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1,660 records · Page 66Linked to original sources

USGS1983

Base flow and ground water in upper Sweetwater Valley, Tennessee

The upper Sweetwater Valley area has a flow system with complex interaction between surface and ground water. A water budget study indicated that during dry years approximately three-fourths of the annual flow to Sweetwater Creek may be derived from ground-water sources. Hydrograph analysis showed seasonal variation of recharge to the ground-water flow system. Streamflow records were analyzed to estimate the frequency of low flow of Sweetwater Creek at river mile 16.7, and indicated the lowest average flow for 1 day in 20 years to be about 5.1 cubic feet per second. Two periods of base-flow measurements of Sweetwater Creek identified channel reaches with significant gains and losses of streamflow. Base flow measurements also showed interbasin transfer of water among sub-basins of the valley. Major flow surpluses were associated with areas in which the majority of flow originated at a spring. Topographically low areas adjacent to the main stem of Sweetwater Creek generally have surplus flow. Topographically higher areas generally have deficient surface outflow unless significant spring flow occurs in the basin. Ground-water recharge occurs by water draining into sinkholes, faults, and fractures. Ground-water flow is regionally diffused across formation strikes from the topographically low areas unless the water is exposed to highly permeable formations or impervious formations. Ground water infiltrates the highly permeable formations and flows along strike. Ground water encountering impervious formations may discharge at small springs at the contact, or may reroute along the contact if the upgradient rock is sufficiently permeable or has well developed secondary porosity. Groundwater discharges to streams at innumerable seeps and at a few large springs. Areas of ground-water flow up-gradient of large springs are hypothesized as likely areas of significant ground-water reservoirs.

Tennessee↗

USGS2026

King Rails in southeastern Arkansas are majority resident

King Rails ( Rallus elegans ), a declining species of secretive marsh bird, have a mixed migratory strategy, with some individuals migrating and some being year-round residents. Determining the distribution of migratory versus resident King Rails is critical to guiding habitat management and assessing risks to populations. We examined the migratory status of adult King Rails at the Choctaw West Wildlife Management Area in southeastern Arkansas, the only known site in Arkansas with multiple breeding pairs. Of the 23 adult King Rails we tagged in 2022 and 2023, two birds migrated away from the local area, one in each year. One migrated 145 km, and the other 450 km. Our findings suggest that the line between the migratory and resident range of Arkansas King Rails could be north of our site.

Arkansas↗

USGS2025

Gulf Coast Basin CORE-CM initiative final report

The Bureau of Economic Geology at the University of Texas at Austin (UT-BEG) is leading the Gulf Coast Carbon Ore, Rare Earth, and Critical Minerals (CORE-CM) Initiative to assess the potential to produce critical minerals (CMs), including rare earth elements (REEs) from coal, coal ash, and produced water related to oil and gas production, and related materials (alumina processing waste [red mud], heavy mineral sands, graphite, and zeolite) within the Gulf Coast Basin. This project represents the first phase in a long-term program and provides reconnaissance data that will be foundational for future work by assessing resources and suggesting plans to be conducted in future work and expanding stakeholder engagement. The project includes several tasks designed to identify, characterize, and assess several necessary aspects for development of CMs and REEs in the Gulf Coast Basin.

Gulf Coast basin↗

USGS2026

Tringa flavipes (Lesser Yellowlegs) from separate breeding sites subdivides the Prairie Pothole Region in space and time during southbound migration

Some staging regions support multiple groups of the same migratory species, each of which may use the region differently. Characterizing the ways, in which separate groups use such regions can therefore help to identify vulnerabilities during this sensitive period of the annual cycle. The Prairie Pothole Region (PPR) is a massive wetland complex in the northern Great Plains of North America used by ∼11 million shorebirds during migration. The PPR has been heavily modified by agriculture and is experiencing varied effects of global climate change, threatening the health of the shorebirds that rely on it. Here, we used 6 seasons of southbound tracking data of Tringa flavipes (Lesser Yellowlegs)—a long-distance migratory shorebird species with an estimated population decline of 63% over the last 4 decades—from 9 sites across their breeding range to explore differences in migratory behavior within this important staging region. We found that 75% of tracked individuals used the region during southbound migration, and T. flavipes from different breeding sites detoured 110–875 km from their most direct migratory route to access the PPR. Individuals that arrived later stayed longer and made more stops within the region than those that arrived early. Individuals originating from different breeding sites also displayed spatial and temporal segregation within the region: T. flavipes from southwest and central Alaska relied heavily on the northwestern PPR, while those from Canada used the central and southeastern portions of the PPR. Finally, timing of use varied among groups, but the southeastern PPR became increasingly important over the course of the southbound migratory window, as other wetlands likely dried out. Our study highlights the portions of the PPR of critical importance to migrating T. flavipes and the diversity of ways, in which different groups from within the same species can use a single staging region.

Alaska, Manitoba, Northwest Territories, Ontario, ↗

USGS2026

Bayesian belief network model to predict human-wildlife conflict in protected areas

Human-wildlife conflict (HWC) poses a pervasive global challenge, affecting livelihoods and threatening biodiversity. To better anticipate and mitigate HWC risk, we developed a large-scale predictive model using a Bayesian Belief Network (BBN). We surveyed 1,011 park rangers across 135 terrestrial protected areas in three Andean countries, documenting recent HWC incidents involving wildlife persecution or killing, livestock depredation, crop damage, or threats to human safety and property. We identified key drivers of HWC risk, including governance, wildlife acceptance, participation, and habitat quality. A sensitivity analysis revealed that enhancing governance and improving wildlife acceptance could reduce HWC risk by > 85%. The BBN model demonstrated scalability, effectively identifying strategies to reduce HWC risk at multiple scales, from individual protected areas to national networks. Our findings highlight the importance of strengthening governance, increasing wildlife acceptance, and enhancing community participation in conservation efforts. BBNs provide a flexible, cost-effective, and data-driven tool to guide protected areas and wildlife managers in monitoring, anticipating, and making informed decisions to mitigate conflict and promote coexistence.

Scientific Reports↗

USGS2025

Central Valley Hydrologic Model version 2 (CVHM2): Decision support tool for groundwater and land subsidence management

The San Joaquin Valley (SJV) of California is one of the world’s most productive agricultural regions. Reliance on groundwater has led to some of the greatest rates of human-induced land subsidence in the world in the 20th century, as well as more recently. The United States Geological Survey (USGS) has recently developed an integrated surface–subsurface hydrologic model, the Central Valley Hydrologic Model 2 (CVHM2), that represents the major components of the hydrologic system of California’s Central Valley. In this study, CVHM2 was applied as a decision support tool while simulating various management strategies to mitigate the land subsidence caused by the extraction of groundwater. CVHM2 was extended through to 2073 and applied to simulate management scenarios in terms of three primary drivers and their impact on subsidence along the Delta–Mendota Canal (DMC), a critical piece of infrastructure in the western SJV. The drivers considered were agricultural water demands, managed aquifer recharge (MAR), and changes in future climate. The results show that future subsidence is most sensitive to water demands, second most sensitive to future changes in climate, and relatively insensitive to MAR when it is applied as a surface application in the western SJV. However, we demonstrate via proof-of-concept scenarios that the MAR is capable of arresting subsidence when implemented via injection below the Corcoran Clay Member of the Tulare Formation instead of as a surface application. We also examine the uncertainty that is the result of climate variability and how to use the tool to identify the most appropriate strategies to constrain future subsidence to acceptable levels.

California↗

USGS2026

Decoding the oxidative digestion mechanism for polystyrene nanoplastic detection in the Great Lakes using a customizable Raman spectral processing algorithm

Despite the concerns surging around nanoplastics (NPs) regarding their prevalence and bioavailability in freshwater systems, robust detection of NPs in complex environmental matrices is hindered by the lack of standardized sample pretreatment and a mechanistic understanding of oxidative digestion. Here, we systematically investigate the interaction between hydrogen peroxide (H 2 O 2 ) and polystyrene (PS) NPs during digestion in deionized (DI) water and four environmental matrices from in and around the Great Lakes Basin. To facilitate high-throughput analysis, we develop Pre_peak, a customizable Raman spectral processing algorithm that achieves >99% accuracy for both NP identification and interference rejection, allowing reliable NP quantification via pixel counting and systematic decoding of the oxidative digestion mechanisms. In DI water, varying H 2 O 2 doses from 0 to 30% has negligible effects on the recovery and Raman signal intensity of PS NPs over 24 hours of digestion. However, morphological changes and aggregation of PS NPs are observed when the H 2 O 2 dose exceeds 20%. Prolonged digestion further leads to progressive NP loss. In natural waters, the optimal dosage and digestion duration depend on matrix characteristics, including dissolved organic matter (DOM) and ion composition. This study provides mechanistic insights into NP–oxidant interactions and underscores the need for matrix-tailored digestion protocols to advance standardized NP detection in freshwater environments.

Great Lakes↗

USGS2023

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

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

Geothermal Resources Council Transactions↗

USGS2024

Uncertainty and spatial correlation in station measurements for mb magnitude estimation

The body‐wave magnitude (⁠⁠) is a long‐standing network‐averaged, amplitude‐based magnitude used to estimate the magnitude of seismic sources from teleseismic observations. The U.S. Geological Survey National Earthquake Information Center (NEIC) relies on in its global real‐time earthquake monitoring mission. Although waveform modeling‐based moment magnitudes are the modern standard to characterize earthquake size, is important because (1) in many cases, waveform modeling is not possible (e.g., low signal‐to‐noise events), (2) is applicable over a broad range of magnitudes, ∼M 4–7, and (3) there is a many decades‐long history of estimating magnitudes. We use the NEIC Preliminary Determination of Epicenters earthquake catalog to investigate the uncertainty in NEIC station measurements. We show that measurements are spatially correlated, which can bias event ⁠, and we describe an empirical relation between this spatial correlation and station‐to‐station distance. We further describe an approach to mitigate bias from the spatial correlation. Accounting for the spatial covariance of observations can change the event from −0.15 to 0.07 units (10th to 90th percentile) for smaller events (⁠⁠). These smaller events have the largest standard deviations ranging from 0.05 to 0.15 units (10th to 90th percentile).

The Seismic Record↗

USGS2024

Seismicity and anisotropic imaging reveal an active detachment beneath the northern Alaska Range foothills

North of the Denali Fault, the collision between the Yakutat block with North America is accommodated by a fold-thrust belt giving rise to the northern Alaska Range foothills. At the western end, the Kantishna Hills anticline hosts prominent microseismicity and surface deformation, interpreted as active folding of the Kantishna Hills anticline above a midcrustal detachment. We test for this detachment by using anisotropy-aware receiver functions to image fabric contrasts within the crust in context with seismicity. Seismic stations near the crest of the Kantishna Hills anticline and near its southern flank show a single strong contrast in dipping fabric at depths of 12–13 km near microseismicity clustering depths, consistent with a detachment plane beneath the fold. A minimum b -value at 10–13 km depth is consistent with seismicity on the detachment, compatible with the imaged anisotropic contrast, while off-fault seismicity is shallower and deeper with smaller magnitudes. South-dipping imbricate thrusts in schist characterize the northern Alaska Range foothills structure. This supports our interpretation of the observed anisotropy as reflecting SSW–SSE-dipping foliation above a detachment at ∼10–13 km depth that exploits existing crustal weaknesses along subtle fabric contrasts observed in the seismically quiescent region north of the actively deforming belt.

Alaska↗

USGS1991

Reconnaissance of the occurrence of agricultural chemicals in ground water in Haywood, Lake, Obion and Shelby Counties, Tennessee

Data on the occurrence of agricultural chemicals in ground wafer in Tennessee are sparse. The surficial alluvial aquifer is an important source of domestic water supply in West Tennessee, and potentially is subject fo contamination from the application of agricultural chemicals in the area. Nineteen shallow wells completed in the alluvial aquifers in areas of high density agricultural use were sampled in the winter and again in the summer of 1988 to ascertain the occurrence of agricultural chemical in ground water. Although no triazine herbicides or organophosphorus insecticides were detected in any of the wells sampled, elevated nitrite plus nitrate (as nitrogen) concentrations were detected. Results from the winter sampling period indicate a range of nitrite plus nitrate (as nitrogen) concentrations of less than 0.1 to 7.8 milligrams per liter with a median concentration of 2.6 milligrams per liter. Results from the summer sampling period indicate a range of nitrite plus nitrate (as nitrogen) concentrations of less than 0.1 to 8.9 milligrams per liter, median, 2.5 milligrams per liter. The highest concentrations occurred in the shallowest wells, and, in one instance, in a shallow well near a heavily irrigated field.

Tennessee↗

USGS2026

Overstorey mortality promotes juvenile piñon pine growth during favourable weather at cooler, wetter sites

Hotter droughts have resulted in widespread tree die-off events globally, frequently leading to regeneration failure. Dry forest recovery often depends on the growth and survival of extant juvenile trees. However, it is unclear how microenvironmental changes following overstorey tree die-off affect juvenile trees, particularly in dryland systems where tree recruitment is typically limited by water availability and heat stress. We simulated an overstorey tree die-off event by girdling trees in piñon-juniper woodlands across the south-western United States. We sampled juvenile piñon pine growth from live and dead overstorey treatments across six study sites spanning a regional latitudinal gradient and local elevational gradients. We examined how juvenile branch and needle growth differed between live and dead overstorey treatments, and whether responses varied with weather conditions and juvenile tree size following overstorey mortality. We found greater juvenile branch and needle growth under dead compared with live overstorey trees for 2 years following overstorey mortality at mid- and high-elevation sites which are typically cooler and wetter than the other sites. These observed growth releases were contingent on favourable post-mortality weather conditions. Higher growth under dead overstorey occurred at sites experiencing near-average climatic water deficits compared with sites experiencing above-average climatic water deficits. Growth at all sites increased from the first to second year after overstorey mortality. Across sites, growth was unrelated to juvenile tree size. Synthesis . Our results underscore differentiation in juvenile responses to overstorey tree die-off driven by local site conditions and weather across the range of Pinus edulis . Overstorey mortality resulted in consistently higher juvenile growth only at climatically favourable sites and during favourable weather, while unmeasured microsite differences could help account for variation observed at the hottest and driest site. Results from less climatically favourable sites suggest that overstorey trees neither directly limit nor facilitate juvenile growth, though further study over longer timeframes is needed to resolve the pace and magnitude of potential recovery or decline. Overall, juvenile vigour may be promoted following overstorey mortality only in a narrow spatial (site) and temporal (weather) environmental context, suggesting additional vulnerabilities for piñon populations under more arid conditions.

Arizona, Colorado↗

USGS2025

New constraints on location and timing of the Great Lakes tectonic zone, central Upper Peninsula, Michigan, USA

The Great Lakes tectonic zone (GLTZ) forms the boundary between the Wawa–Abitibi and Minnesota River Valley subprovinces within the Archean Superior Province. The GLTZ is concealed for all of its 1100 km length, except for a segment in the central Upper Peninsula of Michigan. There, it is exposed as a northwest-striking mylonite zone along a 11 km segment, extending to the onlap of Paleozoic rocks to the east. Farther east, its location has been unknown. Here, we use aeromagnetic and gravity data to develop interpretations of the expression of the GLTZ and to define its extent under cover. Aeromagnetic gradients over the mylonite zone are interpreted to be produced by structurally juxtaposed rocks with varying magnetizations. Gravity data show a regional gradient along the GLTZ, produced by the juxtaposition of a dense greenstone belt on the north against lower-density gneisses and granites on the south. The GLTZ is interpreted to extend ∼55 km under cover to the east. The GLTZ is terminated on the east by the buried eastern arm of the ca. 1100 Ma Midcontinent Rift. An undeformed granitic dike that cuts the mylonitic foliation produces a U–Pb apatite age of 2523 ± 33 Ma, implying no major post-Archean shearing occurred, and is at odds with previous interpretations of major Proterozoic reactivation. A granite intrusion in the Minnesota River Valley subprovince produces a Pb–Pb zircon age of 2606.9 ± 3.6/7.4 Ma. This suggests that magmatism related to the Sacred Heart orogeny, previously known in Minnesota, extended to Michigan.

Michigan↗

USGS2024

Status and performance of the ShakeAlert® earthquake early warning system: 2019-2023

The U.S. Geological Survey (USGS)‐operated ShakeAlert® system is the United States West Coast earthquake early warning system ( Given et al. , 2018 ). In this study we detail ShakeAlert’s performance during some of the largest events seen by the system thus far. Statewide public alerting using ShakeAlert messages was authorized in California in October 2019. Over the next few years, public alerts were expanded into Oregon and then into Washington ( U.S. Geological Survey, 2024 ). ShakeAlert source results are routinely compared to the USGS Comprehensive Catalog (ComCat; Guy et al. , 2015 ; U.S. Geological Survey, Earthquake Hazards Program, 2017 ), which contains the earthquake location and magnitude determined using complete waveform data. M 4.5 and larger is the threshold used for public alerting and was deliberately set below the level where damage is likely to compensate for cases where the system underestimates the magnitude. Between 17 October 2019 and 1 September 2023, the ShakeAlert system created 95 events with maximum magnitude estimates of M ≥4.5, the public alerting threshold. 94 of the 95 events were due to real earthquakes. Seven were categorized “false” per ShakeAlert’s internal definition that there was no matching catalog event within 100 km and 30 s of origin time; however, all but one of these were real earthquakes that were poorly located, primarily because they were at the edges of the seismic network. Three detected events were labeled “missed” because they were very poorly located (>100 km location error). In addition, the system did not produce solutions for four ComCat events M ≥4.5 ( U.S. Geological Survey, Earthquake Hazards Program, 2017 ), which were all at the edge of the alerting and network boundaries. The ShakeAlert system has accurately detected the majority of earthquakes that have occurred within the operational region since completing the public rollout, and alerts from the system have been delivered to millions of cell phone users throughout the West Coast.

California, Oregon, Washington↗

USGS2024

Debris-flow entrainment modelling under climate change: Considering antecedent moisture conditions along the flow path

Debris-flow volumes can increase along their flow path by entraining sediment stored in the channel bed and banks, thus also increasing hazard potential. Theoretical considerations, laboratory experiments and field investigations all indicate that the saturation conditions of the sediment along the flow path can greatly influence the amount of sediment entrained. However, this process is usually not considered for practical applications. This study aims to close this gap by combining runout and hydrological models into a predictive framework that is calibrated and tested using unique observations of sediment erosion and debris-flow properties available at a Swiss debris-flow observation station (Illgraben). To this end, hourly water input to the erodible channel is predicted using a simple, process-based hydrological model, and the resulting water saturation level in the upper sediment layer of the channel is modelled based on a Hortonian infiltration concept. Debris-flow entrainment is then predicted using the RAMMS debris-flow runout model. We find a strong correlation between the modelled saturation level of the sediment on the flow path and the channel-bed erodibility for single-surge debris-flow events with distinct fronts, indicating that the modelled water content is a good predictor for erosion simulated in RAMMS. Debris-flow properties with more complex flow behaviour (e.g., multiple surges or roll waves) are not as well predicted using this procedure, indicating that more physically complete models are necessary. Finally, we demonstrate how this modelling framework can be used for climate change impact assessment and show that earlier snowmelt may shift the peak of the debris-flow season to earlier in the year. Our novel modelling framework provides a plausible approach to reproduce saturation-dependent entrainment and thus better constrain event volumes for current and future hazard assessment.

Illgraben basin↗

USGS2025

Factors regulating the potential for freshwater mineral soil wetlands to function as natural climate solutions

There are increasing global efforts and initiatives aiming to tackle climate change and mitigate its impacts via natural climate solutions (NCS). Wetlands have been considered effective NCS given their capacity to sequester and retain atmospheric carbon dioxide (CO 2 ) while also providing a myriad of other ecosystem functions that can assist in mitigating the impacts of climate change. However, wetlands have a dual impact on climate, influencing the atmospheric concentrations of both CO 2 and methane (CH 4 ). The cooling effect associated with wetland CO 2 sequestration can be counterbalanced by the warming effect caused by CH 4 emissions from wetlands. The relative ability of wetlands to sequester CO 2 versus emit CH 4 is dependent on a suite of interacting physical, chemical, and biological factors, making it difficult to determine if/which wetlands are considered important NCS. The fact that wetlands are embedded in landscapes with surface and subsurface hydrological connections to other wetlands (i.e., wetlandscapes) that flow over and through geochemically active soils and sediments adds a new layer of complexity and poses further challenges to understanding wetland carbon sequestration and greenhouse gas fluxes at large spatial scales. Our review demonstrates how additional scientific advances are required to understand the driving mechanisms associated with wetland carbon cycling under different environmental conditions. It is vital to understand wetland functionality at both wetland and wetlandscape scales to effectively implement wetlands as NCS to maximize ecological, social, and economic benefits.

Wetlands↗

USGS2025

Land application of drill waste: A scope analysis

Drilling fluid waste land application, a process where drilling wastes are spread and tilled into the land surface, has become common in some petroleum-producing states, however, the potential benefits and risks of this practice are not well studied. Drilling fluids can be water- or oil-based and can have high concentrations of total soluble salts and total petroleum hydrocarbons. Comprehensive chemical characterization of these fluids is not well documented in the literature, and the extent of land application is largely unknown. We hypothesized that the land application of drill waste would fluctuate over time due to economic factors. To begin to understand the extent of historical and potential future land application, we analyzed data from over 5,800 drilling fluid land application permits collected by the Oklahoma Corporation Commission for years 2000, 2005, 2010, and 2015–2020. During the years studied, drilling fluid wastes were applied to more than 250,000 acres in Oklahoma, with over 54,000 thousand barrels (Mbbl) of liquids and nearly 21,000 Mbbl of solids applied. Land application is widespread (occurring in 59/77 counties), however recent drilling activity, land availability, and the economics of transportation have created conditions favorable for land application specifically in the Anadarko Basin. Land application can co-occur with sensitive areas, such as important groundwater and surface-water drinking sources and agricultural fields used for subsistence or feed crop production. Our approach for quantifying the extent of land application, along with further chemical characterization studies, can aid operators and land managers who are considering this practice in assessing the associated benefits and risks.

Oklahoma↗

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↗