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

Journal Article (2025)
Author(s)

Samer K. Al-mashharawi (King Abdullah University of Science and Technology, TU Delft - Mathematical Geodesy and Positioning)

S.C. Steele-Dunne (TU Delft - Mathematical Geodesy and Positioning)

Marcel M. El Hajj (King Abdullah University of Science and Technology)

Martin Schrön (Helmholtz Centre for Environmental Research - UFZ)

Claude Doussan (Avignon University)

Dominique Courault (Avignon University)

Trenton E. Franz (University of Nebraska)

Matthew F. McCabe (King Abdullah University of Science and Technology)

Research Group
Mathematical Geodesy and Positioning
DOI related publication
https://doi.org/10.1016/j.agwat.2025.109493
More Info
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Publication Year
2025
Language
English
Research Group
Mathematical Geodesy and Positioning
Volume number
313
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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 N0 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 N0 (N0,opt) was well correlated with VPD in both orchards (R2 = 0.66 for olive and R2 = 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-N0,opt correlation approach could be a promising way to account for the bias due to biomass dynamics on the estimation of area-averaged SM.