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USGS2026

A roadmap for identifying and interpreting physical processes and national water model prediction bias associated with baseflow index regimes across the contiguous United States

Understanding how groundwater–surface water interactions shape streamflow variability is critical for diagnosing low flow behavior and prediction bias in continental scale hydrologic models. We present a process informed framework that links observed baseflow (BF) dynamics, watershed attributes, and National Water Model (NWM) performance across the contiguous United States. Using daily observed streamflow from 797 reference quality streamgages, we developed monthly baseflow index (BFI) signatures using a streamgage specific, calibrated digital filter. Hierarchical clustering of these signatures identified seven distinct BFI regimes capturing regional and seasonal variability. We evaluated NWM v3.0 retrospective streamflow performance within each regime using multiple hydrograph and flow duration curve-based metrics. Model skill varied systematically across regimes: mixed flow systems were simulated most accurately, while predominantly BF dominated and quickflow dominated regimes exhibited substantially poorer performance. Across nearly all regimes, the NWM underestimated observed BFI magnitude and frequently failed to reproduce seasonal BF patterns, indicating systematic biases in simulated low flow contributions. To relate these regimes to potential process controls, we trained a Random Forest classifier using static watershed attributes and applied Shapley Additive Explanations to identify features most strongly associated with each regime. Results highlight regionally varying influences, including the dominant role of snow fraction and seasonal runoff timing in snow dominated basins and the importance of evapotranspiration and aridity in quickflow dominated systems. Collectively, these findings demonstrate how hydrologic signatures combined with interpretable machine learning can diagnose regime specific model biases and generate process-based hypotheses about limitations in large scale hydrologic prediction systems.

contiguous United States↗
USGS2025

Updating and recalibrating the integrated Santa Rosa Plain Hydrologic Model to assess stream depletion and to simulate future climate and management scenarios in Santa Rosa, Sonoma County, California

The Santa Rosa Plain Hydrologic Model (SRPHM) was developed and published in 2014 through a collaboration between the U.S. Geological Survey (USGS) and Sonoma Water to analyze the hydrologic system in the Santa Rosa Plain watershed, help meet the increasing demand for fresh water, and prepare for future uncertainties in water resources. The original model simulated hydrological conditions and water use from water years 1975 to 2010. Recently (2023), the USGS, in cooperation with Sonoma Water and the California State Water Resources Control Board, updated the SRPHM model to extend its simulation period to the end of the 2018 calendar year, incorporate new estimates of rural and agricultural water use, and use efficient input format for climate variables. The updated model was recalibrated, and evaluation of the new model calibration is included in this report. This report presents the results of comparing the hydraulic heads, streamflow, and groundwater budget simulated by the updated model with those generated by the original model and observed data. The main difference in the simulated budget between the original and updated SRPHM is the estimates of agricultural pumping, rural domestic pumping, and return flow generated from rural water use that was not simulated in the original model. The revised agricultural pumping is simulated using the agricultural package, which constrains pumping to available groundwater. The use of the agricultural package leads to a more realistic estimation of agricultural water use, with revised agricultural pumping being one-third less than that in the original model. The revised rural pumping is about half of the pumping in the original model because of using detailed parcel data to estimate population density in rural areas instead of coarse census tracts. Overall, average total inflows for water years 2006–10 simulated by the updated model were about 2 percent less than the original model, and the average total updated outflows were nearly 5 percent less than the original model. The updated model was then used to generate stream depletion maps, simulate climate change scenarios during 2019–99, and simulate water rights allocation using the Model for Decision Support in Integrated River Basin Management (MODSIM). The results from simulating eight future climate scenarios indicated either an increase in groundwater storage or no significant change in the next 80 years, along with an increase in recharge, an increase in actual evapotranspiration in six out of eight climate projections, and an increase in surface runoff. The increases in the simulated future groundwater storage, recharge, evapotranspiration, and runoff in most climate projections are mainly driven by the projected increase in precipitation in most of the future climate scenarios. The updated model also was used to test a pilot case study demonstrating water-resource allocation among different users with different water rights using the integrated MODSIM-Groundwater and Surface-Water Flow Model (GSFLOW) platform. The updated SRPHM serves as a valuable tool for analyzing historical and future hydrologic conditions in the Santa Rosa Plain watershed and preparing for future uncertainties.

California↗
USGS2025

Lunar grid systems, coordinate systems, and map projections for the Artemis missions and lunar surface navigation

Foreward This document contains design specifications of a navigational standard for the Moon, including a Lunar Transverse Mercator system, a Lunar Polar Stereographic system, a Lunar Grid Reference System, and a unique coordinate structure, Artemis Condensed Coordinates, for Artemis mission navigation and lunar surface science. The National Aeronautics and Space Administration (NASA) Artemis campaign seeks to place humans on the Moon for the first time since the Apollo missions. Early Artemis missions are heavily focused on the lunar south pole, which promises to return valuable data on the Moon’s geologic record, amongst other mission objectives. Coordinate systems in use today for the lunar south pole provides crew members on the surface neither an efficient nor intuitive means to communicate their position and orientation. A novel grid coordinate system, the Lunar Grid Reference System, is proposed to address these concerns for use in real-time extravehicular activity operations on the lunar surface. The many stakeholders involved in the Artemis missions will need a common system to communicate position and orientation while astronauts are operating on the lunar surface. To that end, Artemis crew members will need that system to be efficient and intuitive to promote efficient extravehicular activity timelines and reduce confusion. In the context of this document, these characteristics are addressed on the design of lunar coordinate systems: Efficient.—The number of characters required to communicate a location within a desired precision level in both local and global contexts, and how many steps are required for a recipient or sender to interpret a location. Intuitive.—How well the system aligns with human perceptual abilities, and whether the system yields distances that have the same relationship to actual lunar surface distance in all directions from the point where a person is located. Technological systems are currently being investigated to supplement the crew members’ ability to locate and orient themselves and other assets on the lunar surface; however, it is unlikely that those systems will be fully operational for the first few landed missions. Even with future positional aids, crew members will still need an efficient and intuitive means to communicate position and orientation. In addition, if technological systems fail, the crews will require land navigation skills and have maps available, thus providing further motivation for a crew-centric coordinate system. The contents of this U.S. Geological Survey (USGS) document detail a comprehensive framework for standardizing lunar crewed surface navigation within NASA and outlines the protocols, methods, and designs necessary for achieving consistency and interoperability across relevant space mission teams and lunar surface navigators. Key components of this document include designs of map projections, projected coordinate reference systems (Lunar Transverse Mercator and Lunar Polar Stereographic systems), and a grid system (Lunar Grid Reference System and Artemis Condensed Coordinates) for the Moon. The work proposed in this document seeks to accomplish something similar to the National Geospatial-Intelligence Agency (NGA) document SIG 0012 (NGA, 2014a), but for using grid systems for the Moon. This report incorporates initial feedback and input from NASA’s Artemis Geospatial Data Team, NASA’s Flight Operations Directorate, National Geodetic Survey, USGS Astrogeology Science Center, and NGA and is intended to serve as a resource for all involved with the Artemis missions, as well as for engineers designing and operating lunar infrastructure.

Techniques and Methods↗
USGS2024

Stream nitrate dynamics driven primarily by discharge and watershed physical and soil characteristics at intensively monitored sites: Insights from deep learning

We developed a suite of models using deep learning to make hindcast predictions of the 7‐day average backward‐looking nitrate concentration at 46 predominantly agricultural sites across the midwestern and eastern United States. The models used daily observations of discharge and meteorological variables and watershed attributes describing anthropogenic modification to hydrology, nitrogen application, climate, groundwater, land use, watershed physiographic attributes, and soils. Across all sites, discharge and watershed soil and physiographic attributes showed a strong influence on model performance. Analysis of drivers across sites revealed considerable regional differences related to controlling processes such as groundwater contributions. We tested several ways to pool data across sites to develop accurate models and make the most effective use of available data. Single‐site models, in which models are trained and tested at a single location, showed generally strong predictive performance (median Kling‐Gupta Efficiency = 0.66), and accuracy at poorly performing sites could be improved by grouping sites with similar characteristics. Developing a single model for all sites reduced performance at several locations with distinct characteristics, suggesting that there is a threshold of dissimilarity beyond which more data does not improve the model. While many deep learning studies have shown that national or even global models can outperform local models, it is not clear that this is true for water quality constituents. This study demonstrates how data can be combined effectively, using deep learning to develop accurate and interpretable models of instream nitrate at sites where varying processes are responsible for changes in nitrate concentration.

Water Resources Research↗
USGS2024

Afterslip and creep in the rate-dependent framework: Joint inversion of borehole strain and GNSS displacements for the Mw 7.1 Ridgecrest earthquake

The elusive transition toward afterslip following an earthquake is challenging to capture with typical data resolution limits. A dense geodetic network recorded the Mw 7.1 Ridgecrest earthquake, including 16 Global Navigation Satellite System (GNSS) stations and 3 borehole strainmeters (BSM). The sub-nanostrain precision and sub-second sampling rate of BSMs bridges a gap between conventional seismologic and geodetic methods, exemplified by atypical postseismic shear strain reversals observed at nearfield (<2 km) station B921 that remain unexplained. We jointly invert GNSS displacements and BSM strains for coseismic and postseismic slip spanning hours to months over 7 independent periods. Cosiesmically, our model resolves the largest slip magnitudes of up to 6.6 m on the mainshock rupture plane, with similar patterns to other inferred slip distributions. The foreshock fault appears to slip coincidently with mainshock, revealing potential asperities activated during the preceding Mw 6.4 event. Postseismically, the best-fitting models adhere to mechanical rate-and-state expectations of logarithmically decaying slip adjacent to the coseismic rupture terminus, and where deep rheologic conditions favor creep. Most spatial variation occurs in the early postseismic timeframe (<1–2 weeks), with evidence for regional rheologic control and static stress dependence. Triggered creep on the neighboring Garlock Fault unexpectedly persists for >178 days—further highlighting the importance of fault networks in postseismic stress redistribution, critical to assessing future hazard.

Journal of Geophysics Research↗
USGS2026

Predictions of anthropogenic background PFAS concentrations in soil and relation to bedrock lithology and groundwater quality

Detectable concentrations of per- and polyfluoroalkyl substances (PFAS) have been observed in soils in remote areas and presumably originate from atmospheric deposition. These anthropogenic background concentrations may enable some PFAS to leach to groundwater at levels that exceed regulatory criteria for drinking water. However, anthropogenic background soil concentrations and their connection to groundwater are not well characterized. We developed a boosted regression tree model to predict perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) concentrations in shallow soils across northern New England. Low soil pH was the most important predictor of elevated anthropogenic PFOS and PFOA concentrations in background soils, rather than potential PFAS sources, land use, or population density. Total organic carbon (TOC) was also an important predictor for PFOS soil concentrations. Model predictions indicate that 73% of the shallow soils within Maine, Vermont, and New Hampshire exceed New Hampshire’s Soil Remediation Standard for PFOS (0.5 ng/g) and 41% exceed the PFOA standard (0.4 ng/g). Analysis of soil model results and groundwater data suggests that areas with high soil pH are associated with higher groundwater detection frequencies, illustrating how areas with less retention in soil are, conversely, also areas with potentially greater groundwater vulnerability. Further analysis indicates that groundwater may be more vulnerable in calcareous lithologies.

Maine, New Hampshire, Vermont↗
USGS2025

Tracing metal sources and groundwater flow paths in the Upper Animas River watershed using rare earth elements and stable isotopes

Groundwater flow paths and processes that govern metal mobility and transport are difficult to characterize in mountainous bedrock watersheds. Despite the difficulty in holistic characterization, conceptual understanding of subsurface hydrologic and geochemical processes is key to developing remediation plans for locations affected by acid mine drainage, such as the Upper Animas River watershed in southwestern Colorado, USA. Stable isotopes of water and rare earth elements were utilized to evaluate groundwater flow and metal sources within this complex catchment. Stable isotope samples collected from draining mine adits and springs display systematic spatial variation wherein sample sites at higher elevations have greater seasonal variability than sites at lower elevations. The Upper Cement Creek watershed, where multiple draining mines are present, displays the lowest seasonal variation in stable isotopic signatures, potentially indicating the presence of a large, well-mixed volume of groundwater storage or interbasin groundwater flow. Rare earth elements display statistically significant variation between different alteration styles in the catchment. Overprinting of regional propylitic alteration is evident based on enrichment of middle rare earth elements in acidic springs and mines that are not spatially associated with surficial exposures of acid generating alteration styles. Europium anomaly and middle rare earth enrichment signatures from two flooded mine tunnels on opposite sides of a watershed divide indicate connections to the same subsurface flooded mine workings.

Colorado↗
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↗
USGS2026

Age and colony variation in Adélie penguin metapopulation vital rates: Insights from a 25-year mark–recapture study

Understanding how vital rates vary with age, life-history stage, and among populations is fundamental for predicting the demographic consequences of environmental change, especially in longer-lived species with complex life histories. These species often exhibit delayed maturity and iteroparity, making nuanced demographic insights critical for assessing their long-term viability. This study investigated age- and colony-related variation in Adélie penguin vital rates including survival, recruitment, and breeding propensity. We used mark–recapture data collected over 25 years (1996–2020) from three Adélie penguin breeding colonies that differed in population sizes and trends but comprised a metapopulation located at capes Royds, Bird, and Crozier on Ross Island, Antarctica. We used multi-state models to estimate survival and detection rates relative to reproductive state and breeding colony and estimated transition probabilities reflecting movements between reproductive states and colonies. Apparent survival varied by reproductive state, colony, and age and averaged 0.80 (SD = 0.02) at Bird, and 0.72 (SD = 0.03) and 0.73 (SD = 0.03) at Crozier and Royds, respectively, for pre-breeders age 2–7 years with strong declines in pre-breeder survival after age 8. We observed less age-related variation in survival of breeders and non-breeders, but we observed differences between colonies with lower survival for breeders (0.72 to 0.80) compared to non-breeders (0.75 to 0.82). The average probability of surviving the first 2 years after fledging ranged from 0.43 (SD = 0.14) at Royds and Crozier (0.43, SD = 0.10) to 0.55 (SD = 0.15) at Bird. Movement between colonies was highest for pre-breeders (0.00%–12.00% depending on age and colony) and lowest for breeders (<0.20%). We observed the lowest age-related recruitment rates at Royds, with recruitment at Crozier almost twice as high, and intermediate at Bird. Breeding propensity was highest at Crozier and lowest at Bird. Colony-specific variation in vital rates likely contributed differently to population trajectories, suggesting that care must be taken to extrapolate vital rate estimates across colonies even within a metapopulation. These findings also highlight the importance of considering age, life-history stage, and geographic variation when assessing population vital rates in species with complex life histories.

Frontiers in Ecology and Environment↗
USGS1995

Water-quality assessment of the Ozark Plateaus study unit, Arkansas, Kansas, Missouri, and Oklahoma: Analysis of information on nutrients, suspended sediment, and suspended solids, 1970-92

Water-quality data collected during water years 1970-90 (October 1 to September 30) for 83 surface-water sites and during 1970-92 for 395 ground-water sites in the 48,000 square mile Ozark Plateaus study unit of the National Water Quality Assessment Program were analyzed using selected descriptive and statistical methods. The water- quality data include nutrient (nitrogen and phosphorus), suspended sediment, and suspended- solids data, and ancillary information such as fertilizer use, animal waste, sewage treatment plant, and land use. Statistically significant differences exist in surface-water quality that can be attributed to physiography, land use, and other effects. The sites that were considered to be substantially affected by sewage treatment plants had the largest concentrations of nutrients. Nutrient concentrations generally were larger at sites associated with agricultural basins than at sites associated with forested basins. Statistically significant differences existed in the quality of ground water that can be attributed to hydrogeologic and land-use effects. Nutrient concentrations generally were largest where the water source is indicated to be shallow in origin and where parts of the hydrogeologic units are in agricultural land-use areas. Water quality has changed at several surface-water sites since 1970. Nutrient concentrations appear to have increased at some sites and decreased at other sites. Causes of these apparent trends are not known, but many of the sites with apparent trends are in agricultural areas. Surface-water loads of nutrients and suspended sediment were affected by several factors including streamflow, climate, drainage area, reservoir operation, and inputs from point and nonpoint sources. Annual loads were largest in large basins, with large inputs of nutrients or sediment during periods of high streamflows at locations where reservoir operation effects are not substantial.

Arkansas, Kansas, Missouri, Oklahoma↗
USGS2025

Comparisons of shoreline positions from satellite-derived and traditional field- and remote-sensing techniques

Satellite-derived shorelines (SDS) have the potential to help researchers answer critical coastal science questions and support work to predict coastal change by filling in the spatial and temporal gaps present in current field-based and remote-sensing data collection methods. The U.S. Geological Survey conducted comparison analyses of traditionally sourced shorelines and SDS in diverse coastal landscapes to determine how SDS could be used in ongoing and future work across varied coastal environments and provided some initial findings that could be used for implementation. Using CoastSeg, a browser-based program for SDS detection and mapping, SDS for the period 1984–2023 for multiple locations across the United States were compared to shoreline positions from traditionally sourced shoreline data. In this report, the authors present these comparisons alongside lessons learned and challenges encountered when building SDS workflows in different coastal locations. Results show that individual SDS have larger uncertainty and yet produced similar linear trends to sparser, traditionally sourced shoreline data; because SDS methods provide orders of magnitude more data than traditional shoreline-detection methods, they can be used to evaluate shoreline behaviors. Refining average scalar slopes used in tidal corrections did not result in substantial decreases in uncertainty. Using lessons from this work to outline needs for regional implementation, initial setup time would be considerable, being on the order of weeks. However, once complete, shoreline detections and analyses are fast (on the order of minutes to hours) and achievable using a desktop computer.

Alaska, Florida, Massachusetts, Washington↗
USGS2024

Seismicity zoning at Coso geothermal field and stress changes from fluid production and migration

The Coso geothermal field is a major geothermal power production site in the western United States. It has been observed that low-magnitude seismic events ( M < 3.71) are unevenly distributed in three distinct zones, namely, nearfield (<3 km), midfield (3–6 km), and farfield (> 6 km) from the Coso geothermal plant. These zones exhibit distinct changes in earthquake location before and during geothermal production episodes that began in 1986. After 1986, the midfield region of the main flank experiences a significantly lower seismicity rate than the surrounding areas before production episodes. During 2014–2019, the farfield earthquakes cluster in the eastern and western parts of the greater Coso area, which is discernably different from how those pre-production earthquake events were distributed along the conjugate NW-SE and SW-NW trending structures across the main flank. Here, we analyze the stage of stress with finite-element-based poroelastic simulations to illustrate how the spatiotemporal evolution of the seismicity is associated with the pattern of stress perturbations caused by fluid migration amid the operations of geothermal power plants. Generally, ∼70% of co-production seismicity is found in zones of increased Coulomb stress between 2014 and 2019 at >99% confidence. Meanwhile, the midfield zone of seismic paucity overlaps with the zone of decreasing pore-fluid pressure. Overall, the results provide a physical explanation of how decadal geothermal operations at Coso have perturbed stress-field changes and contributed to the evolving characteristic seismic pattern, shedding insights into assessing the seismic hazard in other geothermal settings.

California↗
USGS2025

Decomposing the Tea Bag Index and finding slower organic matter loss rates at higher elevations and deeper soil horizons in a minerogenic salt marsh

Environmental gradients can affect organic matter decay within and across wetlands and contribute to spatial heterogeneity in soil carbon stocks. We tested the sensitivity of decay rates to tidal flooding and soil depth in a minerogenic salt marsh using the Tea Bag Index (TBI). Tea bags were buried at 10 and 50 cm depths across an elevation gradient in a subtropical Spartina alterniflora marsh in Georgia (USA). Plant and animal communities and soil properties were characterized once, while replicate tea bags and porewaters were collected several times over 1 year. TBI decay rates were faster than prior litterbag studies in the same marsh, largely due to rapid green tea loss. Rooibos tea decay rates were more comparable to natural marsh litter, potentially suggesting that is more useful as a standardized organic matter proxy than green tea. Decay was slowest at higher marsh elevations and not consistently related to other biotic (e.g., plants, crab burrows) or abiotic factors (e.g., porewater chemistry), indicating that local hydrology strongly affected organic matter loss rates. TBI rates were 32 %–118 % faster in the 10 cm horizon than at 50 cm. Rates were fastest in the first 3 months and slowed 54 %–60 % at both depths between 3 and 6 months. Rates slowed further between 6 and 12 months, but this was more muted at 10 cm (17 %) compared to 50 cm (50 %). Slower rates at depth and with time were unlikely due to the TBI stabilization factor, which was similar across depths and decreased from 6 to 12 months. Slower decay at 50 cm demonstrates that rates were constrained by environmental conditions in the deeper horizon rather than the composition of this highly standardized litter. Overall, these patterns suggest that hydrological setting, which affects oxidant introduction and reactant removal and is often overlooked in marsh decomposition studies, may be a particularly important control on organic matter loss in the short term (3–12 months).

Georgia↗
USGS2024

Formation of vertical columnar seismic structures and seafloor depressions by groundwater discharge in the drowned Miami Terrace platform and overlying deep-water carbonates, southeastern Florida

The presence of vertical cross-formational fluid migration passageways within sedimentary basins can profoundly impact aquifer and reservoir fluid-flow and their identification is fundamental to informing management of subsurface fluid resources (groundwater, oil, gas). In an onshore and offshore southeastern part of Florida, 2D/3D seismic-reflection and bathymetry data document ∼153 vertical columnar structures composed of reflection disruptions up to 790 m in the height and averaging 360 m in diameter, and ∼219 subcircular to circular seafloor depressions up to 1334 m wide. Our study focuses on these features found within the offshore shallow-marine carbonate Miami Terrace platform, which drowned approximately at the end of the middle Miocene, and within overlying Plio-Quaternary deep-water carbonate slope and drift deposits. Most columnar structures are rooted in stratiform aquifers of the Miami Terrace platform and associated with faults or fault intersections produced by Eocene and circa late Miocene tectonics. The columns commonly terminate within the platform or as subcircular depressions along an amalgamated karstic and drowning unconformity at the platform top. The columns typically stretch upwards from a zone of deep karst cavity collapse through the Miami Terrace platform with upward decreasing sag on internal reflections. Following drowning and Plio-Quaternary partial burial of the Miami Terrace platform by deep-water deposits, the subcircular depressions and faults along the platform top were points of origin for a second phase of column growth upward into the deep-water deposits. The continuation of deep platform cavity collapse and column evolution produced pockmarks along paleo-seafloors within the deep-water deposits and at the present-day sea floor. The Plio-Quaternary pockmarks formed at water depths too deep to suggest an origin related to meteoric karst above or near sea level, but rather their formation is suggested to be related to cyclic sea level falls that drove increased groundwater head and density gradients, and seafloor discharge of offshore freshened groundwater sourced from the underlying platform. Plausibly, mixing of freshened groundwater and seawater at the seafloor discharge sites drove dissolution of the host deep-water deposits, which together with erosion by groundwater venting and current scouring formed the pockmarks. Seaward of the Plio-Quaternary seafloor pockmarks, at the late-middle Miocene upper slope of the Miami Terrace platform and along the regional karst/drowning unconformity is a slope-parallel band of ∼189 densely distributed subcircular seafloor depressions with diameters up to 1334 m at water depths up to ∼660 m. It is plausible that along the upper slope, faults and fractures produced by gravity-driven slope instability and possibly tectonics formed a dense network of fluid passageways that promoted upward artesian freshened groundwater flow to sites of discharge where mixing with seawater generated limestone dissolution and the depressions. But tectonic uplift may have forced emersion and initial meteoric sinkhole formation circa late Miocene with later enhancement by freshened groundwater discharge and bottom current erosion.

Florida↗
USGS2022

South Carolina and Landsat

South Carolina, the eighth State admitted to the union, transcends its size with its deep, rich history; striking beauty; vast natural resources; and extensive cultural diversity. Home to part of the Blue Ridge Mountains of the Central Appalachians, the Upstate is graced with more than 100 waterfalls, while the Lowcountry borders the Atlantic Ocean with 187 miles of coastline and 35 barrier islands. Forests cover two-thirds of the State, and forestry and agriculture together, as agribusiness, make up South Carolina’s leading industry. Two historic crops—cotton and tobacco—still rank in the top 10 commodities, though corn and soybeans now rank higher. Poultry, cattle, peanuts, and flowers also make the list. South Carolina’s population totals more than five million. Other residents include a variety of wildlife, bird, reptile, and fish species, including Ursus americanus (black bears), Alligator mississippiensis (American alligators), and Tursiops truncatus (bottlenose dolphins). More than 100 tree species also reside in South Carolina, which pays homage to one with its “The Palmetto State” nickname. South Carolina’s subtropical climate, long coastline, and lower elevations make it highly susceptible to tornado and hurricane activity and coastal flooding. Projected sea-level rise is a growing concern. A view from space can help monitor and manage natural resources on the land and in rivers, marshes, and the coast. Landsat reveals not just what an area looks like now, but also insights from decades ago.

South Carolina↗
USGS2026

2025 USGS National Seismic Hazard Model for Puerto Rico and the U.S. Virgin Islands: Overview of model and hazard results

The U.S. Geological Survey recently updated the National Seismic Hazard Model (NSHM) for Puerto Rico and the U.S. Virgin Islands (PRVI). The first version of the PRVI NSHM was released in 2003, and therefore this 2025 update includes over 20 years of new geologic, geophysical, and engineering data, methods, and models. Updates follow similar efforts performed in the recent 2023 50-state NSHM. However, this is the first NSHM in which we: (1) apply an inversion methodology to subduction interface fault sources in the earthquake rupture forecast (ERF) model; (2) develop scaled backbone median ground-motion models and independent aleatory variability models that are applied in the ground-motion characterization (GMC) model; and (3) calculate epistemic uncertainty related to alternative scenarios in the ERF and GMC models for all grid points in the study region. Long-term time-independent mean hazard calculations were performed for peak ground acceleration and 5%-damped pseudospectral acceleration at 21 spectral periods from 0.01- to 10.0-s, for eight National Earthquake Hazards Reduction Program site conditions ranging from V S30 = 150 to 1500 m/s, and for 2%, 5%, and 10% in 50-year probabilities of exceedance (return periods of 2475, 975, and 475 years, respectively). Epistemic uncertainty, in the form of selected percentiles, is also provided for a suite of test sites and all grid points in the study region for limited periods, site conditions, and probabilities of exceedance. Selected results, including comparisons with the 2003 PRVI NSHM, are shown and discussed for selected periods, site conditions, and probabilities of exceedance. When comparing the 2025 PRVI NSHM with the 2003 PRVI NSHM, hazard is generally higher at shorter periods and lower at longer periods, as a result of updates in both ERF and GMC models. The 2025 PRVI NSHM is applicable for return periods greater than ∼475 or less than ∼10,000 years.

Puerto Rico, U.S. Virgin Islands↗
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↗