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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↗
USGS2025

Manipulation of the Symbiodiniaceae microbiome confers multigenerational impacts on symbioses and reproductive ecology of its Exaiptasia diaphana host

Symbiodiniaceae-associated microbiota strongly influence cnidarian symbioses. We systematically reduced the bacterial and fungal communities associated with Symbiodiniaceae to study potential effects on the cnidarian holobiont Exaiptasia diaphana (Aiptasia). Clonal anemones were inoculated with xenic Breviolum minutum (SSB01) and microbiome-manipulated cultures after antibacterial or antifungal treatment. The asexual reproduction of pedal laceration allowed for three generations of clonal aposymbiotic Aiptasia to be utilised in this study, from the initial adult generation (G0), to the first (G1), and second (G2) generation. We inoculated small and large G1 Aiptasia with SSB01 algae and monitored onset of symbiosis, rate of algal proliferation, and holobiont characteristics. Sequencing the 16S and 18S rRNA gene regions identified significant differences in the bacterial and fungal communities of the G0 and G1 generations, alongside differences between the size classes of small and large G1 anemones. The microbiome of larger G1 individuals was distinct to the smaller G1 anemones, suggesting a microbiome maturation process. Control Breviolum minutum cultures exhibited a significantly greater proliferation rate in large G1 anemones when compared to antibacterial or antifungal treated cultures, whereas the opposite trend was documented in the small G1 anemones. Although no differences were observed between algal photochemical parameters, or the growth and polyp activity of G1 juveniles, we observed a significant influence in the production of G2 clones between treatments. Overall, we provide strong ecological implications of manipulating Symbiodiniaceae microbiome, not for the algae themselves, but for the maturation of the host Aiptasia, as well as for the cnidarian holobiont over multiple generations.

The ISME Journal↗
USGS2025

Using the D-Claw software package to model lahars in the Middle Fork Nooksack River drainage and beyond, Mount Baker, Washington

Lahars, or volcanic mudflows, are the most hazardous eruption-related phenomena that will affect communities living along rivers that originate on Mount Baker. In the past 15,000 years, the largest lahars from Mount Baker have affected the Middle Fork Nooksack River drainage and beyond. Here we use the physics-based D-Claw software package to model nine lahar scenarios that are initiated as water-saturated landslides between Sherman Crater and the Roman Wall on the Mount Baker edifice and flow down the Middle Fork Nooksack River. The scenarios range in volume from 1 to 260 million cubic meters and have an initial hydraulic permeability from 10 −12 to 10 −10 meters squared. Model output includes data such as flow depth, velocity, runout distance, area inundated, arrival time, and sediment concentration as well as information that allows scientists to calculate other important hydrologic characteristics such as lahar discharge. These data are important to officials who have the responsibility to plan for, or take mitigation measures against, future Mount Baker lahars. To check the validity of the D-Claw results, we compare the scenarios to known geologic information. We also compare D-Claw results with empirical models that have been used in the past to determine potential inundation areas, runout distances, and arrival times. These comparisons highlight similarities and differences between empirical and physics-based models. We also present D-Claw scenario-based animations to help scientists, officials, and lay people alike to visualize how future lahars could affect communities.

Washington↗
USGS2025

Spatiotemporal variability of algal biomass and nitrate in Owasco and Seneca Lakes in the Finger Lakes Region, New York, in 2019

Cyanobacterial harmful algal blooms (CyanoHABs) have become increasingly common, threatening the security of water resources globally. The U.S. Geological Survey conducted high-resolution nearshore mapping surveys using boat-mounted multiparameter sondes and nitrate sensors during the summer and fall of 2019 on Owasco Lake and Seneca Lake, two lakes with documented CyanoHABs in the Finger Lakes region of New York State. Discrete sensor measurements and water-quality samples were collected at fixed points along survey routes and continuous data were generated at open-water monitoring platforms. This investigation examined whether water-quality information from nearshore surveys was representative of open-water conditions and if nearshore surveys could be used to identify areas with localized nearshore CyanoHABs and potential sources of nutrients not captured by tributary sampling. In addition to comparisons across methods, nearshore concentrations of nitrate and chlorophyll were evaluated relative to tributary outlets, cyanobacterial abundance and biovolume at discrete locations, and the locations of near-surface CyanoHABs that were designated as “confirmed with high toxins” by the New York State Department of Environmental Conservation. Nitrate and chlorophyll concentrations were comparable across methods for each lake, although concentration ranges were typically higher for nearshore mapping datasets than for nearshore discrete datasets. Nearshore surveys indicated areas of nitrate enrichment that varied temporally in both lakes. Orthophosphate was not routinely detected. Across methods, median chlorophyll concentrations were higher for the summer survey than for the fall survey in Owasco Lake. Nearshore chlorophyll concentrations varied more temporally in Owasco Lake than in Seneca Lake. Phytoplankton and cyanobacterial abundance and biovolume were about five times higher in Owasco Lake than in Seneca Lake. Cyanobacteria dominated the phytoplankton community in most samples, and Microcystis comprised the bulk of the cyanobacterial biovolume. The most abundant potential cyanotoxin-producing (specifically microcystins) genera were Microcystis , Synechococcus , Aphanocapsa , and Pseudanabaena . The cyanobacterial community composition was comparable between open-water monitoring platforms and nearshore samples. Microcystins were detected in seven survey samples from Owasco Lake, in one survey sample from Seneca Lake, and in one sample each from the open-water monitoring platforms on Owasco and Seneca Lakes that were collected about 7 days before the fall surveys. Microcystin detections were not consistently associated with high cyanobacterial cell counts or cyanotoxin-producing genera. Results from nearshore surveys were comparable to open-water monitoring platforms and discrete nearshore observations in the absence of nearshore or open-water CyanoHABs in these systems during the study. Patterns of nearshore concentrations of nitrate and chlorophyll from nearshore surveys may aid in the identification of areas with localized nitrate loading and shifts in phytoplankton abundance and community composition.

New York↗
USGS2026

The damability function: A probabilistic approach to regional landslide dam susceptibility analysis applied to the Oregon Coast Range, USA

Landslides can dam rivers and require rapid response to mitigate catastrophic outburst floods. Here, we present a workflow to map landslide dam formation susceptibility at a regional scale. We define a probabilistic function that combines river valley width and landslide volume to efficiently determine the likelihood of a landslide dam or “damability”. We combine damability values with landslide susceptibility to estimate landslide dam susceptibility. The valley width measurements are automated using a new elevation threshold-based algorithm. Landslide volume is represented as a statistical distribution from mapped landslides. We validate and apply our approach to the Oregon Coast Range, USA and find that 36 % of river stretches exceed a dam potential threshold; these are in river headwaters and steeper terrain, which in this case correlate with more resistant lithologies. We also estimate volumes of the potential dammed lakes and find that most rivers with high dam susceptibility are less likely to impound large lakes because they have low drainage areas. However, widespread susceptibility, and the potential impacts from exceptionally large landslides, suggest that this hazard should be considered in the Pacific Northwest. The damability function workflow can ingest new data and be applied more broadly to assess future landslide dam hazards.

Oregon↗
USGS2026

Biome-scale spatial patterns of avian abundance reveal proactive conservation opportunities in North American grasslands

North American grassland birds have experienced steeper population declines than any other avian guild, yet conservation efforts remain largely reactive and fragmented. We used nearly four decades of North American Breeding Bird Survey data to identify biome-scale spatial patterns (clustering) of grassland bird abundance for the Great Plains. Our results reveal an ecological core in the north-central Plains where community-level abundance is either increasing by >100% or remains high and stable, providing a strategic roadmap for a “Defend the Core” conservation approach. This approach flips the script from reactive triage centered on isolated population fragments to a proactive strategy of maintaining large-scale ecosystem integrity. Conversely, we found that population losses are more spatially clustered than wins, reflecting the relentless, one-way movement of woody encroachment and agricultural conversion. This asymmetry supports prioritizing intact landscapes, as current restoration rates are often outpaced by the scale of habitat loss. Notably, we found that community-level spatial clustering is a more robust indicator of biome condition than trends of individual flagship species, suggesting that managing for ecosystem integrity provides a more effective multi-species umbrella. Given our results, there is an opportunity for operationalizing a Great Plains Conservation Design that is ecosystem-centric and rooted in the sustainability of the private-land cattle production that maintains these open spaces. By leveraging avian abundance as a biological sensor, managers and producers can deploy a shared vision that matches the spatial scale of the threats, moving from reactive triage to proactive defense of core working grasslands in North America.

Great Plains biome↗
USGS2025

Factors influencing landslide occurrence in low-relief formerly glaciated landscapes: Landslide inventory and susceptibility analysis in Minnesota, USA

In landscapes recently impacted by continental glaciation, landslides may occur where topographic relief has been generated by the drainage of glacial lakes and ensuing post-glacial fluvial network development into unconsolidated glacially derived sediments and exhumed bedrock. To investigate linkages among environmental variables, post-glacial landscape development, and landslides, we created a landslide inventory of nearly 10,000 landslides in five regions of the formerly glaciated low-relief state of Minnesota, USA. Multivariate logistic regression indicates the importance of slope angle, lithology, and the development of stream valleys to landslide distribution. Areas underlain by fine-grained glaciolacustrine and nearshore deposits that are incised by streams are particularly prone to shallow (<1-2 m depth) landslides. Landslides also occur in a wide range of glacial and fluvial deposits, and as rockfall in layered Paleozoic sedimentary rocks in central and southern Minnesota and Precambrian igneous and sedimentary rocks in northeastern Minnesota. Although no more than 1-2% of the studied regions are susceptible to landslides, they can pose risk to life and safety, damage infrastructure, and impact water quality. The combination of recently generated low-relief steep slopes, extensive unconsolidated sediments, and layered sedimentary bedrock make this formerly glaciated landscape more susceptible to landslides than current national-scale models indicate.

Minnesota↗
USGS2026

An improved empirical model for predicting postfire debris-flow volume in the western United States

Reliable estimates of debris-flow volume can be used to help predict the magnitude of debris-flow hazards following wildfire in the western United States. In this study, we compiled and used a database of 227 postfire debris-flow volumes that were collected across the western United States to develop a multiple linear regression model for predicting postfire debris-flow volume. We explored 36 predictor variables related to rainfall, terrain, and fire characteristics, and selected the model with the combination of variables that yielded the most accurate predictions of debris-flow volume. We evaluated model performance against the entire volume database, as well as against four subsets of volume data from southern California, the Intermountain West, the Southwest, and regions with limited volume data, such as northern California and Washington. We also compared model performance against 3 existing postfire debris-flow volume models that were developed for use in southern California, the Intermountain West, and the Southwest. We demonstrate that the new volume model performs as well as the regional models in the regions for which they were developed and outperforms existing models when applied to volumes from data-limited regions in the western United States. These results indicate that the debris-flow volume model introduced in this study can be used to improve postfire hazard assessments across the western United States, especially outside of southern California.

Arizona, California, Colorado, New Mexico, Utah, W↗
USGS2026

Seasonal and hydrologic variation influences habitat and functional structure of stream fish assemblages

Introduction: Hydrologic variability is a key driver of ecological structure in lotic systems, shaping habitat conditions, taxonomic diversity, and the functional traits that mediate species’ persistence and performance (e.g., reproductive success). While many studies examine taxonomic responses to variation in flows, few evaluate how spatiotemporal hydrologic variation influences the functional organization within stream fish communities. Methods: We quantified seasonal habitat structure and functional trait diversity of fish assemblages across six Ozark Plateau headwater streams representing two contrasting flow regimes: Groundwater Flashy and Runoff/Intermittent Flashy. Fish and habitat data were collected seasonally during a dry year (2002) and a wet year (2003). Functional space was constructed using PCoA of morphological, ecological, and life-history traits, and functional diversity was measured using community weighted means (CWMs), functional richness (FRic), functional evenness (FEve), and functional divergence (FDiv). Results: We found that habitat structure differed strongly by flow regime and season, with Runoff/Intermittent streams exhibiting pronounced reductions in depth, area, and velocity, while groundwater streams remained structurally stable. Functional identity of assemblages was similar across flow regimes, dominated by benthic, hydrodynamic taxa with opportunistic and periodic life-history strategies. However, functional structure differed significantly: FEve and FDiv were consistently lower in Runoff/Intermittent Flashy streams in both years, indicating assemblage dominance of species with similar trait combinations and reduced trait partitioning under variable flow. FRic and taxonomic richness remained stable across seasons and flow regimes, suggesting high functional redundancy despite species turnover. Discussion: Together, results show that flow regime mediates both habitat structural stability and functional organization. As climatic warming and extreme drought increase hydrologic instability in headwaters, functional trait approaches provide a sensitive tool for detecting losses of functional roles that may not be evident by using taxonomic metrics alone.

Arkansas, Kansas, Missouri, Oklahoma↗
USGS2025

Characterizing the scale of regional landslide triggering from storm hydrometeorology

Rainfall strongly affects landslide triggering; however, understanding how storm characteristics relate to the severity of landslides at the regional scale has thus far remained unclear, despite the societal benefits that would result from defining this relationship. As mapped landslide inventories typically cover a small region relative to a storm system, here we develop a dimensionless index for landslide-inducing rainfall, A * , based on extremes of modeled soil water relative to its local climatology. We calibrate A * using four landslide inventories, comprising over 11 000 individual landslides over four unique storm events, and find that a common threshold can be applied to estimate regional shallow-landslide-triggering potential across diverse climatic regimes in California (USA). We then use the spatial distribution of A * , along with topography, to calculate the landslide potential area (LPA) for nine landslide-inducing storm events over the past 20 years, and we test whether atmospheric metrics describing the strength of landfalling storms, such as integrated water vapor transport, correlate with the magnitude of hazardous landslide-inducing rainfall. We find that although the events with the largest LPA do occur during exceptional atmospheric river (AR) storms, the strength of landfalling atmospheric rivers does not scale neatly with landslide potential area, and even exceptionally strong ARs may yield minimal landslide impacts. Other factors, such as antecedent soil moisture driven by storm frequency and mesoscale precipitation features within storms, are instead more likely to dictate the patterns of landslide-generating rainfall throughout the state.

California↗
USGS2026

Deep subsurface organic-rich shale supports abundant, diverse, and novel fungi

As Earth’s principal reservoir of organic carbon and microbial biomass, the deep subsurface hosts microorganisms capable of mobilizing this once-sequestered carbon. Contrary to standard assumptions of eukaryotic scarcity, this study documents abundant fungal communities, ranging from 4.2 × 10 3 to 6.8 × 10 3 fungal cells mL −1 , across a methane-producing organic-rich shale 247–556 meters below the surface. Although fungal:bacterial cell ratios ranged from 1:7028 to 1:713, application of biomass conversion factors developed for oceanic systems yielded a median fungal:bacterial biomass ratio of 1:4.7. 16S rRNA gene amplicons revealed bacterial and archaeal communities mirroring those found in well-characterized extremophilic, carbon-degrading environments, while sequencing of 18S rRNA gene and ITS rRNA spacer amplicons collectively identified a eukaryotic hotspot with 689 fungal OTUs across six phyla. The dominant fungal classes, Agaricomycetes and Dothideomycetes, are well-established degraders of recalcitrant carbon compounds at the surface, suggesting they may similarly contribute to organic matter degradation and ecosystem maintenance in the subsurface. Cultivation and isolation efforts yielded 205 fungal strains, including 13 candidate novel taxa, underscoring the deep subsurface as an underexplored eukaryotic habitat. Stable carbon isotopes indicate methane is predominantly generated via microbial conversion of the fossil carbon, while water isotopes suggest in situ geochemical conditions have been relatively stable since the Late Pleistocene, with subglacial recharge as a plausible mechanism for microbial introduction. Collectively, these findings suggest that fungi are underrecognized contributors to organic matter transformation and functional diversity in the deep biosphere, revealing a critical gap in our understanding of deep subsurface ecosystem processes.

Indiana, Michigan, Ohio↗
USGS2026

Hazard potential of compound flooding from rainfall, storm surge, and groundwater in coastal New York and Connecticut

Compound flood events, the co-occurrence of multiple flood drivers, can result in flood hazard potential exceeding that of any single driver alone. To evaluate compound flooding in a semi-urbanized coastal area, historical records dating back to 1970 are used to study the co-occurrences of high precipitation, storm surge, and shallow groundwater conditions along the coastlines of New York and Connecticut. Joint return periods for coincident precipitation-surge events were computed using statistical dependence models and compared to the assumption of independence as a ratio, referred to here as a return period adjustment. Results indicate distinct seasonality where compound events in the area disproportionately occur in the cold season between October and April. Return period adjustments range from a factor of 1 to almost 9, demonstrating the range in precipitation-storm surge dependence across the study area. Across all 24 station triad locations, groundwater levels were elevated during times of precipitation- surge co-occurrence, reflecting the tendency for coastal storms and shallow groundwater conditions to co-occur seasonally. The result is a pseudo-trivariate compound flood hazard score and corresponding hazard map that integrates dependence between daily precipitation-surge events and overall monthly groundwater levels (as a precondition) into a relative compound hazard score. The location with the highest compound flood hazard score is on the south shore of Long Island, as well as locations across coastal Connecticut where groundwater levels compound the co-occurrence of heavy precipitation and storm surge.

Connecticut, New York↗
USGS2025

Increased flood exposure in the Pacific Northwest following earthquake-driven subsidence and sea-level rise

Climate-driven sea-level rise is increasing the frequency of coastal flooding worldwide, exacerbated locally by factors like land subsidence from groundwater and resource extraction. However, a process rarely considered in future sea-level rise scenarios is sudden (over minutes) land subsidence associated with great (>M8) earthquakes, which can exceed 1 m. Along the Washington, Oregon, and northern California coasts, the next great Cascadia subduction zone earthquake could cause up to 2 m of sudden coastal subsidence, dramatically raising sea level, expanding floodplains, and increasing the flood risk to local communities. Here, we quantify the potential expansion of the 1% floodplain (i.e., the area with an annual flood risk of 1%) under low (~0.5 m), medium (~1 m), and high (~2 m) earthquake-driven subsidence scenarios at 24 Cascadia estuaries. If a great earthquake occurred today, floodplains could expand by 90 km 2 (low), 160 km 2 (medium), or 300 km 2 (high subsidence), more than doubling the flooding exposure of residents, structures, and roads under the high subsidence scenario. By 2100, when climate-driven sea-level rise will compound the hazard, a great earthquake could expand floodplains by 170 km 2 (low), 240 km 2 (medium), or 370 km 2 (high subsidence), more than tripling the flooding exposure of residents, structures, and roads under the high subsidence scenario compared to the 2023 floodplain. Our findings can support decision-makers and coastal communities along the Cascadia subduction zone as they prepare for compound hazards from the earthquake cycle and climate-driven sea-level rise and provide critical insights for tectonically active coastlines globally.

California, Oregon, Washington↗
USGS2024

U.S. Geological Survey Earthquake Hazards Program decadal science strategy, 2024–33

Executive Summary Earthquakes represent one of our Nation’s most significant and costly natural hazards, with estimated annual loses from earthquakes close to $15 billion in 2023. Over the past two centuries, 37 U.S. States have experienced an earthquake exceeding a magnitude of 5, and 50 percent of States have a significant potential for future damaging shaking; these statistics speak to the need for nationwide interest and investment in earthquake hazard characterization and risk reduction. Authorized under the Earthquake Hazards Reduction Authorization Act, the U.S. Geological Survey (USGS) Earthquake Hazards Program (EHP) provides the scientific information, situational awareness, and knowledge necessary to reduce deaths, injuries, and economic losses from earthquakes and earthquake-induced tsunamis, landslides, and soil liquefaction. The EHP supports activities in three focused topical areas: (1) earthquake monitoring, (2) hazard assessment, and (3) applied research, using the results of each—and the coordination among them—to further support risk translation and communication in regions at risk nationwide. For earthquake monitoring, the Advanced National Seismic System (ANSS), a cooperative effort of USGS networks, university partner regional seismic networks, and real-time geodetic networks, collects and analyzes data on earthquakes; issues timely, reliable notifications of their occurrence and impacts; and provides data for earthquake research, hazard, and risk assessment as a foundation for building an earthquake-resilient Nation. The USGS-operated ShakeAlert Earthquake Early Warning system is a recent addition to EHP’s ANSS infrastructure. In the realm of earthquake hazard assessment, the EHP contributes to earthquake risk mitigation strategies by developing the National Seismic Hazard Model and maps, and other related products, that describe the likelihood and potential effects of earthquakes nationwide, especially in the urban areas of highest risk. The EHP also conducts research on the causes, characteristics, and effects of earthquakes and prioritizes work that directly increases the accuracy and precision of earthquake hazards assessments, earthquake forecasts, and earthquake monitoring and situational-awareness products and that supports the Nation’s earthquake mitigation practices. Bridging the EHP’s efforts across research, hazard assessments, and earthquake monitoring is a broad and comprehensive collection of earthquake information products, including the National Seismic Hazard Model, ShakeAlert, and other products describing impact, such as ShakeMap and PAGER (Prompt Assessment of Global Earthquakes for Response), which have been developed and integrated into EHP’s real-time monitoring systems. EHP funds external partners to carry out many important collaborative activities through an active external grants program—one of the largest in the USGS—and through cooperative agreements with other partners such as the university-operated regional seismic networks, funded as part of the ANSS. To continue its support of earthquake hazard characterization and risk reduction, the EHP aims to strengthen its foundational products and practices while positioning itself to respond to the evolving needs of the Nation and follow best practices of the scientific community. This document describes a strategy for the program to ensure it can meet these demands. The foundational priorities outlined in this strategy represent those activities that remain critical to the core functionality of the program and those that can be supported under current fiscal year 2024-level appropriations. Priorities described as aspirational are important for future growth, and to maintain the program’s position as a leading global resource in earthquake science, but would require increases in appropriated funding to be fully realized. Across the program’s portfolio of activities, several major themes have been identified as the most critical activities to advance EHP science over the coming decade. Together, these activities provide the framework necessary to integrate critical hazard characterization and risk reduction activities across the program. They provide the structure for research to advance the understanding of where, when, and why earthquakes occur and how we can use improved knowledge to drive short-term and actionable forecasts of seismic activity. They expand the usefulness of critical earthquake products and advance the sophistication of those products to keep pace with the rapidly evolving needs of an ever-expanding user base while maintaining the position of the USGS as a global leader in earthquake science. Focus on system-level science. Establish an automated earthquake-processing pipeline. Enhance the accuracy and reliability of the ShakeAlert Earthquake Early Warning system and plan for extension to other regions. Implement time-dependent earthquake forecasting. Develop physically realistic models. Expand computational capacity. This science strategy is organized into three primary sections. The first section provides an overview of the EHP and its budget, governance, and program council. Readers familiar with the program may wish to focus on the second section, which describes the core of the science strategy, including priorities across each of the EHP’s major program activities in monitoring, hazard assessment, and targeted research. The third section outlines science priorities that cut across program activities, including those involving collaborations external to the EHP.

American Samoa, Guam, Northern Marianas Islands, U↗
USGS2012

Development of vegetation based soil quality indices for mineralized terrane in arid and semi-arid regions

Soil quality indices (SQIs) are often management driven and attempt to describe key relationships between above- and below-ground parameters. In terrestrial systems, indices that were initially developed and modified for agroecosystems have been applied to non-agricultural systems in increasing number. We develop an SQI in arid and semi-arid ecosystems of the Western US impacted by different types of geologic mineralization using the relationship between vegetation community parameters and soil abiotic and biotic properties. We analyze these relations in soils associated with three different mineralization types: podiform chromite, Cu/Mo porphyry, and acid-sulfate gold vein systems at four different sites in California and Nevada. Soil samples were collected from undisturbed soils in both mineralized and nearby unmineralized substrates as well as from waste rock and tailings. Aboveground net primary productivity (ANPP), canopy cover and shrub density were measured for the vegetative communities. Minimum data sets were developed based on correlations between the soil and vegetation parameters, refined using principal components analysis, scored using non-linear functions, and combined into an overall SQI. The indices are comprised of one or two microbial parameters and three to six abiotic parameters, the latter consisting of nutrients and metals. Given the preliminary development of this approach, the parameters and combinations to arrive at an SQI for a given site cannot at this time be correlated or compared with that of another site. This SQI approach provides a means of quantifying disturbed ecosystem recovery resulting from mining, and could be applied to other disturbances in a way that readily distills the information for potential use by land managers. However, severely disturbed areas with little to no aboveground biomass, such as unreclaimed tailings, have likely crossed an ecological threshold that precludes the use of this type of monitoring tool.

California↗
USGS2025

The National Map Corps—Federal Emergency Management Agency and Oak Ridge National Laboratory pilot project report

This report provides an overview of the U.S. Geological Survey National Map Corps —Federal Emergency Management Agency and Oak Ridge National Laboratory pilot project in St. James Parish, Louisiana, that began in February 2024 and ended at the end of March 2024. The project used the power of The National Map Corps’ volunteer community to improve building classifications in the original Federal Emergency Management Agency’s U.S.A. Structures dataset. The report highlights the project’s completion and details the work and results achieved through a collaborative effort to enhance geospatial data quality and utility.

Open-File Report↗
USGS2025

USGS—An Unparalleled Scientific Asset

The U.S. Geological Survey (USGS) delivers information critical to powering our economy, managing our natural resources, and keeping Americans safe and healthy. 1 Mapping the Nation $21B Geologic maps save users an estimated 15% in annual costs: a value of between $14B and $21B. $25.6B in annual value to users of imagery from Landsat satellites, which were codeveloped by NASA and the USGS and operated through their lifespans by the USGS. $13.5B in annual benefits is generated by the USGS's 3D Elevation Program. Securing America’s Energy Independence 44% USGS-identified undiscovered geothermal energy is equal to 44% of current U.S. electricity generation. 29.4B barrels of oil and 391.6 trillion cubic feet of gas in recoverable resources are available on U.S. public lands based on USGS assessments. Protecting Americans’ Health and Safety $424B in recent wildland fire damages highlight the need for USGS fire science, which supports efforts to protect communities and reduce risk. USGS earthquake, volcano, landslide, and coastal hazard monitoring and information save lives and minimize costs; for example, $2.8M can be saved because of USGS enhanced information about a Mauna Loa eruption. $4.5B is the estimated cost of annual flooding. Through a network of over 11,885 streamgages, the USGS supports public safety and enables forecasts, early warning systems, and management actions that protect lives and property. Supporting National Security $3.1B The USGS identified a $3.1B risk to the American economy if China restricts gallium imports. This is one example underscoring the importance of the USGS mapping critical minerals, investigating supply chains, and producing the Nation’s critical minerals list. Enhancing Our Lands and Waters $21B in estimated annual costs results from invasive species. The USGS’s invasive species research informs approaches used to reduce their effects on agriculture, water infrastructure, disease transmission, fisheries, and outdoor recreation. USGS innovations support early warnings for harmful algal blooms—over $2M in yearly benefits are provided to Kansas alone. $45B USGS science informs the management of big game (such as deer and elk). The big-game hunting industry contributes $45B to the U.S. economy. Fostering American Prosperity $4.1T Mineral commodities are necessary for the $4.1T in value added to the GDP by major industries that consume processed mineral materials and employ 1 million workers. Because of this, USGS data on mineral supply, demand, and trade are highly valued. 45,000 metric tons Rare earths power the growing technology economy, including cell phones, electric vehicles, and medical devices. For over 70 years, USGS work has supported the discovery of rare earth resources in California’s Mountain Pass area, which produced 45,000 metric tons of rare earth concentrates in 2024—over 11% of the global supply. Guarding American Food Security $70.2B USGS science informs early warning systems and management strategies to mitigate disease outbreaks in agriculture—critical research on highly pathogenic avian influenza, for example, helps safeguard the $70B value in poultry and egg production. $11.8B USGS groundwater tools are vital for agriculture; for example, in the Mississippi Alluvial Plain, 65% of farming relies on groundwater to support its $11.8B annual industry. 1 Values throughout are given in billions (B), millions (M), and trillions (T) of U.S. dollars. GDP is “Gross Domestic Product.” Percentages are shown as %.

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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.

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