Summary. We present a novel technique for the determination of resistivity structures associated with arbitrary surface topography. The approach represents a t

Summary. We present techniques for the efficient numerical computation of the electrical potential with finite element methods in 3-D and arbitrary topography.

A good understanding of the soil water content (SWC) distribution at the field scale is essential to improve the management of water, soil and crops. Recent studies proved that Electrical Resistivity Tomography (ERT) opens interesting perspectives in the determination of the SWC distribution in 3 dimensions (3-D). This study was conducted (i) to check and validate how ERT is able to monitor SWC distribution in a maize field during the late growing season; and (ii) to investigate how maize plants and rainfall affect the dynamics of SWC distribution. Time Domain Reflectometry (TDR) measurements were used to validate ERT-inverted SWC values. Evolution of water mass balance was also calculated to check whether ERT was capable of giving a reliable estimate of soil water stock evolution. It is observed that ERT was able to give the same average SWC as TDR (R² = 0.98). In addition, ERT gives better estimates of the water stock than TDR thanks to its higher spatial resolution. The high resolution of ERT measurements also allows for the discrimination of SWC heterogeneities. The SWC distribution showed that alternation of maize rows and inter-rows was the main influencing factor of the SWC distribution. The drying patterns were linked to the root profiles, with drier zones under the maize rows. During short periods, with negligible rainfall, the SWC decrease took place mainly in the two upper soil horizons and in the inter-row area. In contrast, rainfall increased the SWC mostly under the maize rows and in the upper soil layer. Nevertheless, the total amount of rainfall during the growing season was not sufficient to modify the SWC patterns induced by the maize rows. During the experimental time, there was hardly any SWC redistribution from maize rows to inter-rows. Yet, lateral redistribution from inter-rows to maize rows induced by potential gradient generates SWC decrease in the inter-row area and in the deeper soil horizons.

SUMMARY: Quantitative estimation of pore fractions filled with liquid water, ice and air is crucial for a process-based understanding of permafrost and its hazard potential upon climate-induced degradation. Geophysical methods offer opportunities to image distributions of permafrost constituents in a non-invasive manner. We present a method to jointly estimate the volumetric fractions of liquid water, ice, air and the rock matrix from seismic refraction and electrical resistivity data. Existing approaches rely on conventional inversions of both data sets and a suitable a priori estimate of the porosity distribution to transform velocity and resistivity models into estimates for the four-phase system, often leading to non-physical results. Based on two synthetic experiments and a field data set from an Alpine permafrost site (Schilthorn, Bernese Alps and Switzerland), it is demonstrated that the developed petrophysical joint inversion provides physically plausible solutions, even in the absence of prior porosity estimates. An assessment of the model covariance matrix for the coupled inverse problem reveals remaining petrophysical ambiguities, in particular between ice and rock matrix. Incorporation of petrophysical a priori information is demonstrated by penalizing ice occurrence within the first two meters of the subsurface where the measured borehole temperatures are positive. Joint inversion of the field data set reveals a shallow air-rich layer with high porosity on top of a lower-porosity subsurface with laterally varying ice and liquid water contents. Non-physical values (e.g. negative saturations) do not occur and estimated ice saturations of 0–50 per cent as well as liquid water saturations of 15–75 per cent are in agreement with the relatively warm borehole temperatures between −0.5 and 3 ° C. The presented method helps to improve quantification of water, ice and air from geophysical observations.

The hydrogeological properties and responses of a productive aquifer in northeastern Switzerland are investigated. For this purpose, 3D crosshole electrical resistivity tomography (ERT) is used to define the main lithological structures within the aquifer (through static inversion) and to monitor the water infiltration from an adjacent river. During precipitation events and subsequent river flooding, the river water resistivity increases. As a consequence, the electrical characteristics of the infiltrating water can be used as a natural tracer to delineate preferential flow paths and flow velocities. The focus is primarily on the experiment installation, data collection strategy, and the structural characterization of the site and a brief overview of the ERT monitoring results. The monitoring system comprises 18 boreholes each equipped with 10 electrodes straddling the entire thickness of the gravel aquifer. A multichannel resistivity system programmed to cycle through various four-point electrode configurations of the 180 electrodes in a rolling sequence allows for the measurement of approximately 15,500 apparent resistivity values every 7 h on a continuous basis. The 3D static ERT inversion of data acquired under stable hydrological conditions provides a base model for future time-lapse inversion studies and the means to investigate the resolving capability of our acquisition scheme. In particular, it enables definition of the main lithological structures within the aquifer. The final ERT static model delineates a relatively high-resistivity, low-porosity, intermediate-depth layer throughout the investigated aquifer volume that is consistent with results from well logging and seismic and radar tomography models. The next step will be to define and implement an appropriate time-lapse ERT inversion scheme using the river water as a natural tracer. The main challenge will be to separate the superposed time-varying effects of water table height, temperature, and salinity variations associated with the infiltrating water.