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Aims: The flow of electric current in the root-soil system relates to the pathways of water and solutes, its characterization provides information on the root architecture and functioning. We developed a current source density approach with the goal of non-invasively image the current pathways in the root-soil system. Methods: A current flow is applied from the plant stem to the soil, the proposed geoelectrical approach images the resulting distribution and intensity of the electric current in the root-soil system. The numerical inversion procedure underlying the approach was tested in numerical simulations and laboratory experiments with artificial metallic roots. We validated the method using rhizotron laboratory experiments on maize and cotton plants. Results: Results from numerical and laboratory tests showed that our inversion approach was capable of imaging root-like distributions of the current source. In maize and cotton, roots acted as “leaky conductors”, resulting in successful imaging of the root crowns and negligible contribution of distal roots to the current flow. In contrast, the electrical insulating behavior of the cotton stems in dry soil supports the hypothesis that suberin layers can affect the mobility of ions and water. Conclusions: The proposed approach with rhizotrons studies provides the first direct and concurrent characterization of the root-soil current pathways and their relationship with root functioning and architecture. This approach fills a major gap toward non-destructive imaging of roots in their natural soil environment.

This paper presents a time-lapse application of electrical methods (electrical resistivity tomography, ERT; and mise-à-la-masse, MALM) for monitoring plant roots and their activity (root water uptake) during a controlled infiltration experiment. The use of non-invasive geophysical monitoring is of increasing interest as these techniques provide time-lapse imaging of processes that otherwise can only be measured at few specific spatial locations. The experiment here described was conducted in a vineyard in Bordeaux (France) and was focused on the behaviour of two neighbouring grapevines. The joint application of ERT and MALM has several advantages. While ERT in time-lapse mode is sensitive to changes in soil electrical resistivity and thus to the factors controlling it (mainly soil water content, in this context), MALM uses DC current injected into a tree stem to image where the plant root system is in effective electrical contact with the soil at locations that are likely to be the same where root water uptake (RWU) takes place. Thus, ERT and MALM provide complementary information about the root structure and activity. The experiment shows that the region of likely electrical current sources produced by MALM does not change significantly during the infiltration time in spite of the strong changes of electrical resistivity caused by changes in soil water content. Ultimately, the interpretation of the current source distribution strengthened the hypothesis of using current as a proxy for root detection. This fact, together with the evidence that current injection in the soil and in the stem produces totally different voltage patterns, corroborates the idea that this application of MALM highlights the active root density in the soil. When considering the electrical resistivity changes (as measured by ERT) inside the stationary volume of active roots delineated by MALM, the overall tendency is towards a resistivity increase during irrigation time, which can be linked to a decrease in soil water content caused by root water uptake. On the contrary, when considering the soil volume outside the MALM-derived root water uptake region, the electrical resistivity tends to decrease as an effect of soil water content increase caused by the infiltration. The use of a simplified infiltration model confirms at least qualitatively this behaviour. The monitoring results are particularly promising, and the method can be applied to a variety of scales including the laboratory scale where direct evidence of root structure and root water uptake can help corroborate the approach. Once fully validated, the joint use of MALM and ERT can be used as a valuable tool to study the activity of roots under a wide variety of field conditions.

Permafrost physicochemical parameters play a key role in controlling the response of permafrost carbon to climate change. We studied the physicochemical parameters of permafrost in an Arctic tundra region to evaluate (1) how soil parameters vary with depth and whether and how they are interrelated, (2) whether and how permafrost soil differs from its overlaying active layer, and (3) whether soil property-depth relationships are different across geomorphic features (e.g., low, flat, and high centered polygons). We also explored the possible biogeochemical processes that led to these soil characteristics and how they may affect biogeochemical reactions upon permafrost thaw. We observed (1) consistent relationships between soil property and depth and between major parameters, (2) large contrasts of key soil parameters between active layer and permafrost, indicative of potentially different response of the permafrost carbon to warming when compared to the active layer, and (3) a correlation between soil hydraulic conductivity and topographic features that impacts soil hydrologic processes. Our analysis suggests that the permafrost has a marine-derived chemical signature that differs from the active layer and shapes the physicochemical fingerprints of the different geomorphic features. Specifically, we revealed the unique signatures of the high center polygons, indicative of possible microbial activity at depth (>1 m). Our study suggested consistent key soil parameter-depth correlations while demonstrating complex lateral and vertical variabilities. These results are valuable for identifying approaches to upscale point-based measurements and for improving model parameterization to predict permafrost carbon behavior and feedback under future climate.

Biosouring is commonly encountered during secondary oil recovery when seawater or another high sulfate water source is utilized for flooding; as a result, effective souring control is of great interest to the oil industry. Here we describe a laboratory study to evaluate the relative effectiveness of souring interventions through the injection of nitrate, chlorate and perchlorate, collectively (per)chlorate, solutions and whether in-situ galvanic potential measurements can be used for convenient and quantitative tracking of sulfide dynamics. Nitrate has typically been the chemical of choice for souring treatments, while the efficacy of (per)chlorate as a new candidate inhibitor has only been explored recently. (Per)chlorate is known to inhibit oil reservoir souring via mechanisms such as toxicity, bio-competitive exclusion and sulfur redox cycling. Two sets of experiments under different matrix and inoculation conditions were conducted to evaluate treatment efficiency under variable baseline physical and biogeochemical conditions. Our data demonstrated the sensitivity of the galvanic potential signals to sulfide concentrations where the sulfide-galvanic potential correlation is similar to the theoretical predictions based on the Nernst equation, demonstrating the feasibility of using galvanic potential as a quick and economical method for quantifying in situ sulfide concentrations for tracking reservoir souring processes and subsequent intervention effectiveness. Our results show that all three chemicals were effective at suppressing sulfidogenesis. A reactive transport model for perchlorate treatment was developed to simulate the reaction processes and explore the interactions between the underlying competing mechanisms of this inhibitor. A baseline simulation captured the temporal patterns of the effluent chemical species. Subsequent simulations in which individual inhibition mechanisms were systematically removed elucidated the relative role that each inhibition mechanism played at the different phases of the experiment. The simulation results complement the experimental findings. Our study supports the potential advantages of souring control with (per)chlorate treatments, and the application of galvanic signal as an economic, in-situ monitoring approach for tracking souring dynamics and treatment efficacy.

© 2017 We conducted laboratory studies on the geophysical signals from Arctic saline permafrost soils to help understand the physical and mechanical processes during freeze-thaw cycles. Our results revealed low electrical resistivity (< 20 Ωm) and elastic moduli (7.7 GPa for Young's modulus and 2.9 GPa for shear modulus) at temperatures down to ~− 10 °C, indicating the presence of a significant amount of unfrozen saline water under the current field conditions. The spectral induced polarization signal showed a systematic shift during the freezing process, affected by concurrent changes of temperature, salinity, and ice formation. An anomalous induced polarization response was first observed during the transient period of supercooling and the onset of ice nucleation. Seismic measurements showed a characteristic maximal attenuation at the temperatures immediately below the freezing point, followed by a decrease with decreasing temperature. The calculated elastic moduli showed a non-hysteric response during the freeze – thaw cycle, which was different from the concurrently measured electrical resistivity response where a differential resistivity signal is observed depending on whether the soil is experiencing freezing or thawing. The differential electrical resistivity signal presents challenges for unfrozen water content estimation based on Archie's law. Using an improved formulation of Archie's law with a variable cementation exponent, the unfrozen water content estimation showed a large variation depending on the choice of the resistivity data during either a freezing or thawing cycle. Combining the electrical and seismic results, we suggest that, rather than a large hysteresis in the actual unfrozen water content, the shift of the resistivity response may reflect the changes of the distribution pattern of the unfrozen water (or ice) in the soil matrix during repeated freeze and thaw processes. Collectively, our results provide an improved petrophysical understanding of the physical and mechanical properties of saline permafrost during freeze – thaw transitions, and suggest that large uncertainty may exist when estimating the unfrozen water content using electrical resistivity data.

Improving understanding of Arctic ecosystem climate feedback and parameterization of models that simulate freeze-Thaw dynamics require advances in quantifying soil and snow properties. Due to the significant spatiotemporal variability of soil properties and the limited information provided by point-scale measurements (e.g., cores), geophysical methods hold potential for improving soil and permafrost characterization. In this study, we evaluate the use of a ground-penetrating radar (GPR) to estimate thaw layer thickness, snow depth, and ice-wedge characteristics in an ice-wedge-dominated tundra region near Barrow, AK, USA. To this end, we analyze GPR and point-scale measurements collected along several parallel transects at the end of the growing season and the end of frozen season. In addition, we compare the structural information extracted from the GPR data with electrical resistivity tomography (ERT) information about ice-wedge characteristics. Our study generally highlights the value of GPR data collected in the frozen season, when conditions lead to the improved GPR signal-To-noise ratio, facilitate data acquisition, and reduce acquisition-related ecosystem disturbance relative to growing season. We document for the first time that GPR data collected during the frozen season can provide reliable estimates of active layer thickness and geometry of ice wedges. We find that the ice-wedge geometry extracted from GPR data collected during the frozen season is consistent with ERT data, and that GPR data can be used to constrain the ERT inversion. Consistent with recent studies, we also find that GPR data collected during the frozen season can provide good estimates of snow thickness, and that GPR data collected during the growing season can provide reliable estimate thaw depth. Our quantification of the value of the GPR and ERT data collected during growing and frozen seasons paves the way for coupled inversion of the datasets to improve understanding of permafrost variability.

TOUGH2 and iTOUGH2 are powerful models that simulate the heat and fluid flows in porous and fracture media, and perform parameter estimation, sensitivity analysis and uncertainty propagation analysis. However, setting up the input files is not only tedious, but error prone, and processing output files is time consuming. In this study, we present an open source Matlab-based tool (iMatTOUGH) that supports the generation of all necessary inputs for both TOUGH2 and iTOUGH2 and visualize their outputs. The tool links the inputs of TOUGH2 and iTOUGH2, making sure the two input files are consistent. It supports the generation of rectangular computational mesh, i.e., it automatically generates the elements and connections as well as their properties as required by TOUGH2. The tool also allows the specification of initial and time-dependent boundary conditions for better subsurface heat and water flow simulations. The effectiveness of the tool is illustrated by an example that uses TOUGH2 and iTOUGH2 to estimate soil hydrological and thermal properties from soil temperature data and simulate the heat and water flows at the Rifle site in Colorado.

Shallow permafrost distribution and characteristics are important for predicting ecosystem feedbacks to a changing climate over decadal to century timescales because they can drive active layer deepening and land surface deformation, which in turn can significantly affect hydrologic and biogeochemical responses, including greenhouse gas dynamics. As part of the U.S. Department of Energy Next-Generation Ecosystem Experiments- Arctic, we have investigated shallow Arctic permafrost characteristics at a site in Barrow, Alaska, with the objective of improving our understanding of the spatial distribution of shallow permafrost, its associated properties, and its links with landscape microtopography. To meet this objective, we have acquired and integrated a variety of information, including electric resistance tomography data, frequency-domain electromagnetic induction data, laboratory core analysis, petrophysical studies, high-resolution digital surface models, and color mosaics inferred from kite-based landscape imaging. The results of our study provide a comprehensive and high-resolution examination of the distribution and nature of shallow permafrost in the Arctic tundra, including the estimation of ice content, porosity, and salinity. Among other results, porosity in the top 2 m varied between 85% (besides ice wedges) and 40%, and was negatively correlated with fluid salinity. Salinity directly influenced ice and unfrozen water content and indirectly influenced the soil organic matter content. A relatively continuous but depth-variable increase in salinity led to a partially unfrozen saline layer (cryopeg) located below the top of the permafrost. The cryopeg environment could lead to year-round microbial production of greenhouse gases. Results also indicated a covariability between topography and permafrost characteristics including icewedge and salinity distribution. In addition to providing insight about the Arctic ecosystem, through integration of lab-based petrophysical results with field data, this study also quantified the key controls on electric resistivity at this Arctic permafrost site, including salinity, porosity, water content, ice content, soil organic matter content, and lithologic properties.

A great deal of interest has developed in estimating site-specific petrophysical relationships between hydrogeological and geophysical properties. We compare two approaches that use either flowmeter (Chen et al., 2001) or tracer test data (Linde et al., 2004) in combination with radar tomograms to infer a petrophysical relationship between radar velocity and permeability, in order to estimate the permeability structure between boreholes. We apply these methods to the Oyster site, VA, and compare the estimated petrophysical relationships. These relationships should be very similar if the assumptions underlying the two methods were fulfilled. We attribute the observed discrepancies between the relationships to space-varying resolution of the radar tomograms, differences in measurement support volume, and the larger sensitivity to 3-D effects in the method that uses tracer test data. We believe that comparisons like this are useful to evaluate the predictive power of hydrogeophysical parameter estimation methods.