Accounting for biomass water equivalent variations in soil moisture retrievals from cosmic ray neutron sensor

Cosmic ray neutron sensor (CRNS) has gained popularity in the last decade for its suitability in estimating area-averaged soil moisture (SM). The presence of fresh biomass influences the CRNS signal due to its water content, introducing bias to soil moisture estimation. Calibration and correction methods have been developed to account for this bias, but they usually require laborious sampling. Here, a novel approach is tested to assess the impact of biomass water equivalent (BWE) on CRNS soil moisture estimation. It was conducted in two contrasting environments from 15/11/21–1/02/23 for an olive orchard in Saudi Arabia, and from 15/02/22–30/03/23 for a cherry orchard in France. Water-uptake rates were monitored using sap flow sensors, as well as actual evapotranspiration (AET) and in-situ SM within the CRNS footprint. Concurrent environmental variables were also measured with a research-grade weather stations. It was found that when vapor pressure deficit (VPD) > 1.8kPa, CRNS-derived SM (CRNS-SM) closely matched in-situ SM measurements, which indicates minimal influence from BWE. Conversely, when VPD is lower than 1.8kPa, CRNS-SM overestimates the in-situ moisture. An optimization approach was used to find a temporally-varying value of N 0 parameter that minimizes the difference between soil moisture estimated with CRNS and in-situ sensors. Furthermore, the results showed that the relative change in the optimized value of N 0 (N 0,opt ) was well correlated with VPD in both orchards (R 2 = 0.66 for olive and R 2 = 0.74 for cherry orchards), indicating a strong correlation between these variables. These findings suggest that integrating VPD and CRNS observations, and using the VPD-N 0,opt correlation approach could be a promising way to account for the bias due to biomass dynamics on the estimation of area-averaged SM. • CRNS soil moisture affected by seasonal biomass water changes in orchards. • Vapor pressure deficit offers potential correction for biomass effects on CRNS signal. • CRNS overestimates soil moisture in dormancy, aligning well in warmer periods. • Time varying optimized N0 minimizes CRNS soil moisture estimation vs. in-situ.

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Publication Details

Journal
Agricultural Water Management
Published
2025-04-25
DOI
https://doi.org/10.1016/j.agwat.2025.109493
Citations
2
Primary Topic
Soil Moisture and Remote Sensing
Type
article
Field-Weighted Citation Impact
1.60

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article

Accounting for biomass water equivalent variations in soil moisture retrievals from cosmic ray neutron sensor

Trenton E. Franz, Claude Doussan, Susan Steele‐Dunne, Mohammad El Hajj et al.
2 citations
Agricultural Water Management
Soil Moisture and Remote Sensing
1.60
article

Accounting for biomass water equivalent variations in soil moisture retrievals from cosmic ray neutron sensor

Trenton E. Franz, Claude Doussan, Susan Steele‐Dunne, Mohammad El Hajj, Martin Schrön, Samer K. Almashharawi, Dominique Courault, Matthew F. McCabe
article en
2 citations

Abstract

Cosmic ray neutron sensor (CRNS) has gained popularity in the last decade for its suitability in estimating area-averaged soil moisture (SM). The presence of fresh biomass influences the CRNS signal due to its water content, introducing bias to soil moisture estimation. Calibration and correction methods have been developed to account for this bias, but they usually require laborious sampling. Here, a novel approach is tested to assess the impact of biomass water equivalent (BWE) on CRNS soil moisture estimation. It was conducted in two contrasting environments from 15/11/21–1/02/23 for an olive orchard in Saudi Arabia, and from 15/02/22–30/03/23 for a cherry orchard in France. Water-uptake rates were monitored using sap flow sensors, as well as actual evapotranspiration (AET) and in-situ SM within the CRNS footprint. Concurrent environmental variables were also measured with a research-grade weather stations. It was found that when vapor pressure deficit (VPD) > 1.8kPa, CRNS-derived SM (CRNS-SM) closely matched in-situ SM measurements, which indicates minimal influence from BWE. Conversely, when VPD is lower than 1.8kPa, CRNS-SM overestimates the in-situ moisture. An optimization approach was used to find a temporally-varying value of N 0 parameter that minimizes the difference between soil moisture estimated with CRNS and in-situ sensors. Furthermore, the results showed that the relative change in the optimized value of N 0 (N 0,opt ) was well correlated with VPD in both orchards (R 2 = 0.66 for olive and R 2 = 0.74 for cherry orchards), indicating a strong correlation between these variables. These findings suggest that integrating VPD and CRNS observations, and using the VPD-N 0,opt correlation approach could be a promising way to account for the bias due to biomass dynamics on the estimation of area-averaged SM. • CRNS soil moisture affected by seasonal biomass water changes in orchards. • Vapor pressure deficit offers potential correction for biomass effects on CRNS signal. • CRNS overestimates soil moisture in dormancy, aligning well in warmer periods. • Time varying optimized N0 minimizes CRNS soil moisture estimation vs. in-situ.

Agricultural Water ManagementVol. 313
University of Nebraska–Lincoln (US), Helmholtz Centre for Environmental Research (DE), Université d'Avignon et des Pays de Vaucluse (FR), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), King Abdullah University of Science and Technology (SA), Delft University of Technology (NL)
King Abdullah University of Science and Technology
Zero hunger
Openalex Percentile: Top 19%
Soil Moisture and Remote Sensing
1.60
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