The method of soil moisture sensing by cosmic-ray neutrons

2021

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:

Earth System Science Data

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 km 2 : 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 Published by Copernicus Publications. 2290 B. Fersch et al.: A dense CRNS network for soil moisture observation 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 rootzone 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:

Geophysical Research Letters

Soil moisture partly controls land-atmosphere mass and energy exchanges and ecohydrological processes in natural and agricultural systems. Thus, many models and remote-sensing products continue to improve their spatio-temporal resolution of soil moisture, with some land surface models reaching 1 km resolution. However, the reliability and accuracy of both modeled and remotely-sensed soil moisture requires comparison with ground measurements at the appropriate spatio-temporal scales. One promising technique is the cosmic-ray neutron probe. Here we further assess the suitability of this technique for real-time monitoring across a large area by combining data from three fixed probes and roving surveys over a 12 by 12 km area in eastern Nebraska. Regression analyses indicated linear relationships between the fixed probe averages and roving estimates of soil moisture for each grid cell, allowing us to derive an 8-hr product at spatial resolutions of 1, 3, and 12 km, with RMSE of 3%, 1.8%...

Monitoring soil moisture is still a challenge: it varies strongly in space and time and at various scales while well established sensors typically suffer from a small spatial support. With a sensor footprint up to several hectares, Cosmic-Ray Neutron Sensing (CRNS) is an emerging 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 5 presents, for the first time, a dense network of 24 CRNS stations that covered, from May to July 2019, an area of just 1 km 2 : 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, that 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 to study soil moisture variability at various spatial scales: roving (mobile) 10 1

South African Journal of Science

Soil moisture is an important hydrological parameter, which is essential for a variety of applications, thereby extending to numerous disciplines. Currently, there are three methods of estimating soil moisture: ground-based (in-situ) measurements; remote sensing based methods and land surface models. In recent years, the cosmic ray probe (CRP), which is an in-situ technique, has been implemented in several countries across the globe. The CRP provides area-averaged soil moisture at an intermediate scale and thus bridges the gap between in-situ point measurements and global satellite-based soil moisture estimates. The aim of this study was to test the suitability of the CRP to provide spatial estimates of soil moisture. The CRP was set up and calibrated in Cathedral Peak Catchment VI. An in-situ soil moisture network consisting of time-domain reflectometry and Echo probes was created in Catchment VI, and was used to validate the CRP soil moisture estimates. Once calibrated, the CRP wa...

Hydrology and Earth System Sciences Discussions

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 <q>rover</q>, 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 ...

2020

Cosmic-ray neutron sensing (CRNS) has emerged as a reliable method for soil moisture and snow estimation. However, the applicability of this method beyond research has been limited due to, among others, the use of relatively large and expensive sensors. This paper presents the tests conducted to a new scintillator-based sensor especially designed to jointly measure neutron counts, total gamma-rays, and muons. The neutron signal is firstly compared against two conventional gas-tube-based CRNS sensors at two locations (Austria and 20 Germany). The estimated soil moisture is further assessed at four agricultural sites in Italy based on gravimetric soil moisture collected within the sensor footprint. The results show that the signal detected by the new scintillator-based CRNS sensor is well in agreement with the conventional CRNS sensors and with the gravimetric soil moisture measurements. In addition, the muons and the total gamma-rays simultaneously detected by the sensor show promising features for a better correction of the incoming variability and for 25 discriminating irrigation and precipitation events, respectively. Further experiments and analyses should be conducted, however, to better understand the added value of these additional data for soil moisture estimation. Overall, the new scintillator design shows to be a valid and compact alternative to conventional CRNS sensors for non-invasive soil moisture monitoring that can open the path to a wide range of applications. 1 Introduction 30 Soil moisture plays a key role in the hydrological cycle controlling water and energy fluxes at the land surface

Water Resources Research, 2014

The semitheoretical universal calibration function (UCF) for estimating soil moisture using cosmic-ray neutron sensors was tested by comparing to field measurements made with the same neutron detector across a range of climates, soil, latitude, altitude, and biomass. There was a strong correlation between neutron intensity and the total amount of hydrogen at each site; however, the relationship differed from that predicted by the UCF. A linear fit to field measurements explained 99% of the observed variation and provides a robust empirical means to estimate soil moisture at other sites. It was concluded that measurement errors, neutron count corrections, and scaling to remove altitudinal and geomagnetic differences were unlikely to explain differences between observations and the UCF. The differences may be attributable to the representation of organic carbon, biomass or detector geometry in the neutron particle code, or to differences in the neutron energy levels being measured by the cosmic-ray sensor and modeled using the particle code. The UCF was derived using simulations of epithermal neutrons; however, lower energy thermal neutrons may also be important. Using neutron transport code, we show the differences in response of thermal and epithermal neutrons to the relative size of the hydrogen pool. Including a thermal neutron component in addition to epithermal neutrons in a modified UCF provided a better match to field measurements; however, thermal neutron measurements are needed to confirm these results. A simpler generalized relationship for estimating soil moisture from neutron counts was also tested with encouraging results for low biomass sites.

Applied and Environmental Soil Science, 2016

With an ever-increasing demand for natural resources and the societal need to understand and predict natural disasters, soil water content (SWC) observations remain a critical variable to monitor in order to optimally allocate resources, establish early warning systems, and improve weather forecasts. However, routine agricultural production practices of soil cultivation, planting, and harvest make the operation and maintenance of direct contact point sensors for long-term monitoring challenging. In this work, we explore the use of the newly established Cosmic-Ray Neutron Probe (CRNP) and method to monitor landscape average SWC in a mixed agricultural land use system in northeast Austria. The calibrated CRNP landscape SWC values compare well against an independentin situSWC probe network (MAE = 0.0286 m3/m3) given the challenge of continuousin situmonitoring from probes across a heterogeneous agricultural landscape. The ability of the CRNP to provide real-time and accurate landscape ...