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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↗
USGS2026

Assessing natural recharge in Indian Wells Valley, California: A Basin Characterization Model case study

The communities in Indian Wells Valley (IWV), in the northern Mojave Desert in California, rely on groundwater for domestic and agricultural use. Mountain front recharge from the surrounding Sierra Nevada is the main source of natural recharge to the valley. Increased urbanization, agricultural development, and groundwater pumping during recent decades put IWV in a state of critical overdraft. The U.S. Geological Survey Basin Characterization Model, version 8 (BCMv8) was used to evaluate historical and future climate and hydrologic conditions in IWV. The BCMv8 estimated natural recharge in IWV at 10.7 million cubic meters (Mm 3 ) per year for the period from 1981 to 2010. Future patterns of water balance variables using three future climate scenarios, hot-wet, hot-dry, and warm-moderately wet, were calculated for mid-century (2040–69) and end-of-century (2070–99) periods. Results for both wet models projected an increase in recharge in both periods, whereas the hot-dry model projected a decrease in recharge in both periods. All models reported a large increase in seasonal variability in recharge, indicating more future availability and frequent occurrences of drought years. All climate scenarios projected an increase in climatic water deficit in both periods. These increases in irrigation demand and variability of water supply highlight the importance of strategic management planning for the sustainability of water resources in IWV.

California↗
USGS2024

2024 Crustal Deformation Modeling Workshop report

The 2024 Crustal Deformation Modeling Workshop was held June 10–14 at the Colorado School of Mines. The workshop included two days of tutorials on using PyLith for crustal deformation modeling, followed by three days of science talks and discussions. The workshop focused on four primary themes: ● Constraining long-term fault slip rates and their uncertainties using geodetic and geologic data; ● Earthquake cycle modeling with a focus on constraining models using seismic and geodetic data; ● Interaction of fluids and faulting; and ● Separating contributions of surface loading and tectonic loading in crustal deformation. The complete agenda is available on the CIG website.

Conference Paper↗
USGS2024

Slope Unit Maker (SUMak): An efficient and parameter-free algorithm for delineating slope units to improve landslide modeling

Slope units are terrain partitions bounded by drainage and divide lines. In landslide modeling, including susceptibility modeling and event-specific modeling of landslide occurrence, slope units provide several advantages over gridded units, such as better capturing terrain geometry, improved incorporation of geospatial landslide-occurrence data in different formats (e.g., point and polygon), and better accommodating the varying data accuracy and precision in landslide inventories. However, the use of slope units in regional ( > 100 km 2 ) landslide studies remains limited due, in part, to the large computational costs and/or poor reproducibility with current delineation methods. We introduce a computationally efficient algorithm for the parameter-free delineation of slope units that leverages tools from within TauDEM and GRASS, using an R interface. The algorithm uses geomorphic laws to define the appropriate scaling of the slope units representative of hillslope processes, avoiding the often ambiguous determination of slope unit size. We then demonstrate how slope units enable more robust regional-scale landslide susceptibility and event-specific landslide occurrence maps.

Natural Hazards and Earth Systems Sciences (NHESS)↗
USGS2026

Family life is critical for migration and survival in a long-lived social bird

Extended parental care is common among birds and particularly well known among long-lived migratory species. Yet, factors influencing the duration of parental care are poorly understood, and empirical evidence for the functional importance of family life for offspring development is scarce. Using unique tracking and genetic data of 55 adult and juvenile migratory Bewick’s swans, among which 18 parent-offspring pairs and 13 sibling pairs, we quantify variation in family bond duration and identify the cause and consequences of their dissolution. Families generally broke up during the second half of the first northward migration of the offspring, when offspring were nearly one year old. Earlier separation occurred on the wintering grounds in response to disturbance ( n = 10 juveniles) and led to delayed migration and, critically, lower survival (40 vs. 86%). Our results provide rare empirical evidence that family bonds, as a pathway for social learning, are not just important, but vital to the migration and survival of young family-living birds.

Behavioral Ecology and Sociobiology↗
USGS2026

Albuquerque Seismological Laboratory strategic vision

This circular presents a strategic outlook for the U.S. Geological Survey (USGS) Albuquerque Seismological Laboratory (ASL) for the next 10 years (2026–36). The ASL is a USGS field office in the Geological Hazards Science Center that operates portions of the Advanced National Seismic System and the Global Seismographic Network and focuses on fundamental research for instrumentation testing and data quality. The strategic outlook is categorized into two types of tasks: “Foundational Tasks” and “Aspirational Tasks.” Foundational Tasks are those that maintain the laboratory’s basic operations and services, including regional and global seismic monitoring, improving data quality, and providing instrument testing and support. A suite of Aspirational Tasks is also articulated; these can be considered priority targets of ASL that could improve ASL’s seismic monitoring capabilities and mission. Such tasks include improvements to remote stations, testing capabilities of nonseismic geophysical instruments, detection threshold monitoring, rapid aftershock deployments, and expanding seismic monitoring networks. This report was written with input from the USGS Geological Hazards Science Center, the USGS Earthquake Hazards Program (EHP), and colleagues with an interest in the work done by the ASL. Although the details of these tasks may change, this document can provide guidance on the overarching tasks at the ASL from 2026 to 2036 and an overview of the various components of the ASL and how they fit into the EHP and the Global Seismographic Network Program.

Circular↗
USGS2025

An early Holocene wet period in the southwestern United States

Multiple generations of spring-fed streams traversed ∼800 km 2 of the Las Vegas Valley in southern Nevada between ca. 10.9 ka and 8.5 ka, depositing an extensive tufa network. The scale of this network and diversity of tufa morphologies is novel in North America and offers an opportunity to obtain quantitative paleoclimate data for the region during the early Holocene. We determined isotopic compositions and estimated past temperatures using clumped isotope data from early Holocene tufa on the valley floor (698 m) as well as tufa forming today at higher elevation in the nearby Spring Mountains at Cold Creek Spring (1856 m). Modern and fossil tufa yielded comparably low δ 18 O values, implying that source waters for both were derived from high-elevation winter precipitation. Clumped isotope temperatures of modern tufa average 15.8 ± 2.5 °C, aligning with mean summer temperatures of the emergent spring water, and indicate equilibrium conditions of tufa formation. The early Holocene tufa yielded similar clumped isotope temperatures, averaging 15.2 ± 3.9 °C, meaning it precipitated at temperatures that occur at much higher elevations today. The Las Vegas tufa record, combined with nearby and temporally correlative paleospring and lacustrine records, suggest that cool/wet conditions prevailed throughout the Mojave Desert during the early Holocene. These records also demonstrate that spring ecosystems responded to millennial-scale hydroclimate variations that supersede climate change driven solely by insolation. The previously unrecognized pattern of ecosystem response to hydroclimate documented here may assist in understanding climate drivers for the early Holocene and provide critical information for the fate of groundwater-dependent ecosystems in the southwestern United States.

Nevada↗
USGS2026

Earthquake ground-motion model adjustments for the San Francisco Bay area

We develop adjustments to ergodic ground‐motion models (GMMs) to improve their performance in the San Francisco Bay Area (SFBA). GMMs are widely used in hazard assessments to estimate characteristics of ground shaking based on known properties of the source, path, and site. Such models are often developed using datasets containing records from various regions, resulting in models that represent median ground‐motion behavior, which may not adequately represent ground motions within subregions. This is true for the SFBA, where ground motions attenuate more rapidly with distance than in many other parts of California that dominate GMM databases. To support improved seismic hazard estimates in the SFBA, we calculate regional constants and anelastic attenuation coefficient adjustments relative to two commonly used ergodic GMMs: BSSA14 ( Boore et al. , 2014 ) and ASK14 ( Abrahamson et al. , 2014 ). These adjustments are obtained for a suite of ground‐motion intensity measures (peak ground acceleration, peak ground velocity, and 5%‐damped pseudospectral acceleration at oscillator periods ranging from 0.075 to 10 s) using mixed‐effects regression. Use of the regionally adjusted models reduces the overall bias by up to 0.5 natural log units for BSSA14 and up to 0.6 natural log units for ASK14. We demonstrate one application of our attenuation adjustments and their implications in an earthquake early warning case study of the 2014 M 6.0 South Napa earthquake. The predicted extent of shaking using the adjusted models better matches observed shaking at large source‐to‐site distances, especially for lower shaking intensities, thus potentially reducing overalerting. We encourage the use of our model adjustments when ergodic models are considered for seismic hazard studies in the SFBA.

California↗
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↗
USGS2024

Potentially toxic elements in wild Agassiz’s desert tortoises: Tissue concentrations and association with disease

Background: Desert tortoise ( Gopherus agassizii ) populations have continued to decline due to infectious and other diseases, predation, and habitat alteration. The potential contribution of minerals and heavy metals to tortoise health and susceptibility to disease remains uncertain. Objective: The objective of this study was to evaluate the results of elemental analysis of trace minerals and macrominerals in scute keratin, kidney, and liver tissue from ill and dying desert tortoises salvaged for necropsy between 1993 and 2000. Methods: Salvaged tortoises were categorized by age (adult, juvenile), geographic location, and primary disease based on necropsy findings. A subset of tortoises that were injured or killed by vehicular trauma or predation but with no notable pathologic abnormalities were used as controls. A panel of 21 trace minerals and 6 macrominerals was analyzed in scute keratin, kidney, and liver tissue samples by inductively-coupled plasma spectrometry and atomic absorption spectrophotometry. Results: Necropsies were done on 46 tortoises, including 9 juveniles salvaged from 5 regions in the Colorado and Mojave deserts of California. Primary diseases were cutaneous dyskeratosis (n=9), infection/ inflammation (n=8), malnutrition (n=7), mycoplasmosis (n=5), and urolithiasis (n=3); 14 tortoises were classified as controls. Concentrations of elements differed significantly by tissue, age, desert region, and disease (P < 0.05). Tortoises with cutaneous dyskeratosis had significantly higher Se concentrations, primarily in keratin and liver, than tortoises with other diseases (P < 0.001). Juveniles were more likely than adults to have high Pb, Sn, and Zn levels (P < 0.05). All tortoises had detectable levels of more than one potentially toxic heavy metal, including As, Cd, Cr, Hg, Ni, Pb, Sn and V. Conclusions: Potentially toxic elements are frequently found in tissue from tortoises in desert regions of California, with significantly higher concentrations in diseased tortoises. Metal exposure from soils, mining, historic and ongoing military activities, and other human activities could increase susceptibility to disease in desert tortoises.

California↗
USGS2025

40Ar/39Ar geochronology supporting mineral resources research at USGS Denver

The 40 Ar/ 39 Ar geochronology method is used to date potassium-bearing rocks and minerals, based on the decay of 40 K to 40 Ar, which provides important temporal constraints for geological events. The USGS Denver Argon Geochronology Laboratory dates samples from a variety of projects, mainly in the USGS Mineral Resource Program and the National Cooperative Geologic Mapping Program, facilitating in-depth research into the timing of geological events and processes. Recent applications of this method include geochronological studies in the Yellow Pine district, revealing mineralization ages that range from 51 to 70 Ma, and investigations into the Bear Lodge alkaline complex, providing insights into the timing of REE carbonatite formation. Additionally, studies at Alunite Ridge highlight the method's potential for understanding concealed mineral deposits. Ongoing projects continue to leverage 40 Ar/ 39 Ar data to enhance understanding of geologic frameworks and mineral resources, underpinning its importance in modern geochronology and mineral resource assessment.

Conference Paper↗
USGS2024

The spatially adaptable filter for error reduction (SAFER) process: Remote sensing-based LANDFIRE disturbance mapping updates

LANDFIRE (LF) has been producing periodic spatially explicit vegetation change maps (i.e., LF disturbance products) across the entire United States since 1999 at a 30 m spatial resolution. These disturbance products include data products produced by various fire programs, field-mapped vegetation and fuel treatment activity (i.e., events) submissions from various agencies, and disturbances detected by the U.S. Geological Survey Earth Resources Observation and Science (EROS)-based Remote Sensing of Landscape Change (RSLC) process. The RSLC process applies a bi-temporal change detection algorithm to Landsat satellite-based seasonal composites to generate the interim disturbances that are subsequently reviewed by analysts to reduce omission and commission errors before ingestion them into LF’s disturbance products. The latency of the disturbance product is contingent on timely data availability and analyst review. This work describes the development and integration of the Spatially Adaptable Filter for Error Reduction (SAFER) process and other error and latency reduction improvements to the RSLC process. SAFER is a random forest-based supervised classifier and uses predictor variables that are derived from multiple years of pre- and post-disturbance Landsat band observations. Predictor variables include reflectance, indices, and spatial contextual information. Spatial contextual information that is unique to each contiguous disturbance region is parameterized as Z scores using differential observations of the disturbed regions with its undisturbed neighbors. The SAFER process was prototyped for inclusion in the RSLC process over five regions within the conterminous United States (CONUS) and regional model performance, evaluated using 2016 data. Results show that the inclusion of the SAFER process increased the accuracies of the interim disturbance detections and thus has potential to reduce the time needed for analyst review. LF does not track the time taken by each analyst for each tile, and hence, the relative effort saved was parameterized as the percentage of 30 m pixels that are correctly classified in the SAFER outputs to the total number of pixels that are incorrectly classified in the interim disturbance and are presented. The SAFER prototype outputs showed that the relative analysts’ effort saved could be over 95%. The regional model performance evaluation showed that SAFER’s performance depended on the nature of disturbances and availability of cloud-free images relative to the time of disturbances. The accuracy estimates for CONUS were inferred by comparing the 2017 SAFER outputs to the 2017 analyst-reviewed data. As expected, the SAFER outputs had higher accuracies compared to the interim disturbances, and CONUS-wide relative effort saved was over 92%. The regional variation in the accuracies and effort saved are discussed in relation to the vegetation and disturbance type in each region. SAFER is now operationally integrated into the RSLC process, and LANDFIRE is well poised for annual updates, contingent on the availability of data.

Fire↗
USGS1993

Ground-water quality near an inactive landfill and sludge-spreading area, Tallahassee, Florida

Ground-water quality of a 120-acre area encompassing an inactive landfill southwest of Tallahassee, Florida, was assessed by installing and sampling 21 monitoring wells. Sludge from a municipal sewage-treatment plant was also applied to the land surface near the landfill site. Water samples were collected from the 21 monitoring wells from June 1987 through September 1990 and analyzed for concentrations of major ions, nitrogen species, trace metals, field measurements, and more than 140 organic constituents. Water quality in the Upper Floridan aquifer at the study site was compared to background water quality in other areas of Leon County. Ground-water quality of the study site was evaluated by the location of wells sampled in relation to the landfill and the sludge-spreading areas. Results of nonparametric statistical analysis indicated that potassium and nitrite plus nitrate as nitrogen concentrations in water samples from wells completed in the Upper Floridan aquifer at the study site were significantly different at the 5 percent probability level from those in samples from background wells completed in this aquifer in Leon County. Median potassium concentrations were 0.4 mg/L (milligrams per liter) in water from wells at the study site and 0.7 mg/L in water from background wells in Leon County. Median nitrite plus nitrate concentrations were 6.48 mg/L in water samples from wells at the study site and 0.51 mg/L in water samples from background wells. Graphical comparison of the water quality characteristics in water from six categories of wells; upgradient, landfill, adjacent to the landfill, downgradient onsite, downgradient offsite, and background Leon County, indicated that sodium, bicarbonate, sulfate, iron, manganese, and dissolved solids concentrations and specific conductance values were highest within the landfill. Upgradient and downgradient well categories include wells in areas affected by sludge spreading. Localized reducing conditions were indicated in a downgradient area by median iron concentrations of 930 and 30 ug/L (micrograms per liter) in samples from wells only 5 feet apart. Nitrite plus nitrate concentrations were lowest in water from wells in the landfill compared to water from the other categories. Concentrations of most trace elements and organic compounds were mostly below detection limits, although State maximum contaminant levels of 1 ug/L for benzene and vinyl chloride and 3 ug/L for tetrachloroethene were exceeded in 14 samples. Concentrations of sodium, potassium, chloride, sulfate, nitrite plus nitrate, total organic and ammonia nitrogen, and ammonia nitrogen in ground water were statistically analyzed in areas affected by sludge-spreading and other areas. Only nitrite plus nitrate and chloride concentrations were significantly different between the two areas. Median nitrite plus nitrate and chloride concentrations in sludge-spreading areas were 6.9 mg/L and 2.9 mg/L, respectively, compared to 1.1 mg/L and 1.8 mg/L in other areas.

Florida↗
USGS2024

The SCEC/USGS community stress drop validation study using the 2019 Ridgecrest earthquake sequence

We introduce a community stress drop validation study using the 2019 Ridgecrest, California, earthquake sequence, in which researchers are invited to use a common dataset to independently estimate comparable measurements using a variety of methods. Stress drop is the change in average shear stress on a fault during earthquake rupture, and as such is a key parameter in many ground motion, rupture simulation, and source physics problems in earthquake science. Spectral stress drop is commonly estimated by fitting the shape of the radiated energy spectrum, yet estimates for an individual earthquake made by different studies can vary hugely. In this community study, sponsored jointly by the U. S. Geological Survey and Southern/Statewide California Earthquake Center, we seek to understand the sources of variability and uncertainty in earthquake stress drop through quantitative comparison of submitted stress drops. The publicly available dataset consists of nearly 13,000 earthquakes of M1 to 7 from two weeks of the 2019 Ridgecrest sequence recorded on stations within 1-degree. As a community study, findings are shared through workshops and meetings and all are invited to join at any time, at any interest level.

Seismica↗
USGS2025

Water supply in the conterminous United States, Alaska, Hawaii, and Puerto Rico, water years 2010–20

We present an assessment of water supply across the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico covering water years 2010–20. Our analysis drew on two national hydrologic models, the National Hydrologic Model Precipitation-Runoff Modeling System and the Weather Research and Forecasting model hydrologic modeling system. Both models produced estimates of streamflow, evapotranspiration, soil moisture, snow water equivalent, and other hydrologic states and fluxes. The models were driven by the bias-adjusted 4-kilometer-resolution, long-term regional hydroclimate simulation over the conterminous United States dataset (CONUS404). We assessed spatial and temporal error distributions by comparing monthly simulations at the 12-digit hydrologic unit code and regional scale from both models against external benchmarking datasets. Results showed that average annual rainfall across the CONUS was 857 millimeters per year for the period of analysis, with water year 2012 the driest year (729 millimeters) and water year 2019 the wettest year (995 millimeters). Key interannual variability results included the following: (1) the California–Nevada hydrologic region had the highest variability in precipitation and snow accumulation, and (2) the Texas hydrologic region was among hydrologic regions with the highest variability in precipitation. We related interannual variability in precipitation to storage volumes in soil moisture, snow water equivalent, and lakes and reservoirs to highlight areas with little storage and large year-to-year variability in precipitation. These areas included the Southern High Plains, Central High Plains, Texas, Souris–Red–Rainy, Mississippi Embayment, and Midwest regions. Our analysis of groundwater-level data showed that several of these areas overlap aquifers where groundwater levels were considerably lower than historical averages, including the Colorado Plateaus aquifers, the Rio Grande aquifer system, and the Central and Southern regions of the High Plains aquifer. Many of these lowered groundwater levels are continuations of decades-long declines from overpumping that started well before the assessment period. The resulting water budgets and their analyses provide a high-resolution foundational assessment of the mean state and variability of the terrestrial hydrologic cycle across the CONUS and Alaska, Hawaii, and Puerto Rico to support a wide range of water resource management applications.

Professional Paper↗
USGS2025

Spatiotemporal variations in strain release and seismic rupture in multifault systems: An example from Panamint Valley, southeastern California

Geometrically complex, multifault ruptures have been observed in recent, damaging earthquakes in southeastern California, sparking renewed efforts to identify physical conditions that promote or inhibit fault discontinuity-spanning coseismic ruptures. The likelihood of ruptures propagating across fault discontinuities is thought to be partly controlled by fault geometries, rupture direction, and the history of strain release. However, these parameters vary in space and time over multiple earthquake cycles, making it difficult to forecast the likelihood that an earthquake on one fault will trigger rupture on a nearby fault. Here we use tectono-geomorphic mapping of a geometrically complex fault zone in Panamint Valley, southeastern California, to assess spatiotemporal variations of paleo-rupture patterns and geometries of fault discontinuities over multiple earthquake cycles. First, we identify ten generations of late Pleistocene to Holocene alluvium using geomorphic parameters and luminescence dating to constrain ages of alluvium and bracket late Holocene earthquake timing. Then, we quantify slip kinematics using high-resolution structure from motion digital surface models. We find the Panamint Valley transtensional relay (PVTR) hosted four late Holocene earthquakes, bracketed to ~5.8–3.4 ka, ~3.8–2.2 ka, ~2.4–0.6 ka, and ~0.64–0.16 ka, with ~0.6–1.1 m of slip per event, correlative to Mw ≈ 6.7–6.9 earthquakes. Additionally, we find similarities in earthquake timing on the Ash Hill, PVTR, and Panamint Valley faults and similarities in the slip magnitude and slip kinematics between the Ash Hill and PVTR faults, implying that the PVTR may co-rupture with nearby faults. Paleo-rupture patterns indicate that seismogenic strain transfer may occur through the PVTR, along different combinations of fault segments and jump distances, over multiple earthquake cycles. These data highlight the utility of tectono-geomorphic mapping in evaluating paleo-rupture patterns and suggest that the PVTR may act to propagate and/or arrest rupture between the Ash Hill and Panamint Valley faults.

California↗
USGS2025

Constraining large magnitude event source and path effects using ground motion simulations

The purpose of this study is to use ground motion simulations to investigate ways in which source and path effects for large magnitude events can be represented in non-ergodic GMMs. While we initially developed computation techniques using CyberShake simulations, the range of magnitudes and source-site combinations is not adequate to replicate what is observed empirically. We therefore designed a new ground motion simulation study, which includes earthquakes with a large range of magnitudes distributed uniformly on a fault plane, and sites covering a large range of rupture distances and azimuths. After running a large suite of simulations (M4-M7), we then develop a non-ergodic GMM with the simulation data. We find that the within-site residuals are dominated by the radiation pattern, rupture directivity, and slip patterns. Next, we modify an existing rupture directivity model to fit and remove the observed radiation pattern and rupture directivity from the residuals. We also minimize the contributions of slip patterns by averaging the within-site residuals among multiple source realizations. Finally, after removing the source effects from the within-site residuals, we compare the path effects computed with different magnitude groups using two approaches. The first approach only considers the small events that have the same shortest path to a site with the large events, while the second approach considers all small events on the fault plane. The results indicate that the path effects of large events cannot be satisfactorily approximated with that of small events using either approach.

Conference Paper↗
USGS2025

Salinas Valley integrated hydrologic and reservoir operations models, Monterey and San Luis Obispo Counties, California

The area surrounding the Salinas Valley groundwater basin in Monterey and San Luis Obispo Counties of California is a highly productive agricultural area, contributes significantly to the local economy, and provides a substantial portion of vegetables and other agricultural commodities to the Nation. This region of California provides about half of the Nation’s lettuce, celery, broccoli, and spinach each year. Thus, this agricultural area provides significant volumes of agricultural products not just for California but the entire United States. Changes in population and increased agricultural development, which includes a shift toward more water-intensive crops, and climate variability, have put increasing demand on both surface water and groundwater resources in the valley. This has resulted in water management challenges in the Salinas Valley that are predominantly related to distribution of water supply throughout the basin. Where and when the water is present in the surface and subsurface does not coincide with where and when the water is needed. To deal with the distribution issue, historically water has been used conjunctively in the valley. Conjunctive use is a water management strategy that coordinates surface water and groundwater use to maximize water availability. Groundwater is used throughout the Salinas Valley to meet water demands when surface water supplies are insufficient. Availability of surface water is constrained by climate. Precipitation and streamflow vary seasonally and year to year. Although there are two reservoirs in the Salinas Valley to capture and store water during wet periods, the only conveyance of reservoir water to coastal agricultural areas is the Salinas River. Increasing demand on groundwater and surface water resources throughout the Salinas Valley has resulted in undesirable effects of unsustainable water use, such as surface water depletion, groundwater level declines, storage depletion in the principal aquifers, and seawater intrusion. To address these escalating issues, local communities, water management agencies, and groundwater sustainability agencies are evaluating how to sustainably manage both their surface water and groundwater resources. To meet water demands and reduce undesirable effects of unsustainable water use, continued conjunctive management of surface water and groundwater would ideally incorporate strategies to deal with increases in demand and a variable climate. To evaluate the challenging water management issues in the Salinas Valley, the U.S. Geological Survey, Monterey County Water Resource Agency, and the Salinas Valley Basin Groundwater Sustainability Agency developed a comprehensive suite of models that represent the Salinas Valley Hydrogeologic system called the Salinas Valley System Model. The Salinas Valley Geologic Framework was developed to characterize the subsurface using various topographic and geologic data sources, including information on hydrogeologic units, their surfaces and extents, geologic structures, lithology, and elevations from borehole data and cross sections, as well as details on faults and existing models. The Salinas Valley Watershed Model simulates the entire Salinas River watershed. Monthly surface water inflows into the integrated hydrologic model domain were simulated using the Salinas Valley Watershed Model. The historical model uses historical climate data, water and land use data, and reservoir releases to simulate agricultural operations, including landscape water demands, diversions, and reclaimed wastewater. The operational model adds an embedded reservoir operations framework to the simulation of the historical model that allows specified operational rules to simulate reservoir releases and changes in reservoir storage. The operational model assumes current reservoir operations and constant land use, which differs from historical conditions. Thus, the operational model is a hypothetical baseline model that can be used by local water managers to evaluate and quantify potential benefits of water supply projects. Together, the geologic framework, watershed, historical, and operational models form a tool that can be used to simulate irrigated agriculture and associated reservoir operations of the integrated hydrologic system of the Salinas Valley.

EarthArXiv↗