Electrical resistivity tomography (ERT) and induced polarization (IP) methods are now widely used in many interdisciplinary projects. Although field surveys using these methods are relatively ...straightforward, ERT and IP data require the application of inverse methods prior to any interpretation. Several established non-commercial inversion codes exist, but they typically require advanced knowledge to use effectively. ResIPy was developed to provide a more intuitive, user-friendly, approach to inversion of geoelectrical data, using an open source graphical user interface (GUI) and a Python application programming interface (API). ResIPy utilizes the mature R2/cR2 inversion codes for ERT and IP, respectively. The ResIPy GUI facilitates data importing, data filtering, error modeling, mesh generation, data inversion and plotting of inverse models. Furthermore, the easy to use design of ResIPy and the help provided inside makes it an effective educational tool. This paper highlights the rationale and structure behind the interface, before demonstrating its capabilities in a range of environmental problems. Specifically, we demonstrate the ease at which ResIPy deals with topography, advanced data processing, the ability to fix and constrain regions of known geoelectrical properties, time-lapse analysis and the capability for forward modeling and survey design.
•Geophysics is more frequently used in interdisciplinary projects by non-specialists.•ResIPy is a simple to use, intuitive, open source graphical user interface and API.•ResIPy is a good teaching tool to learn how to invert and model geoelectrical data.•Data filtering and error modeling of resistivity and IP data improve inversion.•Field applications and survey design with ResIPy is demonstrated.
Geophysics provides a multidimensional suite of investigative methods that are transforming our ability to see into the very fabric of the subsurface environment, and monitor the dynamics of its ...fluids and the biogeochemical reactions that occur within it. Here we document how geophysical methods have emerged as valuable tools for investigating shallow subsurface processes over the past two decades and offer a vision for future developments relevant to hydrology and also ecosystem science. The field of “hydrogeophysics” arose in the late 1990s, prompted, in part, by the wealth of studies on stochastic subsurface hydrology that argued for better field‐based investigative techniques. These new hydrogeophysical approaches benefited from the emergence of practical and robust data inversion techniques, in many cases with a view to quantify shallow subsurface heterogeneity and the associated dynamics of subsurface fluids. Furthermore, the need for quantitative characterization stimulated a wealth of new investigations into petrophysical relationships that link hydrologically relevant properties to measurable geophysical parameters. Development of time‐lapse approaches provided a new suite of tools for hydrological investigation, enhanced further with the realization that some geophysical properties may be sensitive to biogeochemical transformations in the subsurface environment, thus opening up the new field of “biogeophysics.” Early hydrogeophysical studies often concentrated on relatively small “plot‐scale” experiments. More recently, however, the translation to larger‐scale characterization has been the focus of a number of studies. Geophysical technologies continue to develop, driven, in part, by the increasing need to understand and quantify key processes controlling sustainable water resources and ecosystem services.
Key Points:
A review of the emergence and development of hydrogeophysics
Outline of emerging techniques in hydrogeophysics
Presentation of future opportunities in hydrogeophysics
Geophysical imaging has traditionally provided qualitative information about geologic structure; however, there is increasing interest in using petrophysical models to convert tomograms to ...quantitative estimates of hydrogeologic, mechanical, or geochemical parameters of interest (e.g., permeability, porosity, water content, and salinity). Unfortunately, petrophysical estimation based on tomograms is complicated by limited and variable image resolution, which depends on (1) measurement physics (e.g., electrical conduction or electromagnetic wave propagation), (2) parameterization and regularization, (3) measurement error, and (4) spatial variability. We present a framework to predict how core‐scale relations between geophysical properties and hydrologic parameters are altered by the inversion, which produces smoothly varying pixel‐scale estimates. We refer to this loss of information as “correlation loss.” Our approach upscales the core‐scale relation to the pixel scale using the model resolution matrix from the inversion, random field averaging, and spatial statistics of the geophysical property. Synthetic examples evaluate the utility of radar travel time tomography (RTT) and electrical‐resistivity tomography (ERT) for estimating water content. This work provides (1) a framework to assess tomograms for geologic parameter estimation and (2) insights into the different patterns of correlation loss for ERT and RTT. Whereas ERT generally performs better near boreholes, RTT performs better in the interwell region. Application of petrophysical models to the tomograms in our examples would yield misleading estimates of water content. Although the examples presented illustrate the problem of correlation loss in the context of near‐surface geophysical imaging, our results have clear implications for quantitative analysis of tomograms for diverse geoscience applications.
We estimate parameters from the Katz and Thompson permeability model using laboratory complex electrical conductivity (CC) and nuclear magnetic resonance (NMR) data to build permeability models ...parameterized with geophysical measurements. We use the Katz and Thompson model based on the characteristic hydraulic length scale, determined from mercury injection capillary pressure estimates of pore throat size, and the intrinsic formation factor, determined from multisalinity conductivity measurements, for this purpose. Two new permeability models are tested, one based on CC data and another that incorporates CC and NMR data. From measurements made on forty‐five sandstone cores collected from fifteen different formations, we evaluate how well the CC relaxation time and the NMR transverse relaxation times compare to the characteristic hydraulic length scale and how well the formation factor estimated from CC parameters compares to the intrinsic formation factor. We find: (1) the NMR transverse relaxation time models the characteristic hydraulic length scale more accurately than the CC relaxation time (
R2 of 0.69 and 0.33 and normalized root mean square errors (NRMSE) of 0.16 and 0.21, respectively); (2) the CC estimated formation factor is well correlated with the intrinsic formation factor (NRMSE=0.23). We demonstrate that that permeability estimates from the joint‐NMR‐CC model (NRMSE=0.13) compare favorably to estimates from the Katz and Thompson model (NRMSE=0.074). This model advances the capability of the Katz and Thompson model by employing parameters measureable in the field giving it the potential to more accurately estimate permeability using geophysical measurements than are currently possible.
Key Points:
Complex conductivity and NMR predict the parameters of the Katz and Thompson permeability model
A joint complex conductivity and NMR model accurately predicts permeability for sandstones
Prediction uncertainty cannot be attributed to iron (III) content variability alone
Significant spatial and temporal variability of water fluxes may exist at the river–groundwater interface and the assessment of such variability may be important for appreciation of the spatial and ...temporal dynamics of chemical loading to a river or aquifer. Measurement of such variability is limited due to difficulties of applying conventional Darcian flux based methods. Thermal parameters required to distinguish between conductive and advective heat transfers, and hence to determine water fluxes, exhibit a narrower range within sediments than hydraulic properties required for Darcy-based methods. To exploit this we explore a method of utilising temperature time series to calculate vertical water fluxes across riverbed sediments. River and streambed temperatures may be measured using robust, inexpensive loggers which are simple to deploy. These sensors may provide attenuation and phase shift of the diurnal temperature signal which, at depth, varies with the seepage flux (to or from the river). We present an analytical extension to an existing numerical solution of the heat flow equation, which is used in conjunction with Dynamic Harmonic Regression signal processing techniques for the analysis of diurnal oscillations at two or more depths in the river bed. This permits the computation of a time series of vertical seepage fluxes without the need for complex numerical solutions. Furthermore, Monte Carlo analysis allows an assessment of the uncertainty in the seepage flux estimates to be made. The method has been applied to a reach of a UK lowland river in order to demonstrate that, even in such a low energy environment, water fluxes at the river–groundwater interface are significantly variable. Derived fluxes showed significant variation, which is supported by measurements from other methods. We propose that our approach offers a reliable and robust field-based method for quantifying vertical water fluxes at the groundwater–surface water interface and a means of recording seepage flux time series.
Electrical resistivity tomography (ERT) has proved to be a valuable tool for imaging solute transport processes in the subsurface. However, a quantitative interpretation of corresponding ERT results ...is constrained by a number of factors. One such factor is the nonuniqueness of the ERT inverse problem if no additional constraints are imposed. In the vadose zone, further problems arise from the general ambiguity of the imaged bulk electrical conductivity in terms of water content and solute concentration. In this study we address these issues in detail for a solute tracer experiment conducted in an undisturbed unsaturated soil monolith where the tracer transport was monitored by means of 3-D smoothness-constrained ERT and time domain reflectometry (TDR) measurements. The experimental design allowed the determination of solute tracer concentrations directly from imaged bulk electrical conductivity. Independent TDR data and effluent tracer concentrations provided a “ground truth” for the ERT-derived apparent convection-dispersion equation transport parameters. The apparent transport velocity calculated from the ERT results was consistent with that based on TDR data and the sampled effluent, independent of the degree of smoothness imposed in the ERT inversion. On the other hand, the apparent dispersivity calculated from the ERT results was larger than that estimated from TDR data but smaller than that estimated from the sampled effluent, with the magnitude of deviations dependent on the degree of smoothing. Importantly, no mass balance problems were observed in the ERT results. We believe that this is largely a consequence of the uniform application of the tracer as a front and of the configuration of the electrode array with respect to the main transport direction. In conclusion, the study demonstrates that ERT can yield unprecedented quantitative information about local- and column-scale solute transport characteristics in natural soils.
1 Appropriate regularizations of geophysical inverse problems and joint inversion of different data types improve geophysical models and increase their usefulness in hydrogeological studies. We have ...developed an efficient method to calculate stochastic regularization operators for given geostatistical models. The method, which combines circulant embedding and the diagonalization theorem of circulant matrices, is applicable for stationary geostatistical models when the grid discretization, in each spatial direction, is uniform in the volume of interest. We also used a structural approach to jointly invert cross-hole electrical resistance and ground-penetrating radar traveltime data in three dimensions. The two models are coupled by assuming, at all points, that the cross product of the gradients of the two models is zero. No petrophysical relationship between electrical conductivity and relative permittivity is assumed but is instead obtained as a by-product of the inversion. The approach has been applied to data collected in a U.K. sandstone aquifer in order to improve characterization of the vadose zone hydrostratigraphy. By analyzing scatterplots of electrical conductivity versus relative permittivity together with petrophysical models a zonation could be obtained with corresponding estimates of the electrical formation factor, the water content, and the effective grain radius of the sediments. The approach provides greater insight into the hydrogeological characteristics of the subsurface than by using conventional geophysical inversion methods.
There is widespread recognition that the groundwater‐surface water interface can have significant influence on the pattern and form of the transfer of nutrient‐rich groundwater to rivers. ...Characterizing and quantifying this influence is critical for successful management of water resources in many catchments, particularly those threatened by rising nitrate levels in groundwater. Building on previous experimental investigations in one such catchment: the River Leith, UK, we report on a multimeasurement, multiscale program aimed at developing a conceptualization of groundwater‐surface water flow pathways along a 200 m reach. Key to this conceptualization is the quantification of vertical and horizontal water fluxes, which is achieved through a series of Darcian flow estimates coupled with in‐stream piezometer tracer dilution tests. These data, enhanced by multilevel measurements of chloride concentration in riverbed pore water and water‐borne geophysical surveying, reveal a contrast in the contribution of flow components along the reach. In the upper section of the reach, a localized connectivity to regional groundwater, that appears to suppress the hyporheic zone, is identified. Further downstream, horizontal (lateral and longitudinal) flows appear to contribute more to the total subsurface flow at the groundwater‐surface water interface. Although variation in hydraulic conductivity of the riverbed is observed, localized variation that can account for the spatial variability in flow pathways is not evident. The study provides a hydrological conceptualization for the site, which is essential for future studies which address biogeochemical processes, in relation to nitrogen retention/release. Such a conceptualization would not have been possible without a multiexperimental program.
Key Points
Quantification of horizontal and vertical water fluxes
Identification of localised upwelling through geophysics
Integration of multiple methods for improved hydrological conceptualization
Hyporheic hydrodynamics are a control on stream ecosystems, yet we lack a thorough understanding of catchment controls on these flow paths, including valley constraint and hydraulic gradients in the ...valley bottom. We performed four whole‐stream solute tracer injections under steady state flow conditions at the H. J. Andrews Experimental Forest (Oregon, United States) and collected electrical resistivity (ER) imaging to directly quantify the 2‐D spatial extent of hyporheic exchange through seasonal base flow recession. ER images provide spatially distributed information that is unavailable for stream solute transport modeling studies from monitoring wells alone. The lateral and vertical extent of the hyporheic zone was quantified using both ER images and spatial moment analysis. Results oppose the common conceptual model of hyporheic “compression” by increased lateral hydraulic gradients toward the stream. We found that the extent of the hyporheic zone increased with decreasing vertical gradients away from the stream, in contrast to expectations from conceptual models. Increasing hyporheic extent was observed with both increasing and decreasing down‐valley (i.e., parallel to the valley gradient) and cross‐valley (i.e., from the hillslope to the stream, perpendicular to the valley gradient) hydraulic gradients. We conclude that neither cross‐valley nor down‐valley hydraulic gradients are sufficient predictors of hyporheic exchange flux nor flow path network extent. Increased knowledge of the controls on hyporheic exchange, the temporal dynamics of exchange flow paths, and their the spatial distribution is the first step toward predicting hyporheic exchange at the scale of individual flow paths. Future studies need to more carefully consider interactions between spatiotemporally dynamic hydraulic gradients and subsurface architecture as controls on hyporheic exchange.
Key Points
No evidence of hydraulic gradients constricting hyporheic zones in steep valleys
Hyporheic response to changing hydraulic gradients varies with valley constraint
Hydrogeophysical methods characterize hyporheic spatial and temporal dynamics
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