The CASCADE 10B thermal neutron detector and soil moisture sensing by cosmic-ray neutrons

This work connects the three domains of experimental nuclear physics, computational physics and environmental physics centered around the neutron. The CASCADE thermal neutron detector is based on a combination of solid 10B coatings in several layers, GEMs as gas amplification stages, a microstructured readout, multichannel ASICs and FPGA hardware triggered data acquisition. The detailed analysis to improve the system in terms of time-of-flight resolution for Neutron Resonance Spin Echo Spectroscopy required for a simulation model of the detector. The limitations of existing codes led to the development of the Monte Carlo transport code URANOS, which fully integrates the detector components and features a voxel-based geometry definition. The simulation could then successfully be applied to precisely understand neutron transport within the frame of Cosmic-Ray Neutron Sensing. This novel and interdisciplinary method offers the possibility to non-invasively measure soil moisture on the hectare scale using neutrons of the environmental radiation. The endeavor of this work led to the development of the footprint weighting function, which describes the neutron density change by different hydrogen pools in the air-ground interface. Significant influences of the near-field topology around the sensor were predicted by this work, experimentally verified and correction methods were successfully tested

Using Additional Moderator to Control the Footprint of a COSMOS Rover for Soil Moisture Measurement

Cosmic Ray Neutron Probes (CRNP) have found application in soil moisture estimation due to their conveniently large (>100 m) footprints. Here we explore the possibility of using high density polyethylene (HDPE) moderator to limit the field of view, and hence the footprint, of a soil moisture sensor formed of 12 CRNP mounted on to a mobile robotic platform (Thorvald) for better in-field localisation of moisture variation. URANOS neutron scattering simulations are used to show that 5 cm of additional HDPE moderator (used to shield the upper surface and sides of the detector) is sufficient to (i), reduce the footprint of the detector considerably, (ii) approximately double the percentage of neutrons detected from within 5 m of the detector, and (iii), does not affect the shape of the curve used to convert neutron counts into soil moisture. Simulation and rover measurements for a transect crossing between grass and concrete additionally suggest that (iv), soil moisture changes can be sensed over a length scales of tens of meters or less (roughly an order of magnitude smaller than commonly used footprint distances), and (v), the additional moderator does not reduce the detected neutron count rate (and hence increase noise) as much as might be expected given the extent of the additional moderator. The detector with additional HDPE moderator was also used to conduct measurements on a stubble field over three weeks to test the rover system in measuring spatial and temporal soil moisture variation

A dense network of cosmic-ray neutron sensors for soil moisture observation in a highly instrumented pre-Alpine headwater catchment in Germany

Monitoring soil moisture is still a challenge: it varies strongly in space and time and at various scales while conventional sensors typically suffer from small spatial support. With a sensor footprint up to several hectares, cosmic-ray neutron sensing (CRNS) is a modern technology to address that challenge. So far, the CRNS method has typically been applied with single sensors or in sparse national-scale networks. This study presents, for the first time, a dense network of 24 CRNS stations that covered, from May to July 2019, an area of just 1 km2: the pre-Alpine Rott headwater catchment in Southern Germany, which is characterized by strong soil moisture gradients in a heterogeneous landscape with forests and grasslands. With substantially overlapping sensor footprints, this network was designed to study root-zone soil moisture dynamics at the catchment scale. The observations of the dense CRNS network were complemented by extensive measurements that allow users to study soil moisture variability at various spatial scales: roving (mobile) CRNS units, remotely sensed thermal images from unmanned areal systems (UASs), permanent and temporary wireless sensor networks, profile probes, and comprehensive manual soil sampling. Since neutron counts are also affected by hydrogen pools other than soil moisture, vegetation biomass was monitored in forest and grassland patches, as well as meteorological variables; discharge and groundwater tables were recorded to support hydrological modeling experiments. As a result, we provide a unique and comprehensive data set to several research communities: to those who investigate the retrieval of soil moisture from cosmic-ray neutron sensing, to those who study the variability of soil moisture at different spatiotemporal scales, and to those who intend to better understand the role of root-zone soil moisture dynamics in the context of catchment and groundwater hydrology, as well as land–atmosphere exchange processes. The data set is available through the EUDAT Collaborative Data Infrastructure and is split into two subsets: https://doi.org/10.23728/b2share.282675586fb94f44ab2fd09da0856883 (Fersch et al., 2020a) and https://doi.org/10.23728/b2share.bd89f066c26a4507ad654e994153358b (Fersch et al., 2020b)

Improving Calibration and Validation of Cosmic-Ray Neutron Sensors in the Light of Spatial Sensitivity–Theory and Evidence

. In the last few years the method of cosmic-ray neutron sensing (CRNS) has gained popularity among hydrologists, physicists, and land-surface modelers. The sensor provides continuous soil moisture data, averaged over several hectares and tens of decimeters in depth. However, the signal still may contain unidentified features of hydrological processes, and many calibration datasets are often required in order to find reliable relations between neutron intensity and water dynamics. Recent insights into environmental neutrons accurately described the spatial sensitivity of the sensor and thus allowed one to quantify the contribution of individual sample locations to the CRNS signal. Consequently, data points of calibration and validation datasets are suggested to be averaged using a more physically based weighting approach. In this work, a revised sensitivity function is used to calculate weighted averages of point data. The function is different from the simple exponential convention by the extraordinary sensitivity to the first few meters around the probe, and by dependencies on air pressure, air humidity, soil moisture, and vegetation. The approach is extensively tested at six distinct monitoring sites: two sites with multiple calibration datasets and four sites with continuous time series datasets. In all cases, the revised averaging method improved the performance of the CRNS products. The revised approach further helped to reveal hidden hydrological processes which otherwise remained unexplained in the data or were lost in the process of overcalibration. The presented weighting approach increases the overall accuracy of CRNS products and will have an impact on all their applications in agriculture, hydrology, and modeling

Improving Calibration and Validation of Cosmic-Ray Neutron Sensors in Light of Spatial Sensitivity

In the last few years the method of cosmic-ray neutron sensing (CRNS) has gained popularity among hydrologists, physicists, and land-surface modelers. The sensor provides continuous soil moisture data, averaged over several hectares and tens of decimeters in depth. However, the signal still may contain unidentified features of hydrological processes, and many calibration datasets are often required in order to find reliable relations between neutron intensity and water dynamics. Recent insights into environmental neutrons accurately described the spatial sensitivity of the sensor and thus allowed one to quantify the contribution of individual sample locations to the CRNS signal. Consequently, data points of calibration and validation datasets are suggested to be averaged using a more physically based weighting approach. In this work, a revised sensitivity function is used to calculate weighted averages of point data. The function is different from the simple exponential convention by the extraordinary sensitivity to the first few meters around the probe, and by dependencies on air pressure, air humidity, soil moisture, and vegetation. The approach is extensively tested at six distinct monitoring sites: two sites with multiple calibration datasets and four sites with continuous time series datasets. In all cases, the revised averaging method improved the performance of the CRNS products. The revised approach further helped to reveal hidden hydrological processes which otherwise remained unexplained in the data or were lost in the process of overcalibration. The presented weighting approach increases the overall accuracy of CRNS products and will have an impact on all their applications in agriculture, hydrology, and modeling

CRNS-based monitoring technologies for a weather and climate-resilient agriculture: realization by the ADAPTER project

The ADAPTER project involves the development and provision of innovative simulation-based data and information products for weather- and climate-resilient agriculture. In other words, ADAPTER makes daily ("soil") weather and comprehensive long-term climate change information freely available to the agricultural community and all interested parties as easy-to-use analyses, data products, and information. A key technology is thereby cosmic-ray neutron sensing, a non-invasive method to determine environmental water on the hectar scale. Measurements and forecasts focus on the current state and development of the water balance, including groundwater. To support the agricultural community towards an optimized soil management, Forschungszentrum Jülich uses forecast simulations with the hydrological numerical model ParFlow and the regional earth system model Terrestrial Systems Modeling Platform (TSMP) in combination with observations

CRNS-based monitoring technologies for a weather and climate-resilient agriculture: realization by the ADAPTER project

The ADAPTER project involves the development and provision of innovative simulation-based data and information products for weather- and climate-resilient agriculture. In other words, ADAPTER makes daily ("soil") weather and comprehensive long-term climate change information freely available to the agricultural community and all interested parties as easy-to-use analyses, data products, and information. A key technology is thereby cosmic-ray neutron sensing, a non-invasive method to determine environmental water on the hectar scale. Measurements and forecasts focus on the current state and development of the water balance, including groundwater. To support the agricultural community towards an optimized soil management, Forschungszentrum Jülich uses forecast simulations with the hydrological numerical model ParFlow and the regional earth system model Terrestrial Systems Modeling Platform (TSMP) in combination with observations

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

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

Feasibility of irrigation monitoring with cosmic-ray neutron sensors

Accurate soil moisture (SM) monitoring is key in irrigation as it can greatly improve water use efficiency. Recently, cosmic-ray neutron sensors (CRNSs) have been recognized as a promising tool in SM monitoring due to their large footprint of several hectares. CRNSs also have great potential for irrigation applications, but few studies have investigated whether irrigation monitoring with CRNSs is feasible, especially for irrigated fields with a size smaller than the CRNS footprint. Therefore, the aim of this study is to use Monte Carlo simulations to investigate the feasibility of monitoring irrigation with CRNSs. This was achieved by simulating irrigation scenarios with different field dimensions (from 0.5 to 8 ha) and SM variations between 0.05 and 0.50 cm3 cm−3. Moreover, the energy-dependent response functions of eight moderators with different high-density polyethylene (HDPE) thickness or additional gadolinium thermal shielding were investigated. It was found that a considerable part of the neutrons that contribute to the CRNS footprint can originate outside an irrigated field, which is a challenge for irrigation monitoring with CRNSs. The use of thin HDPE moderators (e.g. 5 mm) generally resulted in a smaller footprint and thus stronger contributions from the irrigated area. However, a thicker 25 mm HDPE moderator with gadolinium shielding improved SM monitoring in irrigated fields due to a higher sensitivity of neutron counts with changing SM. This moderator and shielding set-up provided the highest chance of detecting irrigation events, especially when the initial SM was relatively low. However, variations in SM outside a 0.5 or 1 ha irrigated field (e.g. due to irrigation of neighbouring fields) can affect the count rate more than SM variations due to irrigation. This suggests the importance of retrieving SM data from the surrounding of a target field to obtain more meaningful information for supporting irrigation management, especially for small irrigated fields