Repeated electromagnetic induction measurements for mapping soil moisture at the field scale: validation with data from a wireless soil moisture monitoring network

Abstract

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.

How can we model subsurface stormflow at the catchment scale if we cannot measure it?

“…Hydrogeophysical methods may have the potential to identify subsurface flow paths (e.g., Angermann et al, 2017;Binley et al, 2015) or, at least, soil heterogeneity (Martini et al, 2017), but their use is mostly limited to the hillslope scale (Vereecken et al, 2015).…”

Integration of hydrogeophysical datasets and empirical orthogonal functions for improved irrigation water management

“…This type of information has been used for the delineation of irrigation management zones (IMZs; Pan et al 2013). As noted previously, the ECa map is subject to field conditions at the time of the sampling (Martini et al 2016). Therefore, areas of high EC measurements in the southwest quadrant of the field may be due to increased soil cations, soil water content (SWC), and/or temperature anomalies at the time of sampling.…”

“…While changes in SWC do account for over 50% of variability in soil EC readings (Brevik et al 2006), the dynamic nature of SWC causes EC and clay measurements to vary temporally (McCutcheon et al 2006) making the use of a single EC survey problematic. Martini et al (2016) investigated this temporal variability and emphasized the importance of multiple surveys to capture the dynamic SWC patterns represented by EC surveys. Other impacting factors, beyond SWC, include groundwater levels and the concentration of the pore water solution, which influence the electrical conductance pathway (Martini et al 2016).…”

“…Martini et al (2016) investigated this temporal variability and emphasized the importance of multiple surveys to capture the dynamic SWC patterns represented by EC surveys. Other impacting factors, beyond SWC, include groundwater levels and the concentration of the pore water solution, which influence the electrical conductance pathway (Martini et al 2016). Additional commercially available methodologies are available for measuring soil physical variability, however they were not explored in this study [e.g.…”

Principal Component Analysis of the Spatiotemporal Pattern of Soil Moisture and Apparent Electrical Conductivity

“…The basic principle of EMI‐based measurements of ECa (Rhoades et al, 1989) indicates that ECa is a complex physicochemical parameter influenced by any soil property or state that influences electrical conductance pathways in soils (e.g., Corwin et al, 2008) with time‐varying contribution (Farahani et al, 2005). In the last decades, EMI measurements have been applied to address different research questions (e.g., Doolittle et al, 1994; Corwin and Lesch, 2005; Werban et al, 2009; Zhu et al, 2010; Triantafilis et al, 2013; Scudiero et al, 2015; Rudolph et al, 2016; Doolittle and Brevik, 2014), including soil moisture estimation (e.g., García et al, 2010, 2012; Robinson et al, 2012; von Hebel et al, 2014; Shanahan et al, 2015; Pedrera‐Parilla et al, 2016, 2017; Huang et al, 2016; Martini et al, 2017; Huang et al, 2017; Altdorff et al, 2017), and it appears clear that the method is a valuable support to environmental studies because it allows mapping the soil spatial variability with high spatial resolution.…”