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 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

2020 ◽  
Author(s):  
Jannis Weimar ◽  
Markus Köhli ◽  
Martin Schrön ◽  
Ulrich Schmidt
Keyword(s):  
Monte Carlo ◽  
Soil Moisture ◽  
Neutron Transport ◽  
Cosmic Ray ◽  
Data Sets ◽  
Neutron Intensity ◽  
Alpine Regions ◽  
Neutron Count ◽  
Snow Water ◽  
Humidity Dependence

<p>The novel method of Cosmic-ray neutron sensing (CRNS) allows non-invasive soil moisture measurements at a hectometer scaled footprint. Using this technique one can relate the flux density of albedo neutrons, generated in cosmic-ray induced air showers, to the amount of water within a radius of several hundred meters. In the recent years the understanding of neutron transport by Monte Carlo simulations led to major advancements in precision, which have successfully targeted a manifold of use cases. For example the improvements in the signal interpretation have meanwhile also been applied to the determination of snow water in Alpine regions. Up to now, the conversion of soil moisture to a detectable neutron count rate relies mainly on the equation presented by Desilets and Zreda. While in general a hyperbolic expression can be derived from theoretical considerations, their empiric parameterisation needs to be revised as many groups have found site-specific calibrations, which are simply based on different empirical data sets.</p><p>Investigating the above-ground neutron intensity 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 sensor response function. The resulting formula significantly improves the soil-moisture-to-intensity conversion and allows for a more comprehensive instrument data quality, which especially closes the gap between observations of very dry and wet conditions.</p>

scholarly journals Intercomparison of Cosmic-Ray Neutron Sensors andWater Balance Monitoring in an Urban Environment

2017 ◽  
Author(s):  
Martin Schrön ◽  
Steffen Zacharias ◽  
Gary Womack ◽  
Markus Köhli ◽  
Darin Desilets ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Large Scale ◽  
Neutron Transport ◽  
Cosmic Ray ◽  
Environmental Water ◽  
Integration Time ◽  
Multiple Sensors ◽  
Neutron Count ◽  
Urban Terrain ◽  
Neutron Sensors

Abstract. Sensor-to-sensor variability is a source of error common to all geoscientific instruments, which needs to be assessed before comparative and applied research can be performed with multiple sensors. Consistency among sensor systems is especially critical when the signal is an integral value that covers a large volume within complex, urban terrain. Cosmic-Ray Neutron Sensors (CRNS) are a recent technology that is used to monitor large-scale environmental water storages, for which a rigorous comparison study of numerous co-located sensors has never been performed. In this work, nine stationary CRNS probes of type CRS1000 were installed in relative proximity on a grass patch surrounded by complex urban terrain. While the dynamics of the neutron count rates were found to be similar, offsets of a few percent from the absolute average neutron count rates were found. Technical adjustments of the individual detection parameters brought all instruments into good agreement. Furthermore, the arrangement of multiple sensors allowed to find a critical integration time of 6 hours above which all sensors showed consistent dynamics in the data and their RMSE fell below 1 % of gravimetric water content. The residual differences between the nine signals indicated local effects of the complex urban terrain at the scale of several meters. Mobile CRNS measurements and spatial neutron transport simulations in the surrounding area (25 ha) have revealed that CRNS detectors are sensitive to sub-footprint heterogeneity despite their large averaging volume. The paved and sealed areas in the footprint furthermore damp the dynamics of the CRNS soil moisture product. We developed strategies to correct for the sealed-area effect based on theoretical insights about the spatial sensitivity of the sensor. This procedure not only led to reliable soil moisture estimation in drying periods, it further revealed a strong signal of interception and evaporation water that emerged over the sealed ground during and shortly after rain events. The presented arrangement offered a unique opportunity to demonstrate the CRNS performance in complex terrain, and the results indicate great potential for further applications in urban water sciences.

scholarly journals Intercomparison of cosmic-ray neutron sensors and water balance monitoring in an urban environment

2018 ◽  
Vol 7 (1) ◽  
pp. 83-99 ◽  
Author(s):  
Martin Schrön ◽  
Steffen Zacharias ◽  
Gary Womack ◽  
Markus Köhli ◽  
Darin Desilets ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Neutron Transport ◽  
Urban Climate ◽  
Cosmic Ray ◽  
Environmental Water ◽  
Integration Time ◽  
Multiple Sensors ◽  
Neutron Count ◽  
Neutron Sensors ◽  
The Individual

Abstract. Sensor-to-sensor variability is a source of error common to all geoscientific instruments that needs to be assessed before comparative and applied research can be performed with multiple sensors. Consistency among sensor systems is especially critical when subtle features of the surrounding terrain are to be identified. Cosmic-ray neutron sensors (CRNSs) are a recent technology used to monitor hectometre-scale environmental water storages, for which a rigorous comparison study of numerous co-located sensors has not yet been performed. In this work, nine stationary CRNS probes of type “CRS1000” were installed in relative proximity on a grass patch surrounded by trees, buildings, and sealed areas. While the dynamics of the neutron count rates were found to be similar, offsets of a few percent from the absolute average neutron count rates were found. Technical adjustments of the individual detection parameters brought all instruments into good agreement. Furthermore, we found a critical integration time of 6 h above which all sensors showed consistent dynamics in the data and their RMSE fell below 1 % of gravimetric water content. The residual differences between the nine signals indicated local effects of the complex urban terrain on the scale of several metres. Mobile CRNS measurements and spatial simulations with the URANOS neutron transport code in the surrounding area (25 ha) have revealed substantial sub-footprint heterogeneity to which CRNS detectors are sensitive despite their large averaging volume. The sealed and constantly dry structures in the footprint furthermore damped the dynamics of the CRNS-derived soil moisture. We developed strategies to correct for the sealed-area effect based on theoretical insights about the spatial sensitivity of the sensor. This procedure not only led to reliable soil moisture estimation during dry-out periods, it further revealed a strong signal of intercepted water that emerged over the sealed surfaces during rain events. The presented arrangement offered a unique opportunity to demonstrate the CRNS performance in complex terrain, and the results indicated great potential for further applications in urban climate research.

scholarly journals Error Estimation for Soil Moisture Measurements With Cosmic Ray Neutron Sensing and Implications for Rover Surveys

2020 ◽  
Vol 2 ◽  
Author(s):  
Jannis Jakobi ◽  
Johan A. Huisman ◽  
Martin Schrön ◽  
Justus Fiedler ◽  
Cosimo Brogi ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Measurement Uncertainty ◽  
Survey Design ◽  
Time Windows ◽  
Inverse Correlation ◽  
Cosmic Ray ◽  
Environmental Water ◽  
Neutron Intensity ◽  
Estimation Uncertainty ◽  
Neutron Count

Cosmic ray neutron (CRN) sensing allows for non-invasive soil moisture measurements at the field scale and relies on the inverse correlation between aboveground measured epithermal neutron intensity (1 eV−100 keV) and environmental water content. The measurement uncertainty follows Poisson statistics and thus increases with decreasing neutron intensity, which corresponds to increasing soil moisture. In order to reduce measurement uncertainty, the neutron count rate is usually aggregated over 12 or 24 h time windows for stationary CRN probes. To obtain accurate soil moisture estimates with mobile CRN rover applications, the aggregation of neutron measurements is also necessary and should consider soil wetness and driving speed. To date, the optimization of spatial aggregation of mobile CRN observations in order to balance measurement accuracy and spatial resolution of soil moisture patterns has not been investigated in detail. In this work, we present and apply an easy-to-use method based on Gaussian error propagation theory for uncertainty quantification of soil moisture measurements obtained with CRN sensing. We used a 3rd order Taylor expansion for estimating the soil moisture uncertainty from uncertainty in neutron counts and compared the results to a Monte Carlo approach with excellent agreement. Furthermore, we applied our method with selected aggregation times to investigate how CRN rover survey design affects soil moisture estimation uncertainty. We anticipate that the new approach can be used to improve the strategic planning and evaluation of CRN rover surveys based on uncertainty requirements.

scholarly journals Spatio-temporal soil moisture retrieval at the catchment scale using a dense network of cosmic-ray neutron sensors

2021 ◽  
Vol 25 (9) ◽  
pp. 4807-4824
Author(s):  
Maik Heistermann ◽  
Till Francke ◽  
Martin Schrön ◽  
Sascha E. Oswald
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Root Zone ◽  
Cosmic Ray ◽  
Dense Network ◽  
Constrained Interpolation ◽  
Neutron Count ◽  
Spatio Temporal

Abstract. Cosmic-ray neutron sensing (CRNS) is a powerful technique for retrieving representative estimates of soil water content at a horizontal scale of hectometres (the “field scale”) and depths of tens of centimetres (“the root zone”). This study demonstrates the potential of the CRNS technique to obtain spatio-temporal patterns of soil moisture beyond the integrated volume from isolated CRNS footprints. We use data from an observational campaign carried out between May and July 2019 that featured a dense network of more than 20 neutron detectors with partly overlapping footprints in an area that exhibits pronounced soil moisture gradients within one square kilometre. The present study is the first to combine these observations in order to represent the heterogeneity of soil water content at the sub-footprint scale as well as between the CRNS stations. First, we apply a state-of-the-art procedure to correct the observed neutron count rates for static effects (heterogeneity in space, e.g. soil organic matter) and dynamic effects (heterogeneity in time, e.g. barometric pressure). Based on the homogenized neutron data, we investigate the robustness of a calibration approach that uses a single calibration parameter across all CRNS stations. Finally, we benchmark two different interpolation techniques for obtaining spatio-temporal representations of soil moisture: first, ordinary Kriging with a fixed range; second, spatial interpolation complemented by geophysical inversion (“constrained interpolation”). To that end, we optimize the parameters of a geostatistical interpolation model so that the error in the forward-simulated neutron count rates is minimized, and suggest a heuristic forward operator to make the optimization problem computationally feasible. Comparison with independent measurements from a cluster of soil moisture sensors (SoilNet) shows that the constrained interpolation approach is superior for representing horizontal soil moisture gradients at the hectometre scale. The study demonstrates how a CRNS network can be used to generate coherent, consistent, and continuous soil moisture patterns that could be used to validate hydrological models or remote sensing products.

scholarly journals Spatio-temporal soil moisture retrieval at the catchment-scale using a dense network of cosmic-ray neutron sensors

2021 ◽  
Author(s):  
Maik Heistermann ◽  
Till Francke ◽  
Martin Schrön ◽  
Sascha E. Oswald
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Ordinary Kriging ◽  
Cosmic Ray ◽  
Constrained Interpolation ◽  
Neutron Count ◽  
Moisture Variation ◽  
Spatio Temporal

Abstract. The method of Cosmic-Ray Neutron Sensing (CRNS) is a powerful technique to retrieve representative estimates of soil water content at a horizontal scale of hectometers (the field scale) and depths of tens of centimeters (the root zone). This study demonstrates the potential of the CRNS technique to obtain spatio-temporal patterns of soil moisture beyond the integrated volume from isolated CRNS footprints. We use data from an observational campaign between May and July 2019 which featured a network of more than 20 neutron detectors with partly overlapping footprints in an area that exhibits pronounced soil moisture gradients within 1 km2. The present study is the first to combine these observations in order to represent the heterogeneity of soil water content at the sub-footprint scale as well as between the CRNS stations. First, we apply a state-of-the-art procedure to correct the observed neutron count rates for static effects such as sensor sensitivity, vegetation biomass, soil organic carbon and lattice water, as well as for the influence of the temporally dynamic factors barometric pressure, air humidity, and incoming flux of neutrons. Based on the homogenised neutron data, we investigate the robustness of a uniform calibration approach using one calibration parameter value across all CRNS stations. Finally, we benchmark two different interpolation techniques in order to obtain space-time representations of soil moisture: first, Ordinary Kriging with a fixed range; second, a heuristic approach that complements the concept of spatial interpolation by the idea of a geophysical inversion (constrained interpolation). For the latter, we define a geostatistical model of the spatial soil moisture variation in the study area, and then optimize the parameters of that model so that the error of the forward-simulated neutron count rates is minimized. In order to make the optimization problem computationally feasible, we use a heuristic forward operator that is based on the physics of horizontal sensitivity of the neutron detector. The comparison with independent measurements from a cluster of soil moisture sensors (SoilNet) shows that the constrained interpolation approach outperforms Ordinary Kriging by putting a stronger emphasis on horizontal soil moisture gradients at the hectometer scale. The study demonstrates how a CRNS network can be used to generate consistent interpolated soil moisture patterns that could be used to validate hydrological models or remote sensing products.

Sign in / Sign up

Export Citation Format

Share Document