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 ◽  
...  

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.

2017 ◽  
Author(s):  
Martin Schrön ◽  
Steffen Zacharias ◽  
Gary Womack ◽  
Markus Köhli ◽  
Darin Desilets ◽  
...  

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.


2020 ◽  
Author(s):  
Jannis Weimar ◽  
Markus Köhli ◽  
Martin Schrön ◽  
Ulrich Schmidt

<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>


2020 ◽  
Vol 2 ◽  
Author(s):  
Jannis Jakobi ◽  
Johan A. Huisman ◽  
Martin Schrön ◽  
Justus Fiedler ◽  
Cosimo Brogi ◽  
...  

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.


2021 ◽  
Author(s):  
Markus Köhli ◽  
Jannis Weimar ◽  
Benjamin Fersch ◽  
Roland Baatz ◽  
Martin Schrön ◽  
...  

<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>


2020 ◽  
Author(s):  
Jannis Jakobi ◽  
Johan Alexander Huisman ◽  
Martin Schrön ◽  
Justus Fiedler ◽  
Cosimo Brogi ◽  
...  

<p>The cosmic ray neutron (CRN) probe is a non-invasive device to measure soil moisture at the field scale. This instrument relies on the inverse correlation between aboveground epithermal neutron intensity (1eV – 100 keV) and environmental water content. The measurement uncertainty of the neutron detector follows Poisson statistics and thus decreases with decreasing neutron intensity, which corresponds to increasing soil moisture. In order to reduce measurement uncertainty (e.g. < 0.03 m<sup>3</sup>/m<sup>3</sup>), the neutron count rate is often aggregated over large time windows (e.g. 12h or 24h). To enable shorter aggregation intervals, the measurement uncertainty can be reduced either by using more efficient detectors or by using arrays of detectors, as in the case of CRN rover applications. Depending on soil moisture and driving speed, aggregation of neutron counts may also be necessary to obtain sufficiently accurate soil moisture estimates in rover applications. To date, signal aggregation has not been investigated sufficiently with respect to the optimisation of temporal (stationary probes) and spatial (roving applications) resolution. In this work, we present an easy-to-use method for uncertainty quantification of soil moisture observations from CRN sensors based on Gaussian error propagation theory. We have estimated the uncertainty using a third order Taylor expansion and compared the result with a more computationally intensive Monte Carlo approach and found excellent agreement. Furthermore, we used our method to quantify the dependence of soil moisture uncertainty on CRN rover survey design and on selected aggregation time. We anticipate that the new approach helps to quantify cosmic ray neutron measurement uncertainty. In particular, it is anticipated that the strategic planning and evaluation of CRN rover surveys based on uncertainty requirements can be improved considerably.</p>


2013 ◽  
Vol 14 (5) ◽  
pp. 1659-1671 ◽  
Author(s):  
R. Rosolem ◽  
W. J. Shuttleworth ◽  
M. Zreda ◽  
T. E. Franz ◽  
X. Zeng ◽  
...  

Abstract The cosmic-ray method for measuring soil moisture, used in the Cosmic-Ray Soil Moisture Observing System (COSMOS), relies on the exceptional ability of hydrogen to moderate fast neutrons. Sources of hydrogen near the ground, other than soil moisture, affect the neutron measurement and therefore must be quantified. This study investigates the effect of atmospheric water vapor on the cosmic-ray probe signal and evaluates the fast neutron response in realistic atmospheric conditions using the neutron transport code Monte Carlo N-Particle eXtended (MCNPX). The vertical height of influence of the sensor in the atmosphere varies between 412 and 265 m in dry and wet atmospheres, respectively. Model results show that atmospheric water vapor near the surface affects the neutron intensity signal by up to 12%, corresponding to soil moisture differences on the order of 0.10 m3 m−3. A simple correction is defined to identify the true signal associated with integrated soil moisture that rescales the measured neutron intensity to that which would have been observed in the atmospheric conditions prevailing on the day of sensor calibration. Use of this approach is investigated with in situ observations at two sites characterized by strong seasonality in water vapor where standard meteorological measurements are readily available.


2017 ◽  
Author(s):  
David McJannet ◽  
Aaron Hawdon ◽  
Brett Baker ◽  
Luigi Renzullo ◽  
Ross Searle

Abstract. Soil moisture plays a critical role in land surface processes and as such there has been a recent increase in the number and resolution of satellite soil moisture observations and development of land surface process models with ever increasing resolution. Despite these developments, validation and calibration of these products has been limited because of a lack of observations at corresponding scales. A recently developed mobile soil moisture monitoring platform, known as the rover, offers opportunities to overcome this scale issue. This paper describes a research project aimed at producing soil moisture estimates at a range of scales that are commensurate with model and satellite retrievals. Our investigation involved static cosmic ray neutron sensors and rover surveys across both broad (36 × 36 km at 9 km resolution) and intensive (10 × 10 km at 1 km resolution) scales in a cropping district in the Mallee region of Victoria, Australia. We describe approaches for converting rover survey neutron counts to soil moisture and discuss the factors controlling soil moisture variability. Measurements revealed that temporal patterns in soil moisture were preserved through time and regression modelling approaches were utilised to produce time series of property scale soil moisture which may also have application in calibration and validation studies or local farm management. Intensive scale rover surveys produced reliable soil moisture estimates at 1 km resolution while broad scale surveys produced soil moisture estimates at 9 km resolution. We conclude that the multiscale soil moisture products produced in this study are well suited to future analysis of satellite soil moisture retrievals and finer scale soil moisture models.


2015 ◽  
Vol 12 (9) ◽  
pp. 9813-9864 ◽  
Author(s):  
I. Heidbüchel ◽  
A. Güntner ◽  
T. Blume

Abstract. Cosmic ray neutron sensors (CRS) are a promising technique to measure soil moisture at intermediate scales. To convert neutron counts to average volumetric soil water content a simple calibration function can be used (the N0-calibration of Desilets et al., 2010). This calibration function is based on soil water content derived directly from soil samples taken within the footprint of the sensor. We installed a CRS in a mixed forest in the lowlands of north-eastern Germany and calibrated it 10 times throughout one calendar year. Each calibration with the N0-calibration function resulted in a different CRS soil moisture time series, with deviations of up to 0.12 m3 m-3 for individual values of soil water content. Also, many of the calibration efforts resulted in time series that could not be matched with independent in situ measurements of soil water content. We therefore suggest a new calibration function with a different shape that can vary from one location to another. A two-point calibration proved to be adequate to correctly define the shape of the new calibration function if the calibration points were taken during both dry and wet conditions covering at least 50 % of the total range of soil moisture. The best results were obtained when the soil samples used for calibration were linearly weighted as a function of depth in the soil profile and non-linearly weighted as a function of distance from the CRS, and when the depth-specific amount of soil organic matter and lattice water content was explicitly considered. The annual cycle of tree foliation was found to be a negligible factor for calibration because the variable hydrogen mass in the leaves was small compared to the hydrogen mass changes by soil moisture variations. Finally, we provide a best practice calibration guide for CRS in forested environments.


2021 ◽  
Vol 2 ◽  
Author(s):  
Markus Köhli ◽  
Jannis Weimar ◽  
Martin Schrön ◽  
Roland Baatz ◽  
Ulrich Schmidt

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.


2017 ◽  
Vol 21 (12) ◽  
pp. 6049-6067 ◽  
Author(s):  
David McJannet ◽  
Aaron Hawdon ◽  
Brett Baker ◽  
Luigi Renzullo ◽  
Ross Searle

Abstract. Soil moisture plays a critical role in land surface processes and as such there has been a recent increase in the number and resolution of satellite soil moisture observations and the development of land surface process models with ever increasing resolution. Despite these developments, validation and calibration of these products has been limited because of a lack of observations on corresponding scales. A recently developed mobile soil moisture monitoring platform, known as the rover, offers opportunities to overcome this scale issue. This paper describes methods, results and testing of soil moisture estimates produced using rover surveys on a range of scales that are commensurate with model and satellite retrievals. Our investigation involved static cosmic-ray neutron sensors and rover surveys across both broad (36 × 36 km at 9 km resolution) and intensive (10 × 10 km at 1 km resolution) scales in a cropping district in the Mallee region of Victoria, Australia. We describe approaches for converting rover survey neutron counts to soil moisture and discuss the factors controlling soil moisture variability. We use independent gravimetric and modelled soil moisture estimates collected across both space and time to validate rover soil moisture products. Measurements revealed that temporal patterns in soil moisture were preserved through time and regression modelling approaches were utilised to produce time series of property-scale soil moisture which may also have applications in calibration and validation studies or local farm management. Intensive-scale rover surveys produced reliable soil moisture estimates at 1 km resolution while broad-scale surveys produced soil moisture estimates at 9 km resolution. We conclude that the multiscale soil moisture products produced in this study are well suited to future analysis of satellite soil moisture retrievals and finer-scale soil moisture models.


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