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@INPROCEEDINGS{Brogi:1049553,
author = {Brogi, Cosimo and Bogena, Heye Reemt and Huisman, Johan
Alexander and Jakobi, Jannis and Schmidt, Marius and
Montzka, Carsten and Bates, Jordan and Akter, Sonia},
title = {{S}imultaneous monitoring of soil water content and
vegetation with cosmic-ray neutron sensors: novel findings
and future opportunities},
reportid = {FZJ-2025-05357},
year = {2025},
abstract = {Accurate and continuous monitoring of soil water content
(SWC) and plant development provides significant benefits in
various contexts, including long-term environmental
observatories, the development and validation of
environmental models and remote sensing products, as well as
practical applications like digital and sustainable
agriculture. Cosmic-Ray Neutron Sensors (CRNS) are becoming
increasingly popular for continuous and non-invasive
monitoring of SWC, and recent advancements have demonstrated
their potential for vegetation monitoring. CRNS use a
moderated detector to measure epithermal neutron intensity
(En) and estimate SWC over a radius of approximately 200 m.
An additional bare detector measures lower-energy thermal
neutron intensity (Tn), which is more sensitive to
vegetation biomass than to SWC. However, the benefits of
simultaneous monitoring of SWC and vegetation properties
with CNRS for monitoring networks such as ICOS and ILTER
have not been investigated yet.In this study, a CRNS that is
part of the COSMOS-Europe network measured En and Tn over a
10-year period at the ICOS Class 1 ecosystem station in
Selhausen, Germany (integrated into the already-present
TERENO station in 2019). En and Tn were compared to a large
dataset of a) SWC obtained from multiple point-scale sensors
within 30 m of the CRNS, b) gross primary productivity (GPP)
obtained with the eddy covariance (EC) method, and c) manual
and drone-based measurements of plant height (PH), leaf area
index (LAI), and dry aboveground biomass (AGB).Discrepancies
between the CRNS and the point-scale SWC measurements were
observed (RMSE of 0.063 cm3/cm3). These were attributed to
the periodic reinstallation of the point-scale sensors that
sometimes led to abrupt changes in measured SWC, and to the
fact that the CRNS, like the EC station, measures over a
much larger area. Thanks to the co-location of the CRNS and
EC station, a comparison of Tn and GPP showed a clear
co-development during cropping periods and the lower
responsiveness of Tn during senescence and desiccation
indicated that factors such as plant structure and other
hydrogen pools (e.g., below-ground biomass) may affect Tn.
Crop-specific or annual models were used to estimate plant
traits from Tn. The accuracy of plant traits predicted by
the CRNS was relatively lower compared to manual and
destructive methods (RMSE of 0.13 m for PH, 1.01 m for LAI,
and 0.27 kg/m2 for dry AGB). However, the effortless nature
of the CRNS outweighs this reduction in accuracy, opening
the possibility of generating continuous time series of
plant traits with only a few manual measurements.This study
showcases the potential of CRNS for simultaneous field-scale
monitoring of SWC and vegetation, which is of great interest
for monitoring platforms and environmental modelling.
Moreover, the novel findings obtained by comparing Tn and
GPP showed that strengthened collaboration between
observatories and networks such as COSMOS, TERENO, and ICOS,
can provide information that is not only useful for
researchers but also for instruments manufacturers. In fact,
the possibility to extend the usage of CRNS beyond SWC and
toward monitoring of plant traits could increase the
interest towards thermal neutron detection and vegetation
monitoring.},
month = {Apr},
date = {2025-04-27},
organization = {EGU 2025, Vienna (Austria), 27 Apr
2025 - 2 May 2025},
subtyp = {Other},
cin = {IBG-3},
cid = {I:(DE-Juel1)IBG-3-20101118},
pnm = {2173 - Agro-biogeosystems: controls, feedbacks and impact
(POF4-217) / DFG project G:(GEPRIS)413955144 - Verbesserte
Quantifizierung von Bodenfeuchte und Biomasse durch
Kombination von bodengestützter Neutronen- und
LiDAR-Sensorik und Modellierung (413955144)},
pid = {G:(DE-HGF)POF4-2173 / G:(GEPRIS)413955144},
typ = {PUB:(DE-HGF)24},
doi = {10.5194/egusphere-egu25-12743},
url = {https://juser.fz-juelich.de/record/1049553},
}