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330 records · Page 14Linked to original sources
USGS2024

Are field observations of surface rupture useful? An example from the 2023 Mw 7.8 Pazarcık, Turkey (Türkiye), earthquake

Field investigations have long been an important component of the scientific response to surface‐faulting earthquakes. However, in light of advances in remote data and models, the question arises whether field‐based observations of surface rupture remain useful for understanding rupture processes and seismic hazards. We approach this question using a field‐based study of the central 2023 M w 7.8 Pazarcık, Turkey (Türkiye), earthquake rupture, at the intersection of the east Anatolian fault (EAF) and Narlı fault. Our field observations include the surface rupture expression and extent of the central EAF and northernmost Narlı fault in generally forested and steep terrain and 68 measurements of left‐lateral surface displacement. These data improve our understanding of the Pazarcık rupture complexity, resolve the surface geometry of the Narlı fault–EAF connection, and exhibit a clear (>2 m) change in surface displacement across this intersection zone that confirms remote‐based coseismic slip models. Our study shows that focusing field efforts in areas of obscured or low‐resolution remote data can yield essential data for refining rupture extent, documenting perishable on‐fault displacement, and improving postearthquake situational awareness. A comparison of similarly large‐magnitude continental surface‐rupturing earthquakes indicates that displacement uncertainties relate to a complex set of factors, including measurement methods, rupture complexity, and displacement magnitude. Our study validates the need for postearthquake field observations, which, when driven by clear motivating questions and knowledge of methodological strengths and limitations, provide high‐resolution rupture data that complement remote‐based models.

Pazarcık↗
USGS2024

2024 Crustal Deformation Modeling Workshop report

The 2024 Crustal Deformation Modeling Workshop was held June 10–14 at the Colorado School of Mines. The workshop included two days of tutorials on using PyLith for crustal deformation modeling, followed by three days of science talks and discussions. The workshop focused on four primary themes: ● Constraining long-term fault slip rates and their uncertainties using geodetic and geologic data; ● Earthquake cycle modeling with a focus on constraining models using seismic and geodetic data; ● Interaction of fluids and faulting; and ● Separating contributions of surface loading and tectonic loading in crustal deformation. The complete agenda is available on the CIG website.

Conference Paper↗
USGS2024

Improving crop-specific groundwater use estimation in the Mississippi Alluvial Plain: Implications for integrated remote sensing and machine learning approaches in data-scarce regions

Study region The Mississippi Alluvial Plain (MAP) in the United States (US). Study focus Understanding local-scale groundwater use, a critical component of the water budget, is necessary for implementing sustainable water management practices. The MAP is one of the most productive agricultural regions in the US and extracts more than 11 km 3 /year for irrigation activities. Consequently, groundwater-level declines in the MAP region pose a substantial challenge to water sustainability, and hence, we need reliable groundwater pumping monitoring solutions to manage this resource appropriately. New hydrological insights for the region We incorporate remote sensing datasets and machine learning to improve an existing lookup table-based model of groundwater use previously developed by the U.S. Geological Survey (USGS). Here, we employ Distributed Random Forests, an ensemble machine learning algorithm to predict annual and monthly groundwater use (2014–2020) throughout this region at 1-km resolution, using pumping data from existing flowmeters in the Mississippi Delta. Our model compares favorably with the existing USGS model, with higher R 2 (0.51 compared to 0.42 in the previous model), and lower root mean square error (RMSE) and mean absolute error (MAE)— 0.14 m and 0.09 m, respectively in our model, compared to 0.15 m and 0.1 m in the previous model. Therefore, this work advances our ability to predict groundwater use in regions with scarce or limited in-situ groundwater withdrawal data availability.

Journal of Hydrology Regional Studies↗
USGS2025

Dynamic feedbacks between river meandering and landsliding in northwestern Washington glacial terraces

Landsliding in river valleys poses unique risks for cascading hazards and can damage infrastructure and cause fatalities. In postglacial valleys, many landslides are posited to occur in relation to lateral river erosion, but the dynamics of fluvial-hillslope interactions are not well understood. Here, we investigate a section of the Nooksack River in western Washington State where the channel is flanked by landslide-prone glacial terraces similar to those that failed in the 2014 State Route 530 “Oso” landslide. We map 216 landslides through time across 17 aerial imagery data sets (1933–2022) and analyze them in relation to river meandering and curvature. We observe dynamic feedbacks between lateral river meandering and valley-adjacent landsliding. Terrace lateral retreat rates of up to 25 m/year owing to combined fluvial erosion and slope failure occur on pinned, outer meander bends immediately downstream from peaks in river curvature (>0.0075 1/m); these locations are predisposed to both shallow and deep-seated landslides. Deep-seated landslides extending 17%–32% of the active valley width into the floodplain can displace the river away from the floodplain margin and change the channel planform. River-displacing landslides relocate meanders up- or downstream, thereby conditioning the location of subsequent landslides. This conceptual model of coupled landslide-driven meander displacement and valley-adjacent landsliding is exemplified across western Washington river systems. The distance between up- and downstream valley-adjacent landsliding scales with valley width, meander wavelength, and terrace height. Our results can advance our understanding of the river-hillslope interface in landscape evolution and can be used to inform hazard management in river corridors.

Washington↗
USGS2024

The U.S. Geological Survey Ohio Water Microbiology Laboratory

The U.S. Geological Survey Ohio Water Microbiology Laboratory is a part of the Ohio-Kentucky-Indiana Water Science Center. The mission of the laboratory is to provide microbiological data of public health significance from surface waters, groundwaters, and sediments for a variety of study objectives. The laboratory conducts internal projects, works with external cooperators, and assists U.S. Geological Survey offices and National programs. The laboratory offers guidance, study design, and data interpretation expertise to collaborators, all following rigorous quality control and quality assurance procedures.

Fact Sheet↗
USGS2024

Triggering the 2022 eruption of Mauna Loa

Distinguishing periods of intermittent unrest from the run-up to eruption is a major challenge at volcanoes around the globe. Comparing multidisciplinary monitoring data with mineral chemistry that records the physical and spatio-temporal evolution of magmas fundamentally advances our ability to forecast eruptions. The recent eruption of Mauna Loa, Earth’s largest active volcano, provides a unique opportunity to differentiate unrest from run-up and improve forecasting of future eruptions. After decades of intermittent seismic and geodetic activity over 38 years of repose, Mauna Loa began erupting on 27 November 2022. Here we present a multidisciplinary synthesis that tracks the spatio-temporal evolution of precursory activity by integrating mineral and melt chemistry, fluid inclusion barometry, numerical modeling of mineral zoning, syn-eruptive gas plume measurements, the distribution and frequency of earthquake hypocenters, seismic velocity changes, and ground deformation. These diverse data indicate that the eruption occurred following a 2-month period of sustained magma intrusion from depths of 3–5 km up to 1–2 km beneath the summit caldera, providing a new model of the plumbing system at this very high threat volcano. Careful correlation of both the geochemistry and instrumental monitoring data improves our ability to distinguish unrest from the run-up to eruption by providing deeper understanding of the both the monitoring data and the magmatic system—an approach that could be applied at other volcanic systems worldwide.

Hawaii↗
USGS2026

Magnitude conversion relations create substantial differences in seismic hazard models

Earthquake catalogs are essential data inputs for seismic hazard modeling. Because earthquake magnitudes are reported in a variety of types (e.g., local magnitudes and moment magnitudes), magnitude conversion relationships must be used to convert the different magnitude types present in a catalog to a uniform magnitude type to avoid biases in the hazard computation. However, these conversion relationships are often uncertain and have been shown to sometimes perform poorly. Here, we investigate the sensitivity of the gridded seismicity component of the National Seismic Hazard Model (NSHM) to the catalog conversion equations in the Eastern United States. In the 2023 NSHM, magnitudes of various types were converted to moment magnitudes using equations developed by the Central and Eastern United States Seismic Source Characterization for Nuclear Facilities (CEUS‐SSCn), based on least‐squares (LS) regressions made using data from a catalog containing events up through 2008. We recompute these equations using events in the Advanced National Seismic System Comprehensive Earthquake Catalog with multiple magnitudes from 2000 to 2023. Although we prefer the use of orthogonal regressions for our datasets, LS regressions produce broadly similar results, with both approaches exhibiting large deviations from the CEUS‐SSCn conversions, especially at smaller magnitudes. We compare the spatial distribution of annual rates using three different models: (1) the 2023 NSHM conversions, (2) our updated conversions, and (3) no conversions. We find that the choice of conversions leads to substantial differences in the rate forecasts, which can greatly impact the seismic hazard model, particularly in regions with low‐seismicity rates such as the Eastern United States, where the hazard is dominated by gridded seismicity rather than a fault model.

Seismological Research Letters↗
USGS2026

A review and synthesis of post-wildfire shifts in hydrologic processes and streamflow generation mechanisms

Critical water supply watersheds in the western United States (WUS) are impacted by wildfires, with potential negative effects on water quality and quantity. Scientific understanding is currently insufficient to deliver estimates of wildfire consequences for water quantity that are regionally accurate. Regional variability in the directionality and magnitude of post-wildfire shifts in streamflow generation fuels uncertainty in estimates of wildfire effects on water supply. In this work we provide a narrative review of wildfire effects on hydrologic processes and the resulting changes in streamflow generation mechanisms with a focus on the WUS, incorporating other global regions when pertinent. A conceptual model summary of wildfire effects on streamflow generation emphasizes: (1) precipitation seasonality, (2) synchrony of precipitation and potential evapotranspiration, (3) net shifts in interception, evaporation, and transpiration relative to total annual precipitation, (4) vegetation changes, including compensatory uptake and type conversion, (5) degree of overlap in rainfall rates and infiltration, (6) fire extent and severity, (7) burn scar positioning (e.g. in headwaters or proximal to watershed outlet), (8) scale-dependent groundwater leakage, (9) near-surface water storage reduction, and (10) soil to groundwater connectivity. Ongoing gaps and challenges include separating the influences of precipitation variability, water withdrawals, and post-fire land management; compound and overlapping disturbances; and lack of pre-fire data. Notable future opportunities include: harnessing ever-improving gridded and remotely sensed precipitation and fire-effects data; linking geophysical, isotopic tracer, and geochemical signatures to diagnose hydrologic changes; leveraging physically based and data-driven model advancements; and analyzing streamflow generation recovery trajectories across diverse watersheds.

western United States↗
USGS2024

Beyond the wedge: Impact of tidal streams on salinization of groundwater in a coastal aquifer stressed by pumping and sea-level rise

Saltwater intrusion (SWI) is a well-studied phenomenon that threatens the freshwater supplies of coastal communities around the world. The development and advancement of numerical models has led to improved assessment of the risk of salinization. However, these studies often fail to include the impact of surface waters as potential sources of aquifer salinity and how they may impact SWI. Based on field-collected data, we developed a regional, variable-density groundwater model using SEAWAT for east Dover, Delaware. In this location, major users of groundwater from the surficial aquifer are the City of Dover and irrigation for agriculture. Our model includes salinized marshland and tidal streams, along with irrigation and municipal pumping wells. Model scenarios were run for 100 years and included changes in pumping rates and sea-level rise (SLR). We examined how these drivers of SWI affect the extent and location of salinization in the surficial aquifer by evaluating differences in chloride concentration near surface waters and the subsurface freshwater-saltwater interface. We found the presence of the marsh inverts the typical freshwater-saltwater wedge interface and that the edge of the interface did not migrate farther inland. Additionally, we found that tidal streams are the dominant pathways of SWI at our site with salinization from streams being exacerbated by SLR. Our results also show that spatial distribution of pumping affects both the magnitude and extent of salinization, with an increase in concentrated pumping leading to more intensive salinization than a more widely distributed increase of the same total pumping volume.

Delaware↗
USGS2026

Quantifying methane emissions from a rich fen with uncrewed aircraft systems in boreal Alaska

Thawing of permafrost in northern latitudes is accelerating, potentially releasing substantial amounts of methane (CH 4 ) as forested permafrost plateaus transition into wetlands. This ecosystem shift alters the carbon exchange between the soil and atmosphere, influencing the permafrost-carbon feedback. Monitoring these changes may require measurement platforms operating across varied spatial and temporal scales. Recent advancements in small uncrewed aircraft systems (sUAS) enable high resolution CH 4 flux quantification in remote, complex terrains; however, comparisons with established methods such as eddy covariance flux towers remain limited. We used a hexacopter sUAS to quantify CH 4 emissions from the Alaska Peatland Experiment, a wetland within the Bonanza Creek Experimental Forest. Using an ensemble of methods to define the background CH 4 concentration, along with near surface emissions from soil chambers, helped constrain our flux estimates. The sUAS method yielded an average flux of 0.0077 ± 0.0019 mol s −1 CH 4 , within a factor of two concurrent tower-derived total source flux estimates (0.0036 ± 0.00042 mol s −1 CH 4 ). To assess spatial drivers of observed fluxes, we conducted a 2D footprint analysis and overlaid the results with high-resolution hyperspectral land cover classification, quantifying vegetative contributions within each footprint. This revealed higher fen representation in sUAS measurements (73.8%) than in tower footprints (58.8%), and lower tussock meadow representation (15.6% and 30.3%, respectively). These differences were consistent with known variation in vegetation-specific CH 4 emissions. Our results highlight that combining footprint modeling with land cover characterization can enhance interpretations of CH 4 fluxes and guide cross-platform comparisons.

JGR Atmospheres↗
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↗
USGS2026

End-user needs for remote sensing wetlands of the Prairie Pothole Region of North America

The Prairie Pothole Region (PPR) of North America comprises globally important grassland and wetland ecosystems critical for numerous populations of migratory birds. Due to the importance of this region for migratory birds, and particularly waterfowl, and the threats of habitat loss due to intensifying agriculture, there is a mature and diverse system of conservation organizations, agencies, and partnerships that spends hundreds of millions of dollars annually on habitat conservation to support migratory bird populations. Remote sensing can be a powerful tool for observing and evaluating global change at large scales as well as expanding inferences from field studies to the broader landscape with statistical models. However, development and utilization of these tools has lagged behind their demand for several reasons, including concerns over spatial and temporal resolution and accuracy of products; perception of a misalignment with decision-maker needs; technological barriers such as skill sets of conservation professionals, computing resources, data access, and usability. In this report, we summarize the needs of conservation professionals and scientists who use or want to use remote sensing data products to inform science about wetland change and conservation of wetlands in the PPR. We assembled this information through several methods leading up to, during, and following a January 2026 PPR Wetland Remote Sensing Workshop. The workshop included United States and Canadian scientists, conservation professionals, and policy experts. Our goal was to bring together end-users and remote sensing product developers jointly to explore reducing the lag between product development and utilization of products to inform science and conservation. Specifically, we aimed to identify gaps in wetland remote sensing that limit effective monitoring, management, and conservation in the PPR, and to develop a framework that outlines pathways to address these gaps by fostering collaboration, improving communication networks, encouraging discussion, and building on existing and ongoing efforts. This report summarizes our participants’ descriptions of end-user needs and the outcomes of the workshop.

Prairie Pothole region↗
USGS2025

Landsliding follows signatures of wildfire history and vegetative regrowth in a steep coastal shrubland

Five years after the deadly and destructive 9 January 2018 Montecito debris flows (Santa Barbara County, California, USA), an atmospheric river storm on 9 January 2023 triggered widespread landsliding that affected many of the same drainages in the Santa Ynez Mountains. Using high-resolution aerial imagery, we identified >10,000 landslides over an ∼160 km 2 area. Most of the landslides were shallow (<1 m in depth) translational debris slides that initiated on steep (∼40°), south-facing hillslopes, with the highest incidence of landsliding in a sandstone-dominated bedrock unit. The landslides mobilized into debris flows and delivered substantial quantities of sediment downstream, which contributed to costly infrastructure impairments. We detected order-of-magnitude differences in landslide density across the study area that could not be attributed to variations in geomorphology (topographic aspect and slope), geology (bedrock type), or hydrology (seasonal antecedent rainfall, peak hourly storm rainfall intensity, total storm rainfall), which are usually considered relevant factors for shallow landsliding. Rather, we found that vegetation regrowth following wildfire was likely a relevant factor associated with the highly variable landslide densities. Hillslopes with less and different types of vegetation regrowth after fire appear to have been more susceptible to shallow landslides. We identify a possible vegetation control on postfire landsliding, which highlights an opportunity for hypothesis testing using more advanced techniques to track the evolution of vegetation cover and vegetation type in steep shrubland environments following wildfire.

California↗
USGS2026

High-resolution transboundary vegetation community maps of the Sonoran and Mojave Desert ecoregion to support critical landscape conservation planning and habitat management needs

We produced a 30-m resolution binational land cover map of Bird Conservation Region 33 (BCR 33) for the U.S. North American Bird Conservation Initiative. The region covers large portions of the Sonoran and Mojave Deserts. The map can support the U.S. Fish and Wildlife Service (FWS) Migratory Bird Program’s recovery planning efforts and constitutes the first known binational land cover dataset spanning sections of the United States–Mexico border and using a consistent classification system for both countries. The mapped region includes 152 distinct land cover classes, covering a total area of 38,421,453 ha (148,345 mi 2 ), of which 13,148,345 ha (52,706 mi 2 ) are located in Mexico and 24,770,640 ha (95,639 mi 2 ) in the United States. We primarily used Landsat 8 (OLI) imagery, supplemented by limited ground surveys from two field campaigns, drone-based aerial data, and existing vegetation classification frameworks from both countries. The classification applied a data-fusion approach integrating 30-m Landsat 8 imagery, decadal phenology metrics from vegetation indices, and a random forest model trained mainly with datasets from a comprehensive national mapping project from the U.S. Geological Survey (USGS) GAP Analysis Project (GAP) and federal wildland fire agencies’ Landscape Fire and Resource Management Planning Tools (LANDFIRE) (GAP/LANDFIRE) [United States side] and the National Institute of Statistics and Geography (INEGI) [Mexico side] as well as land cover maps and opportunistic open-access and field observations. Mapping of the full BCR 33 region was carried out in two phases: 1) Phase I, the prototype map, covered a smaller portion of the transboundary area and identified 31 land cover classes, and 2) Phase II, the full BCR 33 map (refer to Figure 1), which resulted in 152 land cover classes. Using a Random Forest classifier, we achieved an overall prediction accuracy of 92% for the Phase I map and 87% for the Phase II full region map. This slight decrease can be attributed to working on a larger, more complex area with a greater number of land cover classes. No formal validation was conducted, aside from using a subset of the collected field observations and training data to assess model performance during and after training. The training sites were further verified using Google Earth (Google, 2026) imagery. Two undergraduate students who worked for over a year visually inspected imagery and open access public images to confirm each training site during model training using in-house developed, online, visual tools. A portion of this field training data was reserved for model validation, and the corresponding results are to be presented in later sections. The project developed an end-to-end, medium- and fine-resolution remote sensing–based data fusion mapping approach. This effort produced a map (Nagler et al., 2025) and the online tools to support a dynamic, live, online map for visualizing the transboundary vegetation communities in BCR 33. The toolset is currently hosted by the University of Arizona (UofA) Vegetation Index and Phenology (VIP) Lab to support FWS partners (https://vip.arizona.edu/viplab_data_explorer?LCM_BCR33). The online map is designed to allow rapid updates using new training, validation, or correction data, making it dynamic and maintainable. The approach we took established a framework for rapid updating and correction of land cover maps, as the model can be quickly retrained with new field observations, updated training data, or other sources. This enables dynamic mapping and change detection of the region’s vegetation. This framework is an advance in data fusion and crowdsourced mapping of complex, vulnerable regions, providing support to regional stakeholders and the wider user community. This transboundary map can inform the protection, conservation, and restoration of vegetation, habitat, and ecosystems, particularly for threatened and endangered species across the two nations using consistent and harmonized binational mapping systems. Beyond supporting land management decisions and stakeholders in the transboundary desert ecoregions, this BCR 33 mapping effort establishes a foundation for future rapid, low-cost, cross-border land cover mapping that can benefit and advance ecosystem management.

Arizona, Baja California, California, Nevada, Sina↗
USGS2025

Nanometer-scale relationships between sedimentary organic matter molecular composition, fluorescence, cathodoluminescence, and reflectance: The importance of oxygen content at low thermal maturities

Molecular characterization of sedimentary organic matter (SOM), termed macerals, is a common goal when seeking to understand petroleum generation as well as other geologic processes in deep time. However, unambiguous measurement of discrete macerals is challenging due to the small size of organic particles in sedimentary rocks, the proximity of different organic matter types to one another, mineral-organic matter interactions, and maceral mixing that occurs during SOM isolation prior to ex situ analysis. The recent advent of infrared spectrometers capable of nanometer-scale resolution and the application of these technologies to geologic samples has enabled advances in rapid, in situ molecular characterization of SOM allowing for insights into paleoenvironmental processes, such as organic matter productivity and preservation, among others. Here we employ one such technology, optical photothermal infrared (OPTIR) spectroscopy, to map SOM functional group distributions at 500-nm resolution in a sample from the Lower Cretaceous Sunniland Limestone of the South Florida Basin. Examined fields of view include occurrences of amorphous organic matter (AOM), inertinite, micrinite, solid bitumen, telalginite, and vitrinite. OPTIR data from these macerals are compared against traditional organic petrographic data from the same organic grains including fluorescence intensity and white light reflectance as well as against cathodoluminescence response, an emerging organic petrographic approach. Maceral oxygen content (using carbonyl functional group abundance as a proxy) is observed to vary widely between maceral types but correlates strongly with fluorescence and cathodoluminescence intensity as well as against reflectance. These findings highlight the important role that oxygen content plays in determining the optical properties of SOM and further demonstrate the ability of OPTIR to discriminate subtle molecular differences between SOM types.

Organic Geochemistry↗
USGS2025

Reflections on a trio of North American earthquakes in 1925

In 1925, three moderately large damaging earthquakes occurred in North America over four months: the 28 February (local time; LT) M 6.2 Charlevoix, 27 June (LT) M 6.6 Montana, and 29 June M 6.5 Santa Barbara earthquakes. The centennial anniversaries of these events motivated this retrospective consideration focused on the ground motions generated by the three events, including a reconsideration of early intensity assignments for the Montana earthquake. At the time, these three earthquakes appeared to support the arguments of some geologists who downplayed the severity of seismic hazard in southern California relative to other parts of the country. Some of the arguments advanced at that time, for example that Los Angeles “has the least to fear from ‘Acts of God’ of any city under the American flag,” ( Hill, 1928 ) sound naïve if not laughable now, but a comparison of well‐constrained shaking distributions for the three earthquakes reveals the dramatic difference in wave propagation efficiency in western versus eastern North America (ENAM), which leads to moderate ENAM events being felt to much larger distances. At M 6.2, the 1925 Charlevoix earthquake was a notably large event in ENAM. This earthquake was the largest event in eastern Canada since 1870 and caused damage in the epicentral region in addition to towns as far away as 200 km, with felt shaking extending over 1000 km. In contrast, felt shaking from the Santa Barbara earthquake barely extended beyond ∼200 km. Compiling published intensity distributions for larger ENAM earthquakes, we show that perceptible earthquake shaking is not uncommon in ENAM over century time scales, but experience with weakly felt shaking may incline people to downplay potential earthquake risk.

California, Montana, Quebec↗
USGS2026

Lithium brine potential of North Dakota: Results from the 2025 sampling program

Lithium (Li), classified as a critical mineral and key in energy storage applications because of its high energy density, faces unprecedented demand. This has driven interest in unconventional sources of Li, especially brines from sedimentary basins. Accordingly, the spatial distribution of basinal brinehosted Li resources across North America is becoming better defined, including the Williston Basin underlying Saskatchewan, Canada. This has led to growing investment and exploration by industry throughout the 2020s; however, despite this interest, the Li potential of basinal brines of the Williston Basin in North Dakota remain underexplored. This work presents the results from the 2025 joint brine sampling campaign between the North Dakota Geological Survey, the United States Geological Survey (USGS), and The University of Texas at Austin. Twenty-seven fluid samples were collected from producing oil and water source wells from eight stratigraphic intervals across western North Dakota and analyzed for major cation and anion concentrations. Similar to southeastern Saskatchewan, the highest Li concentrations were identified in the Devonian Duperow Formation, with concentrations up to 179 mg/L being observed in a well commingled between the Duperow and Red River Formations. Some samples from the overlying Birdbear Formation exceeded 75 mg/L, whereas Li concentrations were lower in the Madison Group (33-44 mg/L) and the Three Forks (50 mg/L), Dawson Bay (43 mg/L), Winnipegosis (23 mg/L), and Red River (40.0 mg/L) Formations. This work indicates Li resource potential exists across the Williston Basin and advances our understanding of the Li distribution in basinal brines which could provide a new domestic source of this critical mineral.

North Dakota↗
USGS2025

The 3D National Topography Model Call for Action—Part 2: The Next Generation 3D Elevation Program

The three-dimensional (3D) National Topography Model initiative to integrate elevation and hydrography data includes the next generation of hydrography data from the 3D Hydrography Program and the next generation of elevation data from the 3D Elevation Program (3DEP). The first-ever collection of light detection and ranging (lidar) data for the nation (IfSAR for Alaska) provides a critical baseline reference, and the addition of multiple repeat elevation mapping projects as part of the next generation of 3DEP would substantially expand analysis capabilities. As the U.S. Geological Survey (USGS) is closing in on our goal of complete coverage with 3DEP data available or in progress for 98.3 percent of the Nation at the end of fiscal year 2024, the USGS is already transitioning to the next generation of 3DEP. Based on the 3D Nation Study results and input from a broad range of stakeholders, the USGS National Geospatial Program has finalized a new design for 3DEP that provides increased lidar quality levels and refresh rates. The new program is designed with more flexibility to meet changing user needs and take advantage of improvements in mapping technologies. The program will aim to expand the level of interagency coordination for topobathymetric lidar acquisition for inland rivers. The next generation of 3DEP will also aim to emphasize research, including advancing program design, products, and services and engaging and leveraging the evolving 3D industry. Research goals also include becoming more flexible in meeting user needs and taking advantage of evolving remote-sensing technologies. The program also plans to move from focusing on producing standard products to producing a concept of a 3D Nation Ecosystem with a variety of inputs, products, and services.

Circular↗