Articles | Volume 16, issue 2
https://doi.org/10.5194/gmd-16-449-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-449-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
23 Jan 2023
Model description paper |
| 23 Jan 2023
| 23 Jan 2023
URANOS v1.0 – the Ultra Rapid Adaptable Neutron-Only Simulation for Environmental Research
Markus Köhli
CORRESPONDING AUTHOR
Physikalisches Institut, Heidelberg University, Heidelberg, Germany
Physikalisches Institut, University of Bonn, Bonn, Germany
Martin Schrön
Department of Monitoring and Exploration Technologies, Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany
Steffen Zacharias
Department of Monitoring and Exploration Technologies, Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany
Ulrich Schmidt
Physikalisches Institut, Heidelberg University, Heidelberg, Germany
Related authors
Till Francke, Cosimo Brogi, Alby Duarte Rocha, Michael Förster, Maik Heistermann, Markus Köhli, Daniel Rasche, Marvin Reich, Paul Schattan, Lena Scheiffele, and Martin Schrön
Geosci. Model Dev., 18, 819–842, https://doi.org/10.5194/gmd-18-819-2025, https://doi.org/10.5194/gmd-18-819-2025, 2025
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Multiple methods for measuring soil moisture beyond the point scale exist. Their validation is generally hindered by not knowing the truth. We propose a virtual framework in which this truth is fully known and the sensor observations for cosmic ray neutron sensing, remote sensing, and hydrogravimetry are simulated. This allows for the rigorous testing of these virtual sensors to understand their effectiveness and limitations.
Daniel Rasche, Jannis Weimar, Martin Schrön, Markus Köhli, Markus Morgner, Andreas Güntner, and Theresa Blume
Hydrol. Earth Syst. Sci., 27, 3059–3082, https://doi.org/10.5194/hess-27-3059-2023, https://doi.org/10.5194/hess-27-3059-2023, 2023
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We introduce passive downhole cosmic-ray neutron sensing (d-CRNS) as an approach for the non-invasive estimation of soil moisture in deeper layers of the unsaturated zone which exceed the observational window of above-ground CRNS applications. Neutron transport simulations are used to derive mathematical descriptions and transfer functions, while experimental measurements in an existing groundwater observation well illustrate the feasibility and applicability of the approach.
Maik Heistermann, Till Francke, Lena Scheiffele, Katya Dimitrova Petrova, Christian Budach, Martin Schrön, Benjamin Trost, Daniel Rasche, Andreas Güntner, Veronika Döpper, Michael Förster, Markus Köhli, Lisa Angermann, Nikolaos Antonoglou, Manuela Zude-Sasse, and Sascha E. Oswald
Earth Syst. Sci. Data, 15, 3243–3262, https://doi.org/10.5194/essd-15-3243-2023, https://doi.org/10.5194/essd-15-3243-2023, 2023
Short summary
Short summary
Cosmic-ray neutron sensing (CRNS) allows for the non-invasive estimation of root-zone soil water content (SWC). The signal observed by a single CRNS sensor is influenced by the SWC in a radius of around 150 m (the footprint). Here, we have put together a cluster of eight CRNS sensors with overlapping footprints at an agricultural research site in north-east Germany. That way, we hope to represent spatial SWC heterogeneity instead of retrieving just one average SWC estimate from a single sensor.
Martin Schrön, Markus Köhli, and Steffen Zacharias
Hydrol. Earth Syst. Sci., 27, 723–738, https://doi.org/10.5194/hess-27-723-2023, https://doi.org/10.5194/hess-27-723-2023, 2023
Short summary
Short summary
This paper presents a new analytical concept to answer long-lasting questions of the cosmic-ray neutron sensing community, such as
what is the influence of a distant area or patches of different land use on the measurement signal?or
is the detector sensitive enough to detect a change of soil moisture (e.g. due to irrigation) in a remote field at a certain distance?The concept may support signal interpretation and sensor calibration, particularly in heterogeneous terrain.
Cosimo Brogi, Heye Reemt Bogena, Markus Köhli, Johan Alexander Huisman, Harrie-Jan Hendricks Franssen, and Olga Dombrowski
Geosci. Instrum. Method. Data Syst., 11, 451–469, https://doi.org/10.5194/gi-11-451-2022, https://doi.org/10.5194/gi-11-451-2022, 2022
Short summary
Short summary
Accurate monitoring of water in soil can improve irrigation efficiency, which is important considering climate change and the growing world population. Cosmic-ray neutrons sensors (CRNSs) are a promising tool in irrigation monitoring due to a larger sensed area and to lower maintenance than other ground-based sensors. Here, we analyse the feasibility of irrigation monitoring with CRNSs and the impact of the irrigated field dimensions, of the variations of water in soil, and of instrument design.
Till Francke, Maik Heistermann, Markus Köhli, Christian Budach, Martin Schrön, and Sascha E. Oswald
Geosci. Instrum. Method. Data Syst., 11, 75–92, https://doi.org/10.5194/gi-11-75-2022, https://doi.org/10.5194/gi-11-75-2022, 2022
Short summary
Short summary
Cosmic-ray neutron sensing (CRNS) is a non-invasive tool for measuring hydrogen pools like soil moisture, snow, or vegetation. This study presents a directional shielding approach, aiming to measure in specific directions only. The results show that non-directional neutron transport blurs the signal of the targeted direction. For typical instruments, this does not allow acceptable precision at a daily time resolution. However, the mere statistical distinction of two rates is feasible.
Daniel Rasche, Markus Köhli, Martin Schrön, Theresa Blume, and Andreas Güntner
Hydrol. Earth Syst. Sci., 25, 6547–6566, https://doi.org/10.5194/hess-25-6547-2021, https://doi.org/10.5194/hess-25-6547-2021, 2021
Short summary
Short summary
Cosmic-ray neutron sensing provides areal average soil moisture measurements. We investigated how distinct differences in spatial soil moisture patterns influence the soil moisture estimates and present two approaches to improve the estimate of soil moisture close to the instrument by reducing the influence of soil moisture further afield. Additionally, we show that the heterogeneity of soil moisture can be assessed based on the relationship of different neutron energies.
Benjamin Fersch, Till Francke, Maik Heistermann, Martin Schrön, Veronika Döpper, Jannis Jakobi, Gabriele Baroni, Theresa Blume, Heye Bogena, Christian Budach, Tobias Gränzig, Michael Förster, Andreas Güntner, Harrie-Jan Hendricks Franssen, Mandy Kasner, Markus Köhli, Birgit Kleinschmit, Harald Kunstmann, Amol Patil, Daniel Rasche, Lena Scheiffele, Ulrich Schmidt, Sandra Szulc-Seyfried, Jannis Weimar, Steffen Zacharias, Marek Zreda, Bernd Heber, Ralf Kiese, Vladimir Mares, Hannes Mollenhauer, Ingo Völksch, and Sascha Oswald
Earth Syst. Sci. Data, 12, 2289–2309, https://doi.org/10.5194/essd-12-2289-2020, https://doi.org/10.5194/essd-12-2289-2020, 2020
Till Francke, Cosimo Brogi, Alby Duarte Rocha, Michael Förster, Maik Heistermann, Markus Köhli, Daniel Rasche, Marvin Reich, Paul Schattan, Lena Scheiffele, and Martin Schrön
Geosci. Model Dev., 18, 819–842, https://doi.org/10.5194/gmd-18-819-2025, https://doi.org/10.5194/gmd-18-819-2025, 2025
Short summary
Short summary
Multiple methods for measuring soil moisture beyond the point scale exist. Their validation is generally hindered by not knowing the truth. We propose a virtual framework in which this truth is fully known and the sensor observations for cosmic ray neutron sensing, remote sensing, and hydrogravimetry are simulated. This allows for the rigorous testing of these virtual sensors to understand their effectiveness and limitations.
Paolo Nasta, Günter Blöschl, Heye R. Bogena, Steffen Zacharias, Roland Baatz, Gabriëlle De Lannoy, Karsten H. Jensen, Salvatore Manfreda, Laurent Pfister, Ana M. Tarquis, Ilja van Meerveld, Marc Voltz, Yijian Zeng, William Kustas, Xin Li, Harry Vereecken, and Nunzio Romano
Hydrol. Earth Syst. Sci., 29, 465–483, https://doi.org/10.5194/hess-29-465-2025, https://doi.org/10.5194/hess-29-465-2025, 2025
Short summary
Short summary
The Unsolved Problems in Hydrology (UPH) initiative has emphasized the need to establish networks of multi-decadal hydrological observatories to tackle catchment-scale challenges on a global scale. This opinion paper provocatively discusses two endmembers of possible future hydrological observatory (HO) networks for a given hypothesized community budget: a comprehensive set of moderately instrumented observatories or, alternatively, a small number of highly instrumented supersites.
Eshrat Fatima, Rohini Kumar, Sabine Attinger, Maren Kaluza, Oldrich Rakovec, Corinna Rebmann, Rafael Rosolem, Sascha E. Oswald, Luis Samaniego, Steffen Zacharias, and Martin Schrön
Hydrol. Earth Syst. Sci., 28, 5419–5441, https://doi.org/10.5194/hess-28-5419-2024, https://doi.org/10.5194/hess-28-5419-2024, 2024
Short summary
Short summary
This study establishes a framework to incorporate cosmic-ray neutron measurements into the mesoscale Hydrological Model (mHM). We evaluate different approaches to estimate neutron counts within the mHM using the Desilets equation, with uniformly and non-uniformly weighted average soil moisture, and the physically based code COSMIC. The data improved not only soil moisture simulations but also the parameterisation of evapotranspiration in the model.
Daniel Altdorff, Maik Heistermann, Till Francke, Martin Schrön, Sabine Attinger, Albrecht Bauriegel, Frank Beyrich, Peter Biró, Peter Dietrich, Rebekka Eichstädt, Peter Martin Grosse, Arvid Markert, Jakob Terschlüsen, Ariane Walz, Steffen Zacharias, and Sascha E. Oswald
EGUsphere, https://doi.org/10.5194/egusphere-2024-3848, https://doi.org/10.5194/egusphere-2024-3848, 2024
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The German federal state of Brandenburg is particularly prone to soil moisture droughts. To support the management of related risks, we introduce a novel soil moisture and drought monitoring network based on cosmic-ray neutron sensing technology. This initiative is driven by a collaboration of research institutions and federal state agencies, and it is the first of its kind in Germany to have started operation. In this brief communication, we outline the network design and share first results.
Maik Heistermann, Till Francke, Martin Schrön, and Sascha E. Oswald
Hydrol. Earth Syst. Sci., 28, 989–1000, https://doi.org/10.5194/hess-28-989-2024, https://doi.org/10.5194/hess-28-989-2024, 2024
Short summary
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Cosmic-ray neutron sensing (CRNS) is a non-invasive technique used to obtain estimates of soil water content (SWC) at a horizontal footprint of around 150 m and a vertical penetration depth of up to 30 cm. However, typical CRNS applications require the local calibration of a function which converts neutron counts to SWC. As an alternative, we propose a generalized function as a way to avoid the use of local reference measurements of SWC and hence a major source of uncertainty.
Daniel Rasche, Jannis Weimar, Martin Schrön, Markus Köhli, Markus Morgner, Andreas Güntner, and Theresa Blume
Hydrol. Earth Syst. Sci., 27, 3059–3082, https://doi.org/10.5194/hess-27-3059-2023, https://doi.org/10.5194/hess-27-3059-2023, 2023
Short summary
Short summary
We introduce passive downhole cosmic-ray neutron sensing (d-CRNS) as an approach for the non-invasive estimation of soil moisture in deeper layers of the unsaturated zone which exceed the observational window of above-ground CRNS applications. Neutron transport simulations are used to derive mathematical descriptions and transfer functions, while experimental measurements in an existing groundwater observation well illustrate the feasibility and applicability of the approach.
Maik Heistermann, Till Francke, Lena Scheiffele, Katya Dimitrova Petrova, Christian Budach, Martin Schrön, Benjamin Trost, Daniel Rasche, Andreas Güntner, Veronika Döpper, Michael Förster, Markus Köhli, Lisa Angermann, Nikolaos Antonoglou, Manuela Zude-Sasse, and Sascha E. Oswald
Earth Syst. Sci. Data, 15, 3243–3262, https://doi.org/10.5194/essd-15-3243-2023, https://doi.org/10.5194/essd-15-3243-2023, 2023
Short summary
Short summary
Cosmic-ray neutron sensing (CRNS) allows for the non-invasive estimation of root-zone soil water content (SWC). The signal observed by a single CRNS sensor is influenced by the SWC in a radius of around 150 m (the footprint). Here, we have put together a cluster of eight CRNS sensors with overlapping footprints at an agricultural research site in north-east Germany. That way, we hope to represent spatial SWC heterogeneity instead of retrieving just one average SWC estimate from a single sensor.
Martin Schrön, Markus Köhli, and Steffen Zacharias
Hydrol. Earth Syst. Sci., 27, 723–738, https://doi.org/10.5194/hess-27-723-2023, https://doi.org/10.5194/hess-27-723-2023, 2023
Short summary
Short summary
This paper presents a new analytical concept to answer long-lasting questions of the cosmic-ray neutron sensing community, such as
what is the influence of a distant area or patches of different land use on the measurement signal?or
is the detector sensitive enough to detect a change of soil moisture (e.g. due to irrigation) in a remote field at a certain distance?The concept may support signal interpretation and sensor calibration, particularly in heterogeneous terrain.
Cosimo Brogi, Heye Reemt Bogena, Markus Köhli, Johan Alexander Huisman, Harrie-Jan Hendricks Franssen, and Olga Dombrowski
Geosci. Instrum. Method. Data Syst., 11, 451–469, https://doi.org/10.5194/gi-11-451-2022, https://doi.org/10.5194/gi-11-451-2022, 2022
Short summary
Short summary
Accurate monitoring of water in soil can improve irrigation efficiency, which is important considering climate change and the growing world population. Cosmic-ray neutrons sensors (CRNSs) are a promising tool in irrigation monitoring due to a larger sensed area and to lower maintenance than other ground-based sensors. Here, we analyse the feasibility of irrigation monitoring with CRNSs and the impact of the irrigated field dimensions, of the variations of water in soil, and of instrument design.
Friedrich Boeing, Oldrich Rakovec, Rohini Kumar, Luis Samaniego, Martin Schrön, Anke Hildebrandt, Corinna Rebmann, Stephan Thober, Sebastian Müller, Steffen Zacharias, Heye Bogena, Katrin Schneider, Ralf Kiese, Sabine Attinger, and Andreas Marx
Hydrol. Earth Syst. Sci., 26, 5137–5161, https://doi.org/10.5194/hess-26-5137-2022, https://doi.org/10.5194/hess-26-5137-2022, 2022
Short summary
Short summary
In this paper, we deliver an evaluation of the second generation operational German drought monitor (https://www.ufz.de/duerremonitor) with a state-of-the-art compilation of observed soil moisture data from 40 locations and four different measurement methods in Germany. We show that the expressed stakeholder needs for higher resolution drought information at the one-kilometer scale can be met and that the agreement of simulated and observed soil moisture dynamics can be moderately improved.
Maik Heistermann, Heye Bogena, Till Francke, Andreas Güntner, Jannis Jakobi, Daniel Rasche, Martin Schrön, Veronika Döpper, Benjamin Fersch, Jannis Groh, Amol Patil, Thomas Pütz, Marvin Reich, Steffen Zacharias, Carmen Zengerle, and Sascha Oswald
Earth Syst. Sci. Data, 14, 2501–2519, https://doi.org/10.5194/essd-14-2501-2022, https://doi.org/10.5194/essd-14-2501-2022, 2022
Short summary
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This paper presents a dense network of cosmic-ray neutron sensing (CRNS) to measure spatio-temporal soil moisture patterns during a 2-month campaign in the Wüstebach headwater catchment in Germany. Stationary, mobile, and airborne CRNS technology monitored the root-zone water dynamics as well as spatial heterogeneity in the 0.4 km2 area. The 15 CRNS stations were supported by a hydrogravimeter, biomass sampling, and a wireless soil sensor network to facilitate holistic hydrological analysis.
Andreas Wieser, Andreas Güntner, Peter Dietrich, Jan Handwerker, Dina Khordakova, Uta Ködel, Martin Kohler, Hannes Mollenhauer, Bernhard Mühr, Erik Nixdorf, Marvin Reich, Christian Rolf, Martin Schrön, Claudia Schütze, and Ute Weber
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-131, https://doi.org/10.5194/hess-2022-131, 2022
Preprint withdrawn
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We present an event-triggered observation concept which covers the entire process chain from heavy precipitation to flooding at the catchment scale. It combines flexible and mobile observing systems out of the fields of meteorology, hydrology and geophysics with stationary networks to capture atmospheric transport processes, heterogeneous precipitation patterns, land surface and subsurface storage processes, and runoff dynamics.
Mandy Kasner, Steffen Zacharias, and Martin Schrön
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-123, https://doi.org/10.5194/hess-2022-123, 2022
Publication in HESS not foreseen
Short summary
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Cosmic-ray neutron sensing (CRNS) is a non-invasive technique that is used to quantify field-scale root-zone soil moisture. We hypothesize that unaccounted spatiotemporal changes of soil density may have impact on the quality of CRNS soil moisture products. Our results indicate a significant dependency of neutrons on soil density, which also depends on the soil moisture state. A correction approach is provided that can be recommended for practical use.
Heye Reemt Bogena, Martin Schrön, Jannis Jakobi, Patrizia Ney, Steffen Zacharias, Mie Andreasen, Roland Baatz, David Boorman, Mustafa Berk Duygu, Miguel Angel Eguibar-Galán, Benjamin Fersch, Till Franke, Josie Geris, María González Sanchis, Yann Kerr, Tobias Korf, Zalalem Mengistu, Arnaud Mialon, Paolo Nasta, Jerzy Nitychoruk, Vassilios Pisinaras, Daniel Rasche, Rafael Rosolem, Hami Said, Paul Schattan, Marek Zreda, Stefan Achleitner, Eduardo Albentosa-Hernández, Zuhal Akyürek, Theresa Blume, Antonio del Campo, Davide Canone, Katya Dimitrova-Petrova, John G. Evans, Stefano Ferraris, Félix Frances, Davide Gisolo, Andreas Güntner, Frank Herrmann, Joost Iwema, Karsten H. Jensen, Harald Kunstmann, Antonio Lidón, Majken Caroline Looms, Sascha Oswald, Andreas Panagopoulos, Amol Patil, Daniel Power, Corinna Rebmann, Nunzio Romano, Lena Scheiffele, Sonia Seneviratne, Georg Weltin, and Harry Vereecken
Earth Syst. Sci. Data, 14, 1125–1151, https://doi.org/10.5194/essd-14-1125-2022, https://doi.org/10.5194/essd-14-1125-2022, 2022
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Monitoring of increasingly frequent droughts is a prerequisite for climate adaptation strategies. This data paper presents long-term soil moisture measurements recorded by 66 cosmic-ray neutron sensors (CRNS) operated by 24 institutions and distributed across major climate zones in Europe. Data processing followed harmonized protocols and state-of-the-art methods to generate consistent and comparable soil moisture products and to facilitate continental-scale analysis of hydrological extremes.
Till Francke, Maik Heistermann, Markus Köhli, Christian Budach, Martin Schrön, and Sascha E. Oswald
Geosci. Instrum. Method. Data Syst., 11, 75–92, https://doi.org/10.5194/gi-11-75-2022, https://doi.org/10.5194/gi-11-75-2022, 2022
Short summary
Short summary
Cosmic-ray neutron sensing (CRNS) is a non-invasive tool for measuring hydrogen pools like soil moisture, snow, or vegetation. This study presents a directional shielding approach, aiming to measure in specific directions only. The results show that non-directional neutron transport blurs the signal of the targeted direction. For typical instruments, this does not allow acceptable precision at a daily time resolution. However, the mere statistical distinction of two rates is feasible.
Daniel Rasche, Markus Köhli, Martin Schrön, Theresa Blume, and Andreas Güntner
Hydrol. Earth Syst. Sci., 25, 6547–6566, https://doi.org/10.5194/hess-25-6547-2021, https://doi.org/10.5194/hess-25-6547-2021, 2021
Short summary
Short summary
Cosmic-ray neutron sensing provides areal average soil moisture measurements. We investigated how distinct differences in spatial soil moisture patterns influence the soil moisture estimates and present two approaches to improve the estimate of soil moisture close to the instrument by reducing the influence of soil moisture further afield. Additionally, we show that the heterogeneity of soil moisture can be assessed based on the relationship of different neutron energies.
Maik Heistermann, Till Francke, Martin Schrön, and Sascha E. Oswald
Hydrol. Earth Syst. Sci., 25, 4807–4824, https://doi.org/10.5194/hess-25-4807-2021, https://doi.org/10.5194/hess-25-4807-2021, 2021
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Cosmic-ray neutron sensing (CRNS) is a powerful technique for retrieving representative estimates of soil moisture in footprints extending over hectometres in the horizontal and decimetres in the vertical. This study, however, demonstrates the potential of CRNS to obtain spatio-temporal patterns of soil moisture beyond isolated footprints. To that end, we analyse data from a unique observational campaign that featured a dense network of more than 20 neutron detectors in an area of just 1 km2.
Edoardo Martini, Matteo Bauckholt, Simon Kögler, Manuel Kreck, Kurt Roth, Ulrike Werban, Ute Wollschläger, and Steffen Zacharias
Earth Syst. Sci. Data, 13, 2529–2539, https://doi.org/10.5194/essd-13-2529-2021, https://doi.org/10.5194/essd-13-2529-2021, 2021
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We present the in situ data available from the soil monitoring network
STH-net, recently implemented at the Schäfertal Hillslope site (Germany). The STH-net provides data (soil water content, soil temperature, water level, and meteorological variables – measured at a 10 min interval since 1 January 2019) for developing and testing modelling approaches in the context of vadose zone hydrology at spatial scales ranging from the pedon to the hillslope.
Benjamin Fersch, Till Francke, Maik Heistermann, Martin Schrön, Veronika Döpper, Jannis Jakobi, Gabriele Baroni, Theresa Blume, Heye Bogena, Christian Budach, Tobias Gränzig, Michael Förster, Andreas Güntner, Harrie-Jan Hendricks Franssen, Mandy Kasner, Markus Köhli, Birgit Kleinschmit, Harald Kunstmann, Amol Patil, Daniel Rasche, Lena Scheiffele, Ulrich Schmidt, Sandra Szulc-Seyfried, Jannis Weimar, Steffen Zacharias, Marek Zreda, Bernd Heber, Ralf Kiese, Vladimir Mares, Hannes Mollenhauer, Ingo Völksch, and Sascha Oswald
Earth Syst. Sci. Data, 12, 2289–2309, https://doi.org/10.5194/essd-12-2289-2020, https://doi.org/10.5194/essd-12-2289-2020, 2020
Cited articles
Agostinelli, S., Allison, J., Amako, K., et al.: GEANT4 – a simulation toolkit, Nucl. Instrum.
Meth. A, 506, 250–303,
https://doi.org/10.1016/S0168-9002(03)01368-8, 2003. a
Andreasen, M., Jensen, H. K., Zreda, M., Desilets, D., Bogena, H., and Looms,
C.: Modeling cosmic ray neutron field measurements, Water Resour. Res.,
52, 6451–6471, https://doi.org/10.1002/2015wr018236, 2016. a
Badiee, A., Wallbank, J., Pulido Fentanes, J., Trill, E., Scarlet, P., Zhu,
Y., Cielniak, G., Cooper, H., Blake, J., Evans, J., Zreda, M., Köhli, M.,
and Pearson, S.: Using Additional Moderator to Control the Footprint of a
COSMOS Rover for Soil Moisture Measurement, Water Resour. Res., 57, e2020WR028478,
https://doi.org/10.1029/2020wr028478, 2021. a, b
Baroni, G., Scheiffele, L., Schrön, M., Ingwersen, J., and Oswald, S.:
Uncertainty, sensitivity and improvements in soil moisture estimation with
cosmic-ray neutron sensing, J. Hydrol., 564, 873–887,
https://doi.org/10.1016/j.jhydrol.2018.07.053, 2018. a
Battistoni, G., Boehlen, T., Cerutti, F., Chin, P., Esposito, L., Fasso, A.,
Ferrari, A., Lechner, A., Empl, A., Mairani, A., Mereghetti, A., Ortega, P.,
Ranft, J., Roesler, S., Sala, P., Vlachoudis, V., and Smirnov, G.: Overview
of the FLUKA code, Ann. Nucl. Energ., 82, 10–18,
https://doi.org/10.1016/j.anucene.2014.11.007, 2015. a
Boudard, A., Cugnon, J., David, J.-C., Leray, S., and Mancusi, D.: New
potentialities of the Liège intranuclear cascade model for reactions
induced by nucleons and light charged particles, Phys. Rev. C, 87,
014606, https://doi.org/10.1103/PhysRevC.87.014606, 2013. a
Bramblett, R. and Bonner, T.: Neutron evaporation spectra from (p, n)
reactions, Nucl. Phys., 20, 395–407, https://doi.org/10.1016/0029-5582(60)90182-6,
1960. a
Bramblett, R., Ewing, R., and Bonner, T.: A new type of neutron spectrometer,
Nucl. Instrum. Methods, 9, 1–12,
https://doi.org/10.1016/0029-554X(60)90043-4, 1960. a
Briesmeister, J.: MCNP-A general Monte Carlo N-particle
transport code, Version 4C, LA-13709-M,
https://permalink.lanl.gov/object/tr?what=info:lanl-repo/lareport/LA-13709-M,
2000. a
Brown, D., Chadwick, M., Capote, R., Kahler, A., Trkov, A., Herman, M.,
Sonzogni, A., Danon, Y., Carlson, A., Dunn, M., Smith, D., Hale, G., Arbanas,
G., Arcilla, R., Bates, C., Beck, B., Becker, B., Brown, F., Casperson, R.,
Conlin, J., Cullen, D., Descalle, M.-A., Firestone, R., Gaines, T., Guber,
K., Hawari, A., Holmes, J., Johnson, T., Kawano, T., Kiedrowski, B., Koning,
A., Kopecky, S., Leal, L., Lestone, J., Lubitz, C., Damiá¡n, J. M.,
Mattoon, C., McCutchan, E., Mughabghab, S., Navratil, P., Neudecker, D.,
Nobre, G., Noguere, G., Paris, M., Pigni, M., Plompen, A., Pritychenko, B.,
Pronyaev, V., Roubtsov, D., Rochman, D., Romano, P., Schillebeeckx, P.,
Simakov, S., Sin, M., Sirakov, I., Sleaford, B., Sobes, V., Soukhovitskii,
E., Stetcu, I., Talou, P., Thompson, I., van der Marck, S.,
Welser-Sherrill, L., Wiarda, D., White, M., Wormald, J., Wright, R., Zerkle,
M., Žerovnik, G., and Zhu, Y.: ENDF/B-VIII.0: The 8th Major
Release of the Nuclear Reaction Data Library with CIELO-project Cross
Sections, New Standards and Thermal Scattering Data, Nucl. Data Sheets,
148, 1–142, https://doi.org/10.1016/j.nds.2018.02.001, 2018. a
Brun, R. and Rademakers, F.: ROOT – An Object Oriented Data Analysis
Framework, in: Proceedings of AIHENP’96 Workshop, Lausanne, vol. 389,
81–86, https://doi.org/10.1016/S0168-9002(97)00048-X, 1997. a, b
Caswell, R., Gabbard, R., Padgett, D., and Doering, W.: Attenuation of
14.1-Mev Neutrons in Water, Nucl. Sci. Eng., 2, 143–159,
https://doi.org/10.13182/NSE57-A25383, 1957. a, b, c, d
Chadwick, M., Herman, M., Obložinský, P., Dunn, M., Danon, Y.,
Kahler, A., Smith, D., Pritychenko, B., Arbanas, G., Arcilla, R., Brewer, R.,
Brown, D., Capote, R., Carlson, A., Cho, Y., Derrien, H., Guber, K., Hale,
G., Hoblit, S., Holloway, S., Johnson, T., Kawano, T., Kiedrowski, B., Kim,
H., Kunieda, S., Larson, N., Leal, L., Lestone, J., Little, R., McCutchan,
E., MacFarlane, R., MacInnes, M., Mattoon, C., McKnight, R., Mughabghab,
S., Nobre, G., Palmiotti, G., Palumbo, A., Pigni, M., Pronyaev, V., Sayer,
R., Sonzogni, A., Summers, N., Talou, P., Thompson, I., Trkov, A., Vogt, R.,
van der Marck, S., Wallner, A., White, M., Wiarda, D., and Young, P.:
ENDF/B-VII.1 Nuclear Data for Science and Technology: Cross Sections,
Covariances, Fission Product Yields and Decay Data, Nucl. Data Sheets, 112,
2887–2996, https://doi.org/10.1016/j.nds.2011.11.002, 2011. a
Cnudde, V. and Boone, M.: High-resolution X-ray computed tomography in
geosciences: A review of the current technology and applications,
Earth-Sci. Rev., 123, 1–17, https://doi.org/10.1016/j.earscirev.2013.04.003,
2013. a
Cugnon, J., Volant, C., and Vuillier, S.: Nucleon and deuteron induced
spallation reactions, Nucl. Phys. A, 625, 729–757,
https://doi.org/10.1016/S0375-9474(97)00602-7, 1997. a
Decker, A., McHale, S., Shannon, M., Clinton, J., and McClory, J.: Novel
Bonner Sphere Spectrometer Response Functions Using MCNP6, IEEE
T. Nucl. Sci., 62, 1689–1694,
https://doi.org/10.1109/TNS.2015.2416652, 2015. a
Desilets, D. and Zreda, M.: Footprint diameter for a cosmic-ray soil moisture
probe: Theory and Monte Carlo simulations, Water Resour. Res., 49,
3566–3575, https://doi.org/10.1002/wrcr.20187, 2013. a
Desilets, D., Zreda, M., and Prabu, T.: Extended scaling factors for in situ
cosmogenic nuclides: new measurements at low latitude, Earth Planet.
Sc. Lett., 246, 265–276, https://doi.org/10.1016/j.epsl.2006.03.051, 2006. a
Emmett, M.: The MORSE Monte Carlo Transport Code System, ORNL-4972/R2,
https://inis.iaea.org/collection/NCLCollectionStore/_Public/16/029/16029296.pdf,
1975. a
Federico, C., Gonçalez, O., Fonseca, E., Martin, I., and Caldas, L.:
Neutron spectra measurements in the south Atlantic anomaly region,
Radiat. Meas., 45, 1526–1528, https://doi.org/10.1016/j.radmeas.2010.06.038,
2010. a
Francke, T., Heistermann, M., Köhli, M., Budach, C., Schrön, M., and Oswald, S. E.: Assessing the feasibility of a directional cosmic-ray neutron sensing sensor for estimating soil moisture, Geosci. Instrum. Method. Data Syst., 11, 75–92, https://doi.org/10.5194/gi-11-75-2022, 2022. a, b
Franz, T. E., Zreda, M., Rosolem, R., and Ferre, T. P. A.: A universal calibration function for determination of soil moisture with cosmic-ray neutrons, Hydrol. Earth Syst. Sci., 17, 453–460, https://doi.org/10.5194/hess-17-453-2013, 2013. a
Galassi, M., Davies, J., Theiler, J., Gough, B., Jungman, G., Alken, P., Booth,
M., Rossi, F., and Ulerich, R.: GNU Scientific Library: reference manual for GSL
version 2.7, Free Software Foundation,
https://www.gnu.org/software/gsl/manual/gsl-ref.pdf (last access: 18 January 2023), 2016. a
Garny, S., Mares, V., and Rühm, W.: Response functions of a Bonner
Sphere Spectrometer calculated with GEANT4, Nucl. Instrum.
Meth. A, 604, 612–617, https://doi.org/10.1016/j.nima.2009.02.044,
2009. a
Gelbard, E.: Epithermal scattering in VIM, Tech. Rep. FRA-TM-123, Argonne
National Laboratory, IL, USA, technical Memorandum, 1979. a
Goldhagen, P., Reginatto, M., Kniss, T., Wilson, J., Singleterry, R., Jones,
I., and Van Steveninck, W.: Measurement of the energy spectrum of
cosmic-ray induced neutrons aboard an ER-2 high-altitude airplane, Nucl. Instrum.
Meth. A, 476, 42–51,
https://doi.org/10.1016/S0168-9002(01)01386-9, 2002. a
Goldman, L.: Principles of CT and CT Technology, J. Nucl.
Med. Tech., 35, 115–128, https://doi.org/10.2967/jnmt.107.042978, 2007. a
Goorley, T., James, M., Booth, T., Brown, F., Bull, J., Cox, L., Durkee, J.,
Elson, J., Fensin, M., Forster, R., Hendricks, J., Hughes, H., Johns, R.,
Kiedrowski, B., Martz, R., Mashnik, S., McKinney, G., Pelowitz, D., Prael,
R., Sweezy, J., Waters, L., Wilcox, T., and Zukaitis, T.: Initial MCNP6
Release Overview, Nucl. Tech., 180, 298–315, https://doi.org/10.13182/NT11-135,
2012. a, b
Gudima, K., Mashnik, S., and Toneev, V.: Cascade-exciton model of nuclear
reactions, Nucl. Phys. A, 401, 329–361,
https://doi.org/10.1016/0375-9474(83)90532-8, 1983. a
Gudima, K., Mashnik, S., and Sierk, A.: User Manual for the Code LAQGSM,
LA-UR-01-6804,
https://permalink.lanl.gov/object/tr?what=info:lanl-repo/lareport/LA-UR-01-6804,
2001. a
Hébert, A.: Multigroup Neutron Transport and Diffusion Computations,
Springer US, Boston, 751–911, https://doi.org/10.1007/978-0-387-98149-9_8, 2010. a
Heidbüchel, I., Güntner, A., and Blume, T.: Use of cosmic-ray neutron sensors for soil moisture monitoring in forests, Hydrol. Earth Syst. Sci., 20, 1269–1288, https://doi.org/10.5194/hess-20-1269-2016, 2016. a
Hertel, N. and Davidson, J.: The response of Bonner Spheres to neutrons
from thermal energies to 17.3 MeV, Nucl. Instrum. Meth. A, 238, 509–516, https://doi.org/10.1016/0168-9002(85)90494-2,
1985. a
ISO group 85/SC 2 Radiological protection: Reference neutron radiations –
Part 1, Standard, International Organization for Standardization, Geneva, CH,
https://www.iso.org/standard/25666.html (last access: 18 January 2023), 2001. a
Iwamoto, O., Iwamoto, N., Kunieda, S., Minato, F., and Shibata, K.: The CCONE
Code System and its Application to Nuclear Data Evaluation for Fission and
Other Reactions, Nucl. Data Sheets, 131, 259–288,
https://doi.org/10.1016/j.nds.2015.12.004,
2016. a
Iwase, H., Niita, K., and Nakamura, T.: Development of General-Purpose Particle
and Heavy Ion Transport Monte Carlo Code, J. Nucl. Sci.
Technol., 39, 1142–1151, https://doi.org/10.1080/18811248.2002.9715305, 2002. a, b
Iwema, J., Schrön, M., Da Silva, J. K., Schweiser De Paiva Lopes, R.,
and Rosolem, R.: Accuracy and precision of the cosmic-ray neutron sensor for
soil moisture estimation at humid environments, Hydrol. Process., 35, e14419,
https://doi.org/10.1002/hyp.14419, 2021. a
Iyer, M. and Ganguly, A.: Neutron Evaporation and Energy Distribution in
Individual Fission Fragments, Phys. Rev. C, 5, 1410–1421,
https://doi.org/10.1103/PhysRevC.5.1410, 1972. a
Jakobi, J., Huisman, J., Köhli, M., Rasche, D., Vereecken, H., and Bogena,
H.: The Footprint Characteristics of Cosmic Ray Thermal Neutrons, Geophys.
Res. Lett., 48, e2021GL094281, https://doi.org/10.1029/2021gl094281, 2021. a, b
Kawano, T., Talou, P., Stetcu, I., and Chadwick, M.: Statistical and
evaporation models for the neutron emission energy spectrum in the
center-of-mass system from fission fragments, Nucl. Phys. A, 913, 51–70,
https://doi.org/10.1016/j.nuclphysa.2013.05.020, 2013. a
Kittelmann, T. and Boin, M.: Polycrystalline neutron scattering for Geant4:
NXSG4, Comput. Phys. Commun., 189, 114–118,
https://doi.org/10.1016/j.cpc.2014.11.009, 2015. a
Knuth, D.: The Art of Computer Programming, Volume 2, 3rd Edn.,
Seminumerical Algorithms, Addison-Wesley Longman Publishing Co., Inc.,
Boston, MA, USA, ISBN 9780321635778, 1997. a
Köhli, M.: URANOS v1.0, Harvard Dataverse V1 [code], https://doi.org/10.7910/DVN/THPNZW, 2022a. a, b
Köhli, M.: mkoehli/uranos: URANOS v1.0 (URANOS), Zenodo [data set], https://doi.org/10.5281/zenodo.6578668, 2022b. a
Köhli, M. and Schmoldt, J.-P.: Feasibility of UXO detection via pulsed
neutron-neutron logging, Appl. Radiat. Isotopes, 188, 110403,
https://doi.org/10.1016/j.apradiso.2022.110403, 2022. a, b
Köhli, M., Schrön, M., Zreda, M., Schmidt, U., Dietrich, P., and
Zacharias, S.: Footprint characteristics revised for field-scale soil
moisture monitoring with cosmic-ray neutrons, Water Resour. Res., 51,
5772–5790, https://doi.org/10.1002/2015WR017169, 2015. a, b, c
Köhli, M., Allmendinger, F., Häußler, W., Schröder, T., Klein,
M., Meven, M., and Schmidt, U.: Efficiency and spatial resolution of the
CASCADE thermal neutron detector, Nucl. Instrum. Meth. A, 828, 242–249, https://doi.org/10.1016/j.nima.2016.05.014, 2016. a, b
Köhli, M., Desch, K., Gruber, M., Kaminski, J., Schmidt, F., and Wagner,
T.: Novel neutron detectors based on the time projection method, Physica B, 551, 517–522, https://doi.org/10.1016/j.physb.2018.03.026, 2018a. a, b
Köhli, M., Schrön, M., and Schmidt, U.: Response functions for
detectors in cosmic ray neutron sensing, Nucl. Instrum. Meth. A, 902, 184–189, https://doi.org/10.1016/j.nima.2018.06.052,
2018b. a, b, c
Köhli, M., Weimar, J., Schrön, M., Baatz, R., and Schmidt, U.: Soil
Moisture and Air Humidity Dependence of the Above-Ground Cosmic-Ray Neutron
Intensity, Front. Water, 2, 15, https://doi.org/10.3389/frwa.2020.544847, 2021. a, b, c
Koning, A., Bauge, E., Dean, C., Dupont, E., Nordborg, C., Rugama, Y., Fischer,
U., Forrest, R., Kellett, M., Jacqmin, R., Leeb, H., Mills, R., Pescarini,
M., and Rullhusen, P.: Status of the JEFF Nuclear Data Library, J.
Korean Phys. Soc., 59, 1057–1062, https://doi.org/10.3938/jkps.59.1057,
2011. a
Lefmann, K. and Nielsen, K.: McStas, a general software package for neutron
ray-tracing simulations, Neutron News, 10, 20–23,
https://doi.org/10.1080/10448639908233684, 1999. a
Li, D., Schrön, M., Köhli, M., Bogena, H., Weimar, J., Jiménez
Bello, M., Han, X., Martínez Gimeno, M., Zacharias, S., Vereecken,
H., and Hendricks Franssen, H.: Can Drip Irrigation be Scheduled with
Cosmic-Ray Neutron Sensing?, Vadose Zone J., 18, 190053,
https://doi.org/10.2136/vzj2019.05.0053, 2019. a, b
Liu, H., Hou, Y., Li, H., Song, Y., Hu, L., and Liang, M.: Cosmic-ray neutron
fluxes and spectra at different altitudes based on Monte Carlo
simulations, Appl. Radiat. Isotopes, 175, 109800,
https://doi.org/10.1016/j.apradiso.2021.109800, 2021. a
Maire, E. and Withers, P.: Quantitative X-ray tomography, Int.
Mater. Rev., 59, 1–43, https://doi.org/10.1179/1743280413Y.0000000023, 2013. a
Mares, V. and Schraube, H.: Evaluation of the response matrix of a Bonner
Sphere Spectrometer with LiI detector from thermal energy to 100 MeV,
Nucl. Instrum. Meth. A, 337, 461–473,
https://doi.org/10.1016/0168-9002(94)91116-9, 1994. a
Mares, V., Schraube, G., and Schraube, H.: Calculated neutron response of a
Bonner Sphere Spectrometer with 3He counter, Nucl. Instrum. Meth. A, 307, 398–412,
https://doi.org/10.1016/0168-9002(91)90210-H, 1991. a, b
Matsumoto, M. and Nishimura, T.: Mersenne Twister: A 623-dimensionally
Equidistributed Uniform Pseudo-random Number Generator, ACM T.
Model. Comput. Sim., 8, 3–30, https://doi.org/10.1145/272991.272995,
1998. a
McConn Jr., R., Gesh, C., Pagh, R., Rucker, R., and Williams III, R.:
Compendium of Material Composition Data for Radiation Transport Modeling,
Tech. Rep. PNNL-15870 Rev. 1, Pacific Northwest National Laboratory,
Richland, Washington 99352,
https://www.pnnl.gov/main/publications/external/technical_reports/pnnl-15870rev1.pdf,
2011. a
McKinney, G.: MCNP6 Cosmic and Terrestrial Background Particle Fluxes,
LA-UR-13-24293, release
3,
https://mcnp.lanl.gov/pdf_files/la-ur-13-24293.pdf, 2013. a
McKinney, G., Armstrong, H., James, M., Clem, J., and Goldhagen, P.: MCNP6
Cosmic-Source Option, LA-UR-12-22318,
https://permalink.lanl.gov/object/tr?what=info:lanl-repo/lareport/LA-UR-12-22318,
2012. a
Metropolis, N. and Ulam, S.: The Monte Carlo Method, J. Am.
Stat. Assoc., 44, 335–341, https://doi.org/10.2307/2280232, 1949. a
Nelms, A.: Energy loss and range of electrons and positrons, United States
Department of Commerce, national
Bureau of Standards Circular 577 and Suppl.,
https://catalog.hathitrust.org/Record/007291096 (last access: 18 January 2023), 1956. a
Niita, K.: QMD and JAM Calculations for High Energy Nucleon-Nucleus
Collisions, J. Nucl. Sci. Technol., 39, 714–719,
https://doi.org/10.1080/00223131.2002.10875198, 2002. a
Niita, K., Takada, H., Meigo, S., and Ikeda, Y.: High-energy particle transport
code NMTC/JAM, Nucl. Instrum. Meth. B, 184, 406–420,
https://doi.org/10.1016/S0168-583X(01)00784-4, 2001. a
Otuka, N., Dupont, E., Semkova, V., Pritychenko, B., Blokhin, A., Aikawa, M.,
Babykina, S., Bossant, M., Chen, G., Dunaeva, S., Forrest, R., Fukahori, T.,
Furutachi, N., Ganesan, S., Ge, Z., Gritzay, O., Herman, M., Hlavač,
S., Kato, K., Lalremruata, B., Lee, Y., Makinaga, A., Matsumoto, K.,
Mikhaylyukova, M., Pikulina, G., Pronyaev, V., Saxena, A., Schwerer, O.,
Simakov, S., Soppera, N., Suzuki, R., Takács, S., Tao, X., Taova, S.,
Tárkányi, F., Varlamov, V., Wang, J., Yang, S., Zerkin, V., and
Zhuang, Y.: Towards a More Complete and Accurate Experimental Nuclear
Reaction Data Library (EXFOR): International Collaboration Between Nuclear
Reaction Data Centres (NRDC), Nucl. Data Sheets, 120, 272–276,
https://doi.org/10.1016/j.nds.2014.07.065, 2014. a
Pazianotto, M., Cortés-Giraldo, M., Federico, C., Gonçalez, O.,
Quesada, J., and Carlson, B.: Determination of the cosmic-ray-induced neutron
flux and ambient dose equivalent at flight altitude, J. Phys.
Conf. Ser., 630, 012022, https://doi.org/10.1088/1742-6596/630/1/012022, 2015. a
Peggs, S., et al.: European Spallation Source Technical Design Report,
Technical Design Report ESS, ESS, Lundt, ESS-2013-001,
http://docdb01.esss.lu.se/DocDB/0002/000274/006/TDR_final_130423_print_ch1.pdf,
2013. a
Prael, R. and Lichtenstein, H.: User Guide to LCS: The LAHET Code System,
LA-UR-89-3014,
https://permalink.lanl.gov/object/tr?what=info:lanl-repo/lareport/LA-UR-89-3014,
1989. a
Rasche, D., Köhli, M., Schrön, M., Blume, T., and Güntner, A.: Towards disentangling heterogeneous soil moisture patterns in cosmic-ray neutron sensor footprints, Hydrol. Earth Syst. Sci., 25, 6547–6566, https://doi.org/10.5194/hess-25-6547-2021, 2021. a
Romano, P. and Forget, B.: The OpenMC Monte Carlo particle transport code,
Ann. Nucl. Energ., 51, 274–281, https://doi.org/10.1016/j.anucene.2012.06.040,
2013. a, b
Roth, S.: Ray casting for modeling solids, Comput. Vision Graph., 18, 109–144, https://doi.org/10.1016/0146-664X(82)90169-1, 1982. a
Šaroun, J. and Kulda, J.: RESTRAX – a program for TAS
resolution calculation and scan profile simulation, Physica B, 234-236, 1102–1104, https://doi.org/10.1016/s0921-4526(97)00037-9, 1997. a
Sato, T.: Analytical Model for Estimating Terrestrial Cosmic Ray Fluxes Nearly
Anytime and Anywhere in the World: Extension of PARMA/EXPACS, PLOS ONE, 10,
1–33, https://doi.org/10.1371/journal.pone.0144679, 2015. a
Sato, T. and Niita, K.: Analytical Functions to Predict Cosmic-Ray Neutron
Spectra in the Atmosphere, Radiation Research, 166, 544–555,
https://doi.org/10.1667/RR0610.1, 2006. a
Sato, T., Yasuda, H., Niita, K., Endo, A., and Sihver, L.: Development of
PARMA: PHITS-based Analytical Radiation Model in the Atmosphere,
Radiat. Res., 170, 244–259, https://doi.org/10.1667/RR1094.1, 2008. a, b, c
Schattan, P., Köhli, M., Schrön, M., Baroni, G., and Oswald, S.:
Sensing Area-Average Snow Water Equivalent with Cosmic-Ray Neutrons: The
Influence of Fractional Snow Cover, Water Resour. Res., 55,
10796–10812, https://doi.org/10.1029/2019WR025647, 2019. a, b
Schrön, M., Köhli, M., Scheiffele, L., Iwema, J., Bogena, H. R., Lv, L., Martini, E., Baroni, G., Rosolem, R., Weimar, J., Mai, J., Cuntz, M., Rebmann, C., Oswald, S. E., Dietrich, P., Schmidt, U., and Zacharias, S.: Improving calibration and validation of cosmic-ray neutron sensors in the light of spatial sensitivity, Hydrol. Earth Syst. Sci., 21, 5009–5030, https://doi.org/10.5194/hess-21-5009-2017, 2017. a, b
Schrön, M., Rosolem, R., Köhli, M., Piussi, L., Schröter, I.,
Iwema, J., Kögler, S., Oswald, S., Wollschläger, U., Samaniego, L.,
Dietrich, P., and Zacharias, S.: Cosmic-ray Neutron Rover Surveys of Field
Soil Moisture and the Influence of Roads, Water Resour. Res., 54,
6441–6459, https://doi.org/10.1029/2017WR021719, 2018. a
Schrön, M., Zacharias, S., Womack, G., Köhli, M., Desilets, D., Oswald, S. E., Bumberger, J., Mollenhauer, H., Kögler, S., Remmler, P., Kasner, M., Denk, A., and Dietrich, P.: Intercomparison of cosmic-ray neutron sensors and water balance monitoring in an urban environment, Geosci. Instrum. Method. Data Syst., 7, 83–99, https://doi.org/10.5194/gi-7-83-2018, 2018. a, b, c
Schrön, M., Oswald, S., Zacharias, S., Kasner, M., Dietrich, P., and
Attinger, S.: Neutrons on Rails: Transregional Monitoring of Soil Moisture
and Snow Water Equivalent, Geophys. Res. Lett., 48, e2021GL093924,
https://doi.org/10.1029/2021gl093924, 2021. a
Shibata, K., Iwamoto, O., Nakagawa, T., Iwamoto, N., Ichihara, A., Kunieda, S.,
Chiba, S., Furutaka, K., Otuka, N., Ohsawa, T., Murata, T., Matsunobu, H.,
Zukeran, A., Kamada, S., and Katakura, J.: JENDL-4.0: A New Library for
Nuclear Science and Engineering, J. Nucl. Sci. Technol.,
48, 1–30, https://doi.org/10.1080/18811248.2011.9711675, 2011. a
Smith, A., Fields, P., and Roberts, J.: Spontaneous Fission Neutron Spectrum of
252Cf, Phys. Rev., 108, 411–413,
https://doi.org/10.1103/PhysRev.108.411, 1957. a
Solovyev, A., Fedorov, V., Kharlov, V., and Stepanova, U.: Comparative analysis
of MCNPX and GEANT4 codes for fast-neutron radiation treatment planning,
Nucl. Energ. Technol., 1, 14–19, https://doi.org/10.1016/j.nucet.2015.11.004,
2015. a
Sun Programmers Group: Fortran 77 Reference Manual, Tech. rep., SunSoft,
http://wwwcdf.pd.infn.it/localdoc/f77_sun.pdf,
1995a. a
Sun Programmers Group: Fortran 90 User's Guide, Tech. rep., SunSoft,
http://smdc.sinp.msu.ru/doc/Fortran90UsersGuide.pdf,
1995b. a
Sweezy, J., Hertel, N., and Veinot, K.: BUMS – Bonner Sphere Unfolding
Made Simple: an HTML based multisphere neutron spectrometer unfolding
package, Nucl. Instrum. Meth. A, 476,
263–269, https://doi.org/10.1016/S0168-9002(01)01466-8,
2002. a
Terrell, J.: Fission Neutron Spectra and Nuclear Temperatures, Phys. Rev.,
113, 527–541, https://doi.org/10.1103/PhysRev.113.527, 1959. a
Thomas, D. and Alevra, A.: Bonner Sphere Spectrometers – a critical
review, Nucl. Instrum. Meth. A, 476, 12–20,
https://doi.org/10.1016/S0168-9002(01)01379-1, 2002. a
van der Ende, B., Atanackovic, J., Erlandson, A., and Bentoumi, G.: Use of
GEANT4 vs. MCNPX for the characterization of a boron-lined neutron
detector, Nucl. Instrum. Meth. A, 820, 40–47,
https://doi.org/10.1016/j.nima.2016.02.082, 2016. a
Walsh, J., Forget, B., and Smith, K.: Accelerated sampling of the free gas
resonance elastic scattering kernel, Ann. Nucl. Energ., 69, 116–124,
https://doi.org/10.1016/j.anucene.2014.01.017, 2014. a
Waters, L., McKinney, G., Durkee, J., Fensin, M., Hendricks, J., James, M.,
Johns, R., and Pelowitz, D.: The MCNPX Monte Carlo Radiation Transport
Code, AIP Conf. Proc., 896, 81–90, https://doi.org/10.1063/1.2720459,
2007. a, b
Watt, B.: Energy Spectrum of Neutrons from Thermal Fission of
235U, Phys. Rev., 87, 1037–1041,
https://doi.org/10.1103/PhysRev.87.1037, 1952. a
Wechsler, D., Zsigmond, G., Streffer, F., and Mezei, F.: VITESS: Virtual
instrumentation tool for pulsed and continuous sources, Neutron News, 11,
25–28, https://doi.org/10.1080/10448630008233764, 2000. a
Weimar, J., Köhli, M., Budach, C., and Schmidt, U.: Large-Scale Boron-Lined
Neutron Detection Systems as a 3He Alternative for Cosmic Ray Neutron
Sensing, Front. Water, 2, 16, https://doi.org/10.3389/frwa.2020.00016, 2020. a, b
Weisskopf, V.: Statistics and Nuclear Reactions, Phys. Rev., 52, 295–303,
https://doi.org/10.1103/PhysRev.52.295, 1937. a
X-5 Monte Carlo Team: MCNP-A general Monte Carlo N-particle transport
code, Version 5, LA-UR-03-1987, volume I: Overview and Theory,
https://laws.lanl.gov/vhosts/mcnp.lanl.gov/pdf_files/la-ur-03-1987.pdf,
2003.
a
Yamashita, M., Stephens, L., and Patterson, H.: Cosmic-ray-produced neutrons at
ground level: Neutron production rate and flux distribution, J.
Geophys. Res., 71, 3817–3834, https://doi.org/10.1029/JZ071i016p03817, 1966. a
Ziegler, J.: Terrestrial cosmic ray intensities, IBM J. Res.
Dev., 42, 117–140, https://doi.org/10.1147/rd.421.0117, 1998. a
Zreda, M., Desilets, D., Ferré, T., and Scott, R.: Measuring soil moisture
content non-invasively at intermediate spatial scale using cosmic-ray
neutrons, Geophys. Res. Lett., 35, L21402,
https://doi.org/10.1029/2008GL035655, 2008. a
Zreda, M., Shuttleworth, W. J., Zeng, X., Zweck, C., Desilets, D., Franz, T., and Rosolem, R.: COSMOS: the COsmic-ray Soil Moisture Observing System, Hydrol. Earth Syst. Sci., 16, 4079–4099, https://doi.org/10.5194/hess-16-4079-2012, 2012. a
Zweck, C., Zreda, M., and Desilets, D.: Snow shielding factors for cosmogenic
nuclide dating inferred from Monte Carlo neutron transport simulations,
Earth Planet. Sc. Lett., 379, 64–71,
https://doi.org/10.1016/j.epsl.2013.07.023, 2013. a
Short summary
In the last decades, Monte Carlo codes were often consulted to study neutrons near the surface. As an alternative for the growing community of CRNS, we developed URANOS. The main model features are tracking of particle histories from creation to detection, detector representations as layers or geometric shapes, a voxel-based geometry model, and material setup based on color codes in ASCII matrices or bitmap images. The entire software is developed in C++ and features a graphical user interface.
In the last decades, Monte Carlo codes were often consulted to study neutrons near the surface....
