scholarly journals Radius of influence for a cosmic-ray soil moisture probe : theory and Monte Carlo simulations.

2011 ◽  
Author(s):  
Darin Desilets
Keyword(s):  
Monte Carlo ◽  
Soil Moisture ◽  
Monte Carlo Simulations ◽  
Cosmic Ray ◽  
Radius Of Influence

scholarly journals Soil Moisture and Air Humidity Dependence of the Above-Ground Cosmic-Ray Neutron Intensity

2021 ◽  
Vol 2 ◽  
Author(s):  
Markus Köhli ◽  
Jannis Weimar ◽  
Martin Schrön ◽  
Roland Baatz ◽  
Ulrich Schmidt
Keyword(s):  
Monte Carlo ◽  
Soil Moisture ◽  
Monte Carlo Simulations ◽  
Count Rate ◽  
Neutron Transport ◽  
Cosmic Ray ◽  
Mathematical Treatment ◽  
Specific Response ◽  
Air Humidity ◽  
Parameter Equation

Investigations of neutron transport through air and soil by Monte Carlo simulations led to major advancements toward a precise interpretation of measurements; they particularly improved the understanding of the cosmic-ray neutron footprint. Up to now, the conversion of soil moisture to a detectable neutron count rate has relied mainly on the equation presented by Desilets and Zreda in 2010. While in general a hyperbolic expression can be derived from theoretical considerations, their empiric parameterization needs to be revised for two reasons. Firstly, a rigorous mathematical treatment reveals that the values of the four parameters are ambiguous because their values are not independent. We found a three-parameter equation with unambiguous values of the parameters that is equivalent in any other respect to the four-parameter equation. Secondly, high-resolution Monte-Carlo simulations revealed a systematic deviation of the count rate to soil moisture relation especially for extremely dry conditions as well as very humid conditions. That is a hint that a smaller contribution to the intensity was forgotten or not adequately treated by the conventional approach. Investigating the above-ground neutron flux through a broadly based Monte-Carlo simulation campaign revealed a more detailed understanding of different contributions to this signal, especially targeting air humidity corrections. The packages MCNP and URANOS were used to derive a function able to describe the respective dependencies, including the effect of different hydrogen pools and the detector-specific response function. The new relationship has been tested at two exemplary measurement sites, and its remarkable performance allows for a promising prospect of more comprehensive data quality in the future.

Moisture and humidity dependence of the above-ground cosmic-ray neutron intensity revised

2021 ◽  
Author(s):  
Markus Köhli ◽  
Jannis Weimar ◽  
Benjamin Fersch ◽  
Roland Baatz ◽  
Martin Schrön ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Soil Moisture ◽  
Count Rate ◽  
Cosmic Ray ◽  
Mathematical Treatment ◽  
Specific Response ◽  
Parameter Equation ◽  
Neutron Count ◽  
Dry Conditions ◽  
Humidity Dependence

<p>The novel method of Cosmic-ray neutron sensing (CRNS) allows non-invasive soil moisture measurements at a hectometer scaled footprint. Up to now, the conversion of soil moisture to a detectable neutron count rate relies mainly on the equation presented by Desilets et al. (2010). While in general a hyperbolic expression can be derived from theoretical considerations, their empiric parameterisation needs to be revised for two reasons. Firstly, a rigorous mathematical treatment reveals that the values of the four parameters are ambiguous because their values are not independent. We find a 3-parameter equation with unambiguous values of the parameters which is equivalent in any other respect to the 4-parameter equation. Secondly, high-resolution Monte-Carlo simulations revealed a systematic deviation of the count rate to soil moisture relation especially for extremely dry conditions as well as very humid conditions. That is a hint, that a smaller contribution to the intensity was forgotten or not adequately treated by the conventional approach. Investigating the above-ground neutron flux by a broadly based Monte-Carlo simulation campaign revealed a more detailed understanding of different contributions to this signal, especially targeting air humidity corrections. The packages MCNP and URANOS were used to derive a function able to describe the respective dependencies including the effect of different hydrogen pools and the detector-specific response function. The new relationship has been tested at three exemplary measurement sites and its remarkable performance allows for a promising prospect of more comprehensive data quality in the future.</p>

scholarly journals Assessment of neutrons from secondary cosmic rays at mountain altitudes – Geant4 simulations of environmental parameters including soil moisture and snow cover

2021 ◽  
Author(s):  
Thomas Brall ◽  
Vladimir Mares ◽  
Rolf Bütikofer ◽  
Werner Rühm
Keyword(s):  
Monte Carlo ◽  
Soil Moisture ◽  
Cosmic Rays ◽  
Monte Carlo Simulations ◽  
Neutron Flux ◽  
Snow Cover ◽  
Neutron Energy ◽  
Neutron Fluence ◽  
Environmental Parameters ◽  
Total Neutron

Abstract. Ground based measurements of neutrons from secondary cosmic rays are affected by environmental parameters, particularly hydrogen content in soil. To investigate the impact of these parameters, Geant4 Monte Carlo simulations were carried out. In a previous study the model used for the Geant4 Monte Carlo simulations was already validated by measurements performed with an Extended Range Bonner Sphere Spectrometer (ERBSS) at Zugspitze, Germany, and at Jungfraujoch, Switzerland. In the present study a sensitivity analysis including different environmental parameters (i.e., slope of mountain, snow height, soil moisture, and range of albedo neutrons) and their influence on the flux of neutrons from secondary cosmic rays was performed with Geant4. The results are compared with ERBSS measurements performed in 2018 at the Environmental Research Station “Schneefernerhaus” located at the Zugspitze, Germany. It is shown that the slope of the Zugspitze mountain reduces the neutron flux from secondary cosmic rays between about 25 % and 50 % as compared to a horizontal surface, depending on neutron energy and snow cover. An increasing height of snow cover, simulated as snow water equivalent (SWE), reduces the total neutron flux exponentially down to a factor of about 2.5 as compared to soil without any snow cover, with a saturation for snow heights greater than 10 cm to 15 cm SWE, depending on neutron energy. Based on count rates measured with the individual spheres of the ERBSS, SWE values were deduced for the whole year 2018. Specifically, mean SWE values deduced for the winter months (January to March) are between 6.7 and 10.1 cm or more, while those for the summer months (July to September) are between 2.1 and 3.6 cm. Soil moisture of 5 % water mass fraction in limestone leads to a decrease of the total neutron flux by about 35 % compared to dry limestone. At a height of 1.5 m above ground, 86 % of the total albedo neutron fluence at the detector position are from a ground area with a radius of about 75 m. It is concluded that measurement of neutrons from secondary cosmic radiation can be used to gain information on height of snow cover and its seasonal changes, soil moisture, but also information on local geometry such as mountain topography. Because the influence of such parameters on neutron fluence from secondary cosmic rays depends on neutron energy, analysis of the whole neutron energy spectrum is beneficial.

scholarly journals Muon Measurements with IceTop

2019 ◽  
Vol 208 ◽  
pp. 03003 ◽  
Author(s):  
Javier G. Gonzalez
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Cosmic Ray ◽  
Shower Axis ◽  
South Pole ◽  
Air Showers ◽  
Hadronic Interaction ◽  
Interaction Models ◽  
Lateral Distance ◽  
Cosmic Ray Flux

We present the measurement of the density of GeV muons in near-vertical air showers by the IceTop array at the South Pole. The muon density is measured at 600 m and 800 m lateral distance from the shower axis in air showers between 1 PeV and 100 PeV. This result can be used to constrain hadronic interaction models by comparing it with the outcome of Monte Carlo simulations. We show that some models do not produce muon densities in agreement with this result unless an unphysical composition of the primary cosmic ray flux is assumed.

Monte Carlo Simulations for Changes in the Cosmic-ray Flux on the Earth's Surface Due to Heavy-Metal Pollution in the Atmosphere

2011 ◽  
Vol 61 (8) ◽  
pp. 727-733
Author(s):  
Jaw Won SHIN ◽  
Tae-Sun PARK ◽  
Seung-Woo HONG* ◽  
Oubong GWUN ◽  
Chong Yeal KIM
Keyword(s):  
Heavy Metal ◽  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Metal Pollution ◽  
Heavy Metal Pollution ◽  
Cosmic Ray ◽  
Cosmic Ray Flux

scholarly journals Determination of cosmic-ray primary mass on an event-by-event basis using radio detection

2019 ◽  
Vol 216 ◽  
pp. 02005
Author(s):  
Washington Carvalho ◽  
Jaime Alvarez-Muñiz
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Cosmic Ray ◽  
Primary Mass ◽  
Radio Detection ◽  
Shower Development ◽  
Radio Signals ◽  
Event Basis

Traditionally, the depth of maximum shower development Xmax has been used as a surrogate observable for composition. Here we present the possibility of a new methodology to discriminate between light and heavy cosmic-ray primaries on an event-by-event basis. This method is based on comparisons between detected radio signals and Monte Carlo simulations, but instead of first reconstructing Xmax, we try to infer the cosmic-ray composition directly. We show that a large discrimination efficiency could in principle be reached for zenith angles above θ≃65°, even when some of the typical uncertainties in radio detection are taken into account.

scholarly journals Estimating Root Zone Moisture from Surface Soil Using Limited Data

2017 ◽  
Vol 24 (4) ◽  
pp. 501-516
Author(s):  
Wen-Zhi Zeng ◽  
Guo-Qing Lei ◽  
Hong-Ya Zhang ◽  
Ming-Hai Hong ◽  
Chi Xu ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Soil Moisture ◽  
Linear Regression ◽  
Monte Carlo Simulations ◽  
Linear Regression Model ◽  
Surface Soil ◽  
Root Zone ◽  
Surface Moisture ◽  
Moisture Estimation ◽  
Hydrus 1D

Abstract For estimation of root-zone moisture content from EO-1/Hyperion imagery, surface soil moisture was first predicted by hyperspectral reflectance data using partial least square regression (PLSR) analysis. The textures of more than 300 soil samples extracted from a 900 m × 900 m field site located within the Hetao Irrigation District in China were used to parameterize the HYDRUS-1D numerical model. The study area was spatially discretized into 18,000 compartments (30 m × 30 m × 0.02 m), and Monte Carlo simulations were applied to generate 2000 different soil-particle size distributions for each compartment. Soil hydraulic properties for each realization were determined by application of artificial neural network analysis and used to parameterize HYDRUS-1D to simulate averaged soil-moisture contents within the root zone (0-40 cm) and surface (approximately 0-4 cm). Then the link between surface moisture and root zone was established by use of linear regression analysis, resulting in R and RMSE of 0.38 and 0.03, respectively. Kriging and co-kriging with observed surface moisture, and co-kriging with surface moisture obtained from Hyperion imagery were also used to estimate root-zone moisture. Results indicated that PLSR is a powerful tool for soil moisture estimation from hyperspectral data. Furthermore, co-kriging with observed surface moisture had the highest R (0.41) and linear regression model, and HYDRUS Monte Carlo simulations had a lowest RMSE (0.03) among the four methods. In regions that have similar climatic and soil conditions to our study area, a linear regression model with HYDRUS Monte Carlo simulations is a practical method for root-zone moisture estimation before sowing and it can be easily coupled with remote sensing technology.

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