons. Firstly, a rigorous mathematical treatment reveals that the values of the four parameters are ambiguous because their values are not independent. We find a 3-parameter equation with unambiguous values of the parameters which is equivalent in any other respect to the 4-parameter equation. Secondly, high-resolution Monte-Carlo simulations revealed a systematic deviation of the count rate to soil moisture relation especially for extremely dry conditions as well as very humid conditions. That is a hint, that a smaller contribution to the intensity was forgotten or not adequately treated by the conventional approach. Investigating the above-ground neutron flux by a broadly based Monte-Carlo simulation campaign revealed a more detailed understanding of different contributions to this signal, especially targeting air humidity corrections. The packages MCNP and URANOS were used to derive a function able to describe the respective dependencies including the effect of different hydrogen pools and the detector-specific response function. The new relationship has been tested at three exemplary measurement sites and its remarkable performance allows for a promising prospect of more comprehensive data quality in the future.</p>

scholarly journals Using Cosmic-Ray Neutron Probes in Validating Satellite Soil Moisture Products and Land Surface Models

Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1362 ◽  
Author(s):  
Mustafa Berk Duygu ◽  
Zuhal Akyürek
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Land Surface Model ◽  
Cosmic Ray ◽  
Surface Model ◽  
High Temporal Resolution ◽  
Land Surface Models ◽  
Statistical Measures ◽  
Surface Models ◽  
Global Land

Soil moisture content is one of the most important parameters of hydrological studies. Cosmic-ray neutron sensing is a promising proximal soil moisture sensing technique at intermediate scale and high temporal resolution. In this study, we validate satellite soil moisture products for the period of March 2015 and December 2018 by using several existing Cosmic Ray Neutron Probe (CRNP) stations of the COSMOS database and a CRNP station that was installed in the south part of Turkey in October 2016. Soil moisture values, which were inferred from the CRNP station in Turkey, are also validated using a time domain reflectometer (TDR) installed at the same location and soil water content values obtained from a land surface model (Noah LSM) at various depths (0.1 m, 0.3 m, 0.6 m and 1.0 m). The CRNP has a very good correlation with TDR where both measurements show consistent changes in soil moisture due to storm events. Satellite soil moisture products obtained from the Soil Moisture and Ocean Salinity (SMOS), the METOP-A/B Advanced Scatterometer (ASCAT), Soil Moisture Active Passive (SMAP), Advanced Microwave Scanning Radiometer 2 (AMSR2), Climate Change Initiative (CCI) and a global land surface model Global Land Data Assimilation System (GLDAS) are compared with the soil moisture values obtained from CRNP stations. Coefficient of determination ( r 2 ) and unbiased root mean square error (ubRMSE) are used as the statistical measures. Triple Collocation (TC) was also performed by considering soil moisture values obtained from different soil moisture products and the CRNPs. The validation results are mainly influenced by the location of the sensor and the soil moisture retrieval algorithm of satellite products. The SMAP surface product produces the highest correlations and lowest errors especially in semi-arid areas whereas the ASCAT product provides better results in vegetated areas. Both global and local land surface models’ outputs are highly compatible with the CRNP soil moisture values.

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