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.

Error estimation for soil moisture measurements with cosmic-ray neutron sensing and implications for rover surveys

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

<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>

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.

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>

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 Investigating temporal field sampling strategies for site-specific calibration of three soil moisture–neutron intensity parameterisation methods

2015 ◽  
Vol 19 (7) ◽  
pp. 3203-3216 ◽  
Author(s):  
J. Iwema ◽  
R. Rosolem ◽  
R. Baatz ◽  
T. Wagener ◽  
H. R. Bogena
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Satellite Remote Sensing ◽  
Cosmic Ray ◽  
Sampling Strategies ◽  
Site Specific ◽  
Neutron Intensity ◽  
Soil Wetness ◽  
Semi Arid

Abstract. The Cosmic-Ray Neutron Sensor (CRNS) can provide soil moisture information at scales relevant to hydrometeorological modelling applications. Site-specific calibration is needed to translate CRNS neutron intensities into sensor footprint average soil moisture contents. We investigated temporal sampling strategies for calibration of three CRNS parameterisations (modified N0, HMF, and COSMIC) by assessing the effects of the number of sampling days and soil wetness conditions on the performance of the calibration results while investigating actual neutron intensity measurements, for three sites with distinct climate and land use: a semi-arid site, a temperate grassland, and a temperate forest. When calibrated with 1 year of data, both COSMIC and the modified N0 method performed better than HMF. The performance of COSMIC was remarkably good at the semi-arid site in the USA, while the N0mod performed best at the two temperate sites in Germany. The successful performance of COSMIC at all three sites can be attributed to the benefits of explicitly resolving individual soil layers (which is not accounted for in the other two parameterisations). To better calibrate these parameterisations, we recommend in situ soil sampled to be collected on more than a single day. However, little improvement is observed for sampling on more than 6 days. At the semi-arid site, the N0mod method was calibrated better under site-specific average wetness conditions, whereas HMF and COSMIC were calibrated better under drier conditions. Average soil wetness condition gave better calibration results at the two humid sites. The calibration results for the HMF method were better when calibrated with combinations of days with similar soil wetness conditions, opposed to N0mod and COSMIC, which profited from using days with distinct wetness conditions. Errors in actual neutron intensities were translated to average errors specifically to each site. At the semi-arid site, these errors were below the typical measurement uncertainties from in situ point-scale sensors and satellite remote sensing products. Nevertheless, at the two humid sites, reduction in uncertainty with increasing sampling days only reached typical errors associated with satellite remote sensing products. The outcomes of this study can be used by researchers as a CRNS calibration strategy guideline.

The Effect of Atmospheric Water Vapor on Neutron Count in the Cosmic-Ray Soil Moisture Observing System

2013 ◽  
Vol 14 (5) ◽  
pp. 1659-1671 ◽  
Author(s):  
R. Rosolem ◽  
W. J. Shuttleworth ◽  
M. Zreda ◽  
T. E. Franz ◽  
X. Zeng ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Vapor ◽  
Neutron Transport ◽  
Cosmic Ray ◽  
Atmospheric Water Vapor ◽  
Fast Neutrons ◽  
Atmospheric Conditions ◽  
Atmospheric Water ◽  
Neutron Measurement ◽  
Neutron Intensity

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.

scholarly journals Simultaneous soil moisture and properties estimation for a drip irrigated field by assimilating cosmic-ray neutron intensity

2016 ◽  
Vol 539 ◽  
pp. 611-624 ◽  
Author(s):  
Xujun Han ◽  
Harrie-Jan Hendricks Franssen ◽  
Miguel Ángel Jiménez Bello ◽  
Rafael Rosolem ◽  
Heye Bogena ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Cosmic Ray ◽  
Neutron Intensity

scholarly journals Can canopy interception and biomass be inferred from cosmic-ray neutron intensity? Results from neutron transport modeling

2016 ◽  
Author(s):  
Mie Andreasen ◽  
Karsten H. Jensen ◽  
Darin Desilets ◽  
Marek Zreda ◽  
Heye Bogena ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Epithermal Neutron ◽  
Neutron Transport ◽  
Forest Biomass ◽  
Cosmic Ray ◽  
Ground Level ◽  
Field Site ◽  
Canopy Interception ◽  
Soil Matrix ◽  
Neutron Intensity

Abstract. Cosmic-ray neutron intensity is inversely correlated to all hydrogen present in the upper decimeters of the subsurface and the first few hectometers of the atmosphere above the ground surface. This method has been used for measuring soil moisture and snow water equivalent, but it may also be used to identify and quantify canopy interception and biomass. We use a neutron transport model with various representations of the forest and different parameters describing the subsurface to match measured profiles and time series of thermal and epithermal neutron intensities at a field site in Denmark. A sensitivity analysis is performed to quantify the effect of forest canopy representation, soil moisture, complexity of soil matrix chemistry, forest litter, soil bulk density, canopy interception and forest biomass on neutron intensity. The results show that forest biomass has a significant influence on the neutron intensity profiles at the examined field site, altering both the shape of the profiles and the ground level thermal-to-epithermal neutron ratio. The ground level thermal-to-epithermal neutron ratio increases significantly with increasing amounts of biomass and minor with canopy interception. Satisfactory agreement is found between measurements and model results at the forest site as well as two nearby sites representing agricultural and heathland ecosystems. The measured ground level thermal-to-epithermal neutron ratios of the three site range from around 0.56 to 0.82. The significantly smaller effect of canopy interception on the ground level thermal-to-epithermal neutron ratio was modeled to range from 0.804 to 0.836 for a forest with a dry and a very wet canopy (4 mm of canopy interception), respectively. At the examined field site the signal of the canopy interception is lower than the measurement uncertainty.

scholarly journals The COsmic-ray Soil Moisture Interaction Code (COSMIC) for use in data assimilation

2013 ◽  
Vol 17 (8) ◽  
pp. 3205-3217 ◽  
Author(s):  
J. Shuttleworth ◽  
R. Rosolem ◽  
M. Zreda ◽  
T. Franz
Keyword(s):  
Soil Moisture ◽  
Data Assimilation ◽  
Fast Neutron ◽  
Land Surface ◽  
Soil Depth ◽  
Cosmic Ray ◽  
High Energy ◽  
Fast Neutrons ◽  
Surface Model ◽  
Neutron Intensity

Abstract. Soil moisture status in land surface models (LSMs) can be updated by assimilating cosmic-ray neutron intensity measured in air above the surface. This requires a fast and accurate model to calculate the neutron intensity from the profiles of soil moisture modeled by the LSM. The existing Monte Carlo N-Particle eXtended (MCNPX) model is sufficiently accurate but too slow to be practical in the context of data assimilation. Consequently an alternative and efficient model is needed which can be calibrated accurately to reproduce the calculations made by MCNPX and used to substitute for MCNPX during data assimilation. This paper describes the construction and calibration of such a model, COsmic-ray Soil Moisture Interaction Code (COSMIC), which is simple, physically based and analytic, and which, because it runs at least 50 000 times faster than MCNPX, is appropriate in data assimilation applications. The model includes simple descriptions of (a) degradation of the incoming high-energy neutron flux with soil depth, (b) creation of fast neutrons at each depth in the soil, and (c) scattering of the resulting fast neutrons before they reach the soil surface, all of which processes may have parameterized dependency on the chemistry and moisture content of the soil. The site-to-site variability in the parameters used in COSMIC is explored for 42 sample sites in the COsmic-ray Soil Moisture Observing System (COSMOS), and the comparative performance of COSMIC relative to MCNPX when applied to represent interactions between cosmic-ray neutrons and moist soil is explored. At an example site in Arizona, fast-neutron counts calculated by COSMIC from the average soil moisture profile given by an independent network of point measurements in the COSMOS probe footprint are similar to the fast-neutron intensity measured by the COSMOS probe. It was demonstrated that, when used within a data assimilation framework to assimilate COSMOS probe counts into the Noah land surface model at the Santa Rita Experimental Range field site, the calibrated COSMIC model provided an effective mechanism for translating model-calculated soil moisture profiles into aboveground fast-neutron count when applied with two radically different approaches used to remove the bias between data and model.

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