Geology topics

Scott Ikard

Publications and source records attributed to Scott Ikard.

At least 19 recordsLinked to original sources

USGS2026

Localization of spatiotemporally heterogeneous subsurface flows using autoencoder-based deep learning framework for time-lapse self-potential tomography

Self-potential (SP) monitoring has emerged as a valuable method for characterizing subsurface hydrogeological features and processes due to its sensitivity to fluid-induced electrokinetic effects. Despite advancements in SP inversion, challenges remain in imaging groundwater dynamics from SP activities due to complex hydrological settings and transient noise. In this study, a deep learning autoencoder (AE)-based framework is proposed for the spatiotemporal localization of subsurface fluid movement from time-lapse SP tomography. Temporal segments of time-lapse numerical inversions were first derived from long-term SP monitoring conducted from a floodplain site in Oak Ridge, Tennessee, known for active hyporheic exchange. Subsequently, AE models based on vision transformer (ViT), convolutional long short-term memory (ConvLSTM), convolutional neural network, and temporal convolutional network were individually trained and compared on the SP tomography segments for reconstruction performance. Finally, the reconstruction error over time serves as an anomaly score to identify moments of active SP variation, whereas spatial distributions of errors within these moments are analyzed to image and localize regions associated with anomalous subsurface fluid movement. The results demonstrate that ConvLSTM- and ViT-AE are most capable for the localization task with contrasting error distributions and consistent delineation of anomalies. Applying the method to both SP arrays parallel and perpendicular to the stream produced consistent anomaly zones near a fault or karst feature, validating the robustness and generalization of the approach. These results demonstrate the potential of the proposed framework as a scalable and interpretable tool for spatiotemporal analysis of subsurface flow dynamics in complex hydrogeological systems.

Tennessee↗

USGS2025

Imaging hyporheic exchange by integrating deep learning and physics-informed inversion of time-lapse self-potential data

Self-potential (SP) monitoring is increasingly used for subsurface flow characterization due to its sensitivity to hydrogeological and geochemical processes. However, SP inversion remains challenging due to its ill-posed nature, sparse data coverage, and strong transient noise. This study proposes a hybrid framework to image hyporheic exchange using a time-lapse SP data set monitored from a streamflow site in Oak Ridge, Tennessee. Dipole moment tomography grids generated from the physics-informed numerical inversion is first used to train a Vision Transformer (ViT) model that maps surface SP sequences to 2D source distributions. While the numerical method is more responsive to transient signals, the ViT model better captures persistent spatial structures. Their complementary outputs are jointly analyzed in the spatiotemporal domain to isolate dynamic hyporheic exchange zones and distinguish transient from steady state subsurface flow features. This approach integrates physical inversion and deep learning to enhance interpretability, generalization, and temporal awareness in SP analysis.

Geophysical Research Letters↗

USGS2024

Self-potential tomography preconditioned by particle swarm optimization— Application to monitoring hyporheic exchange in a bedrock river

A self-potential (SP) data-inversion algorithm was developed and tested on an analytical model of electrical-potential profile data attributed to single and multiple polarized electrical sources. The developed algorithm was then validated by an application to SP-monitoring field data measured on the floodplain of East Fork Poplar Creek, Oak Ridge, Tennessee, to image electrical sources in areas conducive to preferential flow into the flood plain from the bedrock-lined riverbed. The algorithm combined stochastic source-localization by particle-swarm-optimization (PSO) of electrical sources characterized by simplified geometries with source tomography by regularized weighted least-squares minimization of a quadratic objective function. Prior information was incorporated by preconditioning the tomography algorithm by PSO results. Variable percentages of random noise were added to analytical-model data to evaluate the algorithm performance. Results indicated that true parameters of single-source models were inverted and approximated with small residual error, whereas inversion of analytical-model data representing multiple electrical sources accurately approximated the locations of the sources but miscalculated some parameters because of the non-uniqueness of the inverse-model solution. Source tomography applied to analytical model data during testing produced a spatially continuous parameter field that identified the locations of point-scale synthetic dipole sources of electrical current flow with varying degrees of accuracy depending on the prior information incorporated into the tomography. When applied to SP-monitoring field data, the algorithm imaged electrical sources within a known fault that intersects the bedrock riverbed and flood plain of East Fork Poplar Creek and depicted dynamic electrical conditions attributed to hyporheic exchange.

Tennessee↗

USGS2023

Discrete streamflow measurements and waterborne self-potential logging of a 43-kilometer-long reach of the Elm Fork Trinity River upstream from Dallas, Texas

Continuous and discrete streamflow data were combined with waterborne self-potential (WaSP), surface-water temperature and surface-water conductivity surveys obtained along an approximately 43-kilometer (26.7 mile) surveyed reach of the Elm Fork Trinity River (hereinafter referred to as “Elm Fork”) upstream from Dallas, Texas, to investigate areas of gaining and losing streamflow under various streamflow and seasonal climatic conditions. Discrete streamflow measurements were made at 17 locations on October 12, 2021, and January 25, 2022, at 19 locations on May 17, 2022, and at 18 locations on August 9, 2022. WaSP data were measured from a kayak in January 2022 during a period of base flow along three individually surveyed reaches between the Lake Lewisville Dam and Frasier Dam on the Elm Fork. Together, these data indicated different parts of the Elm Fork functioned as either a gaining or losing stream depending on streamflow and seasonal climatic conditions. Overall, there were estimated net gains in streamflow during the first two discrete-measurement events of about 107 cubic feet per second (ft 3 /s) and 2 ft 3 /s in October 2021 and January 2022, respectively, and estimated net losses in streamflow in May 2022 and August 2022 of about 24 ft 3 /s and 18 ft 3 /s, respectively.

Texas↗

USGS2023

Geoelectric monitoring of the electric potential field of the Lower Rio Grande before, during, and after Intermittent Streamflow, May–October, 2022

Understanding the intermittent hydraulic connectivity between ephemeral streams and alluvial aquifers is a key challenge for managing water resources in arid environments. The lower Rio Grande flows for short, discontinuous periods during the irrigation season through the Mesilla Basin in southeastern New Mexico and southwestern Texas. Hydraulic connections between the Rio Grande and the Rio Grande alluvial aquifer in the Mesilla Basin vary spatially and temporally and are not well understood. Self-potential (SP) monitoring and time-lapse electric resistivity tomography (ERT) were therefore performed along linear cross-sections spanning the riverbed and flood plain for more than 4 months to monitor the transient hydraulic connection between the river and the alluvial aquifer by measuring time-lapse changes in the electric potential field in the riverbed and flood plain. The monitoring period began on 21 May 2022, when the riverbed was completely dry, continued through the irrigation season while streamflow was provided by reservoir releases from upstream dams, and ended on 4 October 2022, when the riverbed was again dry. SP monitoring data show (1) a background condition in the dry riverbed consisting of (a) a positive electric potential anomaly with a maximum amplitude of about +100 mV attributed predominantly to a subsurface vertical salt concentration gradient and (b) diurnal electric potential fluctuations with amplitudes of 40,000–90,000 mV attributed to near-surface heat conduction driven by weather variability, in addition to (2) a streaming potential anomaly during the irrigation season with a maximum amplitude of about −3500 mV whose transient behavior clearly exhibited a change from the background anomaly to depict exclusively losing streamflow conditions that persisted through the irrigation season. Time-lapse ERT monitoring results depict rapid infiltration of streamflow into the subsurface and imply the river and Rio Grande alluvial aquifer established a full hydraulic connection within a few hours after streamflow arrival at the monitoring site. SP monitoring data show an apparent transition from hydraulic connection to disconnection at the end of the irrigation season and indicate that the transitional phase between connection and disconnection may last substantially longer than the transition from disconnection to connection. The combination of SP and ERT monitoring demonstrated herein shows the potential for broader applications of time-lapse monitoring of hydraulic intermittency and near-surface heat fluxes in different rivers.

New Mexico, Texas↗

USGS2023

A model of transmissivity and hydraulic conductivity from electrical resistivity distribution derived from airborne electromagnetic surveys of the Mississippi River Valley Alluvial Aquifer, Midwest USA

Groundwater-flow models require the spatial distribution of the hydraulic conductivity parameter. One approach to defining this spatial distribution in groundwater-flow model grids is to map the electrical resistivity distribution by airborne electromagnetic (AEM) survey and establish a petrophysical relation between mean resistivity calculated as a nonlinear function of the resistivity layering and thicknesses of the layers and aquifer transmissivity compiled from historical aquifer tests completed within the AEM survey area. The petrophysical relation is used to transform AEM resistivity to transmissivity and to hydraulic conductivity over areas where the saturated thickness of the aquifer is known. The US Geological Survey applied this approach to a gain better understanding of the aquifer properties of the Mississippi River Valley alluvial aquifer. Alluvial-aquifer transmissivity data, compiled from 160 historical aquifer tests in the Mississippi Alluvial Plain (MAP), were correlated to mean resistivity calculated from 16,816 line-kilometers (km) of inverted resistivity soundings produced from a frequency-domain AEM survey of 95,000 km 2 of the MAP. Correlated data were used to define petrophysical relations between transmissivity and mean resistivity by omitting from the correlations the aquifer-test and AEM sounding data that were separated by distances greater than 1 km and manually calibrating the relation coefficients to slug-test data. The petrophysical relation yielding the minimum residual error between simulated and slug-test data was applied to 2,364 line-km of AEM soundings in the 1,000-km 2 Shellmound (Mississippi) study area to calculate hydraulic property distributions of the alluvial aquifer for use in future groundwater-flow models.

Mississippi River Valley Alluvial Aquifer↗

USGS2022

Evaluation of electrical and electromagnetic geophysical techniques to inspect earthen dam and levee structures in Arkansas

Within the state of Arkansas there is an increasing number of aging dams and levees that have little to no documentation concerning their construction or composition. Surface geophysical surveys offer a non-intrusive method for investigating these structures: To describe their lithologic makeup, to evaluate the materials that they were constructed upon, and to identify potential flow paths through them. Techniques such as electrical resistivity tomography, seismic refraction, and electromagnetic induction have all been used to image dams and levees and require additional information from geologic outcrops, geotechnical borings, or drill cores in order to make informed geologic interpretations of the geophysical models. These geologic models then allow the owners of these structures to make more informed decisions about their operation and maintenance. Between 2011 and 2018, the U.S. Geological Survey conducted geophysical and geotechnical investigations of three earthen structures within the state of Arkansas. Electrical and electromagnetic geophysical data were used to develop lithologic models of these structures and the underlying geology. Self-potential surveys were utilized to detect the movement of water through these structures indicating possible seepage pathways. Geotechnical methods such as electric and hydraulic direct-push well logs and cores acted as both a control on the geophysical interpretations and a confirmation of anomalies. This integrated approach detected the lack of an impermeable core within a levee, imaged a change in lithology of the bedrock forming the seal beneath a gravity dam, and identified a potential seepage feature within the core of an earthen dam. These results further support that this method of extending known lithologic features via surface and borehole geophysics is a useful approach for characterizing earthen water control structures.

Arkansas↗

USGS2021

Gradient self-potential logging in the Rio Grande to identify gaining and losing reaches across the Mesilla Valley

The Rio Grande/Río Bravo del Norte (hereinafter referred to as the “Rio Grande”) is the primary source of recharge to the Mesilla Basin/Conejos-Médanos aquifer system in the Mesilla Valley of New Mexico and Texas. The Mesilla Basin aquifer system is the U.S. part of the Mesilla Basin/Conejos-Médanos aquifer system and is the primary source of water supply to several communities along the United States–Mexico border in and near the Mesilla Valley. Identifying the gaining and losing reaches of the Rio Grande in the Mesilla Valley is therefore critical for managing the quality and quantity of surface and groundwater resources available to stakeholders in the Mesilla Valley and downstream. A gradient self-potential (SP) logging survey was completed in the Rio Grande across the Mesilla Valley between 26 June and 2 July 2020, to identify reaches where surface-water gains and losses were occurring by interpreting an estimate of the streaming-potential component of the electrostatic field in the river, measured during bankfull flow. The survey, completed as part of the Transboundary Aquifer Assessment Program, began at Leasburg Dam in New Mexico near the northern terminus of the Mesilla Valley and ended ~72 kilometers (km) downstream at Canutillo, Texas. Electric potential data indicated a net losing condition for ~32 km between the Leasburg Dam and Mesilla Diversion Dam in New Mexico, with one ~200-m long reach showing an isolated saline-groundwater gaining condition. Downstream from the Mesilla Diversion Dam, electric-potential data indicated a neutral-to-mild gaining condition for 12 km that transitioned to a mild-to-moderate gaining condition between 12 and ~22 km downstream from the dam, before transitioning back to a losing condition along the remaining 18 km of the survey reach. The interpreted gaining and losing reaches are substantiated by potentiometric surface mapping completed in hydrostratigraphic units of the Mesilla Basin aquifer system between 2010 and 2011, and corroborated by surface-water temperature and conductivity logging and relative median streamflow gains and losses, quantified from streamflow measurements made annually at 16 seepage-measurement stations along the survey reach between 1988 and 1998 and between 2004 and 2013. The gaining and losing reaches of the Rio Grande in the Mesilla Valley, interpreted from electric potential data, compare well with relative median streamflow gains and losses along the 72-km long survey reach.

New Mexico, Texas↗

USGS2021

Geoelectric survey of the Granite Gravel aquifer, Llano Uplift, Central Texas, to determine locations for water wells

An electrical geophysical survey was completed within a small area of the Llano Uplift of central Texas to determine locations to install two water wells in the Granite Gravel aquifer (GGA). Electrical resistivity tomography (ERT) was performed along two 188-m long profiles that intersected at the approximate center of a 100-m by 100-m self-potential (SP) map. The ERT survey was completed to map two-dimensional (2D) electric resistivity distributions in the GGA and the underlying Precambrian Town Mountain Granite (TMG) bedrock, whereas SP mapping was performed to delineate apparent streaming potential anomalies at the land surface that appeared correlated to the subsurface resistivity distributions, which exhibited strong lateral heterogeneity in the upper 35 m of the weathered layer that comprises the GGA. The depth to TMG bedrock, as shown by the resistivity distributions, varied substantially over relatively small profile distances and surface areas; however, the general electrical structure showed resistivity increasing with depth, beginning with a thin electrically conductive layer at the surface characterized by resistivity in the range of about 30–100 Ω-m, followed by a resistivity increase to 300–500 Ω-m at a depth that coincided with the water-table depth observed in the installed water wells. Resistivity of the TMG bedrock was generally greater than 500 Ω-m and exceeded 1000 Ω-m in some locations of the tomograms. Electrical structure beneath the survey area, as shown by the 2D resistivity distributions beneath the ERT profiles, delineated a relatively thick weathered section of GGA that spatially aligned with a conspicuous negative anomaly observed in the SP map after electrode-drift and terrain corrections were made. The combination of ERT and SP mapping guided selection of locations for two productive water wells within the small survey area despite substantial heterogeneity in the weathering profile of the GGA beneath the survey area.

Texas↗

USGS2021

Investigation of scale-dependent groundwater/surface-water exchange in rivers by gradient self-potential logging: Numerical modeling and field experiments

Exchanges of groundwater and surface-water are fundamental to a wide range of water-supply and water-quality management issues but challenging to map beyond the reach scale. Waterborne gradient self-potential (SP) measurements are directly sensitive to water flow through riverbed sediments and can be used to infer exchange locations, direction (gain versus loss), scale, and relative changes, but to date applications to river corridor hydrology are limited. Numerical modeling and field experiments were therefore performed herein, each emphasizing waterborne gradient SP logging for identifying and locating focused vertical groundwater discharge (surface-water gain) and recharge (surface-water loss) in a river. Two and three-dimensional numerical models were constructed to simulate the polarities, appearances, and peak amplitudes of streaming-potential and electric-field anomalies on a riverbed and in the surface-water that were attributable to steady-state vertical fluxes of groundwater through high-permeability conduits in the riverbed. Effects of varied hydraulic length-scale of exchange and surface-water depth were tested through numerical modeling. Modeling results aided in data acquisition and interpretation for three repeated field experiments performed along a 1.5–2.0 km reach of the Quashnet River in Cape Cod, Massachusetts, where focused, meter-scale groundwater discharges occur at discrete locations within otherwise ubiquitous and more diffuse groundwater upwelling conditions. Strong gradient SP anomalies were repeatedly measured in the Quashnet River at previously confirmed locations of focused groundwater discharge, showing the efficacy of waterborne gradient SP logging in identifying and characterizing groundwater/surface water exchange dynamics at multiple river network scales.

Massachusetts↗

USGS2021

Waterborne gradient Self-Potential (WaSP) logging in the Rio Grande to map localized and regional surface and groundwater exchanges across the Mesilla Valley

The Rio Grande is the primary source of recharge to the Mesilla Basin/Conejos-Médanos aquifer system (“Mesilla Basin aquifer system”) in the Mesilla Valley of New Mexico and Texas. The Mesilla Basin aquifer system is the primary source of water supply to several large cities along the United States–Mexico border. Identifying gaining and losing reaches of the Rio Grande in the Mesilla Valley is therefore critical for managing the quality and quantity of surface and groundwater-resources available to stakeholders in the Mesilla Valley and downstream. A Waterborne gradient Self-Potential (WaSP) logging survey was completed in the Rio Grande across the Mesilla Valley between June 26 and July 2, 2020 to identify reaches where surface-water gains and losses were occurring by interpreting an estimate of the streaming-potential component of the electrostatic field in the river, measured during bank-full flow. The WaSP survey, completed as part of the Transboundary Aquifer Assessment Program, began at Leasburg Dam State Park, New Mexico near the northern terminus of the Mesilla Valley and ended ~72 kilometers (km) downstream in Canutillo, Texas. Electric potential data indicated a net losing condition for ~32 km between Leasburg Dam and Mesilla Diversion Dam in New Mexico, with one 200-m long reach showing a localized gaining condition. Downstream from Mesilla Diversion Dam, electric-potential data indicated a neutral-to-mild gaining condition for 12-km that transitioned to a mild-to-moderate gaining condition between 12 and ~22 km from the dam before transitioning back to a losing condition along the remaining 18 km of the survey reach. The interpreted gaining and losing reaches are substantiated by potentiometric surface mapping in hydrostratigraphic units of the Mesilla Basin aquifer system between 2010 and 2011 and streamflow gains and losses quantified from annual streamflow gaging at 16 stations along the survey reach between 1988 and 1998 and between 2004 and 2013. The gaining and losing reaches of the Rio Grande in the Mesilla Valley, interpreted from electric potential data, compare notably well with streamflow gains and losses quantified at 16 locations along the 72-km long survey reach.

New Mexico, Texas↗

USGS2018

Preferential groundwater seepage in karst terrane inferred from geoelectric measurements

The Ellenburger–San Saba aquifer discharges spring flows into the overlying Hamilton Creek bed in Burnet County, central Texas. The aquifer is susceptible to contamination from surface‐water reservoirs because of the presence of dissolution cavities that are hydraulically connected to the reservoirs in some locations. There is concern that preferential groundwater seepage from reservoirs into the aquifer in these locations might ultimately degrade the quality of the springwater that enters Hamilton Creek. To investigate preferential groundwater seepage patterns and hydraulic connectivity between surface‐water reservoirs and the Ellenburger–San Saba aquifer, geophysical reconnaissance surveys were completed between July 2017 and January 2018 to map dissolution cavities and locate preferential groundwater seepage within a specific region of the aquifer. Two‐dimensional electric resistivity tomography and self‐potential profiling were utilized, and a simplified, three‐dimensional finite‐element model of the field site was constructed to provide an interpretive aid. The self‐potential data indicated the occurrence of preferential groundwater seepage through a porous seepage conduit that was imaged by the electric resistivity tomography data but did not indicate the occurrence of groundwater seepage through two fluid‐filled dissolution cavities that were imaged by electric resistivity tomography data. Collectively, the surveying and modelling results demonstrate the efficacy of geoelectric methods for mapping the locations of dissolution cavities and preferential groundwater seepage in the electrically resistive karst terrane of the Ellenburger–San Saba aquifer.

Near Surface Geophysics↗

USGS2018

New insights on scale-dependent surface-groundwater exchange from a floating self-potential Dipole

In south-central Texas the lower Guadalupe River has incised into the outcrop of the Carrizo-Wilcox aquifer. The river and the aquifer are hydraulically connected across the outcrop, although the connectivity is obscured at the surface by alluvium and surface-water and groundwater exchange dynamics are currently poorly understood. To investigate surface-water and groundwater exchange dynamics between the lower Guadalupe River and the Carrizo-Wilcox aquifer, a geophysical study was completed along a 14.86 km reach of the river by using water-borne gradient self-potential (SP) profiling and two-dimensional direct-current electric resistivity tomography. This paper explores the applicability of these water-borne geoelectric methods in delineating gaining and losing channel reaches, and demonstrates that geoelectric signals in the form of total electric field strength can be logged with an electric dipole and decomposed into component SP signals depicting regional and local groundwater flow patterns attributable to regional and localized hydraulic gradients. Localized SP anomalies of several tens of millivolts, indicative of hyporheic exchange flows, are observed and superimposed upon a 124 mV regional SP anomaly indicative of ambient groundwater exchange flows between the river and the aquifer. The observed SP signals are interpreted through two-dimensional finite-element modeling of streaming potentials attributable to ambient groundwater exchange and hyporheic exchange flow patterns. Variables of the channel environment such as temperature and concentration gradients, depth, and velocity are considered and subsequently eliminated as alternative sources of the SP signals that are presented.

Texas↗

USGS2017

Hydrogeophysical investigations of earthen dams – Two California case studies

Excessive groundwater seepage can be a common engineering concern with earthen dams. The application of geophysical methods, whether for characterization or for long-term monitoring, to help inform mitigation strategies is becoming a more common addition to these investigations. The U.S. Geological Survey (USGS) has completed geophysical investigations at several earthen dams in cooperation with the U.S. Army Corps of Engineers (USACE) to help characterize subsurface hydrogeologic conditions and to identify potential sources of seepage. Summaries of the investigations of Martis Creek Dam and Hidden Dam, both located in California, are presented.

California↗

USGS2016

Changes between early development (1930–60) and recent (2005–15) groundwater-level altitudes and dissolved-solids and nitrate concentrations In and near Gaines, Terry, and Yoakum Counties, Texas

Llano Estacado Underground Water Conservation District, Sandy Land Underground Water Conservation District, and South Plains Underground Water Conservation District manage groundwater resources in a part of west Texas near the Texas-New Mexico State line. Declining groundwater levels have raised concerns about the amount of available groundwater in the study area and the potential for water-quality changes resulting from dewatering and increased vertical groundwater movement between adjacent water-bearing units. In 2014, the U.S. Geological Survey, in cooperation with Llano Estacado Underground Water Conservation District, Sandy Land Underground Water District, and South Plains Underground Water Conservation District, began a multiphase project to develop a regional conceptual model of the hydrogeologic framework and geochemistry of the Ogallala, Edwards-Trinity, and Dockum aquifers. The Ogallala aquifer is the shallowest aquifer in the study area and is the primary source of water for agriculture and municipal supply in the area. This report describes the results of the first phase of the study, during which groundwater-level-altitude and selected water-quality data from wells in and near Gaines, Terry, and Yoakum Counties were compiled and evaluated for the Ogallala, Edwards-Trinity, and Dockum aquifers. Readily available digital groundwater data for the study area (geologic, well-construction, groundwater-level-altitude, and selected water-quality data) were compiled to assess temporal and spatial changes in groundwater resources from early development (1930–60) to recent (2005–15) periods. Pertinent data were compiled from available sources for the study area and for a 5-mile buffer area around the study area to prevent gridding errors near the boundary. Geologic and well-construction data were used to determine or verify the aquifer in which each well was completed. Depending on the available data, the aquifer assignment (aquifer in which a given well was completed) was determined on the basis of the following criteria, in order of priority: (1) the screened or open interval(s) of the well, (2) the total depth of the well, or (3) the completed aquifer reported for a given well by the data source. Potentiometric-surface maps were created to depict changes in groundwater-level altitudes for the Ogallala and Edwards-Trinity aquifers. In addition to comparing groundwater-level altitudes and water quality from the early development and recent periods, hydrographs of groundwater-level altitudes were created, and changes in water quality for various periods between 1930 and 2015 were evaluated. Variance maps for each groundwater-level-altitude grid were used to evaluate the spatial data coverage and to identify areas with higher uncertainty because of spatially limited data availability for some of the aquifers. For this report, existing dissolved-solids and nitrate concentration data were compiled and assessed for evidence of spatial patterns and changes over time. These data were compiled for samples collected from wells completed in the Ogallala, Edwards-Trinity, or Dockum aquifer during the early development period (1930–60) or the recent period (2005–15); temporal and spatial variations were assessed from depictions of the measured concentration values. Dissolved-solids and nitrate concentrations measured in samples from three wells completed in the Ogallala aquifer (well identifiers 11524, 11824, and 11825) for which long-term monitoring was done for various periods between 1950 and 2015 were also compiled and analyzed. Groundwater-level altitudes of the Ogallala aquifer are generally higher in the northwestern part of the study area and lower in the southeastern part of the study area, varying by as much as 800 feet. Groundwater flow paths for the early development period generally trend from northwest to southeast across the study area. Compared to those for the early development period, local features in the potentiometric surface for the recent period are more pronounced, likely as a result of additional data coverage, increased groundwater withdrawals, and local flow paths that are more variable. For the Edwards-Trinity aquifer potentiometric-surface map of the recent period, a general northwest to southeast flow gradient was also evident, with some subtle differences compared to the early development period. The Edwards-Trinity aquifer water-level-altitude change map between the early development and recent periods indicated similar spatial trends as in the Ogallala aquifer and indicated that groundwater-level altitudes declined over a large amount of the area for which sufficient data were available for reliably mapping changes. During the recent period, median dissolved-solids concentrations of less than 1,000 milligrams per liter (mg/L) were predominantly measured in the western part of the study area, and median concentrations of more than 1,000 mg/L were predominantly measured in the eastern part of the study area. A general pattern of increasing nitrate concentrations from west to the northeast was evident in the study area. Nitrate concentrations measured in samples collected from 16 wells completed in the Ogallala aquifer for the recent period were equal to or greater than 10 mg/L, the primary drinking water standard for finished drinking water.

Texas↗

USGS2016

Improving our understanding of hydraulic-electrical relations: A case study of the surficial aquifer in Emirate Abu Dhabi

Transmissivity is a bulk hydraulic property that can be correlated with bulk electrical properties of an aquifer. In aquifers that are electrically-resistive relative to adjacent layers in a horizontally stratified sequence, transmissivity has been shown to correlate with bulk transverse resistance. Conversely, in aquifers that are electrically-conductive relative to adjacent layers, transmissivity has been shown to correlate with bulk longitudinal conductance. In both cases, previous investigations have relied on small datasets (on average less than eight observations) that have yielded coefficients of determination (R 2 ) that are typically in the range of 0.6 to 0.7 to substantiate these relations. Compared to previous investigations, this paper explores hydraulic-electrical relations using a much larger dataset. Geophysical data collected from 26 boreholes in Emirate Abu Dhabi, United Arab Emirates, are used to correlate transmissivity modeled from neutron porosity logs to the bulk electrical properties of the surficial aquifer that are computed from deep-induction logs. Transmissivity is found to be highly correlated with longitudinal conductance. An R 2 value of 0.853 is obtained when electrical effects caused by variations in pore-fluid salinity are taken into consideration.

Conference Paper↗

USGS2011

Hydrogeophysical investigations at Hidden Dam, Raymond, California

Self-potential and direct current resistivity surveys are carried out at the Hidden Dam site in Raymond, California to assess present-day seepage patterns and better understand the hydrogeologic mechanisms that likely influence seepage. Numerical modeling is utilized in conjunction with the geophysical measurements to predict variably-saturated flow through typical two-dimensional dam cross-sections as a function of reservoir elevation. Several different flow scenarios are investigated based on the known hydrogeology, as well as information about typical subsurface structures gained from the resistivity survey. The flow models are also used to simulate the bulk electrical resistivity in the subsurface under varying saturation conditions, as well as the self-potential response using petrophysical relationships and electrokinetic coupling equations. The self-potential survey consists of 512 measurements on the downstream area of the dam, and corroborates known seepage areas on the northwest side of the dam. Two direct-current resistivity profiles, each approximately 2,500 ft (762 m) long, indicate a broad sediment channel under the northwest side of the dam, which may be a significant seepage pathway through the foundation. A focusing of seepage in low-topography areas downstream of the dam is confirmed from the numerical flow simulations, which is also consistent with past observations. Little evidence of seepage is identified from the self-potential data on the southeast side of the dam, also consistent with historical records, though one possible area of focused seepage is identified near the outlet works. Integration of the geophysical surveys, numerical modeling, and observation well data provides a framework for better understanding seepage at the site through a combined hydrogeophysical approach.

California↗

USGS2010

Geophysical investigations at Hidden Dam, Raymond, California: Summary of fieldwork and data analysis

Geophysical field investigations have been carried out at the Hidden Dam in Raymond, California for the purpose of better understanding the hydrogeology and seepage-related conditions at the site. Known seepage areas on the northwest right abutment area of the downstream side of the dam are documented by Cedergren. Subsequent to the 1980 seepage study, a drainage blanket with a subdrain system was installed to mitigate downstream seepage. Flow net analysis provided by Cedergren suggests that the primary seepage mechanism involves flow through the dam foundation due to normal reservoir pool elevations, which results in upflow that intersects the ground surface in several areas on the downstream side of the dam. In addition to the reservoir pool elevations and downstream surface topography, flow is also controlled by the existing foundation geology as well as the presence or absence of a horizontal drain within the downstream portion of the dam. The purpose of the current geophysical work is to (1) identify present-day seepage areas that may not be evident due to the effectiveness of the drainage blanket in redirecting seepage water, and (2) provide information about subsurface geologic structures that may control subsurface flow and seepage. These tasks are accomplished through the use of two complementary electrical geophysical methods, self-potentials (SP) and direct-current (DC) electrical resistivity, which have been commonly utilized in dam-seepage studies. SP is a passive method that is primarily sensitive to active subsurface groundwater flow and seepage, whereas DC resistivity is an active-source method that is sensitive to changes in subsurface lithology and groundwater saturation. The focus of this field campaign was on the downstream area on the right abutment, or northwest side of the dam, as this is the main area of interest regarding seepage. Two exploratory self-potential lines were also collected on the downstream left abutment of the dam to identify potential seepage in that area. This report is primarily a summary of the field geophysical data acquisition, with some preliminary results and interpretation. Further work will involve a more rigorous analysis of the geophysical datasets and an examination of a large dataset of historical observations of water levels in a number of observation wells and piezometers compared with reservoir elevation. In addition, a partially saturated flow model will be developed to better understand seepage patterns given the available information about dam construction, geophysical results, and data from installed observation wells and piezometers.

California↗