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USGS2023

Don’t Let Negatives Hold You Back: Accounting for Underlying Physics and Natural Distributions of Hydrothermal Systems When Selecting Negative Training Sites Leads to Better Machine Learning Predictions

Selecting negative training sites is an important challenge to resolve when utilizing machine learning (ML) for predicting hydrothermal resource favorability because ideal models would discriminate between hydrothermal systems (positives) and all types of locations without hydrothermal systems (negatives). The Nevada Machine Learning project (NVML) fit an artificial neural network to identify areas favorable for hydrothermal systems by selecting 62 negative sites where the research team had confidence that no hydrothermal resource exists. Herein, we compare the implications of the expert selection of negatives (i.e., the NVML strategy) with a random sample strategy, where it is assumed that areas outside the favorable structural ellipses defined by NVML are negative. Because hydrothermal systems are sparse, it is highly probable that, in the absence of a favorable geological structure, hydrothermal favorability is low. We compare three training strategies: 1) the positive and negative labeled examples from NVML; 2) the positive examples from NVML with randomly selected negatives in equal frequency as NVML; and 3) the positive examples from NVML with randomly selected negatives reflecting the expected natural distribution of hydrothermal systems relative to the total area. We apply these training strategies to the NVML feature data (input data) using two ML algorithms (XGBoost and logistic regression) to create six favorability maps for hydrothermal resources. When accounting for the expected natural distribution of hydrothermal systems, we find that XGBoost performs better than the NVML neural network and its negatives. Model validation was less reliable using F1 scores, a common performance metric, than comparing probability estimates at known positives, likely because of the extreme natural class imbalance and the lack of negatively labeled sites. This work demonstrates that expert selection of negatives for training in NVML likely imparted modeling bias. Accounting for the sparsity of hydrothermal systems and all the types of locations without hydrothermal systems allows us to create better models for predicting hydrothermal resource favorability.

Geothermal Resources Council Transactions↗

USGS1999

Streamflow, base flow, and ground-water recharge in the Housatonic River basin, western Massachusetts and parts of eastern New York and northwestern Connecticut

Streamflows for selected flow durations from 1 to 99 percent and the August median streamflows were estimated for 11 long-term streamflow-gaging stations in and near the study area. Estimates of streamflow and associated standard errors were determined for selected flow durations from 50 to 99 percent and the August median streamflows for 21 low-flow partial-record stations and for selected flow durations from 1 to 99 percent and the August median streamflows for two partial-record stations and seven short-term discontinued streamflow-gaging stations. Median streamflows per square mile for the 10-, 50-, and 90-percent flow durations and the August median streamflows were 3.90, 1.01, 0.185, and 0.248 cubic feet per second per square mile. Streamflows per square mile at selected flow-duration discharges between 1 and 99 percent at the 41 stations were related to basin characteristics to explain differences in streamflow characteristics. Basin characteristics included basin elevations, extent of stratified-drift deposits, land use, aspect, and underlying bedrock geology types. Most streamflow differences were positively correlated to basin elevation differences, most likely because precipitation increases with elevation, and to stratified-drift deposits, which allow more precipitation to recharge the ground water and to discharge later than do till and bedrock deposits. Mean base flow was computed from continuous records of daily mean discharge at 11 long-term streamflow-gaging stations in and near the study area. Mean annual base flow ranged from 13.4 to 24.5 inches per year. Minimum annual base flow ranged from 45 to 72 percent of mean annual rates at the 11 long-term stations, and the ratio of base flow to streamflow (base-flow index) ranged from 0.55 to 0.80. Base-flow durations between 1 and 99 percent were calculated from streamflow records at the 11 long-term streamflow-gaging stations. Base flow accounted for 45.5 to 85.0 percent of total annual streamflow at the 1- and 99-percent flow durations. Ground-water-recharge rates were computed from continuous records of daily mean discharge at 11 long-term streamflow-gaging stations in and near the study area. Mean annual ground-water-recharge rates ranged from 17.5 to 22.4 inches per year at 10 of the 11 long-term stations. Mean annual ground-water-recharge rates ranged from 2 to 7 inches per year higher than base flow. Minimum annual ground-water-recharge rates ranged from 48 to 72 percent of mean annual ground-water-recharge rates. Mean annual potential ground-water recharge was estimated from monthly climatological data collected at six climatological stations in and near the study area. Mean potential ground-water recharge ranged from about 17.9 to 28.9 inches per year, with a median value of 22.6 inches per year. This median value compares well to that calculated by use of streamflow records at the 11 streamflow-gaging stations (20.0 inches per year). Streamflows per square mile for the 10-, 50-, and 90-percent flow durations at stations in and near the study area were similar to those computed for other unregulated long-term continuous streamflow-gaging stations in central and eastern Massachusetts. Base-flow and ground-water-recharge rates in the study area compared closely to results from other studies in southeastern Massachusetts and Rhode Island, which were based on the same computational methods.

Connecticut, Massachusetts, New York↗

USGS2025

Detecting hidden sedimentary geothermal systems in the Upper Colorado River Basin

Geothermal resources exist in sedimentary rock where circulation of water for efficient extraction or storage of heat is possible. Except in rare instances where hot water is expressed at the land surface, sedimentary geothermal resources are hidden, so the identification of these systems is optimally accomplished using predictive subsurface modeling. An integrated approach using detailed paleogeographic interpretations, subsurface geologic mapping, and numerical modeling has produced regional geologic and temperature models for the Upper Colorado River Basin, a large watershed in central North America that contains many sedimentary basins. These models identify areas of hidden sedimentary geothermal resource potential in low temperature (<90°C), moderate temperature (90–150°C), and high temperature (>150°C) fairways across the study area. These models incorporate maps of key horizons in outcrop and the subsurface to create a robust structural framework that can be used to target favorable geology for natural or engineered permeability. This framework is populated with lithologies derived from detailed palaeogeographical maps and over 40,000 bottom hole temperature (BHT) values were used to create a calibrated three-dimensional (3D) temperature model across the region. The resulting maps serve as a regional sedimentary geothermal play fairway screening tool for evaluating different grades of sedimentary geothermal resources and for identifying areas of interest where more detailed, prospect-scale studies can be undertaken.

Arizona, Colorado, New Mexico, Utah, Wyoming↗

USGS2008

Late Jurassic igneous rocks in south-central Arizona and north-central Sonora: Magmatic accompaniment of crustal extension

In Middle Jurassic time, the region of south-central Arizona and north-central Sonora was part of a continental magmatic arc. In early Late Jurassic time, this magmatic arc gradually gave way to a extensional regime. Late Jurassic rifting was accompanied by magmatism, typically small in volume relative to the preceding arc phase, and with mildly alkaline compositions. These igneous rocks, the 158- to 146-Ma Ko Vaya Suite, make up much or most of the Comobabi, Artesa, Quijotoa, and Brownell Mountains and Sierra del Cobre. The bimodal Ko Vaya Suite constitutes volcanic to shallow plutonic complexes comprising chiefly trachyandesite and volcanic wacke; monzodiorite; rhyolite porphyry; distinctive, compositionally and texturally heterogeneous, quartzpoor granite (the Ko Vaya Granite); A-type perthite granite and quartz syenite; aphyric intrusive rhyolite; and locally abundant hematite veins. Alteration, particularly potassic alteration, is widespread. Minimally altered samples of granite and quartz syenite have the composition of trachyte or trachydacite and alkali rhyolite. The Ko Vaya Suite is nonconformably overlain by the latest Jurassic Sand Wells Formation, approximately correlative with the Glance Conglomerate, the basal unit of the Bisbee Group. The Ko Vaya Suite is in some ways analogous to the coeval Independence dike swarm of eastern California, but less diffuse. We infer that the Ko Vaya Suite represents especially intense or focused Late Jurassic extensional magmatism.

Arizona, Sonora↗

USGS2026

Investigating the influence of climate and volcanic surface aging on fluvial erosion: A case study of Réunion Island, Indian Ocean

Precipitation is one of the dominant drivers of landscape erosion and evolution; however, the effects of typical rainfall compared with less frequent, high-magnitude precipitation events on erosion remain unclear. Volcanic islands are ideal locations to study such phenomena due to their simple geometries, nontectonic construction, and strong spatiotemporal rainfall gradients. However, spatial variation in surface age, created during their construction, often complicates their degradation histories by introducing temporal changes in erosion rates as drainage networks develop. Réunion Island (western Indian Ocean) presents a clear example of this, with an east–west gradient in both surface age and mean annual precipitation, as well as infrequent cyclones that alter the background rainfall pattern. In this study, we analyze the effects of surface age, average rainfall, and rainfall variability on basin development and fluvial erosion across the island. We calculate basin-averaged values of basin morphology, age, precipitation, river discharge, eroded volumes, and erosion rates, and use these to analyze the dominant drivers of landscape evolution through a series of correlation analyses. Our results indicate a temporal dependence on the influence of precipitation, with young surfaces being dominantly eroded by high-rainfall events and older surfaces eroded by mean annual rainfall patterns. Furthermore, we show that drainage development of shield volcanoes follows similar trends to other volcano types, and suggest that surface permeability and groundwater structure are important controls on runoff-driven erosion on shield volcanoes. These results add new components to the question of how precipitation impacts erosion.

Réunion Island↗

USGS2025

Extracting data from maps: Lessons learned from the artificial intelligence for critical mineral assessment competition

The U.S. Geological Survey (USGS), Defense Advanced Projects Research Agency (DARPA), NASA Jet Propulsion Laboratory (JPL), and MITRE ran a 12-week machine learning competition aimed at accelerating development of AI tools for critical mineral assessments. The Artificial Intelligence for Critical Mineral Assessment Competition solicited innovative solutions for two challenges: 1) automated georeferencing of historical maps, and 2) automated feature extraction from historical maps. Competitors used a new dataset of historical map images to train, validate, and evaluate their models. Automated georeferencing pipelines attained a median root-mean square error of 1.1 km. Prompt-based extraction (i.e., with user input) of polygons, polylines, and points from geologic maps yielded median F1-scores of 0.77, 0.56, 0.35, respectively. Geologic maps pose numerous challenges for AI workflows because they vary significantly. However, despite its short duration, the competition yielded promising results that have since spurred further innovation in this area and led to the development of new AI tools to semi-automate key, time-consuming parts of the assessment workflow.

Applied Computing and Geosciences↗

USGS2025

Waning greenhouse gas emissions from U.S. Federal lease coal production by the mid-21st century

This study presents estimates of future years (2024–2051) United States Federal lease coal production and the resulting greenhouse gas (GHG) emissions from the combustion, transport, and mining of that fuel. Results from the coal production estimate indicate a decline in production from Federal leases; with known production of 240 million short tons (mtn) in 2023 and a projected decline to 34.0 mtn by 2051, which represents a reduction to 14.2% of the 2023 value. In parallel with this projection, total GHG emissions are estimated to decrease from 402.2 million metric tons of carbon dioxide equivalent (MMT CO 2 eq.) in 2024 to 55.0 MMT CO 2 eq. in 2051, a decline to 13.7% of 2024 emissions estimates. The reductions in coal production and emissions are mainly the result of planned coal combustion power plant closures, with major projected closures in 2037 and 2048. However, GHG emissions estimates for future years can be uncertain as they rely heavily on coal production estimates from operators' public business plans and other publicly available resources. Forward looking plans of this type are subject to significant changes if economic and political factors deviate from current information. Results suggest that average GHG emissions over the time series breakout to 95% end point combustion, 3.7% transportation combustion emissions, and 1.3% fugitive emissions, although there is uncertainty associated with these figures. Uncertainty stemming from production projections, sector distributions, and emissions factors on the future emissions estimates increases with time, ranging from −28% to +48% within the 2024–2051 timeframe.

Alabama, Colorado, Montana, North Dakota, Utah, Wy↗

USGS2026

Wavelet Inversion for SliP (WISP): Open-source earthquake slip modeling software

Models of the spatiotemporal evolution of earthquake slip, termed finite-fault models, are a critical component of rapid earthquake and tsunami response, earthquake forecasting, seismic ground-motion estimates, and studies of earthquake kinematics. Here, we detail a newly released finite-fault modeling software, Wavelet Inversion for SliP (WISP), in use at the U.S. Geological Survey’s National Earthquake Information Center (NEIC) and available to the public. WISP version 1.1.0 allows inversion of teleseismic body and surface waves, as well as local strong-motion, static and dynamic Global Navigation Satellite System, and satellite imagery (e.g., Interferometric Synthetic Aperture Radar) observations on single or multiple planar fault segments. The software is used in NEIC rapid response of earthquakes M w ≥ 7, generally resulting in a published model within the first few hours after the event origin time. The rupture location and dimensions are then used as inputs to downstream products to estimate earthquake shaking, predict loss, and model the likelihood of secondary hazards, namely landslides and liquefaction. WISP is also used in research studies to evaluate the characteristics of complex ruptures including multifault ruptures and earthquake doublets, among others. The WISP version 1.1.0 software release is composed of Python-wrapped FORTRAN code to accomplish the inversion procedure. A simple command line interface facilitates ease of use even for those with only a cursory knowledge of Python scripting. WISP version 1.1.0 includes a Jupyter Notebook tutorial demonstrating use of the software for modeling the 2015 M w 8.3 Illapel, Chile, earthquake. In parallel with the tutorial, we demonstrate the typical usage of the WISP software using the M w 8.3 Illapel earthquake example here.

Seismological Research Letters↗

USGS2026

Hydrothermal manganese-oxide mineralization of a carbonate ooze, Samoan hotspot region, South Pacific Ocean

Low-temperature hydrothermal manganese oxides occur throughout the global oceans. However, the hydrothermal replacement of a carbonate ooze by manganese oxides is described here for the first time. The 24 samples dredged from three locations around the Territory of American Samoa in the South Pacific Ocean include six samples with remnant carbonate and volcaniclastic sediments, which we refer to as “low Mn,” and 18 samples in which the mineralization is pervasive and has replaced most original sediment, termed “high Mn.” The 18 high-Mn samples exhibit a mean Mn content of 51 wt.%. Higher Li and Mn contents and lower Fe contents in the high-Mn samples indicate a hydrothermal origin and distinguish these samples from hydrogenetic ferromanganese crusts. Mn-oxide layers are up to 90 mm thick, some with columns to 44 mm long and 10 mm wide, the magnitude of which has not been described previously. Samples are composed of birnessite and 10 Å phyllomanganate minerals. Textures of the thickest Mn layers indicate mineralization below the seabed from ascending fluids during multiple hydrothermal pulses. Mineralization took place by complete to partial replacement and cementation of foraminiferal sediments intermixed with volcaniclastic sediments in varying amounts. Our results highlight the production of carbonate sediment-hosted hydrothermal Mn oxides from multiple hydrothermal sources within the Samoan volcanic chain. The potential extensive distribution on the regional scale of this newly described mineralization process and unique element enrichments raise questions about its broader distribution globally and potential importance to hydrothermal processes, element mass balance, and seabed mineral resources.

Geochemistry, Geophysics, Geosystems↗

USGS1997

Water-quality assessment of south-central Texas: Occurrence and distribution of volatile organic compounds in surface water and ground water, 1983-94, and implications for future monitoring

The study area of the South-Central Texas study unit of the National Water-Quality Assessment Program comprises the Edwards aquifer in the San Antonio region and its catchment area. The first phase of the assessment includes evaluation of existing water-quality data for surface water and ground water, including volatile organic compounds, to determine the scope of planned monitoring. Most analyses of volatile organic compounds in surface water are from the National Pollutant Discharge Elimination System sites in San Antonio, Texas. Nine volatile organic compounds were detected at the six sites. The three compounds with the most detections at National Pollutant Discharge Elimination System sites are 1,2,4-trimethylbenzene, toluene, and xylene. Analysis of volatile organic compounds in ground water was limited to Edwards aquifer wells. Twenty-eight volatile organic compounds were detected in samples from 89 wells. The five most commonly detected compounds in samples from wells, in descending order, are tetrachloroethene, trichloroethene, bromoform, chloroform, and dibromochloromethane. Detections of volatile organic compounds in surface water and ground water within the South-Central Texas study area are limited to site-specific sources associated with development; therefore, planned monitoring for possible detections of volatile organic compounds as part of the National Water-Quality Assessment Program will emphasize areas of expanding population and development. Monitoring of volatile organic compounds is planned at National Pollutant Discharge Elimination System sites, at basic fixed surface-water sites, and in the ground-water study-unit surveys.

Texas↗

USGS2026

Early Miocene volcanic rocks and associated tectonics, Lava Hills and southern Bristol Mountains, California

Volcanic rocks of latest Oligocene to early Miocene age form an east-west belt across part of the central eastern Mojave Desert from the Whipple Mountains on the east to the Rosamond Hills on the west. We term this the central belt because it is separated from northern and southern belts by swaths with no volcanic rocks. Limited geochronologic data indicate that much of the belt is latest Oligocene and early Miocene in age, about 24 to 19 Ma, a finding that is consistent with these rocks being overlain by the 18.8 Ma Peach Spring Tuff in many places. We describe Miocene geology in a central area of the belt, in the Lava Hills, southern Bristol Mountains, and southern Old Dad Mountains. Sedimentary basins formed coeval with early andesite to rhyolite volcanism, progressing from fluvial and lacustrine tuffaceous sandstone to volcanic lavas, tuffs, and breccias, indicating that early basins formed proximal to volcanic edifices. Higher strata are fluvial and lacustrine with lavas punctuating the sequence. Although basins may partly have been formed within topographic lows bounded by volcanic domes, plateaus, and stratovolcanoes, consistent stratigraphic sections over wide areas indicate that tectonic basin evolution affected broad areas. The volcanic section is capped by local basalt flows and the regional Peach Spring Tuff. Limited data on normal faults support interpretations of early extensional basin development caused by northeast-southwest oriented stretching. Later extension caused stratal rotations, tilting early deposits down to the southwest. This tilted and subsequently beveled basin architecture was overlain by the youngest volcanic deposits, primarily rhyolite and basalt. The Peach Spring Tuff, 18.8 Ma, lies within this upper unit. Similar stratigraphic and structural relations are exposed in the nearby Marble Mountains and Van Winkle Mountain sections, reinforcing that a broad area underwent similar volcanism and tectonism. In our study area the upper unit is only very gently tilted except near dextral strike-slip faults of the eastern California shear zone. These late Miocene to Recent faults are represented as four main fault zones spaced about 5 km apart, representing distributed shear north of the Bristol Lake basin.

California↗

USGS2025

Risk implications of Poisson assumptions and declustering inferred from a fully time-dependent earthquake forecast

We use the Third Uniform California Earthquake Rupture Forecast Epidemic Type Aftershock Sequence model, which is fully time-dependent in terms of including spatiotemporal clustering, to evaluate the effects of the Poisson assumption and declustering algorithms on statewide loss exceedance curves. The model is simulation based, meaning it produces synthetic catalogs that exhibit realistic behavior with respect to aftershocks and multi-fault earthquakes. A Poisson version of the model was constructed by randomizing event times, and the influence of two declustering algorithms was examined as well. We demonstrate that the probability of one-or-more loss exceedances (occurrence exceedance probability) is greater for the Poisson model because it has fewer seismically quiet time windows. The discrepancy between dollar loss estimates with a given exceedance probability is up to a factor of 32% but varies depending on the loss threshold (the x-axis value) and the forecast duration (we examined a range between 24 h and 50 years, with the discrepancy for the latter being negligible). We discuss how the one-or-more loss exceedance metric is questionable because it ignores all but the maximum loss experienced in each timeframe. An alternative metric based on total aggregate loss in each time window (aggregate exceedance probability) was therefore also examined, for which the Poisson model again implies higher risk at intermediate losses but lower risk at higher losses (because large, triggered events now contribute to total aggregate losses for the fully time-dependent model). We also argue that declustering is not a scientifically justifiable way to deal with full time dependence, in agreement with a chorus from other recent studies. It is difficult to draw generally applicable conclusions from our study, in part because application specific details will likely be important, but our results highlight how full time dependence can be reckoned with once authoritative forecast models are made available.

California↗

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

Forecasting volcanic activity in Germany—A multi-criteria approach

Igneous activity, including shallow intrusions and volcanism, has the potential to disrupt underground critical infrastructure. Notably, future underground infrastructure projects like high-level radioactive waste repositories must be sited in areas of extremely low disruption probability by igneous activity. In Germany, according to the Repository Site Selection Act of 2017 (Standortauswahlgesetz, or StandAG), areas in which Quaternary volcanism is either present or future volcanic activity is expected within the next 1 million years (m.y.) must be excluded from the site selection process. Although the locations of regions with Quaternary volcanism are reasonably well known in Germany, forecasting potential igneous activity at intraplate volcanic fields is challenging, as many processes and their interactions control the spatial distribution of volcanic centers. Here, a semi-quantitative, multi-criteria approach is proposed for a regional evaluation of the relative potential of future igneous activity in Germany. A variety of geoscientific indicators are used, including seismic anomalies in Earth’s mantle, gravity data, tectonic activity, sutures, ground motion, earthquakes, mantle degassing centers, and geochronological data of volcanic rocks. The indicators describe the sequence of processes from potential melt generation in Earth’s mantle, through ascent and accumulation of melt within the lithosphere, to eruption at Earth’s surface. In total, 15 out of 30 proposed geoscientific indicators are selected and quantified using 20 total assigned parameters. Defined threshold values are used to spatially delimit relevant parameter properties to focus on areas with higher potential of future magmatic activity. To consider uncertainties of parameters and their underlying processes, which are usually more spatially extensive below ground, buffer zones are defined in which values of relevance decrease with increasing distance from the initial lateral shape of a parameter. Normalized parameters are combined into an index, whose spatial value distribution is used to differentiate the relative potential of future igneous activity (within the next 1 m.y.). The sensitivity of the results is shown by varying the weighting factors for the relevant parameters in country-wide index maps. Thereby, profiles illustrate the distribution of the resulting index values and respective index fractions of various parameters. Different index maps for the relative potential of future igneous activity are presented and can be used for hazard assessments.

Professional Paper↗

USGS2025

Combining scanning electron microscopy, X-ray diffraction, and X-ray fluorescence to characterize shear zones at the Pogo gold deposit, Alaska

This study employs a multi-method analytical approach to characterize the mineralogical, geochemical, and textural properties of fault rocks from the Pogo gold mine in the Yukon-Tanana Upland, central Alaska. Specifically, we examine cataclasites, to document the structural and geochemical evolution of shear zones and their associations with gold mineralization. To investigate the shear zone, we integrate portable X-ray fluorescence (pXRF), scanning electron microscopy-based automated mineralogy (SEM-AM), X-ray diffraction (XRD), and high-resolution micro-X-ray fluorescence (micro-XRF) mapping. These methods collectively provide insights into bulk and trace element chemistry, mineralogical composition, and deformation-related textures across multiple scales. Handheld pXRF enables rapid geochemical screening, guiding SEM-AM and XRD analyses to ensure consistent mineralogical interpretation. X-ray diffraction identifies and quantifies crystalline phases, while SEM-AM produces high-resolution mineral maps, revealing mineral abundances, grain-scale textures, and gold associations. Micro-XRF mapping further refines our understanding by showing visual trace element distributions at sub-millimetre resolution. By integrating these techniques, we improve our understanding of the nature and geochemistry of Pogo shear zones, their role in gold mineralization, and support metallurgical processing strategies. This approach enhances exploration models and resource characterization for structurally complex gold deposits.

Alaska↗

USGS2023

Advancing subsurface investigations beyond the borehole with passive seismic horizontal-to-vertical spectral ratio and electromagnetic geophysical methods at transportation infrastructure sites in New Hampshire

The U.S. Geological Survey (USGS), in cooperation with the New Hampshire Department of Transportation (NHDOT), surveyed transportation infrastructure sites using rapidly deployable geophysical methods to assess benefits added to a comprehensive site characterization with traditional geotechnical techniques. Horizontal-to-vertical spectral-ratio (HVSR) passive-seismic and electromagnetic-induction (EMI) methods were applied at 4 sites including a roadway-stream crossing, roadway-bridge rail-trail crossing, commuter-parking expansion, and a railroad-adjacent river-cutbank slope-failure site. Additionally, ground-penetrating-radar (GPR) was used at the slope-failure site. Typically, subsurface geotechnical properties are determined from boring data; however, borings are often spaced hundreds of feet apart, potentially missing important spatial variability between boreholes. Geotechnical site characterization including geophysical surveys helped provide a more accurate characterization by using continuous or near continuous profiling. Three-component ambient noise measured with HVSR methods were used to determine resonance frequency and estimate sediment thickness. The method works when there is a strong shear-wave acoustic impedance contrast (> 2:1) between sediment and bedrock. Sediment thickness estimates from HVSR measurements were combined with boring data to make detailed maps of the bedrock surface altitude. The bulk electrical conductivity of the subsurface was indirectly measured with EMI methods and was used to identify lithologic variations, shallow bedrock, and conductive groundwater. Ground penetrating radar, which transmits pulses of electromagnetic energy into the subsurface and records the amplitude and timing of reflected signals, was used to identify bedding and changes in lithology or water content. By combining geophysical and boring data analyses, transportation projects produced more spatially comprehensive representations of geotechnical subsurface conditions than would be determined using conventional borings alone.

New Hampshire↗

USGS2026

Flood-inundation maps for Río Grande De Loíza in and near Caguas, Puerto Rico, 2026

Digital flood-inundation maps for a 2.7-mile reach of Río Grande De Loíza in Caguas, Puerto Rico, were created by the U.S. Geological Survey. Water-surface profiles were computed for the stream reach by using a one-dimensional, steady-state, step-backwater model. The model was calibrated to the current (2025) stage-streamflow relation (rating curve) for the U.S. Geological Survey streamgage 50055000, Río Grande De Loíza, Puerto Rico. The resulting hydraulic model was then used to compute 16 water-surface profiles for water levels (flood stages) ranging from 19.00 to 34.00 feet at the streamgage; these flood stages range from “moderate flood stage” to above “major flood stage” as defined by the National Weather Service. The 34.00-foot stage exceeds the historical maximum peak stage of 33.20 feet, recorded at the streamgage in 1945. The simulated water-surface profiles were used in combination with a digital elevation model derived from light detection and ranging (lidar) data to map the inundated areas associated with each flood profile. The flood-inundation maps and the supporting hydraulic model produced by this study can be used by emergency managers and local officials to assess flood-mitigation strategies and to define flood-hazard areas to help protect life and property, to coordinate flood-response activities such as evacuations and road closures, and to aid post-flood recovery efforts.

Puerto Rico↗

USGS2026

From collision to subduction: Thermal-kinematic inversions constrain plate boundary structure and dip-slip activity in southwestern New Zealand

Constraints on three-dimensional fault system geometry and kinematics are required to understand both long-term tectonics and contemporary seismic hazard. In many cases, these parameters must be inferred from a combination of different data or analyses. Here, we invert low-temperature thermochronological data to quantitatively parameterize both the crustal-scale geometry and late Cenozoic dip-slip activity of the plate boundary system in southwest New Zealand. We find that the modern transpressive plate boundary system has accommodated the bulk of Australian-Pacific Plate convergence since establishment in the middle Miocene-early Pliocene. Shortening has occurred via (a) dextral-reverse slip on the moderate angle, listric central Alpine Fault décollement, and (b) reverse-slip on either the sharply curved, anti-listric northern Puysegur subduction interface or low-angle offshore thrust fault system that splays from the high-angle southern Alpine Fault at depth. We resolve late Cenozoic shortening rates on these structures that are indistinguishable, and interpret these to reflect the transfer of convergent deformation outboard of the predominantly strike-slip southern Alpine Fault. Our work helps elucidate the transition from strain localized oblique continental collision to strain partitioned subduction. We also provide an estimate of the across-strike width of the central-southern Alpine Fault section boundary at seismogenic depths. This is the first quantitative constraint on the geometry of a structural feature inferred to have arrested several major prehistoric earthquakes. This study furthers understanding of fault structure and dip-slip kinematics along the greatest sources of seismic hazard in and offshore of southwest New Zealand.

South Island↗