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USGS2025

A crosswalk of the 2015 World Terrestrial Ecosystems to the International Union for the Conservation of Nature Global Ecosystem Typology Framework

To support ecosystem mapping and accounting applications, we aligned the 2015 U.S. Geological Survey/Esri/The Nature Conservancy-World Terrestrial Ecosystems (WTEs) with the International Union for Conservation of Nature Global Ecosystem Typology (GET) framework. This process, known as “crosswalking,” enabled the development of a global map of GET level 3 Ecosystem Functional Groups (EFGs) at a 250-meter spatial resolution. Crosswalking involved manually assigning 1,781 biogeographically stratified WTEs to their most probable EFG based on similarities in climate, terrain, vegetation, and geographic distribution. We compared attributes of the WTE dataset with summary characteristics of the EFGs. The resulting crosswalked global map of International Union for Conservation of Nature GET ecosystems is intended to be useful for standardizing ecosystem classification and reporting under frameworks such as the Kunming-Montreal Global Biodiversity Framework and the United Nations System of Environmental-Economic Accounting. We discuss key challenges in reconciling non-identical classifications, such as many-to-one relationships and variation in data quality.

Open-File Report↗
USGS2025

Laboratory assessment for recovery of porcine circovirus 2 and porcine reproductive and respiratory syndrome virus using two types of commercially available hollow-fiber ultrafilters

Groundwater near swine farms is an uninvestigated reservoir for porcine reproductive and respiratory syndrome virus (PRRSV) and porcine circoviruses (PCVs). Enteric microorganisms are often collected from groundwater via dead-end ultrafiltration, but recovery of PRRSV and PCV with this method has not been assessed. We recovered PRRSV2 and PCV2 by dead-end ultrafiltration followed by polyethylene glycol (PEG) precipitation, nucleic acid extraction, and reverse-transcription quantitative real-time PCR. We also compared 2 commercial hemodialysis ultrafilters (Asahi Kasei Rexeed-25A, Nipro Elisio-25H) and compared PRRSV2 recovery in these filters to other waterborne microorganisms. On average, 8 ± 1% of PRRSV2 was recovered by dead-end ultrafiltration and PEG precipitation, compared to 25 ± 6% for adenovirus 41. Full-process recovery of bacteria in the same filters was 5–15%; Cryptosporidium parvum recovery was 42 ± 12%. PCV2 was detected in 4 of 12 replicate filters, but low stock concentrations precluded quantitative recovery estimates. Elisio-25H ultrafilters performed similarly to Rexeed-25A filters for all organisms tested and is an effective replacement for the Rexeed-25A, which is no longer available in the United States. Our recovery of PRRSV2 and PCV2 by dead-end ultrafiltration in the laboratory suggests that PRRSV2 detection limits are as low as 3–50 genomic copies/L in sample volumes of 100–1,500 L. Based on quantitative microbial risk assessment, these concentrations are relevant to PRRSV2 infection rates in the U.S. swine herd.

Journal of Veterinary Diagnostic Investigation↗
USGS2025

Estimated average annualized tsunami losses for the United States

Tsunami hazards are substantial threats to coastal communities across the United States (U.S.) and its territories. U.S. states and territories collaborate through the National Tsunami Hazard Mitigation Program (NTHMP) to develop their own tsunami-hazard information for outreach and evacuation planning. An effort to curate this tsunami-hazard information to support comprehensive risk analysis at the national level has not yet been completed. In support of this effort, the Federal Emergency Management Agency (FEMA) collaborated with the NTHMP, the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Geological Survey (USGS) starting in 2023. This collaboration included the collection and analysis of existing tsunami hazard data and methods in the U.S. Tsunami subject matter experts identified and selected scientifically defensible methods for estimating the risks to buildings and populations in coastal communities. These efforts may support decision making regarding resilience policies, priorities, strategies and funding levels. Tsunamis can be triggered by earthquakes, subaerial or submarine landslides, volcanic eruptions, glacial calving, near-earth objects, weather or other events. These events can cause severe destruction, injuries, and loss of life due to powerful currents and flooding. Tsunamis pose a substantial threat to the western United States and all U.S. territories, as described below. ■ Hawaii is threatened by distant tsunamis due to its central location in the Pacific Ocean basin and has a history of local events. ■ Alaska, particularly the Aleutian Islands, faces local tsunami threats due to proximity to the Alaska-Aleutian Subduction Zone, as well as distant tsunamis from around the Pacific Ocean basin. ■ The western coast of the U.S. is threatened by distant tsunamis from around the Pacific Ocean basin and local source tsunamis from earthquakes generated within the Cascadia Subduction Zone in the Pacific Northwest. ■ American Samoa faces local tsunami threats from earthquakes generated in the nearby Tonga Trench, as well as distant tsunami threats. ■ Guam and the Commonwealth of the Northern Mariana Islands are threatened by local tsunamis from the nearby Mariana Subduction Zone, as well as distant sources from around the Pacific Ocean Basin. ■ Puerto Rico and the United States Virgin Islands are threatened by multiple local and distant tsunami sources, such as the Puerto Rico Trench (PRT), given their location in the complex seismic region of the Caribbean Sea. Several historical events stand out because of their catastrophic impacts. ■ In the Pacific Northwest, the 1700 Cascadia earthquake caused a tsunami that affected coastal Native American communities, though the extent of the damage is not fully documented (Ludwin, et al., 2005). ■ In Puerto Rico, the 1918 earthquake triggered a tsunami that caused $77 million in damage in 2022 dollars and 116 fatalities, primarily along the western coast (Coffman et al., 1982). ■ The 1946 Aleutian Islands earthquake triggered a massive tsunami that devastated Hilo, Hawaii, killing 158 people and resulting in approximately $375 million in damage (adjusted to 2022 dollars) (Fisher et al., 2023). ■ The 1964 Alaska earthquake (M 9.2) generated tsunamis that caused severe destruction in some communities across Alaska, Oregon, and California. This disaster led to a total of 124 fatalities and approximately $2.9 billion in property damage (adjusted to 2022 dollars) (Brocher et al., 2014) (Alaska Science Center, 2024). ■ In American Samoa, a tsunami generated by the 2009 Samoa earthquake (Mw 8.1) caused widespread devastation, resulting in 34 confirmed fatalities (Apatu et al., 2013) and economic losses exceeding $160 million (adjusted to 2022 dollars) (DHS, 2011). More recent events, including the 2010 Chile earthquake, the 2011 Japan earthquake, and the 2022 Tonga volcanic eruption, resulted in millions of dollars in damage to numerous ports and harbors in the U.S. South Pacific territories, Hawaii, and along the west coast of the U.S. (Lynett, et al., 2022) (Wilson, et al., 2013). Since these events, the expansion of the built environment in lowlying areas along the coast has increased the exposure of buildings and people, thereby further escalating community risk from tsunamis. This report provides a comprehensive national assessment of earthquake-generated tsunami risk. It does not include impacts from tsunamis generated by landslides, volcanic eruptions, glacial calving, near-earth objects, weather, or other events. This study is based on the best available hazard data from the U.S. Pacific Coast (California, Oregon and Washington), Alaska, Hawaii, U.S. Pacific Territories (American Samoa, Guam and Commonwealth of the Northern Mariana Islands) and Caribbean Territories (Puerto Rico and United States Virgin Islands). Tsunami risks associated with states along the East Coast, Gulf Coast, and Great Lakes are not included in this study because Hazus 6.1 software (FEMA 2024a) does not currently include the ability to analyze tsunami risk in those states. Once modeling capabilities and tsunami hazard data become available for additional states, FEMA may incorporate these data into future editions of this study.

Alaska, California, Hawaii Oregon, Washington↗
USGS2026

PFAS mixture composition and internal exposure profiles shape biological responses under field-realistic exposure

Per- and polyfluoroalkyl substances (PFAS) occur as complex mixtures, yet mixture-dependent biological effects under environmentally realistic exposure conditions remain poorly understood. We conducted multiyear (2018, 2019, 2021) continuous-flow, field-based exposures of male fathead minnows ( Pimephales promelas ) using a low-PFAS reference well (REF; sum of measured PFAS (∑PFAS) 0.1–0.2 μg L –1 ) and PFAS-contaminated groundwater from a fire-training area (FTA) at Joint Base Cape Cod, Massachusetts. Dilution treatments enabled separation of concentration and mixture effects. Groundwater from well FTA1 was perfluorooctanesulfonate (PFOS) dominated (∑PFAS 10–31 μg L –1 ), whereas groundwater from well FTA2 had higher concentrations and was enriched in perfluorooctanoate (PFOA) and diverse precursors (∑PFAS ∼ 80 μg L –1 ). Despite comparable plasma ∑PFAS and PFOS in FTA1–100% and FTA2–50% on day-7, cumulative mortality reached approximately 35% in FTA2–50% and 17% in FTA2–100%, and secondary sex trait expression was reduced by approximately 65–80% relative to REF, whereas sperm motility effects were mixture- and time-dependent. Plasma PFAS profiles were dominated by perfluorohexanesulfonate (PFHxS), PFOS, and sulfonamide precursors. Liver transcriptomics from REF-acclimated fish revealed robust disruption of metabolic, mitochondrial, and endocrine pathways that link PFAS mixture chemistry and internal exposure profiles to organismal outcomes, and testis transcriptomics provided complementary insight into reproductive impairment. These results indicate that PFAS mixture composition and internal exposure profiles, including precursor-associated differences, are important determinants of ecotoxicological outcomes under field-realistic conditions.

Massachusetts↗
USGS2024

Developing international standards and guidelines for disseminating and validating simulated ground motions

We are leading an effort to develop international standards and guidelines for curating, disseminating, and validating simulated ground-motion data. This effort is organized as a working group within the Consortium of Organizations for Strong Motion Observation Systems (COSMOS). In 2022 we held online workshops on 7 and 8 June and 20 October. The first workshop focused on curating and disseminating simulated ground-motion data. The second workshop focused on validating simulated ground-motions for engineering applications. About 100 people participated in each of the workshops with strong representation from North America, Europe, and western Asia. In the coming year, we intend to form a technical committee to draft the international guidelines and standards while continuing to engage stakeholders from across the globe through online and in-person meetings. The key points from the workshops include: (1) Numerous groups are generating simulated earthquake ground motions and making them openly available; however there is very little coordination among groups to provide consistent interfaces for searching and retrieving data; (2) Standardizing interfaces for metadata and data access should consider agile approaches that can adapt to changing capabilities and user needs while building upon existing efforts; (3) A distributed architecture is preferred by most participants to allow institutions to host and manage their own data while broadcasting their holdings to a combined catalog; (4) Validation of ground-motion simulations applies to the entire workflow for simulating earthquake ground-motions, including the rupture model, seismic velocity model, and seismic wave propagation software; (5) Metrics to evaluate the validation are application dependent; more research is needed to tie structural response characteristics to ground-motion characteristics; and (6) Validation results should provide a clear, transparent, and quantitative assessment of the simulated ground motions.

Conference Paper↗
USGS2024

Will there be water? Climate change, housing needs, and future water demand in California

Climate change in California is expected to alter future water availability, impacting water supplies needed to support future housing growth and agriculture demand. In groundwater-dependent regions like California's Central Coast, new land-use related water demand and decreasing recharge is already stressing depleted groundwater basins. We developed a spatially explicit state-and-transition simulation model that integrates climate, land-use change, water demand, and groundwater gain-loss to examine the impact of future climate and land use change on groundwater balance and water demand in five counties along the Central Coast from 2010 to 2060. The model incorporated downscaled groundwater recharge projections based on a Warm/Wet and a Hot/Dry climate future from a spatially explicit hydrological process-based model. Two urbanization projections from a parcel-based, regional urban growth model representing 1) recent historical and 2) state-mandated housing growth projections were used as alternative spatial targets for future urban growth. Agricultural projections were based on recent historical trends from remote sensing data. Annual projected changes in groundwater balance were calculated as the difference between land-use related water demand, based on historical estimates, and climate-driven recharge plus agriculture return flows. Results indicate that future changes in climate-driven groundwater recharge, coupled with cumulative increases in agricultural water demand, result in overall declines in future groundwater balance, with a Hot/Dry future resulting in cumulative groundwater decline in all but Santa Cruz County. Cumulative declines by 2060 are especially prominent in San Luis Obispo (−2.9 to −5.1 Bm 3 ) and Monterey counties (−6.5 to −8.7 Bm 3 ), despite limited changes in agricultural water demand over the model period. These two counties show declining groundwater reserves in a Warm/Wet future as well, while San Benito and Santa Barbara County barely reach equilibrium. These results suggest future groundwater supplies may not be able to keep pace with regional demand and declining climate-driven recharge, resulting in a potential reduction in water security in the region. However, our county-scale projections showed new housing and associated water demand does not conflict with California's groundwater sustainability goals. Rather, future climate coupled with increasing agricultural groundwater demand may reduce water security in some counties, potentially limiting available groundwater supplies for new housing.

California↗
USGS2026

A practical framework for identifying genetic subpopulations and ESUs: Insights for IUCN assessments and broader management

Species conservation assessments evaluate extinction risk, and recovery potential, advancing species persistence through guiding resource prioritization and planning. Assessment frameworks, including the International Union for Conservation of Nature Red List and Green Status of Species, typically focus on species as a whole. Importantly, they do not routinely account for genetically distinct units or do not have standardized methods of unit delineation. This limits the representation of genetically distinct components, including adaptive genetic diversity that underpins long-term resilience and recovery. Incorporating standardized within-species units like subpopulations and Evolutionarily Significant Units (ESUs) into species assessments could help address this oversight. However, identifying and delineating such units remain challenging, particularly when molecular data are limited. Here, we propose a flexible framework that integrates molecular and non-molecular evidence to identify both subpopulations and ESUs across taxa, providing a practical tool to incorporate within-species diversity into conservation assessments.

BioScience↗
USGS2024

Following the tug of the audience from complex to simplified hazards maps at Cascade Range volcanoes

Volcano-hazard maps are broadly recognized as important tools for forecasting and managing volcanic crises and for disseminating spatial information to authorities and people at risk. As scientists, we might presume that hazards maps can be developed at the time and with the methods of our discretion, yet the co-production of maps with stakeholder groups, who have programmatic needs of their own, can sway the timing, usability, and acceptance of map products. We examine two volcano hazard map-making efforts by staff at the U.S. Geological Survey. During the 1990s and early 2000s scientists developed a series of hazard assessments and maps with detailed zonations for volcanoes in Washington and Oregon. In 2009, the National Park Service expressed the need for simplified versions of the existing hazard maps for a high-profile visitor center exhibit. This request created an opportunity for scientists to rethink the objectives, scope, content, and map representations of hazards. The primary focus of this article is a discussion of processes used by scientists to distill the most critical information within the official parent maps into a series of simplified maps using criteria specified. We contextualize this project with information about development of the parent maps, public response to the simplified hazard maps, the value of user engagement in mapmaking, and with reference to the abundance of guidance available to the next generation of hazard-mapmakers. We argue that simplified versions of maps should be developed in tandem with any hazard maps that contain technical complexities, not as a replacement, but as a mechanism to broaden awareness of hazards. We found that when scientists endeavor to design vivid and easy-to-understand maps, people in many professions find uses for them within their organization’s information products, resulting in extensive distribution.

Washington↗
USGS2024

Framework for mapping liquefaction hazard–Targeted design ground motions

Liquefaction-induced ground failure poses substantial challenges to geotechnical earthquake engineering design. Current approaches for designing against liquefaction hazards, as specified in most seismic provisions, focus on estimating a liquefaction factor of safety ( 𝐹⁢𝑆𝐿 ) and typically characterize earthquake loading using design parameters based on probabilistic or deterministic ground motion levels. Because 𝐹⁢𝑆𝐿 is estimated deterministically, this basis of design neglects considerable uncertainties for estimating liquefaction triggering and its consequences and results in a lack of liquefaction-specific design criteria, particularly as structural design has advanced toward risk-targeted performance objectives. This study presents a framework for developing liquefaction-targeted design criteria based on a minimum acceptable return period of liquefaction, informed by probabilistic liquefaction hazard analysis (PLHA). PLHA quantifies annualized rates of liquefaction by considering contributions from (1) the full ground-motion probability space, and (2) uncertainties in liquefaction triggering using probabilistic models. PLHA is used in this study to characterize the current, effective return periods of 𝐹⁢𝑆𝐿 ( 𝑇𝑅,𝐹⁢𝑆 ) obtained from conventional liquefaction hazard analysis (CLHA) using uniform-hazard ground motions. 𝑇𝑅,𝐹⁢𝑆 is evaluated in a parametric study of nearly 100 sites throughout the conterminous United States. The results indicate large geographic variations in acceptable liquefaction hazard levels, with implied 𝑇𝑅,𝐹⁢𝑆 ranging between approximately 1,000 to 3,000 years. To address these inconsistencies without the computational demands of full PLHA, a framework is proposed for developing a liquefaction-targeted design peak ground acceleration, 𝑃⁢𝐺⁢𝐴𝐿 , for use in liquefaction models that result in consistent liquefaction design levels across all geographic locations. The mapped 𝑃⁢𝐺⁢𝐴𝐿 is shown to be somewhat sensitive to site-specific properties, and adjustment factors are developed and presented. The proposed 𝑃⁢𝐺⁢𝐴𝐿 mapping procedure produces 𝐹⁢𝑆𝐿 estimates that are consistent with those obtained from full PLHA at a target 𝑇𝑅,𝐹⁢𝑆 , providing a promising roadmap to incorporating PLHA concepts into current liquefaction design methods.

Journal of Geotechnical and Geoenvironmental Engin↗
USGS2026

Monitoring changes in Landsat thermal features in urban and non-urban interfaces from 1986 to 2023 in two international urban centers: Implications for climate and global issues

Rapid urbanization is reshaping thermal environments worldwide, with the strongest impacts occurring at the interface between urban and non-urban areas. Impervious surfaces, as key indicators of urban expansion, are critical for monitoring urban growth and assessing surface urban heat island (SUHI) effects. Land use and land cover change (LULCC) provides an essential link between urban dynamics and their environmental and societal consequences. Here, we integrated the U.S. Geological Survey (USGS) Climate Global Issues (CGI) Land Cover Product with Landsat thermal time-series to investigate SUHI evolution in two contrasting metropolitan regions: Wuhan, China, and Brasília, Brazil. Using data spanning 1986–2023, we analyzed the relationships between land cover, Landsat-based land surface temperature (LST), and SUHI intensity, and identified persistent thermal hotspots. Results demonstrate that the land cover data utilized increases the accuracy of impervious surface mapping along urban–rural gradients. Average SUHI intensities were 3.4 °C in Wuhan and 3.3 °C in Brasília, with statistically significant warming trends of 0.04 °C/year and 0.01 °C/year, respectively. Maximum temperature proved to be a robust indicator of SUHI intensification, capturing long-term upward trends. Our findings highlight the important role of urban land cover dynamics in shaping temporal SUHI variability and hotspot emergence. This prototype framework demonstrates the scientific and policy value of combining long-term land cover monitoring information with satellite thermal monitoring to quantify and track SUHI at city scale, supporting sustainable urban planning and climate adaptation strategies.

Remote Sensing↗
USGS2026

Nonstationary demographic state-space models using unreplicated counts for species undergoing environmental stressors

A fundamental task in ecological statistics is to estimate abundance and growth rate distributions from wildlife monitoring data to inform conservation management. Modeling time series of wildlife populations presents a number of challenges from both statistical and ecological perspectives, including discreteness; lack of replication; nonstationarity; and observation, demographic, and other phenomenological processes. Nonstationary dynamics are often exhibited by populations undergoing environmental stressors. Models must account for these characteristics to produce reliable estimates of abundance and trends, yet estimation can be challenging with unreplicated data. We propose nonstationary demographic state-space models using unreplicated counts for populations undergoing environmental stressors. A reduced growth rate model matches the complexity of the unreplicated count data, and a fecundity bound on growth rate distributions allows the separation of processes affecting growth rates like environmental stressors from those affecting abundance external to growth rates like migration. NDSSMs allow for the embedding of nonstationary model components, and we explore the use of changepoints, volatility clustering, and migration processes. We apply the proposed nonstationary models in case studies of herons affected by predator/competitor reestablishment and three bat species affected by a fungal pathogen causing white-nose syndrome. Nonstationary models outperform stationary models and generalized linear mixed effects models according to model scoring and visual inspection of predictions, and provide estimates more consistent with published values. Incorporating migration improves model fit universally, even with approximate one-way immigration, most likely because populations are extirpated, recolonized, and increase multiple-fold over the upper bound set by species fecundity. In addition, estimates of the timing and severity of the environmental stressor differed for models with migration. Including nonstationary and demographic components in a fecundity-bounded growth rate model improves inference and benefits interpretability of hyperparameters. In turn, this adjusts uncertainties in predictions of abundance and growth rates over time, providing the ingredients needed for informed conservation analysis and for directing future monitoring of at-risk species.

Journal of Agricultural, Biological and Environmen↗
USGS2026

Groundwater quality near an oil field in a stream-dominated recharge setting, California, USA

Alluvial valley aquifers are important sources of water supply in many areas but effects of co-located oil and gas development on these resources have not been widely reported, especially in settings where recharge is dominated by stream infiltration. Interpreting the presence of geochemical indicators in the context of hydrology, geology, and other factors provides a more complete understanding of the relations between groundwater and sources of oil-field fluids and aids in identifying risks associated with oil and gas development. Groundwater and Salinas River water samples were collected in an alluvial valley near the San Ardo Oil Field in Monterey County, California and analyzed for a wide range of dissolved chemical, gas, and isotopic constituents to determine if oil-field fluids (water and gas from oil-producing and non-producing zones) have mixed with fresh groundwater used for supply. Hydraulic gradients, age-dating tracers, and other geochemical indicators show that recharge from the Salinas River has the potential to dilute oil-field fluids that might migrate or seep into the aquifer. Groundwater and Salinas River water collected downgradient of the San Ardo Oil Field showed little or no evidence of mixing with oil-field fluids. Some samples within the oil field contained trace amounts of hydrocarbons or elevated temperatures, indicating that any potential effects from oil-field activities are minor or have been diluted by recharge from the Salinas River. The two samples with the most geochemical evidence of potential mixing with oil-field fluids (SP-18 and GW-17) were collected west of or along the Los Lobos fault, where naturally occurring hydrocarbons are near the land surface. Those samples are also near active or inactive oil-field wells, and so anthropogenic activities and pathways cannot be ruled out as a cause of trace detections of hydrocarbons and elevated temperatures in the aquifer.

California↗
USGS2026

Open-source gravity reduction workflows for geothermal resource assessment

Potential-field geophysical data such as gravity can enhance understanding of geothermal resources at all stages of the resource life cycle, including assessment, exploration, development, and monitoring, and at multiple scales, from the reservoir scale to regional scale. However, to make gravity data useful for geothermal resource characterization, several processing steps are required to isolate the effects of density variations in the Earth’s crust to enable the identification of structural features associated with geothermal resources. Although this process is well-established, standard computational implementations for processing gravity data that are FAIR (Findable, Accessible, Interoperable, and Reproduceable) are still lacking. This paper details ongoing efforts at the U.S. Geological Survey (USGS) to develop a standard set of open-source Python tools for gravity data reduction that align with the FAIR principles. This workflow makes use of existing open-source tools for geophysical data processing with the goal of maximizing opportunities for rapid improvements, interoperability, and adaptability to other types of geophysical data.

Conference Paper↗
USGS2024

Declining groundwater storage expected to amplify mountain streamflow reductions in a warmer world

Groundwater interactions with mountain streams are often simplified in model projections, potentially leading to inaccurate estimates of streamflow response to climate change. Here, using a high-resolution, integrated hydrological model extending 400 m into the subsurface, we find groundwater an important and stable source of historical streamflow in a mountainous watershed of the Colorado River. In a warmer climate, increased forest water use is predicted to reduce groundwater recharge resulting in groundwater storage loss. Losses are expected to be most severe during dry years and cannot recover to historical levels even during simulated wet periods. Groundwater depletion substantially reduces annual streamflow with intermittent conditions predicted when precipitation is low. Expanding results across the region suggests groundwater declines will be highest in the Colorado Headwater and Gunnison basins. Our research highlights the tight coupling of vegetation and groundwater dynamics and that excluding explicit groundwater response to warming may underestimate future reductions in mountain streamflow.

Nature Water↗
USGS2025

The feasibility of using lidar-derived digital elevation models for gravity data reduction

Gravity data require submeter elevation accuracy for data processing, and differential global navigation satellite system (dGNSS) equipment is commonly used to acquire three-dimensional positional data to achieve such accuracy. However, lidar (light detection and ranging) data are commonly used to develop digital elevation models (DEMs) of Earth’s surface. Therefore, using elevations from lidar-derived DEMs for gravity-data acquisition and reduction may improve field efficiency and reduce cost. This study examines the feasibility of using DEMs for gravity-data reduction by comparing dGNSS elevation data from 435 gravity stations in Michigan, Wyoming, and Colorado with their respective DEM elevations. The results show that the average difference between DEM and dGNSS elevations is 13 centimeters (cm) and that 93 percent of those differences are less than 50 cm, even in areas with steep terrain. Because an elevation discrepancy of 50 cm corresponds to an error of roughly 0.1 milligals (mGal) in the simple Bouguer gravity anomaly, the results suggest that lidar-derived DEMs are a viable source for acquiring the elevation data needed to process gravity data, thus improving both the cost and efficiency of data collection for regional surveys where an accuracy of less than 1.0 mGal is desired.

Open-File Report↗
USGS2026

Development of liquefaction-targeted design basis in U.S. seismic provisions

Seismic design criteria for new buildings in the United States have historically focused on life safety performance objectives through minimizing the potential for structural collapse. Development of design criteria to meet this performance objective has evolved over time, leading to the current, risk-targeted maximum considered earthquake (MCE R ) design basis. Corresponding MCE R seismic design loads incorporate the full range of probabilistic ground motion hazard information available from U.S. Geological Survey National Seismic Hazard Models, as well as a representation of the uncertainty in structural collapse capacity. Despite these considerable advances in structural design criteria, guidelines for geotechnical hazards such as liquefaction-induced damage, which continue to be based on uniform ground-shaking hazard (i.e., MCE ground motions), are not well-connected with risk-based, collapse prevention performance objectives. This study, undertaken as part of Building Seismic Safety Council efforts to update recommended seismic provisions through the National Earthquake Hazards Reduction Program, presents probabilistic, liquefaction-targeted design objectives and corresponding ground motion parameters, with a focus on improving consistency in first-level screening criteria for liquefaction hazard assessment. This study identifies a potential maximum acceptable annualized probability of liquefaction triggering ( P L,max ) of 2.5% in 50 years, above which liquefaction consequences and potential mitigation measures would be considered. The P L,max -based design basis is calibrated to effective probabilistic liquefaction hazard levels obtained in practice using current MCE peak ground accelerations, and could be implemented via a new liquefaction-targeted maximum considered earthquake (MCE L ) peak ground acceleration ( PGA L ). The proposed PGA L is derived from probabilistic liquefaction hazard curves and includes uncertainties inherent to liquefaction hazard modeling. The potential design effects of the proposed PGA L are demonstrated via comparison with current MCE PGA levels, effects on first-level liquefaction screening analyses, and improvements in the consistency of P L,max levels across the United States, and for a wide range of site conditions.

conterminous United States↗
USGS2025

Leveraging wildfire to augment forest management and amplify forest resilience

Successive catastrophic wildfire seasons in western North America have escalated the urgency around reducing fire risk to communities and ecosystems. In historically frequent-fire forests, fuel buildup as a result of fire exclusion is contributing to increased fire severity. The probability of high-severity fire can be reduced by active forest management that reduces fuels, prompting federal and state agencies to commit significant resources to increase the pace and scale of fuel reduction treatments. However, lower severity areas of wildfires also have the potential to act as “treatments,” and even catastrophic fires with large areas of high severity can still have substantial areas of lower severity fire that may be improving forest conditions locally. We quantified active management and wildfire severity across yellow pine and mixed conifer (YPMC) forests in the Sierra Nevada of California over a 22-year period (2001–2022). We did not detect increases in the area treated through time, but the area of beneficial wildfire (low to moderate severity) increased substantially, exceeding active treatment area in 8 of 22 years. Overall, beneficial wildfire treated ~17% more area than all treatments combined, and roughly four times more area than fire-related treatments alone. We then used disturbance history to evaluate resistance to high-severity wildfire and forest loss across the YPMC range. Of the 2.3 million ha YPMC of forests in 2001, 20% lost mature forests due to high-severity fire by 2022, which is nearly half of all YPMC area burned. Most of the landscape (47%) remains at risk of high-severity fire because it had no restorative disturbances, but 33% of the study area has some level of resistance to high-severity wildfire. In these areas, resistance will need to be enhanced and maintained over time via active management or managed wildfire, but these treatment needs will likely outpace capacity even under optimistic implementation scenarios. Given limited resources for implementing active management and the likelihood of a more fiery future, incorporating beneficial wildfire into landscape-level treatment planning has the potential to amplify the impact of active management treatments.

California, Nevada↗
USGS2026

HyFlood: A surrogate-model-based framework for compound coastal flooding

Compound coastal flooding is a major threat to low-lying coastal regions and is expected to intensify under future climate change projections. However, modeling the joint interaction of waves, storm surge, tides, and rainfall remains computationally demanding, limiting the development of fast and reliable forecast tools. Here we present HyFlood, a hybrid statistical-numerical downscaling framework capable of computing and mapping high-resolution compound flood hazards while substantially reducing the computational cost compared with fully process-based hydrodynamic modeling. HyFlood combines statistical sampling and selection algorithms with a cascade of reduced-complexity surrogate models that emulate nearshore wave transformation, surf-zone hydrodynamics, and coastal, fluvial, and pluvial flooding. The surrogate models employ machine-learning and regression algorithms applied to a low-dimensional representation of the flooding outputs, obtained through statistical dimensionality reduction. The framework is demonstrated in southern O'ahu, Hawai'i, a region exposed to elevated sea levels driven by tides, waves, and storm surge along with frequent precipitation-driven flash flooding. Validation of the surrogates against the physics-based model outputs demonstrates that HyFlood accurately reproduces daily maxima of spatially distributed flooding depths. This hybrid approach offers a scalable and efficient tool to better quantify how changes in flooding drivers translate into hazard and impact assessments, and to support compound-flood risk assessments and climate-change adaptation planning.

Hawaii↗