Geology topics

Martin A. Briggs

Publications and source records attributed to Martin A. Briggs.

11 recordsLinked to original sources

USGS2026

Tracking baseflow supply dynamics using SWOT data from small groundwater-dominated lakes

In situ surface-water monitoring strategies are biased towards larger perennial streams and lakes and are generally not designed to track mechanisms of baseflow supply contributed by the dynamic storage of aquifers. Additionally, small (< 1 km 2 ) groundwater-influenced lakes and wetlands globally have little in situ monitoring infrastructure. We explored the utility of remotely sensed Surface Water Ocean Topography Satellite (SWOT) data, collected from 2023 onward, to characterise the seasonal and multi-year water-level trends of groundwater flow-through kettle lakes distributed across the permeable sediments of eastern Massachusetts, USA. This analysis indicated that water levels for kettle lakes with areas down to approximately 0.05 km 2 are resolvable in the study area. Our examination of 17 kettle lakes found that SWOT water-surface elevation data closely tracked groundwater levels in adjacent monitoring wells where available, including the timing of seasonal patterns (highest levels generally in late spring), although there was some variation between years and there was a substantial lag in the timing of high water levels for a lake located downgradient from a 30-m-thick vadose zone. Furthermore, SWOT-observed water-level increases in kettle lakes tracked with baseflow increases in two adjacent groundwater-dominated streams, as would be expected from increased hydraulic gradients. Unlike spectral remote sensing, SWOT data are generally not affected by cloud cover, resulting in a potential for groundwater-dominated lakes to be sentinels of dynamic storage patterns, including identification of baseflow drought lags, which are currently ill-defined hydrological processes. SWOT monitoring of groundwater-influenced surface waters shows potential for augmenting existing monitoring wells and streamgages as continuous monitors of groundwater levels and baseflow supply in permeable terrain.

Massachusetts↗

USGS2025

Quantifying groundwater response and uncertainty in beaver-influenced mountainous floodplains using machine learning-based model calibration

Beavers ( Castor canadensis ) alter river corridor hydrology by creating ponds and inundating floodplains, and thereby improving surface water storage. However, the impact of inundation on groundwater, particularly in mountainous alluvial floodplains with permeable gravel/cobble layers overlain by a soil layer, remains uncertain. Numerical modeling across various floodplain structures considers topographic and sediment complexity and multidirectional flow, linking inundation to groundwater response. This study develops a model-data integration workflow to address uncertainty in groundwater response to beaver-induced inundations in a mountainous alluvial floodplain in the Upper Colorado River Basin. Uncertain factors include seasonal hydrologic dynamics, hydraulic conductivities, floodplain structures, and meteorological forcings. We employed an ensemble of groundwater models, based on geophysical and hydrologic data, with machine learning-based calibration using a neural density estimator. This allowed us to quantify the vertical flux from the soil layer to the permeable gravel bed, the down-valley underflow within the gravel bed, and their ratios. Results show a significant increase in the vertical flux relative to down-valley underflow, from 2% during dry pond periods to 20% during wet periods, serving as an analogy for conditions without and with beaver ponds. The study highlights the influence of floodplain structure on groundwater storage, water balance, and water quality impacted by beaver ponds. A thick gravel bed layer, with a large down-valley underflow, minimizes the effect of beaver-induced inundation on water quality. We emphasize the need for field-scale measurements of floodplain structure and improved characterization of evapotranspiration changes to reduce uncertainty in groundwater response.

Colorado↗

USGS2025

Multi-scale geophysical imaging of a hydrothermal system in Yellowstone National Park, USA

Little is known about the local plumbing systems that fuel Yellowstone’s famous hot springs, geysers and mud pots. A multi-method, multi-scale geophysical investigation was carried out in the Obsidian Pool Thermal Area (OPTA) to: (i) delineate the lateral extent of the hydrothermal area and associated surface features; (ii) estimate the dimensions of the upflow zone and identify its main controlling structures; (iii) assess fluids circulation pathways from depth to surface. Ground and airborne geophysical data were acquired to connect local and regional scales, from shallow to large depths. Maps of surface electrical resistivity show a strong correlation with hydrothermal features. At in-termediate depths, electrical resistivity permits delineating the upper limit of the upflow zone, while Poisson’s ratio highlights differences in subsurface fluid content. Combining these results with surface observations and topographic information, we speculate that differential mixing of hydrothermal and fresh water could explain the wide diversity of features observed at OPTA. Low electrical resistivity observed at large depths also suggest that a vast upflow zone, controlled by rhyolite flows and conjugate faults, underlies the OPTA. We speculate that hydrothermal fluids rise along fractures and reach the surface in topographic lows to form hydrothermal features. Our results show that synoptic, multi-scale geophysical measurements provide a roadmap for understanding where and how geologic heterogeneity, topography, fluid-gas separation, and the mixing of thermal and meteoric waters conspire to produce the wide variety of Yellowstone’s renowned hydrothermal features.

Wyoming↗

USGS2025

Fiber-optic distributed temperature sensing of hydrologic processes—Diverse deployments and new applications by the U.S. Geological Survey

Fiber-optic distributed temperature sensing instruments harness the temperature-dependent properties of glass to measure temperature continuously along optical fibers by using precise pulses of laser light. In the mid-2000s, this technology was refined for environmental monitoring purposes such as snowpack-air exchange, groundwater/surface-water exchange, and lake-water stratification. Fiber-optic distributed temperature sensing has revealed unprecedented details about preferential flow processes; however, the method is labor intensive and requires specific training, resulting in limited use by the broader water community. With the ongoing national implementation of the U.S. Geological Survey Next Generation Water Observing System, there has been renewed interest in harnessing the unique spatiotemporal monitoring capabilities of fiber-optic distributed temperature sensing. This fact sheet briefly describes this technology, highlights uses by the U.S. Geological Survey, and discusses current applications and future opportunities.

Fact Sheet↗

USGS2025

James Buttle review: The characteristics of baseflow resilience across diverse ecohydrological terrains

The dynamic storage of aquifers is the portion of groundwater that can potentially drain to any given point along a stream to create baseflow. Baseflow typically occurs year-round in perennial streams, though the characteristics and stability of dynamic storage are often most important to instream processes during extended dry periods (without precipitation and snowmelt) when runoff and quickflows are minimised. The term ‘baseflow resilience’ is defined for this review as the tendency of baseflow in streams to maintain a consistent volume and water quality year to year while under stress from climate variability and extremes, along with anthropogenic stressors such as water withdrawals, land use change, and water quality degradation. ‘Baseflow resilience’ has, in part, a user-defined meaning spanning water supply and water quality variables of primary interest. Watershed characteristics that directly impact resilience can often produce non-intuitive feedbacks that enhance some attributes of baseflow while simultaneously impairing others. For example, permeable stream corridor geology creates strong stream-groundwater hydrologic connectivity, yet fast groundwater drainage via preferential high-permeability flowpaths can lead to streamflow not being sustained during extended dry periods. Also, shallow groundwater sources are generally more immediately vulnerable to extreme events, warming, salinization, transpiration, and precipitation drought, compared to deeper groundwater. Yet baseflow drought in streams influenced by deeper groundwater can lag precipitation drought by years, and contaminant legacies may propagate through deep groundwater flowpaths to receiving waters for decades to centuries. Finally, irrigation withdrawals can intercept groundwater that would have drained to streams, and the application of irrigation may leach contaminants from the soil zone by unnaturally raising water tables, yet irrigation return flows can sustain baseflow and groundwater-dependent habitats in semiarid areas. This review covers the concept of hydrologic resilience in the context of stream baseflow processes and summarises the common hydrogeological controls on, and multiscale stressors of, dynamic groundwater storage. Further, we present several quantitative metrics to assess a range of water supply to water quality baseflow characteristics using both broadly available and boutique data types, a subset of which are demonstrated using data from the Delaware River Basin, USA.

Delaware River Basin↗

USGS2025

Preferential groundwater discharges along stream corridors are disregarded sources of greenhouse gases

Groundwater delivery of greenhouse gases (GHGs) to stream banks and riparian areas, before mixing with surface waters, has not been well quantified. We measured preferential groundwater delivery of GHGs to stream banks within three stream reaches, and found that stream banks with discharging groundwater emitted more CO 2 and were sources of N 2 O compared to stream banks without actively discharging groundwater, which emitted less CO 2 and were N 2 O sinks. At one of our stream reaches, groundwater CO 2 and N 2 O concentrations were 1.4–19.2 and 1.1–40.6 times higher than those in surface water, respectively, and groundwater delivery rates of CO 2 and N 2 O were 1.5 and 1.6 times higher than surface water emissions per unit area. On average, 21% (range 0%–100%) of CO 2 and N 2 O were emitted at the stream bank before mixing with surface waters. Preferential groundwater GHG emissions may contribute substantially to stream corridor emissions and may be underestimated when using a channel-centric approach to estimate riverine GHG budgets.

JGR Biogeosciences↗

USGS2025

Enhanced hydrologic monitoring and characterization of groundwater drainage features

Groundwater drains to the land surface, generating the baseflow of streams, lakes, and wetlands. The hydrologic resilience of baseflow during prolonged dry periods and after disturbance can be assessed with evolving remote sensing analysis paired with localized monitoring of groundwater drainage features and creative model calibration strategies.

Nature Water↗

USGS2025

Groundwater flowpath characteristics drive variability in per- and polyfluoroalkyl substances (PFAS) loading across a stream-wetland system

Groundwater-dependent ecosystems in areas with industrial land use are at risk of exposure to a PFAS chemicals. We investigated one such system with several known PFAS source areas, where high and low permeability sediments (glacial) coupled with groundwater-lake and groundwater/surface-water interactions created complex ‘source to seep’ dynamics. Using heat-tracing and chemical methods, numerous preferential groundwater discharge zones were identified and sampled across the upper Quashnet River stream-wetland system in Mashpee, MA, USA, downgradient of Joint Base Cape Cod (JBCC). Surface-water and groundwater samples were analyzed for 40 PFAS compounds between March and October 2022. Samples were collected from groundwater seeps identified as preferential discharge points (PDPs), wells upgradient of the stream-wetland system, contributing flow-through kettle lakes, and along Quashnet River surface-waters. PFAS from sampled waters contained perfluorinated carboxylates (PFPea, PFHxA, PFNA), perfluorinated sulfonates (PFBS, PFPeS, PFHxS, PFOS), fluorotelomer sulfonates (6:2, 8:2 FtS), and perfluoroalkyl sulfonamides (PFOSA). Samples from PDPs and wells had measured PFAS concentrations ranging from non-detect to 4677 ng/L ng/L (mean = 418 ng/L, std. = 709 ng/L), and a range of deuterium excess values (3.2 to 15.9 per mil) indicative of varying degrees of groundwater-lake interaction prior to groundwater flowpath emergence at PDPs. Correlations ( p < 0.01) between deuterium excess, %PFAS precursors, and terminal PFAS compounds highlighted potential precursor transformations associated with lake-groundwater exchange along flowpaths sourcing PDPs. However, some seepages had higher total PFAS concentrations (>1000 ng/L) than upgradient kettle lakes despite showing lake (evaporative) isotopic signatures, indicating the potential for groundwater flowpath convergence at wetland discharge zones and the influence of lakebed PFAS precursor reactions. Results from these synoptic surveys address gaps in the existing PFAS literature by demonstrating the importance of subsurface fate and transport on PFAS compound concentrations and mass loading in preferential groundwater discharge zones.

Massachusetts↗

USGS2025

A spatiotemporal deep learning approach for predicting daily air-water temperature signal coupling and identification of key watershed physical parameters in a montane watershed

Seasonal shifts from runoff to groundwater dominance influence daily headwater stream temperatures, especially where local groundwater input is strong. This input buffers temperature during hot periods, supporting cold-water habitats. Recent studies use air–water temperature signal metrics to identify zones of strong stream–groundwater connectivity. While Previous studies used air–water signal ratios as proxies for groundwater influence but were limited to specific sites and periods, without dynamic forecasting. This study is the first to forecast daily A r as a spatiotemporal signal using a Graph Convolutional Network–Long Short-Term Memory (GCN-LSTM) model. The model was trained using hydroclimate data (air temperature, precipitation, shortwave radiation, streamflow) and watershed physical features (e.g., sand content, slope). Results showed high predictive skill, achieving R 2 (NSE, RMSE) of 0.86 (0.73, 0.0004) for one-day-ahead to 0.52 (0.50, 0.0009) for seven-days ahead forecasts. Prior studies often have not explicitly incorporated spatial hydrogeologic drivers, but this model explicitly incorporates them to assess their impact on A r forecasting and stream-groundwater connectivity. Feature analysis identified mean sand, elevation, slope, clay, and TWI as key predictors of A r . Stronger groundwater signals appeared in hillslopes, elevations, and tributaries, highlighting watershed influence on streamflow. However, limitations include reliance on historical air–water temperature patterns for training and limited representation of extreme climate conditions. Despite these limitations, unlike previous studies relying on measured in-situ stream and air temperature, this study forecasts A r directly from climate and physiographic features after training, avoiding in-situ data requirements. Findings aiding predictions of stream ecosystem resilience.

New York↗

USGS2024

Utility of an instantaneous salt dilution method for measuring streamflow in headwater streams

Streamflow records are biased toward large streams and rivers, yet small headwater streams are often the focus of ecological research in response to climate change. Conventional flow measurement instruments such as acoustic Doppler velocimeters (ADVs) do not perform well during low-flow conditions in small streams, truncating the development of rating curves during critical baseflow conditions dominated by groundwater inflow. We revisited an instantaneous solute tracer injection method as an alternative to ADVs based on paired measurements to compare their precision, efficiency, and feasibility within headwater streams across a range of flow conditions. We show that the precision of discharge measurements using salt dilution by slug injection and ADV methods were comparable overall, but salt dilution was more precise during the lowest flows and required less time to implement. Often, headwater streams were at or below the depth threshold where ADV measurements could even be attempted and transects were complicated by coarse bed material and cobbles. We discuss the methodological benefits and limitations of salt dilution by slug injection and conclude that the method could facilitate a proliferation of streamflow observation across headwater stream networks that are highly undersampled compared to larger streams.

Virginia↗

USGS2024

Geophysical identification of potential groundwater – surface water interactions in the Bonita Peak Mining District, San Juan County, Colorado

This report includes the results and interpretation of geophysical investigations to aid in the location, identification, and conceptual site model (CSM) development of the near surface groundwater and surface water hydrology of the Upper Cement Creek and California Gulch of the Animas Rivers within the Bonita Peak Mining Districts (BPMD). Mine influenced water (MIW) from numerous mine adits within the BPMD has altered the geochemistry and ecology of these ground and surface waters. Many studies of varying scales have investigated the geology, hydrogeology, geochemistry, and aqueous chemistry of these adits and impacted areas. Field investigations using non-invasive geophysical methods were conducted in the summer of 2019 to aid in identifying potential groundwater inputs to these streams and further the CSM of the near surface within and along these streams. Two field deployments were completed in August and September of 2019. In August 2019, Phase 1 was completed using multifrequency electromagnetic induction (EMI) and thermal infrared imaging (TIR) to measure the bulk electrical conductivity, magnetic susceptibility, and the temperature response at known and suspected groundwater seeps into the Upper Cement Creek and California Gulch stretches of these alpine streams. Results and interpretation from Phase 1 were used to co-locate stretches of these streams for further detailed fiber optic distributed temperature system (FODTS) monitoring of the temperature dynamics for submeter identification of potential groundwater seeps during Phase 2. Phase 2 included additional EMI measurements, FODTS measurements, and repeated some Phase 1 measurements for improved data quality. All these data were used for the combined qualitative interpretation identifying seep locations. The data from both Phase 1 and Phase 2 are available in the USGS data release at: https://www.sciencebase.gov/catalog/item/5f18a30082cef313ed84879b. These data include detailed near-surface electrical conductivity and magnetic susceptibility mapping, discrete TIR imaging, and several kilometers of FODTS data. These data were georeferenced and used to identify potential groundwater seeps into these streams. The results indicate a complex near surface geophysical and hydrogeologic regime. Seeps are classified and spatially correlated to the EMI, TIR, and geochemical sampling results. This report is a thorough compilation of the geophysical field efforts in the summer of 2019, the data processing, and interpretations of these data. These data alone should not be used for final interpretations of the complex hydrogeology within these alpine systems. Rather, these data should be combined with other known data from various investigations to further refine the CSM and guide decisions for future investigations, watershed protective measures, and other site decisions. Geographical information system (GIS) layers of these results are available to project managers for such integration and combined interpretations.

Colorado↗