The cosmic ray neutron method was developed for intermediate-scale soil moisture detection, but may potentially be used for other hydrological applications. The neutron signal of different hydrogen pools is poorly understood and separating them is difficult based on neutron measurements alone. Including neutron transport modeling may accommodate this shortcoming. However, measured and modeled neutrons are not directly comparable. Neither the scale nor energy ranges are equivalent, and the exact neutron energy sensitivity of the detectors is unknown. Here a methodology to enable comparability of the measured and modeled neutrons is presented. The usual cosmic ray soil moisture detector measures moderated neutrons by means of a proportional counter surrounded by plastic, making it sensitive to epithermal neutrons. However, that configuration allows for some thermal neutrons to be measured. The thermal contribution can be removed by surrounding the plastic with a layer of cadmium, which absorbs neutrons with energies below 0.5 eV. Likewise, cadmium shielding of a bare detector allows for estimating the epithermal contribution. First, the cadmium difference method is used to determine the fraction of thermal and epithermal neutrons measured by the bare and plastic-shielded detectors, respectively. The cadmium difference method results in linear correction models for measurements by the two detectors, and has the greatest impact on the neutron intensity measured by the moderated detector at the ground surface. Next, conversion factors are obtained relating measured and modeled neutron intensities. Finally, the methodology is tested by modeling the neutron profiles at an agricultural field site and satisfactory agreement to measurements is found.

Core Ideas Numerous studies have been conducted to develop and examine the accuracy of the method. Cosmic‐ray neutron soil moisture estimates compare well with independent measurements. These estimates are useful for modeling, data assimilation, and calibration of satellite products. Many studies have used the neutron detector for other applications; results have been promising. Since the introduction of the cosmic‐ray neutron method for soil moisture estimation, numerous studies have been conducted to test and advance the accuracy of the method. Almost 200 stationary neutron detector systems have been installed worldwide, and roving systems have also started to gain ground. The intensity of low‐energy neutrons produced by cosmic rays, measured above the ground surface, is sensitive to soil moisture in the upper decimeters of the ground within a radius of hectometers. The method has been proven suitable for estimating soil moisture for a wide range of land covers and soil types and has been used for hydrological modeling, data assimilation, and calibration and validation of satellite products. The method is challenged by the effect on neutron intensity of other hydrogen pools such as vegetation, canopy interception, and snow. Identifying the signal of the different pools can be used to improve the cosmic‐ray neutron soil moisture method as well as extend the application to, e.g., biomass and canopy interception surveying. More fundamental research is required for advancement of the method to include more energy ranges and consider multiple height levels.

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 correlation forms the base of the cosmic-ray neutron soil moisture estimation method. The method is, however, complicated by the fact that several hydrogen pools other than soil moisture affect the neutron intensity. In order to improve the cosmic-ray neutron soil moisture estimation method and explore the potential for additional applications, knowledge about the environmental effect on cosmic-ray neutron intensity is essential (e.g., the effect of vegetation, litter layer and soil type). In this study the environmental effect is examined by performing a sensitivity analysis using neutron transport modeling. We use a neutron transport model with various representations of the forest and different parameters describing the subsurface to match measured height profiles and time series of thermal and epithermal neutron intensities at a field site in Denmark. Overall, modeled thermal and epithermal neutron intensities are in satisfactory agreement with measurements; however, the choice of forest canopy conceptualization is found to be significant. Modeling results show that the effect of canopy interception, soil chemistry and dry bulk density of litter and mineral soil on neutron intensity is small. On the other hand, the neutron intensity decreases significantly with added litter-layer thickness, especially for epithermal neutron energies. Forest biomass also has a significant influence on the neutron intensity height profiles at the examined field site, altering both the shape of the profiles and the ground-level thermal-to-epithermal neutron ratio. This ratio increases with increasing amounts of biomass, and was confirmed by measurements from three sites representing agricultural, heathland and forest land cover. A much smaller effect of canopy interception on the ground-level thermalto-epithermal neutron ratio was modeled. Overall, the results suggest a potential to use ground-level thermal-to-epithermal neutron ratios to discriminate the effect of different hydrogen contributions on the neutron signal.

Abstract. This paper's objective is to present generic calibration functions for organic surface layers derived for the soil moisture sensors Decagon ECH2O 5TE and Delta-T ThetaProbe ML2x, using material from northern regions, mainly from the Finnish Meteorological Institute's Arctic Research Center in Sodankylä and the study area of the Danish Center for Hydrology (HOBE). For the Decagon 5TE sensor such a function is currently not reported in the literature. Data were compared with measurements from underlying mineral soils including laboratory and field measurements. Shrinkage and charring during drying were considered. For both sensors all field and lab data showed consistent trends. For mineral layers with low soil organic matter (SOM) content the validity of the manufacturer's calibrations was demonstrated. Deviating sensor outputs in organic and mineral horizons were identified. For the Decagon 5TE, apparent relative permittivities at a given moisture content decreased for increased SOM content, which was attributed to an increase of bound water in organic materials with large specific surface areas compared to the studied mineral soils. ThetaProbe measurements from organic horizons showed stronger nonlinearity in the sensor response and signal saturation in the high-level data. The derived calibration fit functions between sensor response and volumetric water content hold for samples spanning a wide range of humus types with differing SOM characteristics. This strengthens confidence in their validity under various conditions, rendering them highly suitable for large-scale applications in remote sensing and land surface modeling studies. Agreement between independent Decagon 5TE and ThetaProbe time series from an organic surface layer at the Sodankylä site was significantly improved when the here-proposed fit functions were used. Decagon 5TE data also well-reflected precipitation events. Thus, Decagon 5TE network data from organic surface layers at the Sodankylä and HOBE sites are based on the hereproposed natural log fit. The newly derived ThetaProbe fit functions should be used for hand-held applications only, but prove to be of value for the acquisition of instantaneous large-scale soil moisture estimates.

Abstract. Climate change increases the occurrence and severity of droughts due to increasing temperatures, altered circulation patterns, and reduced snow occurrence. While Europe has suffered from drought events in the last decade unlike ever seen since the beginning of weather recordings, harmonized long-term datasets across the continent are needed to monitor change and support predictions. Here we present soil moisture data from 66 cosmic-ray neutron sensors (CRNSs) in Europe (COSMOS-Europe for short) covering recent drought events. The CRNS sites are distributed across Europe and cover all major land use types and climate zones in Europe. The raw neutron count data from the CRNS stations were provided by 24 research institutions and processed using state-of-the-art methods. The harmonized processing included correction of the raw neutron counts and a harmonized methodology for the conversion into soil moisture based on available in situ information. In addition, the uncertainty estimate is provided with the dataset, information that is particularly useful for remote sensing and modeling applications. This paper presents the current spatiotemporal coverage of CRNS stations in Europe and describes the protocols for data processing from raw measurements to consistent soil moisture products. The data of the presented COSMOS-Europe network open up a manifold of potential applications for environmental research, such as remote sensing data validation, trend analysis, or model assimilation. The dataset could be of particular importance for the analysis of extreme climatic events at the continental scale. Due its timely relevance in the scope of climate change in the recent years, we demonstrate this potential application with a brief analysis on the spatiotemporal soil moisture variability. The dataset, entitled “Dataset of COSMOS-Europe: A European network of Cosmic-Ray Neutron Soil Moisture Sensors”, is shared via Forschungszentrum Jülich: https://doi.org/10.34731/x9s3-kr48 (Bogena and Ney, 2021).