Although research on cosmic-ray particles is connected to a variety of disciplines and applications, they all share similar questions and challenges regarding the physics of detection, modeling, and the influence of environmental factors.
The session brings together scientists from all fields of research that are related to monitoring and modeling of cosmogenic radiation. It will allow the sharing of expertise amongst international researchers as well as showcase recent advancements in their field. The session aims to stimulate discussions about how individual disciplines can share their knowledge and benefit from each other.
We solicit contributions related but not limited to:
- Health, security, and radiation protection: cosmic-ray dosimetry on Earth and its dependence on environmental and atmospheric factors
- Planetary space science: satellite and ground-based neutron and gamma-ray sensors to detect water and soil constituents
- Neutron and Muon monitors: detection of high-energy cosmic-ray variations and its dependence on local, atmospheric, and magnetospheric factors
- Hydrology and climate change: low-energy neutron sensing to measure water in reservoirs at and near the land surface, such as soil, snowpack, and vegetation
- Cosmogenic nuclides: as tracers of atmospheric circulation and mixing; as a tool in archaeology or glaciology for dating of ice and measuring ablation rates; and as a tool for surface exposure dating and measuring rates of surficial geological processes
- Detector design: technological advancements in the detection of cosmic rays and cosmogenic particles
- Cosmic-ray modeling: advances in modeling of the cosmic-ray propagation through the magnetosphere and atmosphere, and their response to the Earth's surface
- Impact modeling: How can cosmic-ray monitoring support environmental models, weather and climate forecasting, agricultural and irrigation management, and the assessment of natural hazards
Orals: Thu, 7 May, 08:30–10:15 | Room -2.92
Cosmic-ray neutron sensing (CRNS) has emerged as a powerful tool for monitoring near-surface water across a wide range of spatial scales, from soil moisture and snowpack on Earth to hydrogen mapping on planetary surfaces. While most terrestrial CRNS applications focus on environments with appreciable liquid water, far less is known about neutron behavior in extremely dry systems where hydrogen is sparse and primarily bound in minerals. These conditions are directly relevant to planetary neutron spectroscopy and provide an opportunity to connect environmental CRNS research with space science.
Here we present results from portable CRNS deployments at ultra-dry terrestrial analog sites, including Alvord Desert, Oregon, and the Namib Desert, Namibia. These campaigns targeted sites spanning very dry to dry conditions, dune and interdune settings, and minimal vegetation, allowing us to examine local-scale variability in moderated and bare neutron measurements under low-moisture endmember conditions. We apply state-of-the-art corrections for atmospheric pressure, water vapor, and incoming cosmic-ray intensity, and propagate counting statistics to assess uncertainty at rover-scale and field-scale integration times.
A central motivation for this work is the interpretation of passive neutron data acquired by the Dynamic Albedo of Neutrons (DAN) instrument on the Curiosity rover following the loss of its active pulsed neutron generator. Unlike terrestrial CRNS studies, Mars lacks direct ground-truth soil moisture measurements, and near-surface liquid water or ice is unstable at equatorial latitudes. As a result, the neutron signal is dominated by mineral-bound hydrogen and bulk composition effects. The terrestrial analog sites presented here provide a controlled framework for understanding neutron sensitivity, spatial variability, and correction strategies in similarly dry environments, while leveraging active neutron measurements and in situ sensors on Earth as calibration anchors.
Our results demonstrate that even under extremely dry conditions, corrected neutron counts exhibit measurable spatial and temporal structure, and that uncertainties associated with environmental corrections can be comparable to or exceed those from counting statistics. These findings highlight the value of cross-disciplinary collaboration between planetary science and environmental CRNS communities, and suggest that dry terrestrial analogs can play a key role in improving neutron-based water detection and modeling across Earth and planetary applications.
How to cite: Hardgrove, C. and Franz, T.: Cosmic-Ray Neutron Sensing in Ultra-Dry Environments: Linking Terrestrial Mars Analogs and Planetary Neutron Spectroscopy, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3177, https://doi.org/10.5194/egusphere-egu26-3177, 2026.
Cosmic Ray Neutron Sensing (CRNS) is a ground based technique that utilises epithermal neutron measurements as a proxy for environmental hydrogen content. Similarly, to other ground based cosmic ray detectors (e.g. neutron monitors), CRNS detectors observe the solar cycle and space weather events. Typically, these effects must be corrected, but CRNS detectors have also been specifically used to observe space weather. The specific sensitivity of CRNS detectors to the primary spectrum and the relationship to other cosmic ray measurements is not fully understood. During the maximum of solar cycle 25 a latitude survey utilising a mini neutron monitor (MNM), two CRNS detectors of different design and a muon telescope was undertaken onboard the German Research Vessel Polarstern. The observations are used to derive differential response functions and yield functions for two neutron detectors. While the differential response, between neutron detectors is similar, it strongly deviates between muon and neutron detectors. The yield functions of CRNS and MNM are in good agreement with each other, indicating that CRNS detectors and MNM observe a comparable range of the primary cosmic ray spectrum.
How to cite: Hertle, L., Baird, F., Schmidt, U., Heber, B., Walter, M., Krebs, N., Schattan, P., Dietrich, P., Zacharias, S., Landmark, S., Rasche, D., Kossatz, M., Womack, G., Hamann, S., Gazzola, E., and Schrön, M.: Latitude Survey of Neutrons and Muons to Determine Cosmic Ray Neutron Sensing YieldFunction, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18390, https://doi.org/10.5194/egusphere-egu26-18390, 2026.
Cosmic Rays Neutron Sensing (CRNS) is a method to derive the amount of water in the environment by the measurement of neutron albedo in the proximity of the soil. The signal is strongly affected by the incoming cosmic rays modulation, requiring a continuous real-time correction that is typically achieved by taking as a reference the observations provided by the Neutron-Monitor DataBase (NMDB). Using the incoming flux of muons as a reference has been proposed as an alternative method of correction by Finapp, whose CRNS detector is capable of contextually measuring both neutrons and muons.
What is noise for some can be signal for others, which leads to increasing collaboration between the CRNS and the Space Weather communities. While CRNS devices cannot provide a level of accuracy and resolution comparable to dedicated neutron monitors, they would compensate with the number of deployed detectors. Being low-cost, easy to install and maintain, their use is spreading fast for various purposes, from agriculture to environmental monitoring. This can be seen as a low-cost world-wide diffuse observatory, potentially with a much higher spatial density than the NMDB and spontaneously growing.
Assessing how neutron and muon count rates measured by these devices are affected by space weather events, like Forbush decreases or Ground-Level Enhancements (GLE), could increase the understanding and monitoring of such events by providing a mapping of their impact on the Earth surface. If the CRNS station is equipped with a Finapp detector, the contextual detection of muons can provide additional information.
In this presentation we will analyze how a small set of Finapp CRNS probes, located in different locations of Earth, responded to some major events of Furbush decrease or GLE, in the neutron and muon count rate signals. The set includes, among others, two probes located in NMDB sites (OULU and JUNG) and a probe installed in Svalbard. This aims to be an example of the potential interest of CRNS for Space Weather investigation. A large database of collected data may be already available and underused.
Acknowledgement
We acknowledge the NMDB database (www.nmdb.eu), founded under the European Union's FP7 programme (contract no. 213007) for providing data. Jungfraujoch neutron monitor data were kindly provided by the Physikalisches Institut, University of Bern, Switzerland. Oulu neutron monitor data were kindly provided by the Sodankyla Geophysical Observatory (https://cosmicrays.oulu.fi). CaLMa neutron monitor data were kindly provided by the Space Research Group (SRG-UAH), University of Alcala, Spain.
How to cite: Cracco, G., Gazzola, E., Schrön, M., Salzano, R., Landmark, S., Rödiger, T., and Daccache, A.: Can Cosmic Rays Neutron Sensors provide valuable data about space weather events?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11732, https://doi.org/10.5194/egusphere-egu26-11732, 2026.
Reliable assessment of soil water regime at the field scale is essential for understanding plant–soil interactions in managed grassland systems, yet remains challenging due to strong spatial heterogeneity and scale mismatches between soil moisture observations and vegetation response. Point-scale sensors provide detailed local measurements but often fail to represent field-scale conditions, while integrative approaches require independent validation to ensure their relevance for agrosystem functioning.
This study presents an integrated framework combining Cosmic-Ray Neutron Sensing (CRNS) with soil hydrophysical characterisation based on Soil Water Retention Curves (SWRC) to assess soil water regime dynamics and their relationship with vegetation response. CRNS-derived volumetric water content was interpreted relative to physically meaningful hydrophysical thresholds obtained from SWRC analysis, enabling continuous classification of soil moisture conditions across wet, optimal, and water-limited regimes.
Vegetation data were used as an independent indicator of soil water status to evaluate the consistency of CRNS–SWRC-derived regimes with observable plant responses. Field-scale grass growth dynamics were compared against classified soil moisture regimes to assess whether transitions in soil water availability were reflected in changes in vegetation productivity. This comparison allowed the identification of periods where vegetation response deviated from expected soil moisture conditions, highlighting potential anomalies related to root-zone decoupling, management interventions, or sub-footprint soil heterogeneity.
The results demonstrate that the combined CRNS–SWRC approach captures seasonal and event-scale variability in soil water regimes that correspond with observed grass growth patterns. At the same time, mismatches between soil moisture regimes and vegetation response provide valuable diagnostic information, enabling the detection of anomalous conditions not evident from soil moisture data alone.
The proposed framework extends beyond soil moisture monitoring by linking integrative hydrological measurements with biological response, offering a robust tool for field-scale assessment of soil–plant water interactions. This approach supports improved interpretation of soil water dynamics in heterogeneous agricultural landscapes and provides a foundation for anomaly detection and decision support in grassland management.
How to cite: Shishkin, K., Fenton, O., Murphy, P., Finkele, K., and Hochstrasser, T.: Linking field-scale soil water regimes with vegetation response using CRNS and soil hydrophysical thresholds: a case study in Ireland, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21790, https://doi.org/10.5194/egusphere-egu26-21790, 2026.
Cosmic-ray neutron sensing (CRNS) has shown its capability for estimating soil water content by providing spatially integrated measurements at an intermediate scale between invasive in-situ and satellite remote sensing observations. This constitutes a major advantage over point-scale sensors, which are often sparsely installed and are affected by small-scale heterogeneity, leading to uncertain absolute values. CRNS thus serves as an important link between local and larger scales and is increasingly used as a reference for remote sensing products and hydrological or land-surface models and other applications related to soil water balance. However, to fully close the scale gap observations are needed that reach the km scale.
Within the DFG-research Cosmic Sense and the European project SoMMet (21GRD08), a multiscale soil moisture monitoring was implemented by establishing a cluster of CRNS integrated with a range of complementary in-situ observations. This Potsdam Soil Moisture Observatory (PoSMO) was established in 2023 and features an accumulated CRNS footprint size of close to one km2 in total, constituting the largest long-term observation of epithermal cosmic-ray neutrons so far as well as the highest accumulated count rate of stationary CRNS worldwide. It comprises 16 stationary CRNS sensors located at an agricultural research site in the northeast of Germany, with some of the CRNS stations operated since end of 2019. They provide estimates of root-zone soil moisture at daily resolution, that is soil water content within the first decimeters of soil, but also co-located point-scale soil moisture measurements from shallow depth in 5 cm down to one meter. Intensive manual sampling campaigns of soil water content, bulk density, organic matter, and soil texture complement the dataset and enable robust CRNS calibration.
We discuss the PoSMO field set up, challenges associated with its design and the long-term monitoring operation. And we present the results of two years of harmonized soil water content time series from the different sensor types, including the CRNS cluster, shallow soil water content measurements, and soil water content profile data. Beyond the large area covered, CRNS and point sensors deliver also spatially resolved observations that will be shown as interpolated time-series of soil moisture maps for the inner part of the cluster. A sparser installation at the periphery and more singular sensors in the vicinity provide potential to even derive a soil moisture estimate for an area of up to 3.4 km2. Also, the potential benefit of accompanying physical measurements of the neutron spectrum (via Bonner spheres), muon measurements with a scintillator-based CRNS or roving CRNS may be discussed as well as the link to the Brandenburg state CRNS network.
How to cite: Oswald, S. E., Scheiffele, L., Grosse, P. M., Schiel, M., Heistermann, M., and Francke, T.: Results from a newly established long-term cosmogenic neutron observatory at kilometer scale with focus on soil water dynamics and distribution, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19089, https://doi.org/10.5194/egusphere-egu26-19089, 2026.
When high‑energy cosmic rays strike the upper atmosphere, they produce cascades of secondary particles, including fast neutrons that reach the Earth's surface. These neutrons are efficiently moderated by collisions with hydrogen atoms; consequently, the intensity of the neutron flux above ground decreases in proportion to the amount of water present—whether stored in the soil, in liquid form, or frozen as snow.
A stationary cosmic-ray neutron sensing (CRNS) detector records counts of these epithermal neutrons, and a single local water‑content reference is sufficient to convert the count rate into a quantitative estimate of soil moisture. The count‑versus‑moisture relationship has been shown to be remarkably consistent across diverse soils, climates, and geographic regions.
Because the calibration curve is essentially universal, typically only a single in‑situ reference measurement is required; thereafter, and retrospectively, the detector can continuously monitor spatially integrated changes in soil moisture. This simplicity has established CRNS as a valuable tool for agricultural water management, hydrological research, and field‑scale climate monitoring.
In contrast, converting neutron counts to snow water equivalent (SWE) for a sensor positioned above the snowpack has required extensive site‑specific calibration, which has hindered rapid network expansion. This difficulty arises from discrepancies between theoretical models and the limited empirical data available.
Based on a compilation of extensive in‑situ measurements at several montane locations within the Pre‑Alpine Terrestrial Environmental Observatory (TERENO Pre‑Alpine), we derived a set of empirical coefficients for the count–SWE relationship. Most locations in our dataset show good agreement with these empirical coefficients, although some outliers exist. Nevertheless, this empirical approach can reduce the effort required to establish new CRNS stations for SWE monitoring. We also evaluate transferability to alpine–nival sites—characterized by shallow soils, steep topography, and very high SWE—and analyze causes of deviations in the empirical approach’s performance due to site-specific environmental conditions.
How to cite: Fersch, B., Krebs, N., and Schattan, P.: Assessing an empirical approach to derive SWE from CRNS for pre‑alpine to high‑alpine locations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13972, https://doi.org/10.5194/egusphere-egu26-13972, 2026.
The accurate quantification of field-scale volumetric water content (VWC) is a critical requirement across multiple disciplines, from optimizing irrigation in precision agriculture to assessing slope stability and managing regional water resources. Cosmic-Ray Neutron Sensing (CRNS) is a pivotal non-invasive technology, providing integrated VWC estimates over large footprints (10–20 hectares) and significant depths (up to 80 cm). However, the interpretation of CRNS data in heterogeneous environments remains challenging. The inherently non-linear relationship between neutron intensity and hydrogen content, combined with a complex spatial weighting function, leads to "dry-region dominance," where the sensor response is disproportionately influenced by the drier portions of the soil. This research investigates these effects through a multidisciplinary workflow that integrates CRNS monitoring with preliminary geophysical spatial characterization. The first stage involved a purely synthetic investigation using the URANOS Monte Carlo neutron transport code to replicate the subsurface heterogeneity of the Borgo Grignanello site (Siena, Italy). To ensure a controlled and quantifiable comparison, the site was represented through a simplified two-region ground model characterized by distinct VWC values, constrained by several high-resolution Electrical Resistivity Tomography (ERT) transects and Electromagnetic Induction (EMI) data. This simplified framework provided a robust "forward model" and numerical proof of the dry-region bias: the derived VWC in the heterogeneous domain demonstrated an agreement with RMSE of 1.01% with the values of the drier region.
To provide empirical evidence for these synthetic findings, the second part of the research compares real CRNS time series with local TDR sensors during selected infiltration events. Given that the local sensors are positioned within the wetter units of the site, a significant incongruence between the two datasets is observed. This discrepancy serves as a direct experimental validation of the dry-region dominance predicted by the forward model, confirming that the CRNS signal is governed by the drier soil components, which effectively overshadow the moisture values of the wetter units in such heterogeneous contexts.
In conclusion, this work demonstrates that a multidisciplinary geophysical strategy is key to a more accurate interpretation of CRNS datasets. By integrating synthetic modeling with prior site characterization, this framework provides the reliable, spatially-aware insights necessary for effective hydrological modeling, natural hazard mitigation, and sustainable land management
How to cite: Cioffi, V., Peruzzo, L., Censini, M., Pavoni, M., Manca, F., Köhli, M., Weimar, J., and Cassiani, G.: Bridging Synthetic Modeling and Field Reality: Assessing Dry-Region Dominance in Cosmic-Ray Neutron Sensing via Geophysical Integration, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7994, https://doi.org/10.5194/egusphere-egu26-7994, 2026.
After three years, the European research project SoMMet (Soil Moisture Metrology) has come to an end. One of PTB’s (Physikalisch-Technische Bundesanstalt) tasks within this collaboration with 17 other institutes was to develop the Bonner sphere spectrometer (BSS) system NEMUS-UMW, capable of performing continuous, automated neutron spectrometry under outdoor conditions. PTB now plans to continue these activities by identifying new scientifically interesting sites for such measurements.
The BSS NEMUS-UMW uses 11 proportional counters to detect the neutron component of secondary cosmic radiation. By varying the sizes (3" to 10" in diameter) of the polyethylene moderating spheres surrounding the counters, and by using copper or lead shells in the larger spheres, the system covers an energy range from 10⁻⁹ MeV to 10³ MeV. Using the known response functions of the individual spheres, the neutron energy spectrum can be unfolded. The system was calibrated in the PTB neutron reference fields and is therefore capable of determining outdoor neutron spectra and radiation levels in absolute units of neutron fluence rate.
During SoMMet, the BSS NEMUS-UMW was deployed at the test field site ATB Marquardt (Potsdam, Germany). In collaboration with the University of Potsdam and Heidelberg University, surrounding field and soil parameters were monitored, and the measured neutron-spectrum time series was used to benchmark URANOS-based neutron simulations.
In January 2026, the BSS NEMUS-UMW was installed on the PTB premises in Braunschweig (Germany), where it has also been used to study the impact of heavy snowfall on neutron radiation in early 2026.
This presentation introduces the BSS NEMUS-UMW setup and data analysis, including corrections for environmental influences, and compares measurement results with simulations.
How to cite: Marach, J., Köhli, M., Weimar, J., Grosse, P., Reginatto, M., and Zboril, M.: Environmental Neutron Spectrometry: Continuous outdoor measurement with the PTB Bonner sphere spectrometer NEMUS-UMW, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19701, https://doi.org/10.5194/egusphere-egu26-19701, 2026.
Cosmic-ray muography is a developing geophysical method that uses high energy cosmic muon particles to explore the inner structure of large objects, such as volcanoes, pyramids or mountains. Cosmic muons originate from upper atmosphere and have a known, steady, angle dependent flux on the surface. Muons are absorbed as they pass through matter, depending on the density of the material along their trajectories. By comparing the expected and the measured muon flux and using geoinformatic models of the observed area it is possible to calculate the density distribution inside these structures. Our research group at the HUN-REN Wigner Research Centre for Phyiscs has been conducting muographic measurements in the abandoned iron ore mine of Esztramos Hill (located in northeastern Hungary) for more than six years. Over the years we created muographic images of the hill from multiple drifts, resulting in a detailed understanding of its inner structure around the abandoned parts of the mine and the Rákóczi cave system, the main cave of which is part of the UNESCO World Heritage List. Based on a 3-D muographic inversion, our results were able to confirm the location of partially collapsed, inaccessible mined-out stopes and indicate the existence of a possible cave nearby, which was published in Scientific Reports last year.
How to cite: Rábóczki, B., Surányi, G., Balázs, L., and Hamar, G.: Exploring the inner structure of Esztramos Hill using cosmic rays, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19012, https://doi.org/10.5194/egusphere-egu26-19012, 2026.
Muography is a rapidly evolving interdisciplinary field that uses cosmic-ray muons to image the internal structure of large objects. Muons are highly penetrating particles whose energy loss depends on the distance traveled in a medium (e.g., rock) and on the medium’s density. By detecting and analyzing muons that pass through an object, it is possible to reconstruct its internal density distribution. This emerging method offers new opportunities in areas such as mining, volcano monitoring, cave exploration, archaeology, and structural diagnostics.
The muography project portfolio of HUN-REN Wigner Research Centre for Physics is actively engaged in developing hardware and software for muography detectors, as well as in advancing data-processing techniques and exploring potential applications. We maintain several international collaborations, within which multiple successful measurements have been conducted in active European mines.
In this presentation, we focus on muograpic measurements conducted in the Jánossy Underground Laboratory. This lab is located on the KFKI Campus in Budapest, Hungary, provides a well-characterized environment ideally suited for testing our detectors and evaluating the various steps of muography data processing. The main objective of this measurement program is to build a comprehensive dataset that supports the refinement of data processing methods, the testing of different inversion techniques, and precision parameter analysis using well-defined artificial anomalies (tunnels). We will discuss the results of a series of measurements carried out at the laboratory and the developments derived from these studies:
- validation of the direct problem
-inversion distortion analysis and sensitivity test
-precision parameter analysis (diameter, direction, position) using known tunnels
How to cite: Stefán, B. A., Hamar, G., Balázs, L., and Surányi, G.: Development of muography data processing and procedures, inversion and precision parameter analysis based on measurements performed at the Jánossy Underground Laboratory, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1255, https://doi.org/10.5194/egusphere-egu26-1255, 2026.
Since mid 2024 a CRNS detector has been installed in Kiel close to the Kiel neutron monitor (NM). The latter is a measure of the incoming cosmic ray induced neutron environment and is used to correct the CRNS data in order to determine the soil moisture in the surrounding area of the system.
The fact that the CRNS detector and the NM are at the same location allows a unique insight into the correlation of both measurements. Since both count rates are expected to decrease during Forbush Decreases (FDs) we can investigate their correlation during all FDs observed from mid 2024. In contrast, the correlation is far lower during the occurrence of rain events, which can lead to a similar shaped decrease in the count rate. The analysis has been repeated utilizing NMs at different locations (e.g. Jungfraujoch) in order to estimate the uncertainties of the above analysis. Furthermore, the count rates of different CRNS detectors have been compared for FDs as well as rain events to see if a distinction between both is possible without the use of a NM.
How to cite: Giese, H., Böttcher, S., Heber, B., Herbst, K., Hertle, L., and Schrön, M.: Cosmic Ray Neutron Sensing (CRNS) as a Space Weather Tool?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12686, https://doi.org/10.5194/egusphere-egu26-12686, 2026.
Cosmic rays generate an ever-present radiation field in Earth’s atmosphere, right down to the ground. On rare occasions, high energy particles accelerated at the Sun can increase this radiation field, in events known as Ground Level Enhancements (GLEs). November 11th 2025 saw the strongest GLE in nearly 25 years: GLE 77. The event resulted in the count rate of some sea level neutron monitors exceeding 100% of the pre-event mean. In this contribution, we present a comprehensive set of observations of the event made from the UK and the Netherlands. At ground level, we present data from the Compact Neutron Monitors in Guildford, in the south of the England, and Shetland, off the north coast of Scotland. Dose rate measurements are presented from SAIRA instruments onboard two trans-Atlantic flights during the event. In addition, the data from SAIRA instruments onboard weather balloons, launched from Shetland, Cornwall, and the Netherlands, are presented. Finally, modelling results derived from the MAIRE-S system will be shown briefly.
How to cite: Baird, F., Clewer, B., Davis, C., Ryden, K., Dyer, C., and Lei, F.: Observations of GLE 77 from the Ground, On Aircraft and Balloons, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20506, https://doi.org/10.5194/egusphere-egu26-20506, 2026.
Cosmic-ray neutron sensors (CRNSs) provide state-of-the-art soil moisture measurements at a field scale. This sensing technique utilises cosmic-ray neutrons which need to be corrected for any temporal changes due to the external factors other than soil moisture. These typically include corrections for changes in humidity, pressure and the incoming flux of neutrons. The last correction is strongly linked with the changes in the solar activity and typically uses standardized neutron monitors (NMs), which are in operation around the world, as the reference signal. Different approaches have emerged for calculating the correction parameter, often referred to as ‘tau’, which accounts for location differences between the CRNS and NM stations. This work is a case study of the published incoming neutron flux correction parameters (taus) applied to the UK COsmic-ray Soil Moisture Observing System (COSMOS-UK) network. We investigate the impact of the different approaches on the resulting soil moisture and compare them against a correction parameter derived using the local CRNS data (gamma), and also against the available point sensor soil moisture measurements. We discuss the potential causes of discrepancies between the published (tau-based) methods and our insitu (gamma-based) method, especially in the context of soil moisture trends visible at some COSMOS-UK sites when using the tau-based methods.
How to cite: Evans, J., Szczykulska, M., and Howson, T. and the COSMOS-UK Team: COSMOS-UK incoming neutron intensity correction case study for soil moisture monitoring using cosmic-ray neutron sensors, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20428, https://doi.org/10.5194/egusphere-egu26-20428, 2026.
Cosmic Ray Neutron Sensing (CRNS) has been established as a reliable method for measuring Soil Moisture (SM) at an intermediate spatial scale, bridging the gap between point-scale measurements and satellite observations. While CRNS stations are increasingly included in meteorological and environmental monitoring networks, integration and intercomparison between different methods remain tricky.
Different technologies not only explore different scales of observations, but they do that through different physical methods, with possibly different responses to the same event. CRNS relies on the correlation of SM with the count of environmental neutrons, generated by cosmic rays and absorbed by hydrogen in water. While a standard conversion formula is widely used, it’s known to significantly deviate from experimental validation under extreme conditions of either dryness or wetness. For this reason, new formulas have been proposed and are in a phase of validation.
The SoMMet (Soil Moisture Metrology) project, funded by EURAMET (European Partnership on Metrology), was set up to develop metrological tools to enhance traceability and harmonization across different methods of SM observation. As part of the SoMMet project activities, various commercial CRNS probes were tested in SI-traceable reference neutron fields at participating national metrology institutes. The understanding of detector performance under laboratory conditions and the validation of Monte Carlo (MC) neutron transport modelling can be used to predict the detector response under real field conditions.
The development and validation of the specific MC model for the CRNS detector manufactured by Finapp has been recently published by the SoMMet Collaboration [1] and it introduces a new conversion formula. We will here review the SoMMet activities on characterization and MC model validation of the Finapp CRNS probe, performed in the reference neutron fields of Czech Metrology Institute (CMI) and Slovak Institute of Metrology (SMU) and consequent model verification at the Physikalisch-Technische Bundesanstalt (PTB), Germany.
As a first application to real-world conditions, we apply the SoMMet conversion formula to the datasets of two automated snow stations managed by the Office for Hydrology and Dams of the Civil Protection Agency of the Autonomous Province of Bolzano, Italy, equipped with Finapp CRNS sensors. The two sites (Pian dei Cavalli and Malga Fadner) are mountain sites at elevations above 2000 m, characterized by a very low soil bulk density and a very high water content, with presence of peatland in the footprint. The CRNS measurement was calibrated by the standard gravimetric campaign, but the standard conversion formula provides physically unrealistic results. The formula proposed by SoMMet is successfully applied.
[1] Z. Vykydal et al. (2025), Monte Carlo Simulation and Experimental Validation of the Finapp Model 3 Cosmic-Ray Neutron Sensor. Meas. Sci. Technol., in press, DOI:10.1088/1361-6501/ae2649
Aknowledgments: The project 21GRD08 SoMMet received funding from the European Partnership on Metrology, co-financed from the European Union’s Horizon Europe Research and Innovation Programme and by the Participating States.
How to cite: Gazzola, E., Vykydal, Z., Nadalet, R., Pernter, M., Dinale, R., Gianessi, S., and Biasuzzi, B.: The SoMMet characterization of a Finapp Cosmic-Ray Neutron Sensor and its first real-world application, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18160, https://doi.org/10.5194/egusphere-egu26-18160, 2026.
Accurate estimation of soil water content in the root zone (e.g., 0 – 30 cm) is essential for designing irrigation schedules and requires measurements that represent the field scale. Cosmic Ray Neutron Sensing (CRNS) offers a non-invasive solution that provides integrated soil moisture measurements with a horizontal footprint of approximately 7 to14 hectares and depths ranging from 15 to 83 cm, making it suitable in an area with a homogenous land use, like agricultural fields. However, CRNS sensitivity varies with both distance and depth relative to the sensor, complicating its use for estimating soil moisture in specific layers. When soil moisture is known, it is feasible to perform a forward calculation to derive neutron counts from soil water content. In this study, such calculations were performed using COSMIC, integrated with the HYDRUS-1D model. However, backward calculations, deriving soil water content from neutron counts, are not straightforward. This is because wetting and drying processes start at the soil surface, where CRNS is most sensitive. Consequently, the integrated measurement disproportionately reflects changes in the upper layers, creating a non-unique or hysteretic relationship between neutron counts and soil moisture during wetting and drying cycles. This makes predicting the 0 – 30 cm water content from neutron counts particularly challenging.
To address these limitations, we explore the application of the Long Short-Term Memory (LSTM) model to predict the average soil water content in the 0 – 30 cm layer by training the model using time series of average 0 – 30 cm soil water content and neutron counts (simulated with HYDRUS-1D COSMIC) as well as meteorological data (precipitation and reference evapotranspiration). The LSTM model is well-suited because it can learn temporal dependencies and patterns of long sequence data. The initial simulations were based on three years record of synthetic data under bare soil conditions for a region in Flanders, Belgium. While initial findings indicate a potential, further research will focus on improving the model’s robustness by training the model with more diverse variables, expanding the dataset, and integrating field measurement soil moisture records to enhance its applicability across different scenarios. This research highlights the feasibility of combining CRNS measurement, physically based modelling, and data-driven techniques to improve soil moisture estimation for irrigation management.
How to cite: Kalsum, A. U., Janssens, P., Vanderborght, J., and Diels, J.: Long Short-Term Memory model to predict root zone soil water content from neutron count measured by Cosmic Ray Neutron Sensing, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16311, https://doi.org/10.5194/egusphere-egu26-16311, 2026.
The exponentially growing population drives the intensification of agricultural production, which contributes to land and water quality degradation, biodiversity loss, and climate change. In this regard, nature-based solutions like silvoarable agroforestry systems, which integrate trees on arable land, have taken a new dawn due to their potential multifaceted benefits derived from nature’s contributions to people. Among the limiting factors in sustainable agricultural production is water availability, which governs biogeochemical processes, such as the regulation of material fluxes, nutrient availability and movement, carbon sequestration, microbial activity, and modification of soil properties. In temperate agroforestry systems, soil moisture regimes are not well understood. Efforts in collecting long-term data are of high importance, particularly in determining how agroforestry systems in temperate climates affect water availability and, therefore, their potential to support food production under current and future climate conditions. Knowledge of soil moisture could help in understanding whether agroforestry systems improve water availability for crop growth, which would offer resilience against droughts, or, on the other hand, cause competition with trees that reduces soil moisture availability.
In this ongoing study, we investigate point- and field-scale soil moisture dynamics in a six-year-old organic alley cropping system in Hessen, Germany. The system consists of six strips of 3-meter-wide tree rows with apple, poplar, and timber trees, alternated with 18-meter-wide crop alleys. We instrumented three transects with Frequency Domain Reflectometry (FDR) soil moisture sensors at 1, 2.5, 6, and 10.5 meters perpendicular from the tree row (upslope and downslope) at 10, 40, and 60 cm depths, to study soil moisture dynamics along the tree-crop interface. We also employed three cosmic ray neutron sensors (CRNS) to assess the field-scale trend and dynamics of the soil moisture based on the inverse relationship of the amount of hydrogen (water) in the soil and the intensity of epithermal neutrons over its dynamic footprint. Here, we present our experimental setup to capture both the transect-point scale and field-scale spatiotemporal soil moisture patterns and show preliminary findings for a full cropping season. Such an approach has the potential to provide soil moisture data at different scales relevant to efficient system design, tree-crop species selection, and agricultural water management.
How to cite: Felipe, A. J., Asadi, F., Breuer, L., and Jacobs, S.: Estimation of Spatiotemporal Soil Moisture Dynamics in a Temperate Organic Alley Cropping System in Hessen, Germany, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11143, https://doi.org/10.5194/egusphere-egu26-11143, 2026.
Memory effects are ubiquitous in geophysical systems, arising from internal dynamics and interactions with external forcings across multiple timescales. Within land surface systems, soil moisture memory is a key factor governing land–atmosphere feedbacks, influencing the intensity, persistence, and predictability of hydro-climatic extremes such as droughts and floods. This study quantifies soil moisture memory across the CosmOz-Australia network using long-term Cosmic Ray Neutron Sensing (CRNS) observations and characterizes memory across land surface and meteorological timescales.
The CRNS technique offers a novel, field-scale measurement of soil moisture with high temporal resolution and a time-varying effective sensing depth, thereby overcoming the limitations of traditional point-scale observations and enabling the robust characterization of soil moisture memory across various timescales. Despite the widespread application of CRNS data for soil moisture monitoring and validation, their potential for systematic, multi-timescale soil moisture memory estimation has not yet been explored.
This study estimates the short-term energy-limited (τs) and long-term water-limited (τL) memory components applying a hybrid stochastic-deterministic modeling framework that represents rapid surface-layer responses and slower root-zone and subsurface controls at the land surface scale. In addition, to capture memory at the meteorological scale, we estimate a non-parametric, model-free entropy-based effective memory timescale that quantifies information persistence beyond linear correlations, and compute the e-folding memory timescale as a standard measure of decorrelation. Results reveal pronounced spatial heterogeneity in soil moisture memory across Australia. Short-term memory is consistently low (median τs ≈ 0.3–1.0 days), reflecting rapid drying over the effective sensing depth and low memory in drylands. Long-term memory (median τL ≈ 4–11 days) is highest over the humid eastern and south-eastern regions, consistent with a water-limited evapotranspiration regime where higher precipitation frequency, lower aridity, finer soils, and denser vegetation enhance root-zone storage and slow anomaly decay. Entropy-based effective memory ranges from approximately 19 to 36 days, indicating substantial information retention at monthly timescales, while e-folding timescales extend up to ~70 days in temperate and monsoon-influenced regions. The strong spatial agreement between entropy-based and correlation-based metrics suggests robust and consistent soil moisture memory regimes across Australia, highlighting their dependence on hydro-climate, soil texture, and vegetation. The results provide observation-based characterization of multi-timescale soil moisture memory using CRNS data, with important implications for land surface model evaluation, drought diagnostics, and sub-seasonal to seasonal climate forecasting.
How to cite: Mishra, N., Rajdeep, N., Pichuka, S., Faggian, R., and McJannet, D.: Characterizing Multi-Timescale Soil Moisture Memory across Australia's CosmOz Network, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4249, https://doi.org/10.5194/egusphere-egu26-4249, 2026.
The need to measure soil moisture accurately and continuously and to monitor its climatic impact has moved into the public focus through the rising number of flood events and droughts in recent years. Currently the German Meteorological Service (DWD) operates a soil moisture viewer based on the soil-vegetation-atmosphere-model AMBAV and provides agrometeorological consultation. In addition to modelled soil moisture data, several institutions and some federal states started to set up their own soil moisture observations locally, but a nationwide observation network is still lacking in Germany.
The DWD’s internal project IsaBoM (“Integration of standardized and automatized soil moisture measurements in the DWD observation network”) aims to prepare the introduction of automized soil moisture measurements with two complementary measuring systems (in-situ sensors and Cosmic-Ray Neutron Sensing - CRNS), following the guidelines of the WMO (World Meteorological Organization) to permanently monitor this essential climate variable. The project’s tasks are, amongst other aspects, testing and selecting suitable sensors and calibration procedures, setting up data analysis methods, preparing the automatic dataflow and public data provisioning and ultimately providing solutions to integrate the soil moisture data into the existing operational models.
Here, we present the progress of the project IsaBoM for the preparation of a nationwide soil moisture network starting with 20 preliminary designated stations of the DWD’s operational network, where the chosen locations are representative of the soil properties and climatic conditions throughout Germany, while also being equally distributed geographically. We report on first results from our two test sites in Braunschweig and Dürnast (Freising), where the parallel measurements of multiple arrays of in-situ sensors and several CRNS sensors are tested on two operational DWD measurement sites differing in soil type and climate and providing additional meteorological measurements. We show first comparisons of soil moisture estimates from CRNS detectors with different sensitivities and the observed effects of precipitation, vegetation cover and irrigation on the signal. The CRNS signals at both stations are calibrated using repeated soil sampling campaigns with varying equipment. Additionally, experimental sensor layouts (arrangement of in-situ profiles towards the CRNS) are used to further test the comparability and synergies between the two systems.
Feasible solutions and means for the optimal utilization of both soil moisture measuring systems, while adapting to the particular conditions when deployed on operational meteorological measurement sites, are discussed with regards to the chances and challenges from the perspective of a meteorological service.
How to cite: Albert, M., Herbst, M., Hufnagl, L., Kurtz, W., and Lenkeit, J.: Integration of in-situ and Cosmic-Ray Neutron Sensing derived soil moisture measurements into the observation network of the German Meteorological Service – progress of the project IsaBoM, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4197, https://doi.org/10.5194/egusphere-egu26-4197, 2026.
Reliable soil moisture observations are pivotal for informing sustainable agricultural decisions under an ongoing changing climate. A cosmic-ray soil moisture observing system (SI-COSMOS) network was established for the period 2025-2040 to enhance soil moisture monitoring in Slovenia. The rationale was based on extensive experience with point soil moisture sensors in operational decision-making at the farm level, where they proved highly vulnerable to damage from land operations and wildlife activity. At the same time, the information was limited to micro-local conditions. As an alternative, a less vulnerable, non-invasive, intermediate soil-moisture network was established. As of Jan 2026, the network consists of 14 cosmic ray neutron sensors (CRNS). In this contribution, we present the network architecture, current calibration experiences, and discuss the network's role in the national and international context.
SI-COSMOS locations spread across the Continental, Alpine, Karst, Mediterranean, and Pannonian regions. Installed are lithium fluoride and boron carbide-based CRNS. The network's elevation ranges from 10 m to 500 m above sea level. Land use at locations includes olive groves (3), grasslands and pastures (2), hop plantations (2), mixed land-use systems (6), and forest (1), mainly under rainfed, but also irrigated (drip, drum, and pivot) conditions. Soil moisture is captured in various soil types.
At the national scale, the vision of SI-COSMOS is to support investigating soil–water-plant–atmosphere interactions under diverse climate, land-use, and soil conditions, to support improved drought detection and management, as well as hydrological modelling and applications. Additionally, the network aims to further develop and validate surface soil moisture products based on remote sensing or modelled data, for improved large-scale soil moisture observations at the national and international scales. Products based on SI-COSMOS will support development of transferable real-time land management tools for enhanced water resilience.
Acknowledgements: This research was funded by the Slovenian Research Agency (ARRS) with a grant to the Ph.D. students Nejc Golob and Špela Srdoč, and partially supported by research programme P4-0085, national targeted research project (V4-2406), Interreg Alpine Space program, project Alpine Space Drought Prediction (A-DROP) (grant number 101147797), European Union – LIFE Programme (LIFE23-IPC-SI-LIFE4ADAPT), OPTAIN Horizon 2020 (grant number 862756), the NextGenerationEU project ULTRA 4. Sustainable Environment, and the Slovenian CAP Strategic Plan 2023–2027.
How to cite: Cvejić, R., Bavec, M., Glavan, M., Golob, N., Klopčič, M., Korošec, T., Mikoš, M., Naglič, B., Noč, M., Pečan, U., Pirman, T., Podgornik, M., Rusjan, D., Srdoč, Š., Stajnko, D., Švegelj, Ž., and Zupanc, V.: Recent developments in cosmic ray soil moisture observing system in Slovenia, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8396, https://doi.org/10.5194/egusphere-egu26-8396, 2026.
Soil water content (SWC) is a key variable in hydrology, agriculture, and climate research, but large-scale measurements remain challenging due to spatial heterogeneity and logistical limitations. Stationary Cosmic Ray Neutron Sensing (CRNS) provides intermediate-scale estimates (~200m footprint), yet covers only local areas. Mobile Rail-CRNS platforms overcome this by enabling continuous SWC mapping along hundreds of kilometers of railway networks. In 2024, the UFZ operated five such Rail-CRNS systems, collecting data up to hundredth of kilometer daily across diverse landscapes in Germany. However, rail roving multiplies exposure to dynamic environmental influences (e.g., tunnels, bridges, parallel tracks, urban areas, water bodies, roads, topography, biomass/forest types), which can systematically bias neutron signals. Further, inaccuracies in GPS positioning can cause the measurement positions to be several meters off the track. At this data volume, manual screening is infeasible, automated detection, flagging, and quantitative scoring of these influences are required for data quality control and correction.
Here we present a fully automated, Python-based pre-processing pipeline that evaluates measurements at both point and segment levels. GPS positions are first snapped to OSM railway tracks (nearest-points projection) to correct for localization errors. Each point is then queried for proximity to OSM features, tree species from the German Aerospace Center and DEM-derived topography, using configurable minimum feature sizes (e.g. length of a river, tunnel), influence radii, and weights (e.g., tunnel > bridge). These parameters can be flexibly adjusted and regionally adapted. To address the integral nature of mobile measurements, we introduce segment-based scoring: Intervals between consecutive points are subdivided into subsamples (minimum 3, additional every ~10 m for longer segments), incorporating direction (azimuth) for asymmetric effects (e.g., lateral slopes) guaranteeing its real length but its planar projection. Influences are evaluated proportionally. In addition, for segments above a defined length, a speed flag is added to indicate reduced data density and reliability.
An interactive map allows you to review the selected settings in relation to the potentially influencing features: Segment colors reflect its cumulative scores, flags as rings in relation to its cause, and geo-layers toggleable. Mouse-over tooltips provide instant score breakdowns for iterative parameter tuning.
The pipeline enables targeted filtering of uncertain segments, application of region- or forest-type-specific correction factors, and integrative comparison of land-use groups (point vs. segment scale). Initially tested on a pilot transect in the Harz Mountains (~ 8 km), ~60% were marked as having substantial impacts, demonstrating its necessity as well as its robustness and practical applicability. Fully transferable across Germany, it paves the way for consistent, large-scale Rail-CRNS SWC mapping. Future steps include machine-learning-based weight optimization.
How to cite: Altdorff, D., Landmark, S., Zacharias, S., Oswald, S. E., Dietrich, P., Attinger, A., and Schrön, M.: Automated Contextual Pre-processing of Mobile Rail-CRNS Measurements for Large-Scale Soil Water Content Assessment , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12026, https://doi.org/10.5194/egusphere-egu26-12026, 2026.
The highly interdisciplinary method of Cosmic Ray Neutron Sensing (CRNS) has emerged as a key technology for monitoring root-zone soil moisture at the hectare scale. The technique bridges the spatial gap between traditional point-scale measurements and coarser remote sensing products. While CRNS is widely used in agriculture and weather services, processing of its data requires advanced knowledge about cosmic-ray physics. With the increasing adoption of CRNS across research infrastructures and observatories world-wide, standardised, flexible, and easy-to-use processing tools are essential for supporting data integration within these networks. Here we present neptoon, an open-source Python tool for neutron data processing that addresses these highly interdisciplinary challenges. It implements a modular, expandable framework to support both operational deployment of CRNS, as well as methodological innovation. Building from previous CRNS processing tools, we will present the overall architecture of neptoon and how it implements established processing methodologies while maintaining extensibility for emerging approaches. Through an intuitive configuration system and graphical user interface, neptoon streamlines data processing workflows and ensures reproducibility across research sites. As our understanding of the sensor signal continues to improve, the ability for research infrastructures to quickly implement the latest advancements becomes ever more important. We will demonstrate how neptoon facilitates rapid deployment of these latest processing methodologies, supports cross-site harmonisation, whilst also enabling robust testing of experimental correction methods. Through its support of multiple stakeholders, from researchers to sensor owners, the latest advancements can be pushed quickly back to the broader community. By providing a standardised yet flexible processing framework, neptoon aims to accelerate the integration of CRNS measurements into critical zone research and enhance our understanding of soil moisture dynamics across scales.
How to cite: Schrön, M., Power, D., Köhli, M., Rosolem, R., Francke, T., Trinkle, L., Erxleben, F., and Zacharias, S.: Neptoon: An open-source and extensible software tool for data processing of cosmic-ray neutron sensors , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20716, https://doi.org/10.5194/egusphere-egu26-20716, 2026.
