Estimating the characteristics of soil surface represents a significant area in applications such as hydrology, climatology, and agriculture. Signals transmitted from Global Navigation Satellite Systems (GNSSs) can be used for soil monitoring after reflection from the Earth's surface. In this paper, the feasibility of obtaining surface characteristics from the power ratio of lefthand (LH) reflected signal-to-noise ratio (SNR) over direct righthand (RH) is investigated. The analysis was done regardless of the surface roughness and the incoherent components of the reflected power. First, the analysis was carried out on data collected during several in situ measurements in controlled environments with known characteristics. Then, further data were collected by a GNSS receiver prototype installed on a small aircraft and analyzed. This system was calibrated on the basis of signals reflected from water. The reflectivity and the estimated permittivity showed good correlation with the types of underlying terrain.

The dynamics of fluid displacement in porous media often affect phase entrapment and shape macroscopic transport properties and thus are of considerable interest for a range of natural and engineering applications. The macroscopic motion of a displacement front is composed of numerous abrupt pore‐scale invasion events that involve rapid interfacial jumps and reconfigurations with associated mechanical and interfacial energy release detectable as acoustic emissions (AE). We conducted systematic experiments of fluid displacement and measured associated AE during passage of fluid fronts (primarily drainage) within assemblies of glass beads of different sizes. Results indicated distinct acoustic signatures associated with different displacement processes, reflecting dependency on porous media pore size, displacement flow rate, and liquid properties. The rich AE signals associated with front dynamics exhibited power law relationships between the number of AE events and their amplitudes, reminiscent of avalanche‐like invasion processes. In addition to AE signals emanating from rapid emptying or filling of pores (Haines jumps), other processes such as redistribution and interfacial reconfigurations behind a drainage front and grain rearrangement may generate AE. Characteristic AE signatures generated by displacement processes in different media and under various boundary conditions offer a promise for remote detection of pore‐scale fluid interfacial dynamics in porous media that may shape macroscopic transport properties (e.g., linked with phase entrapment).

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).

International audienceKnowledge of the soil water retention function is fundamental to quantifying the flow of water and dissolved contaminants in the vadose zone. This function is usually determined by fitting a particular model (see, for example, van Genuchten (1980) or Brooks-Corey (1964)) to observed retention points. Independent of the model chosen, interpretation and identification of the water retention parameters are subjective and prone to error, particularly as it is common that the hysteresis history in measured data points is unknown. Experimental data sets from three different field soils are used to clearly demonstrate how the lack of hysteresis knowledge can lead to an inconsistent and incorrect interpretation of the retention data, and therefore to the incorrect estimation of soil hydraulic parameters. By using a hysteresis model to interpret this same data set, it is easily shown that consistent and reliable estimates of soil retention parameters can be obtained. This is true for any physically based hysteresis model. The difficulty in reading water retention measurements may be evident when both drying and wetting data are measured. However, in practice, users are rarely aware of this problem since generally only one set of drying data is measured, making comparison impossible. Such erratic interpretation of water retention field data in the literature will be probably far more common than expected