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@INPROCEEDINGS{Bogena:1049555,
author = {Brogi, Cosimo and Nieberding, Felix and Daccache, Andre and
Scheiffele, Lena and Dogar, Sardar Salar Saeed},
collaboration = {Bogena, Heye},
title = {{I}rrigation {M}anagement and {S}oil {M}oisture
{M}onitoring with {C}osmic-{R}ay {N}eutron {S}ensors:
{L}essons {L}earned and {F}uture {O}pportunities},
reportid = {FZJ-2025-05359},
year = {2025},
abstract = {Cosmic Ray Neutron Sensing (CRNS) is attracting attention
in irrigation management. CRNS can non-invasively and
accurately measure soil moisture (SM) in the root zone at
the field scale, thus addressing scale and logistics issues
typical of point-scale sensor networks. CRNS are effectively
used to inform large pivot irrigation systems but most
agricultural landscapes in Europe and elsewhere consist of
highly diversified and small fields. These are challenging
for CRNS as the measured signal integrates an area of ~200m
radius where multiple fields, soil heterogeneities, or
variable amount of water applications can be found.In this
work, we present results from three case studies, and we
develop and test solutions to improve CRNS accuracy in
irrigated contexts. In 2023, a potato field in Leerodt
(Germany) where strip irrigation is practiced was equipped
with three CRNS (with moderators and thermal shielding),
three meteorological stations, and six profile SM probes
measuring at six different depths (up to 60 cm). In the same
year, in Davis (California, USA), two CRNS with a 15 mm
moderator, one of which also had a thermal shielding, were
installed in an alfalfa field where flood irrigation is
practiced. These were supported by meteorological
measurements and point-scale TDR sensors. Similarly, a CRNS
installed in a winter wheat field in Oehna (Germany) where
pivot irrigation is applied. As the origin and propagation
of neutrons detected by a CRNS cannot be inferred from the
measured signal, we used the URANOS model to analyze neutron
transport in the three case studies under varying soil
moisture scenarios. To account for soil heterogeneity in the
Leerodt study, we assessed the spatial distribution of soil
characteristics by integrating soil sampling and
Electromagnetic Induction (EMI) measurements in a
machine-learning framework.The Leerodt study showed that
CRNS outperformed point-scale sensors, which were strongly
affected by soil erosion in the top 10 cm. However, CRNS was
unexpectedly sensitive only to nearby irrigation. Here, key
insights on sub-footprint heterogeneity and soil roughness
were gained through the analysis of URANOS simulations. In
the Davis study, CRNS effectively monitored irrigation but
also showed unexpected sensitivities to the irrigation of
distant fields. Again, important insights were gained thanks
to URANOS simulations. In the Oehna study, large
quantitative differences between the CRNS and point-scale
sensors were observed. However, the CRNS provided clear
responses to irrigation that can outperform the information
provided by the point-scale devices. Overall, the
limitations of CRNS-based irrigation management in complex
agricultural environments can generally be overcome through
a synergetic use of measurements and modelling. Nonetheless,
more efforts are needed to improve the understanding of the
underlying processes and to standardize measurement
procedures, which ultimately requires the involvement not
only of researchers but also of manufacturers and
stakeholders.},
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-egu25-12351},
url = {https://juser.fz-juelich.de/record/1049555},
}