USGS Science⌕ Search

FIND YOUR NEXT DISCOVERY

Results for “Earth and Planetary Science Letters”

Original records, connected by a shared subject.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

1,226 records · Page 3Linked to original sources
USGS2026

Widespread landslide activity in an extreme wet season and implications for regional sediment management, eastern San Francisco Bay area, California

Watershed sediment production is expected to increase in a warmer future with more extreme rain, with cascading effects throughout drainage and sediment-transport networks. This study investigated landscape-scale sediment movement in the eastern San Francisco Bay area, California, USA, during the extreme 2016–2017 wet season that brought major rainfall, landslides, and flooding. Mapping 8,928 landslides across a 1,050-km 2 study area revealed new sediment yield of 510–956 t/km 2 , equivalent to denudation of 193–361 mm/ky. These results correspond closely to long-term denudation rates in the northern and central California Coast Ranges, indicating that mass wasting in very wet years dominates long-term sediment mobilization. However, due to long residence times in drainage networks, the 2017 landslides contributed at most ∼1%–2% of the estimated locally derived fluvial sediment transport to San Francisco Bay. Although the amount of sediment mobilized did not threaten municipal water supplies, small rangeland impoundments in this mixed-use landscape lost storage capacity to new sedimentation. Considering regional sediment supply and demand, even the exceptionally large sediment delivery in an extreme wet year cannot meet the need for sediment to accrete tidal wetlands in the bay. To keep pace with rising sea levels, this abnormally high terrestrial sediment input would need to occur in 50 of the next 75 years, an unlikely occurrence due to the prevalence of recent drought years. Shoreline protection and restoration in the bay would need additional sources of sediment, such as through management of dredged sediment through beneficial-reuse programs.

California↗
USGS2025

Nodal seismic deployment on Mauna Loa volcano, Hawaii: Dataset and preliminary insights

Mauna Loa is the largest active volcano on Earth, comprising ∼51% of the Island of Hawai‘i’s landmass and posing significant risks to the island’s communities, infrastructure, and natural environment. Historical eruptions have produced lava flows that have reached the ocean in as little as 3 hr. The timing and location of such lava flows in the past 200 yr underscore how critical determination of the location and geometry of magma storage and structure is for volcanic hazard assessment and eruption forecasting. Now, after nearly 38 yr of volcanic quiescence, Mauna Loa has erupted again. On 27 November 2022, fissures initiated within the summit caldera and then migrated to the northeast rift zone, where they generated a large lava flow that threatened a major highway. To improve our understanding of the geometry of this magma system, we deployed a temporary nodal array on Mauna Loa in the summer of 2024. This increased our seismic coverage sufficiently to image this magmatic system. This nodal array consists of 33 seismometers distributed on and around the volcano and was deployed for over three months to record seismic signals. The primary objective of this project is to resolve the high‐resolution seismic velocity structure and characterize seismic features associated with magma storage and ascent pathways. In this article, we present an overview of the deployment, evaluate the quality of the data, and show example recordings to evaluate the suitability of the data set for future seismic investigations, including earthquake relocation, seismic tomography, and receiver function analysis. Comparisons with nearby permanent broadband and short‐period seismic stations demonstrate that the nodal array recorded high‐quality waveforms, making it a valuable resource for constraining the magmatic system beneath Mauna Loa at multiple scales.

Hawaii↗
USGS2026

Patterns and drivers of cliff erosion in Big Sur, California, USA using repeat photogrammetry, 2017–2023

Seacliff erosion in steep terrain poses major risks to transportation and critical infrastructure. In Big Sur, California, USA, seacliff erosion threatens the sustainability of the central coast stretch of California State Route 1, a transportation corridor that is critical to the region's economy. Published cliff retreat rates for the region range from 1 to 40 cm yr −1 , highlighting that high-resolution, process-based studies could enhance understanding of the causes of spatial and temporal variability. We quantified cliff erosion and investigated its drivers along ∼13 km of the Big Sur coastline at week–month timescales during the late fall to early spring wet seasons between January 2017 and June 2023 by analyzing 3D point clouds developed from aerial imagery using four-dimensional structure-from-motion (4D SfM) photogrammetry techniques. We calculated cliff face retreat rates of 2.23 ± 3.06 cm yr −1 (mean ±1 σ ), an order of magnitude lower than long-term estimated rates for the region (which included large deep-seated landslides), but in line with short-term rates reported across California. Change detection imagery comparison, cliff profiles through time, and statistical analysis reveal a cyclical cliff evolution process in which erosion by wave action at the cliff base destabilizes the cliff and primes it for subsequent failure during precipitation events. Although more erosion by volume could be attributed to precipitation-induced increases in soil moisture (784 m 3 km −1 yr −1 ) compared with erosion attributed to wave power (282 m 3 km −1 yr −1 ), our observations underscore the coupled nature of these processes in driving cliff evolution, consistent with established theory and observations.

California↗
USGS2026

Lunar analog study using portable gamma-ray neutron detector: Radiochemical mapping of silicic-to-basaltic volcanic terrains in the San Francisco Volcanic Field, Arizona

Studying lunar silicic volcanism provides key insights into the Moon’s crustal evolution, magmatic processes, and volcanic history. The Lunar-VISE (Lunar Vulkan Imaging and Spectroscopy Explorer) mission will investigate the Gruithuisen domes, a unique lunar region hypothesized to have formed through silicic volcanism. Using instruments on a Firefly Aerospace lander and a Honeybee Robotics rover, Lunar-VISE will analyze mineralogy, geochemistry, and surface properties to determine the origin and evolution of the domes, with a gamma-ray and neutron spectrometer (LV-GRNS) among its payload instruments. In preparation for this mission, we conducted preliminary fieldwork using a handheld gamma-ray neutron detector with NaI(Tl) and Cs LiYCl :Ce (CLYC) scintillators. This study focuses on various rhyolitic and basaltic volcanic centers in the San Francisco Volcanic Field (SFVF) near Flagstaff, Arizona—specifically Sugarloaf Peak, Bonito Lava Flow, and Robinson Mountain, a region containing several well-characterized lunar analog sites. The SFVF was selected for this study due to its broad compositional diversity spanning basaltic to rhyolitic compositions, its well-preserved volcanic morphologies, and its extensive use in previous NASA field campaigns and astronaut training exercises, making it an ideal terrestrial laboratory for testing planetary exploration techniques. We measured natural radioactivity, specifically from potassium (K), thorium (Th), and uranium (U) and other elements in their decay chains, which serve as diagnostic tracers of magmatic differentiation and crustal evolution processes, to assess geochemical variability across compositionally diverse terrains. The detector’s sensitivity was assessed across varying concentration levels. Regionally averaged concentrations of radioisotopes were determined by gamma-ray spectroscopy at selected sites. Our measurements reveal significant compositional variations between sites, with Sugarloaf Peak (rhyolitic, silicic dome) exhibiting the highest average radioisotope concentrations (K: 3.29 ± 0.24 wt%, U: 14.35 ± 1.81 ppm, Th: 27.14 ± 2.43 ppm), while Bonito Lava Flow (K: 1.13 ± 0.08 wt%, U: 3.86 ± 0.52 ppm, Th: 7.52 ± 1.02 ppm), and Robinson Mountain (K: 1.46 ± 0.16 wt%, U: 5.59 ± 1.06 ppm, Th: 11.75 ± 1.98 ppm) show lower concentrations aligned with basaltic compositions. Gamma-ray fluxes were elevated by a factor of approximately three to four at Sugarloaf Peak relative to nearby basaltic terrains, consistent with expected geochemical differentiation patterns. Furthermore, at meter scales, proximity to geological features significantly affects measurements. Th concentrations adjacent to a cliff face at Sugarloaf’s base were 28% higher than values measured 3-5 meters away from the same feature, demonstrating localized compositional heterogeneity. Analysis of station-by-station measurements reveals that K, U, and Th concentrations show an elevation trend at Robinson Mountain and generally higher concentrations near Sugarloaf Peak’s summit, suggesting progressive magmatic differentiation and/or the presence of more evolved lithologies at higher elevations. By mapping these elements on Earth using GRNS, we aim to optimize measurement techniques for Lunar-VISE and similar rover-borne missions by demonstrating the applicability of portable GRNS instruments for planetary surface exploration in an analog environment.

Arizona↗
USGS2025

SURF: An automated method for building nonplanar 3D fault models from earthquake hypocenters

Accurately characterizing 3D fault geometry is vital for improving our understanding of earthquake behavior and informing the development of seismic hazard models. Despite their importance, subsurface fault structures tend to be poorly constrained because of limitations in observational data. Improvements to the seismic networks and earthquake detection algorithms have increased the precision and volume of earthquake catalogs, which help illuminate detailed subsurface fault structure and provide the most direct information available about fault geometries at depth. We present a Python package to automate generating 3D fault geometries directly from hypocentral seismicity patterns. This method begins with clustering events based on their spatial density, identifying coherent patterns. Nearby clusters are then merged based on the similarity of their orientations. We fit nonplanar surfaces using support vector regression to balance surface accuracy with minimal deviations from planarity. The fault models are output as quadrilateral meshes at user‐defined resolution. In the process of generating the 3D fault surfaces, we compute the spatial density of seismicity around the surface and the planarity as quantitative metrics of the model outputs. As a proof of concept, we apply this approach to the San Andreas–Calaveras fault junction region and the 2019 Ridgecrest earthquake sequence, both in California, which contain complex subparallel faults well defined at the Earth’s surface and abundant microseismicity. These case studies demonstrate the method’s ability to model complex fault structures, including long continuous fault surfaces, crossing faults, variably dipping segments, and subparallel faults. We test the method on both standard network catalogs and double‐difference relocated catalogs. We find that our seismicity‐based fault model results align with published 3D models that incorporate additional constraints and interpretations ( Plesch et al. , 2020 ; Aagaard and Hirakawa, 2021 ). This workflow provides a low‐user‐input solution for estimating fault geometries at depth from earthquake catalogs.

California↗
USGS2026

Understanding the resource potential of natural hydrogen on Earth: Scientific gaps, uncertainties and recommendations

A comprehensive scientific research roadmap is essential to bridge knowledge gaps and deepen the understanding of key geological, geochemical, and geophysical aspects of natural hydrogen (H 2 ) as a potential new energy resource. This paper reviews major scientific uncertainties on natural H 2 , suggesting research priorities, as a guide for defining exploration strategies, techniques, and data interpretation. The uncertainties concern all phases of the natural H 2 cycle, from generation (source rocks) through migration (advection and diffusion) and accumulation (reservoir and cap rocks) to the application and interpretation of subsurface and surface geochemical and geophysical exploration techniques. Understanding H 2 sources and generation rates (the amount of H 2 generated by a given volume of rock over time) is crucial for determining whether a geological H 2 system operates as a short-term dynamic system with rapid H 2 production and release, or as a conventional gas system with long-term accumulations, analogous to petroleum reservoirs. Preliminary estimates for serpentinisation, radiolysis, and organic matter degradation suggest that H 2 generation is not inherently fast, especially for non-hydrothermal continental systems (crystalline basement of shields, ophiolites, peridotite massifs, sedimentary basins), and long-term accumulations, like those of fossil natural gas systems, represent the most likely scenario. The mechanisms of H 2 migration through geological formations require application of fundamental principles of fluid-flow physics, distinguishing advection and diffusion, as well as their forms (from gas-phase, bubble flows to aqueous solutions). Additional studies of H 2 accumulation and retention in subsurface reservoirs could improve understanding of mechanisms of H 2 migration by focusing on the rock fluid-bearing properties and the factors affecting H 2 preservation, such as the presence of cap rocks impermeable to H 2 , pressure conditions, residence times, and microbial or abiotic consumption. Advanced techniques, including reservoir modelling, flow simulations, 3D imaging (micro-CT) of H 2 -bearing rocks, and extraction and analysis of gas occluded in rocks, can provide insights into the stability and potential recoverability of H 2 accumulations. The interpretation of surface exploration techniques, including gas geochemistry, geophysics, and remote sensing, long employed in mineral and energy resource exploration, is now being adapted for natural H 2 studies, but challenges remain in the data interpretation. Distinguishing H 2 seepage due to geological degassing from H 2 produced near the surface by modern microbial processes or artificial sources, such as hammering or drilling for soil-gas sampling, drilling into aquifers, and corrosion in boreholes, is an essential step in exploration. The simple detection of H 2 in soils, even in morphological structures like sub-circular depressions or “fairy circles”, cannot be cursorily interpreted as a signal of natural H 2 seepage from a deep source. A holistic geochemical approach, including isotopic analyses of gases associated with H 2 , is recommended to distinguish among the variety of possible H 2 origins. Observations of H 2 in wells should be interrogated to rule out possible artifacts such as corrosion and drill bit metamorphism. The integration of multiple geophysical methods, including seismic, gravimetric, magnetic, and electro-magnetic surveys, is recommended to mitigate interpretation ambiguities regarding the structure of a subsurface H 2 system (source and reservoir rocks, including fluid and gas storage), due to the non-uniqueness of rock-specific physical properties.

Earth-Science Reviews↗
USGS2025

Invited perspectives: Integrating hydrologic information into the next generation of landslide early warning systems

Although rainfall-triggered landslides are initiated by subsurface hydro-mechanical processes related to the loading, weakening, and eventual failure of slope materials, most landslide early warning systems (LEWS) have relied solely on rainfall event information. In previous decades, several studies demonstrated the value of integrating proxies for subsurface hydrologic information to improve rainfall-based forecasting of shallow landslides. More recently, broader access to commercial sensors and telemetry for real-time data transmission has invigorated new research into hydrometeorological thresholds for LEWS. Given the increasing number of studies across the globe using hydrologic monitoring, mathematical modeling, or both in combination, it is now possible to make some insights into the advantages versus limitations of this approach. The extensive progress demonstrates the value of in situ hydrologic information for reducing both failed and false alarms, through the ability to characterize infiltration during, as well as the drainage and drying processes between major storm events. There are also some areas for caution surrounding the long-term sustainability of subsurface monitoring in landslide-prone terrain, as well as unresolved questions in hillslope hydrologic modeling, which relies heavily on the assumptions of diffuse flow and vertical infiltration but often ignores preferential flow and lateral drainage. Here, we share a collective perspective based on our previous collaborative work across Europe, North America, Africa, and Asia to discuss these challenges and provide some guidelines for integrating knowledge of hydrology and climate into the next generation of LEWS. We propose that the greatest opportunity for improvement is through a measure-and-model approach to develop an understanding of landslide hydro-climatology that accounts for local controls on subsurface storage dynamics. Additionally, new efforts focused on the subsurface hydrology are complementary to existing rainfall-based methods, so leveraging these with near-term precipitation forecasts is a priority for increasing lead times.

Alaska↗
USGS2026

Ground-motion simulations for the 2024 Mw 4.8 Tewksbury, New Jersey, earthquake

Ground-motion simulations of notable earthquakes in the central and eastern United States are limited and typically assume one-dimensional (1D) Earth structure. In this study, we use a three-dimensional (3D) seismic velocity model to better constrain the depth and focal mechanism of the April 5th, 2024, moment magnitude 4.8 Tewksbury earthquake and investigate the spatial variability of earthquake ground motions and the effects of nearby sedimentary basins. We perform earthquake ground-motion simulations up to 0.5 Hz using the 3D spectral-element wave-propagation solver SPECFEM3D over a region 280-km wide by 260-km long by 77-km deep. Topography and subsurface geophysical structure are assigned using the U.S. Geological Survey National Crustal Model with a minimum shear-wave velocity of 200 m/s. We use earthquake time series from 13 broadband seismic stations in the region that have a uniform azimuthal distribution and epicentral distances ranging from 76 to 131 km to compare with synthetics and explore the effects of 1D versus 3D seismic structure on focal mechanism and depth solutions. Ground-motion intensity metrics are also presented relative to the NGA-East ground-motion models (GMMs) currently used in seismic hazard assessments for the region. We find that the 3D model, which reveals a wide spatial variability of period-dependent ground motions, yields better predictions of earthquake ground motions relative to the 1D model and the NGA-East ergodic ground-motion model, with 76 percent reduction of residual variance in observed ground motions averaged over 3-, 5-, 7-, and 10-second periods. Use of the 3D model to solve for a focal mechanism yields a shallower focal depth at 4 km and a shallower east-dipping focal plane relative to the U.S. Geological Survey regional moment tensor and Global Centroid Moment Tensor. Our study demonstrates that use of 3D seismic velocity models can improve estimates of earthquake focal mechanisms, ground motions, and seismic hazard.

New Jersey↗
USGS2026

Sedimentological and geochemical characterization of lacustrine deposits of the Babouri-Figuil basin, northern Cameroon: Implications for source rocks distribution and petroleum exploration

The West and Central African Rift System (WCARS) refers to the series of Cretaceous rift basins where commercial hydrocarbon accumulations have been discovered. Some of the WCARS frontier basins are currently being investigated to increase our understanding of these basins in light of new commercial discoveries. The present study was performed in the Babouri-Figuil Basin (BFB), which is genetically related to the WCARS and constitutes an area of interest in terms of petroleum prospecting, where the distribution of petroleum source rocks and potential targets for petroleum exploration across the entire basin is poorly understood. For the current study, an integrated facies analysis along with organic and inorganic geochemical techniques were applied to the basin's Cretaceous deposits with the aim of reconstructing the paleodepositional environment, assessing factors that triggered the input of organic matter, and providing a spatial overview of the organic matter accumulation in the basin based on outcrop samples. An alluvial fan-lacustrine-braided river system is inferred from the facies analysis of the stratigraphic sequence consisting of conglomerate, sandstone, siltstone, limestone, marlstone, and claystone. Bulk analysis of organic matter reveals that black shale and massive claystone are the main prospective petroleum source rocks in the basin. Inorganic geochemical analyses reveal the influence of anoxic conditions, moderate to high primary productivity, and low terrigenous inputs in organic matter enrichment. The formations rich in organic matter are predominantly concentrated in the western and eastern parts of the basin which may represent areas with depressions, characterized by high accommodation space. In terms of the regional context of the WCARS rift basins, typical hydrocarbon exploration in the BFB may target basal-conglomerate, sandstone beds situated directly above or/and interbedded with the Lower Cretaceous source rocks, and the Upper Cretaceous sandstone beds. Basement rocks (granite, granodiorite, and gneisses) and oil shale deposits may represent potential unconventional hydrocarbon exploration. The current integrated study provides an insight that should guide future hydrocarbon exploration campaigns in the basin.

Babouri-Figuil basin↗
USGS2025

U.S. Geological Survey—Department of the Interior, Region 11, Alaska—2023–24 biennial science report

Introduction U.S. Geological Survey (USGS) Mission—The USGS national mission is to monitor, analyze, and predict the current and evolving dynamics of complex human and natural Earth-system interactions and to deliver actionable information at scales and timeframes relevant to decision makers. Consistent with the national mission, the USGS in Alaska provides timely and objective scientific information to help address issues and inform management decisions across five interconnected focus areas: Energy and Minerals; Geospatial Mapping; Natural Hazards; Water Quality, Streamflow, and Ice Dynamics; and Ecosystems. The USGS in Alaska consists of approximately 350 scientists and support staff working in 3 Alaska-based science centers. USGS science activities are also initiated by the Cooperative Research Unit and USGS centers outside Alaska. In the last 5 years, USGS research in Alaska has produced many scientific benefits resulting from more than 900 publications. Publications relevant to Alaska can be conveniently searched by keyword through the USGS Publications Warehouse at https://pubs.usgs.gov/.

Alaska↗
USGS2024

Probabilistic assessment of postfire debris-flow inundation in response to forecast rainfall

Communities downstream of burned steep lands face increases in debris-flow hazards due to fire effects on soil and vegetation. Rapid postfire hazard assessments have traditionally focused on quantifying spatial variations in debris-flow likelihood and volume in response to design rainstorms. However, a methodology that provides estimates of debris-flow inundation downstream of burned areas based on forecast rainfall would provide decision-makers with information that directly addresses the potential for downstream impacts. We introduce a framework that integrates a 24 h lead-time ensemble precipitation forecast with debris-flow likelihood, volume, and runout models to produce probabilistic maps of debris-flow inundation. We applied this framework to simulate debris-flow inundation associated with the 9 January 2018 debris-flow event in Montecito, California, USA. When the observed debris-flow volumes were used to drive the probabilistic forecast model, analysis of the simulated inundation probabilities demonstrates that the model is both reliable and sharp. In the fully predictive model, however, in which debris-flow likelihood and volume were computed from the atmospheric model ensemble's predictions of peak 15 min rainfall intensity, I 15 , the model generally under-forecasted the inundation area. The observed peak I 15 lies in the upper tail of the atmospheric model ensemble spread; thus a large fraction of ensemble members forecast lower I 15 than observed. Using these I 15 values as input to the inundation model resulted in lower-than-observed flow volumes which translated into under-forecasting of the inundation area. Even so, approximately 94 % of the observed inundated area was forecast to have an inundation probability greater than 1 %, demonstrating that the observed extent of inundation was generally captured within the range of outcomes predicted by the model. Sensitivity analyses indicate that debris-flow volume and two parameters associated with debris-flow mobility exert significant influence on inundation predictions, but reducing uncertainty in postfire debris-flow volume predictions will have the largest impact on reducing inundation outcome uncertainty. This study represents a first step toward a near-real-time hazard assessment product that includes probabilistic estimates of debris-flow inundation and provides guidance for future improvements to this and similar model frameworks by identifying key sources of uncertainty.

California↗
USGS2025

Estimation of dynamic geologic CO2 storage resources in the Illinois Basin, including effects of brine extraction, anisotropy, and hydrogeologic heterogeneity

Since the vast majority of carbon dioxide (CO 2 ) storage resources in the United States are in deep saline aquifers, optimizing the use of these saline storage resources could be crucial for efficient development of geologic CO 2 storage (GCS) resources and basin- or larger-scale deployment of GCS in the country. Maximum CO 2 injection rates can be enhanced by extracting brine from the CO 2 storage unit. However, disposal of the extracted brine is both a technological and economic challenge. The lowest-cost option would likely be reinjection of the extracted brine into another formation above or below the CO 2 storage unit. Therefore, it is important to estimate brine injectivity as it will constrain the potential to increase CO 2 injectivity at an injection site that has access to multiple geologic storage units where either CO 2 or brine can be injected. Using a simulation-optimization framework, coupled with a non-isothermal, multiphase CO 2 -water-salt equation-of-state module, we developed a computationally efficient method for evaluating optimization of simultaneous CO 2 injection, brine extraction, and brine (re)injection at hypothetical injection sites deployed across a geologic basin. The Illinois basin is ideal for testing our methodology because it contains multiple geologic storage units with seals in between them to isolate injection of CO 2 in one unit from interfering with the injection of either brine or CO 2 in another unit above or below it. In addition, we investigated the relative effects of variation in key geologic parameters as well as two reservoir structures (hydrogeologic heterogeneity/anisotropy and homogeneity/isotropy) on CO 2 injectivities and enhancement of CO 2 injectivity through extracting brine. Results suggest that permeability, depth, and especially thickness of the storage unit could be the most influential parameters determining CO 2 injectivity. They also suggest that only injecting CO 2 into the storage unit with the greatest injectivity, enhancing that unit’s injectivity by extracting brine, and disposing of the produced brine in other suitable units could maximize total CO 2 injectivity in limited regions of the basin. At the majority of simulated injection sites, however, we found that injecting CO 2 into all of the accessible and suitable storage units was more likely to maximize the CO 2 storage resource.

Illinois, Kentucky, Indiana↗
USGS2024

A benchmark dataset and workflow for landslide susceptibility zonation

Landslide susceptibility shows the spatial likelihood of landslide occurrence in a specific geographical area and is a relevant tool for mitigating the impact of landslides worldwide. As such, it is the subject of countless scientific studies. Many methods exist for generating a susceptibility map, mostly falling under the definition of statistical or machine learning. These models try to solve a classification problem: given a collection of spatial variables, and their combination associated with landslide presence or absence, a model should be trained, tested to reproduce the target outcome, and eventually applied to unseen data. Contrary to many fields of science that use machine learning for specific tasks, no reference data exist to assess the performance of a given method for landslide susceptibility. Here, we propose a benchmark dataset consisting of 7360 slope units encompassing an area of about 4,100 km 2 "> 4,100 km 2 in Central Italy. Using the dataset, we tried to answer two open questions in landslide research: (1) what effect does the human variability have in creating susceptibility models; (2) how can we develop a reproducible workflow for allowing meaningful model comparisons within the landslide susceptibility research community. With these questions in mind, we released a preliminary version of the dataset, along with a “call for collaboration,” aimed at collecting different calculations using the proposed data, and leaving the freedom of implementation to the respondents. Contributions were different in many respects, including classification methods, use of predictors, implementation of training/validation, and performance assessment. That feedback suggested refining the initial dataset, and constraining the implementation workflow. This resulted in a final benchmark dataset and landslide susceptibility maps obtained with many classification methods. Values of area under the receiver operating characteristic curve obtained with the final benchmark dataset were rather similar, as an effect of constraints on training, cross–validation, and use of data. Brier score results show larger variability, instead, ascribed to different model predictive abilities. Correlation plots show similarities between results of different methods applied by the same group, ascribed to a residual implementation dependence. We stress that the experiment did not intend to select the “best” method but only to establish a first benchmark dataset and workflow, that may be useful as a standard reference for calculations by other scholars. The experiment, to our knowledge, is the first of its kind for landslide susceptibility modeling. The data and workflow presented here comparatively assess the performance of independent methods for landslide susceptibility and we suggest the benchmark approach as a best practice for quantitative research in geosciences.

Earth-Science Reviews↗
USGS2024

Editorial: From cold seeps to hydrothermal vents: Geology, chemistry, microbiology, and ecology in marine and coastal environments

This Research Topic compiles contemporary studies on cold seeps, hydrothermal vents, mud volcanoes, and related seafloor features that are associated with focused fluid emissions and the transfer of carbon, other chemical species, and sometimes heat from the geosphere to the ocean. Because these features sometimes tap fluids and gas originating kilometers below the seafloor, they provide an important window into deep processes that are otherwise inaccessible to scientists. At the shallow portion of their journey, migrating fluids nearing the seafloor contribute to a range of unique biological, physical, and chemical processes within the sediments themselves and at the sediment-water interface. Seafloor fluid emissions play a critical role in global biogeochemical cycles, ocean chemistry, and possibly even climate change. Seafloor leakage points often emit hydrocarbon gases (especially methane and CO 2 ) and are sometimes the loci for deposition of seafloor minerals that have economic value. A burgeoning area of research focuses on natural products generated at these features, seeking compounds with potential pharmaceutical or other applications. Multidisciplinary studies have become routine for characterization of seafloor fluid emission sites, attesting to the inseparability of geologic, physical, chemical, and biological processes in these settings. It is increasingly common for researchers to combine in a single research cruise: subbottom imaging and seafloor mapping; porewater and water column geochemistry and gas sampling; sediment retrieval for lithologic, biostratigraphic, and solid phase analyses; and studies of benthic and subseafloor communities at the microbial to macrofaunal scales. This multidisciplinary approach has the advantage of ensuring the spatial and temporal coincidence of surveys and samples, an important factor at highly dynamic seafloor fluid emission sites. In addition, researchers often use remotely operated vehicles (ROVs), autonomous underwater vehicles (AUVs), or human-occupied vehicles (HOVs) to record video of the seafloor, compile photomosaics, collect targeted samples, and survey with high-resolution geophysical near-seafloor systems, providing a degree of detail about seafloor fluid emission sites that is unprecedented compared to most areas of the deep ocean. While rarer, long-term cabled observatories or shorter-term deployments of portable observatories are also used at some loci for seafloor fluid flux and are particularly helpful for capturing temporal variations at these dynamic features. Here we summarize the Research Topic’s contribution to multidisciplinary seafloor emission studies in the categories of cold seeps, mud volcanoes, and hydrothermal vents. Figure 1 shows the geographic distribution of the studies in this Research Topic and key features referred to in this Introduction.

Frontiers in Earth Science↗
USGS2026

Guidelines for producing integrated 210Pb and 14C age-models

Accurate reconstructions of past environmental changes are crucial in paleoecological research and require reliable chronologies of sedimentary archives. Establishing robust age-models and obtaining the most appropriate proxies for analysis is a complex scientific endeavor, requiring extensive resources and collaboration among specialists, including radiochronologists. Radiometric dating methods, such as 210 Pb and radiocarbon ( 14 C), are frequently employed to establish chronologies in aquatic sedimentary deposits and peat bogs. In this study, we review key aspects of sampling, analysis, and the principles underlying 210 Pb and 14 C age-models, focusing on methods for developing robust joint chronologies for paleoenvironmental research. Drawing largely from the authors' experiences and group discussions during and after a scientific workshop in 2022, we discuss important considerations for site selection, sampling strategies, and radiometric dating to construct integrated 210 Pb and 14 C age-models. Using expert consensus, this group – called Paleostats – aims to provide a set of best practices for other geochronologists with this methods paper. Among our conclusions, we emphasize the importance of accounting for site-specific factors such as prior information on sedimentation rates to establish appropriate sampling and analytical strategies. The use of appropriate coring devices can minimize disturbance to sediments and ensure the core surface remains intact and preserved until sectioning. Where excess 210 Pb is expected, sectioning at intervals of ≤1 cm provides an adequate sampling resolution for 210 Pb dating. Exceptions are possible, allowing for ~2–3 cm sections in areas with confirmed high sedimentation rates (e.g., > 1 cm yr −1 ). Recovering deeper core sections for 14 C dating with sufficient overlap allows for accounting errors in depth estimates made in the field. Special attention is advised during time intervals where validation proxies, such as the human-made radionuclides 137 Cs or post-bomb 14 C, are expected, and to determine the depth of secular equilibrium between 210 Pb and 226 Ra. Radiocarbon analyses are commonly performed by accelerator mass spectrometry, and age models are constructed mainly using Bayesian statistics with Markov Chain Monte Carlo techniques (e.g., Bacon ). A Bayesian approach ( Plum ) is now available for producing 210 Pb age-models, which infers the 210 Pb ex flux, eliminates the need for selecting an equilibrium depth, and allows dating cores with incomplete 210 Pb ex inventory. Plum offers improved chronologies by integrating raw 210 Pb and 14 C data, and these age-models can be enriched with other dating methodologies, such as identifying tephras and other well-recorded historical events. Harmonized reporting would contribute to making radiometric age-models reproducible, which would benefit from an international effort. Using 210 Pb and 14 C to produce integrated age-models may yield better insights into the interplay between natural and recent anthropogenic forcings on ecosystems. This can enhance our understanding of environmental processes and their impacts on climate change, ultimately supporting science-based assessments and decisions.

Earth-Science Reviews↗
USGS2025

Constraining landslide frequency across the United States to inform county-level risk reduction

Informative landslide hazard estimates are needed to support landslide mitigation strategies to reduce landslide risk across the United States. Whereas existing national-scale landslide susceptibility products assess where landslides are likely to occur, they do not address how often , which is a critical element of landslide hazard and risk assessments. In particular, the U.S. Federal Emergency Management Agency's National Risk Index (NRI) requires landslide frequency estimates to inform expected annual loss estimates. We present county-level landslide frequency (landslides per area per year) estimates for the 50 US states. We applied Bayesian negative binomial regression to estimate both the expected (average) reported landslide frequency and full distribution of annual landslide counts for each county. We compared a suite of models that used combinations of landslide-susceptible area, probability of potentially triggering earthquakes, frequency of potentially triggering precipitation, and ecological region as predictors. We trained our models with landslide inventory data from counties with the most comprehensive records available nationwide and used zero-inflated negative binomial distributions as an incompleteness model to correct for temporal reporting gaps. We selected a preferred frequency model to inform the NRI based on information criteria and physically plausible parameter estimates. The model showed that average annual reported landslide frequencies vary by 5 orders of magnitude across US counties, ranging from 0.002 (0.00015–0.05) landslides 1000 km −2 yr −1 in Kusilvak Census Area, Alaska, to 29 (19–46) landslides 1000 km −2 yr −1 in Lake County, California, reflecting the country's strong variations in landslide susceptibility, earthquake probability, and other factors for which ecological region serves as a proxy. Counties with estimated frequencies in the top 20 % of all counties are predominately along the West Coast of the continental United States, in mountainous regions of the Pacific Northwest and Intermountain West, in locally steep or earthquake-prone regions of the Midwest and Southeast, along the Appalachians, in southern and southeastern Alaska, and on some Hawaiian islands. By examining the number of landslides predicted in 99th percentile years for each county, we identified that 26 % of US counties likely have potential for widespread landsliding with more than 10 landslides 1000 km −2 yr −1 , even when such large events have not been reported in the training data for that county. Overall, our results better represent the range of possible landslide frequencies and spatial variations than previous national-scale estimates reported in the NRI, and our approach can inform other risk-reduction and loss-mitigation efforts across the United States and globally.

Natural Hazards and Earth System Sciences↗
USGS2025

System characterization report on the Environmental Mapping and Analysis Program (EnMAP)

This report addresses system characterization of the Environmental Mapping and Analysis Program hyperspectral sensor by the DLR (German Aerospace Center, ground segment project management), GFZ (Deutsches Geoforschungszentrum, science lead) and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence. These reports present and detail the methodology and procedures for characterization; present technical and operational information about the EnMAP hyperspectral sensor; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions. The Earth Resources Observation and Science Cal/Val Center of Excellence system characterization team completed data analyses to characterize the geometric (interior and exterior), and radiometric performances of the EnMAP hyperspectral sensor. Results of these analyses indicate that the Environmental Mapping and Analysis Program has a band-to-band geometric performance in the range of −0.135 to 0.15 pixel, geometric performance relative to the Operational Land Imager in the range of −27.716 meters (−0.92 pixel) to 32.892 meters (1.09 pixels) offset in comparison to Landsat 8 Operational Land Imager, offset of a radiometric comparison in the range of −0.012 to 0.020, slope of a radiometric comparison in the range of 0.947 to 1.031.

Open-File Report↗
USGS2025

Permafrost–wildfire interactions: active layer thickness estimates for paired burned and unburned sites in northern high latitudes

As the northern high-latitude permafrost zone experiences accelerated warming, permafrost has become vulnerable to widespread thaw. Simultaneously, wildfire activity across northern boreal forest and Arctic/subarctic tundra regions impacts permafrost stability through the combustion of insulating organic matter, vegetation, and post-fire changes in albedo. Efforts to synthesis the impacts of wildfire on permafrost are limited and are typically reliant on antecedent pre-fire conditions. To address this, we created the FireALT dataset by soliciting data contributions that included thaw depth measurements, site conditions, and fire event details with paired measurements at environmentally comparable burned and unburned sites. The solicitation resulted in 52 466 thaw depth measurements from 18 contributors across North America and Russia. Because thaw depths were taken at various times throughout the thawing season, we also estimated end-of-season active layer thickness (ALT) for each measurement using a modified version of the Stefan equation. Here, we describe our methods for collecting and quality-checking the data, estimating ALT, the data structure, strengths and limitations, and future research opportunities. The final dataset includes 48 669 ALT estimates with 32 attributes across 9446 plots and 157 burned–unburned pairs spanning Canada, Russia, and the United States. The data span fire events from 1900 to 2022 with measurements collected from 2001 to 2023. The time since fire ranges from 0 to 114 years. The FireALT dataset addresses a key challenge: the ability to assess impacts of wildfire on ALT when measurements are taken at various times throughout the thaw season depending on the time of field campaigns (typically June through August) by estimating ALT at the end-of-season maximum. This dataset can be used to address understudied research areas, particularly algorithm development, calibration, and validation for evolving process-based models as well as extrapolating across space and time, which could elucidate permafrost–wildfire interactions under accelerated warming across the high-northern-latitude permafrost zone. The FireALT dataset is available through the Arctic Data Center ( https://doi.org/10.18739/A2RN3092P , Talucci et al., 2024).

Arctic↗