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Recent advances in wireless sensor technology allow monitoring of soil moisture dynamics with high temporal resolution at varying spatial scales. The objectives of this study were to: (i) develop an efficient strategy for monitoring soil moisture dynamics at the hillslope scale using a wireless sensor network; and (ii) characterize spatial patterns of soil moisture and infer hydrological processes controlling the dynamics of such patterns, using a method of analysis that allows the identification of the relevant hydrological dynamics within large data sets. We combined soil hydrological and pedological expertise with geophysical measurements and methods from digital soil mapping for designing the monitoring setup for a grassland hillslope in the Schäfertal catchment, central Germany. Hypothesizing a wet and a dry soil moisture state to be characteristic of the spatial pattern of soil moisture, we described the spatial and temporal evolution of such patterns using a method of analysis based on the Spearman rank correlation coefficient. We described the persistence and switching mechanisms of the two characteristic states, inferring the local properties that control the observed spatial patterns and the hydrological processes driving the transitions. The spatial organization of soil moisture appears to be controlled by different processes in different soil horizons, and the topsoil's moisture does not mirror processes that take place within the soil profile. The results will help to improve conceptual understanding for hydrological model studies at similar or smaller scales and to transfer observation concepts and process understanding to larger or less instrumented areas.

Root water uptake is one of the essential processes within the soil–plant–atmosphere continuum. We present a method for monitoring soil‐water redistributions due to water uptake by roots. Our aim is to image and monitor diurnal soil‐water redistribution during a small‐scale (centimeter‐to‐decimeter range) indoor experiment and to correlate water content determined by applied geoelectrical time‐lapse imaging techniques with values from single‐point time domain reflectometry (TDR) measurements. This includes establishing pedophysical relationships within the root zone and deriving the water‐content distribution from the electrical‐resistivity model. Using DC geoelectrics of high resolution (970 data points for 220 cm2), we monitored significant spatial heterogeneity of soil moisture with time, whereas no irrigation was applied. Thus, we imaged the high heterogeneity of fluid movements within the soil. We found diurnal variations with high spatial variability of soil water content during the morning and afternoon hours. The water content continuously increased from dawn to noon, whereas the increase started in the near‐surface zone from 1 cm to 3 cm above the main root zone. Between 8:00 a.m. and 10:00 a.m., water content decreases along most of the sections. Water content irregularly decreases and increases during the afternoon. During night time, we observed nearly no changes in soil water content due to the absence of transpiration and subsequently soil‐water redistribution. Most of these diurnal variations in soil water content lie within the intensive root zone, as measurements showed on soil samples excavated from these areas after the experiment. Furthermore, we quantified water content derived from geoelectrical tomography of the monitored area before and after an irrigation event using a geophysical pedotransfer function of Archie, established specifically for the used lupine and the applied physico‐chemical boundary conditions of the experiment. The resulting average water content from 2D geoelectrical tomography agreed well with the values determined by the TDR measurements.

In the face of rapid global change it is imperative to preserve geodiversity for the overall conservation of biodiversity. Geodiversity is important for understanding complex biogeochemical and physical processes and is directly and indirectly linked to biodiversity on all scales of ecosystem organization. Despite the great importance of geodiversity, there is a lack of suitable monitoring methods. Compared to conventional in-situ techniques, remote sensing (RS) techniques provide a pathway towards cost-effective, increasingly more available, comprehensive, and repeatable, as well as standardized monitoring of continuous geodiversity on the local to global scale. This paper gives an overview of the state-of-the-art approaches for monitoring soil characteristics and soil moisture with unmanned aerial vehicles (UAV) and air- and spaceborne remote sensing techniques. Initially, the definitions for geodiversity along with its five essential characteristics are provided, with an explanation for the latter. Then, the approaches of spectral traits (ST) and spectral trait variations (STV) to record geodiversity using RS are defined. LiDAR (light detection and ranging), thermal and microwave sensors, multispectral, and hyperspectral RS technologies to monitor soil characteristics and soil moisture are also presented. Furthermore, the paper discusses current and future satellite-borne sensors and missions as well as existing data products. Due to the prospects and limitations of the characteristics of different RS sensors, only specific geotraits and geodiversity characteristics can be recorded. The paper provides an overview of those geotraits.

Abstract. Electromagnetic induction (EMI) measurements are widely used for soil mapping, as they allow fast and relatively low-cost surveys of soil apparent electrical conductivity (ECa). Although the use of non-invasive EMI for imaging spatial soil properties is very attractive, the dependence of ECa on several factors challenges any interpretation with respect to individual soil properties or states such as soil moisture (θ ). The major aim of this study was to further investigate the potential of repeated EMI measurements to map θ , with particular focus on the temporal variability of the spatial patterns of ECa and θ . To this end, we compared repeated EMI measurements with high-resolution θ data from a wireless soil moisture and soil temperature monitoring network for an extensively managed hillslope area for which soil properties and θ dynamics are known. For the investigated site, (i) ECa showed small temporal variations whereas θ varied from very dry to almost saturation, (ii) temporal changes of the spatial pattern of ECa differed from those of the spatial pattern of θ , and (iii) the ECa-θ relationship varied with time. Results suggest that (i) depending upon site characteristics, stable soil properties can be the major control of ECa measured with EMI, and (ii) for soils with low clay content, the influence of θ on ECa may be confounded by changes of the electrical conductivity of the soil solution. Further, this study discusses the complex interplay between factors controlling ECa and θ , and the use of EMI-based ECa data with respect to hydrological applications.

In this paper we present the results of seasonal monitoring and irrigation tests performed on an experimental farm in a semiarid region of Southern Sardinia. The goal of the study is to understand the soil–vegetation interactions and how they can affect the soil water balance, particularly in view of possible climatic changes. We used long‐term electromagnetic induction (EMI) time lapse monitoring and short‐term irrigation experiments monitored using electrical resistivity tomography (ERT) and EMI, supported by time domain reflectometry (TDR) soil moisture measurements. Mapping of natural γ‐ray emission, texture analysis, and laboratory calibration of an electrical constitutive relationship on soil samples complete the dataset. We observe that the growth of vegetation, with the associated below‐ground allocation of biomass, has a significant impact on the soil moisture dynamics. It is well known that vegetation extracts a large amount of water from the soil particularly during summer, but it also reduces evaporation by shadowing the soil surface. Vegetation represents a screen for rainfall and prevents light rainfall infiltration but enhances the wetting process by facilitating the infiltration and the ground water recharge. In many cases, the vegetation creates a positive feedback system. In our study, these mechanisms are well highlighted by the use of noninvasive techniques that provide data at the scale and resolution necessary to understand the hydrological processes of the topsoil, also in their lateral and depth spatial variability. Unlike remote sensing techniques, noninvasive geophysics penetrates the soil subsurface and can effectively image moisture content in the root zone. We also developed a simple conceptual model capable of representing the vegetation–soil interaction with a simple enough parameterization that can be fulfilled by measurements of a noninvasive nature, available at a large scale and evidences possible relevant developments of our research.