Biomass water content effect on soil moisture assessment via proximal gamma-ray spectroscopy
Marica Baldoncini, Matteo Alberi, Carlo Bottardi, Enrico Chiarelli,, Kassandra Giulia Cristina Raptis, Virginia Strati, Fabio Mantovani

TL;DR
This study demonstrates that proximal gamma-ray spectroscopy, with proper biomass correction, can reliably monitor topsoil water content over time, offering a promising tool for automatic irrigation management at the field scale.
Contribution
The paper introduces a Monte Carlo-based biomass correction method for gamma-ray soil moisture assessment, validated through a 7-month field experiment with continuous data collection.
Findings
Gamma-ray signals inversely correlate with soil moisture levels.
Biomass correction reduces measurement discrepancy to about 3-4%.
Method effectively tracks soil water dynamics in agricultural fields.
Abstract
Proximal gamma-ray spectroscopy supported by adequate calibration and correction for growing biomass is an effective field scale technique for a continuous monitoring of top soil water content dynamics to be potentially employed as a decision support tool for automatic irrigation scheduling. This study demonstrates that this approach has the potential to be one of the best space-time trade-off methods, representing a joining link between punctual and satellite fields of view. The inverse proportionality between soil moisture and gamma signal is theoretically derived taking into account a non-constant correction due to the presence of growing vegetation beneath the detector position. The gamma signal attenuation due to biomass is modelled with a Monte Carlo-based approach in terms of an equivalent water layer which thickness varies in time as the crop evolves during its life-cycle. The…
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