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USGS2025

Climate change and future water availability in the United States

The steady rise in global temperature as a result of human activity is causing changes in Earth’s water cycle. The balance of water stored within and moving between vapor, liquid, and frozen states in the water cycle is shifting, with consequences for water availability that include increases in drought, fire weather, flooding, and heavy precipitation, as well as cryosphere decline and sea-level rise. In this chapter of the U.S. Geological Survey Integrated Water Availability Assessment—2010–20, we provide an overview of climate-change observations and projections from Earth-system model simulations that relate to future water availability, from global and national climate assessments and from the published literature. Effects of climate change on primary water-cycle components are discussed in context of how global-scale hydroclimate drivers influence regional processes within the United States. Understanding the major climate drivers impacting the water cycle is crucial to predicting future changes in water availability and developing adaptation strategies to ensure human and ecosystem water supplies. First, we provide background information on the water cycle, the climate-model ensemble simulations developed to produce projections based on warming scenarios, and attribution and certainty levels. Tipping points, self-reinforcing feedbacks, cascading effects, and compound extremes are introduced. The framework of climatic impact drivers (CIDs) outlined in the Intergovernmental Panel on Climate Change Sixth Assessment Report (IPCC AR6) is used to show primary drivers of physical change to the water cycle and to understand and predict changes in future water availability. Specific climate-change related observations and projections are discussed for water cycle components of precipitation, evapotranspiration, soil moisture, streamflow, lakes and wetlands, ice and snow, and groundwater, as well as their implications for future water availability for humans and ecosystems. The chapter concludes with a synthesis discussion of three examples of complex regional-scale hydroclimate processes that influence water availability for populations in the United States, including (1) mountain and coastal precipitation, (2) aridification and drought, and (3) the influence of forest-cover change on terrestrial water-vapor recycling.

Professional Paper↗
USGS2000

Biodegradation of chlorinated ethenes at a karst site in middle Tennessee

This report presents results of field and laboratory investigations examining the biodegradation of chlorinated ethenes in a karst aquifer contaminated with trichloroethylene (TCE). The study site, located in Middle Tennessee, was selected because of the presence of TCE degradation byproducts in the karst aquifer and available site hydrologic and chlorinated-ethene information. Additional chemical, biological, and hydrologic data were gathered to evaluate whether the occurrence of TCE degradation byproducts in the karst aquifer was the result of biodegradation within the aquifer or simply transport into the aquifer. Geochemical analysis established that sulfate-reducing conditions, essential for reductive dechlorination of chlorinated solvents, existed in parts of the contaminated karst aquifer. Other areas of the aquifer fluctuated between anaerobic and aerobic conditions and contained compounds associated with cometabolism, such as ethane, methane, ammonia, and dissolved oxygen. A large, diverse bacteria population inhabits the contaminated aquifer. Bacteria known to biodegrade TCE and other chlorinated solvents, such as sulfate-reducers, methanotrophs, and ammonia-oxidizers, were identified from karst-aquifer water using the RNA-hybridization technique. Results from microcosms using raw karst-aquifer water found that aerobic cometabolism and anaerobic reductive-dechlorination degradation processes were possible when appropriate conditions were established in the microcosms. These chemical and biological results provide circumstantial evidence that several biodegradation processes are active in the aquifer. Additional site hydrologic information was developed to determine if appropriate conditions persist long enough in the karst aquifer for these biodegradation processes to be significant. Continuous monitoring devices placed in four wells during the spring of 1998 indicated that pH, specific conductance, dissolved oxygen, and oxidation-reduction potentials changed very little in areas isolated from active ground-water flow paths. These stable areas in the karst aquifer had geochemical conditions and bacteria conducive to reductive dechlorination of chlorinated ethenes. Other areas of the karst aquifer were associated with active ground-water flow paths and fluctuated between anaerobic and aerobic conditions in response to rain events. Associated with this dynamic environment were bacteria and geochemical conditions conducive to cometabolism. In summary, multiple lines of evidence developed from chemical, biological, and hydrologic data demonstrate that a variety of biodegradation processes are active in this karst aquifer.

Tennessee↗
USGS2024

Layered intrusions in the Precambrian: Observations and perspectives

Layered intrusions are plutonic bodies of cumulates that form by the crystallization of mantle-derived melts. These intrusions are characterized by igneous layering distinguishable by shifts in mineralogy, texture, or composition. Layered intrusions have been fundamental to our understanding of igneous petrology; however, it is their status as important repositories of critical metals – such as platinum-group elements, chromium, and vanadium – that has predominantly driven associated research in recent decades. Many layered intrusions were emplaced during the Precambrian, predominantly at the margins of ancient cratons during intervals of supercontinent accretion and destruction. It appears that large, layered intrusions require rigid crust to ensure their preservation, and their geometry and layering is primarily controlled by the nature of melt emplacement. Layered intrusions are best investigated by integrating observations from various length-scales. At the macroscale, intrusion geometries can be discerned, and their presence understood in the context of the regional geology. At the mesoscale, the layering of an intrusion may be characterized, intrusion-host rock contact relationships studied, and the nature of stratiform mineral occurrences described. At the microscale, the mineralogy and texture of cumulate rocks and any mineralization are elucidated, particularly when novel microtextural and mineral chemical datasets are integrated. For example, here we demonstrate how mesoscale observations and microscale datasets can be combined to understand the petrogenesis of the perplexing snowball oiks outcrop located in the Upper Banded Series of the Stillwater Complex. Our data suggest that the orthopyroxene oikocrysts did not form in their present location, but rather formed in a dynamic magma chamber where crystals were transported either by convective currents or within crystal-rich slurries. Critical metals may be transported to the level of a nascent intrusion as dissolved components in the melt. Alternatively, ore minerals are entrained from elsewhere in a plumbing system, potentially facilitated by volatile-rich phases. There are many ore-forming processes propounded by researchers to occur at the level of emplacement; however, each must address the arrival of the ore mineral, its concentration of metals, and its accumulation into orebodies. In this contribution, several of these processes are described as well as our perspectives on the future of layered intrusion research.

Precambrian Research↗
USGS2025

No evidence for an active margin-spanning megasplay fault at the Cascadia Subduction Zone

It has been previously proposed that a megasplay fault within the Cascadia accretionary wedge, spanning from offshore Vancouver Island to Oregon, has the potential to slip during a future Cascadia subduction zone earthquake. This hypothetical fault has major implications for tsunami size and arrival times and is included in disaster-planning scenarios currently in use in the region. This hypothesis is evaluated in this study using CASIE21 deep-penetrating and U.S. Geological Survey high-resolution seismic reflection profiles. We map changes in wedge structural style and seismic character to identify the inner-outer wedge transition zone where a megasplay fault has been previously hypothesized to exist and evaluate evidence for active faulting within this zone. Our results indicate that there is not an active, through-going megasplay fault in Cascadia, but instead, the structure and activity of faulting at the inner-outer wedge transition zone is highly variable and segmented along strike, consistent with the segmentation of other physical and mechanical properties in Cascadia. Wedge sedimentation, plate dip, and subducting topography are proposed to play a major role in controlling megasplay fault development and evolution. Incorporating updated megasplay fault location, geometry, and activity into modeling of Cascadia earthquakes and tsunamis could help better constrain associated hazards.

British Columbia, Oregon, Washington↗
USGS2024

Groundwater quality near the Placerita Oil Field, California, 2018

Groundwater-quality data and potential fluid-migration pathways near the Placerita Oil Field in Los Angeles County, California, were examined by the U.S. Geological Survey to determine if oil-field fluids (water and gas from oil-producing and non-producing zones) have mixed with groundwater resources. Six of the 13 new groundwater samples collected for this study contained petroleum hydrocarbons, thermogenic gas, inorganic chemical signatures, and (or) isotopic values consistent with potential mixing with fluids from hydrocarbon-bearing formations. For historical groundwater samples, benzene was the most detected petroleum hydrocarbon. The historical groundwater samples with a benzene concentration greater than 0.5 micrograms per liter were from environmental monitoring wells at industrial or commercial facilities unrelated to oil and gas development that, in many cases, have identified soil or groundwater contamination and were not typically analyzed for other constituents that could provide additional lines of evidence for potential mixing with oil-field fluids. Methane was not detected in any of the 12 historical samples with a reported measurement. Reviewing historical data revealed factors that could potentially adversely affect groundwater quality in the study area. These factors include modified hydraulic gradients caused by large volumes of water extracted from the main production area and reinjected downgradient into nonproducing zones, well-barrier failures in wells constructed in the northern part of the oil field before the 1970s, well-barrier failures in produced-water disposal wells downgradient from the main production area, and naturally occurring hydrocarbons at shallow intervals. The groundwater samples most geochemically similar to samples from hydrocarbon-bearing formations were in areas where hydrocarbons are naturally occurring at shallow intervals and where oil development is at shallow depths. Additional data for hydraulic heads, water quality, and formation temperatures at multiple depths in areas with large injection volumes and well-integrity issues are needed to evaluate whether those factors have contributed to mixing between fluids from oil-producing or injection formations and groundwater resources.

California↗
USGS2026

Bottom-up characterization of geologic methane emissions in the San Juan Basin in the southwestern USA

Methane is a potent greenhouse gas that plays an important role in atmospheric chemistry and global warming. The current global methane budget has large uncertainties, and a better understanding of the budget would help to guide strategies for reducing anthropogenic emissions to fight climate change. Natural geologic methane emissions are a particularly poorly constrained source, with top-down estimates from 14 C in ice cores suggesting much lower geologic emissions than bottom-up scaling of direct flux measurements. Our study aims to contribute to resolving this discrepancy through improved bottom-up characterization of geologic methane seepage in the San Juan Basin in southwestern Colorado and northwestern New Mexico, USA. We performed 983 new flux chamber measurements in this basin during summer 2022 and winter 2023 field campaigns. Our results, in combination with prior measurements, suggest that natural seepage in the San Juan Basin only occurs on or near the Fruitland coal outcrop. Specifically, our new measurements confirm previous measurements of seepage along the northwestern exposure of the Fruitland outcrop in Colorado (a known hydrodynamic overpressure region) and for the first time, identified seepage locations along the southernmost Fruitland outcrop exposure in New Mexico, in association with a coal cleat and a fault. Overall, seepage along the Fruitland coal outcrop is heterogeneously distributed, with both positive and negative (interpreted as microbial soil sink) methane fluxes. Features that are hypothesized to be predictive of seepage (e.g., faults) were not associated with positive methane fluxes in areas outside of the Fruitland outcrop. Our best estimate for total geologic methane seepage in the San Juan Basin from spatial interpolation and statistical upscaling is approximately 0.14 Tg CH 4 /yr, with a range from 0.029 to 0.48 Tg CH 4 /yr. This best-estimate value is lower than a previous bottom-up estimate from a gridded seepage inventory, but higher than a previous top-down estimate.

Colorado, New Mexico↗
USGS2025

Methods for estimating selected low-flow statistics at gaged and ungaged stream sites in Massachusetts

The U.S. Geological Survey, in cooperation with the Massachusetts Department of Conservation and Recreation, Office of Water Resources, computed selected at-site streamflow statistics at U.S. Geological Survey streamgages in and near Massachusetts and developed regional regression equations for estimating selected streamflows at ungaged stream sites in Massachusetts. Two sets of regional regression equations were developed: (1) the “mainland” equations, for mainland Massachusetts excluding the area covered by the second set, and (2) the “southeastern” equations, for the Plymouth-Carver-Kingston-Duxbury aquifer area in southeastern Massachusetts and for Cape Cod. The regression equations and at-site statistics may be used by Federal, State, and local water managers in addressing water-resources issues relevant in Massachusetts. Regional regression analyses for the mainland equations were developed to estimate the following 27 streamflow statistics: 99-, 98-, 95-, 90-, 85-, 80-, 75-, 70-, 60-, and 50-percent flow durations; monthly June, July, August, and September 90- and 50-percent flow durations; February, June, and August median of the monthly means; harmonic mean; and medians of the following annual low-flow frequency statistics: 7-day; 7-day, 2-year; 7-day, 10-year; 30-day, 2-year; and 30-day, 10-year. The analyses used 81 streamgages with minimal to no regulations in and near Massachusetts. The regression analyses determined that four basin characteristics—drainage area, combined hydrologic soils A and B, streamflow variability index, and annual mean temperature—were the only significant explanatory variables for the different mainland equations. Regional regression equations were developed for the Plymouth-Carver-Kingston-Duxbury aquifer area in southeastern Massachusetts and Cape Cod, because surface-water drainage areas and groundwater contributing areas do not always coincide in this area of the State. The regression analyses to estimate 10 flow durations from the 99th to 50th percentiles used 18 streamflow sites with some occasional minor regulations—because there are few unregulated streams in southeastern Massachusetts. The analyses determined that groundwater contributing area and storage (combined water bodies and wetlands) were the only significant explanatory variables in the southeastern equations.

Massachusetts↗
USGS2024

A comparative analysis of OpenET for evaluating evapotranspiration in California almond orchards

The almond industry in California faces water management challenges that are being exacerbated by droughts, climate change, and groundwater sustainability legislation. The Tree-crop Remote sensing of Evapotranspiration eXperiment (T-REX) aims to explore opportunities to improve precision irrigation management for woody perennial cropping systems. Almond orchards in the California Central Valley were equipped with eddy covariance flux measurements to evaluate satellite remote sensing-based evapotranspiration (RSET) models. OpenET provides high-resolution (30-m spatial and daily temporal) RSET data, synthesizing decades of research for practical water management. This study provides an evaluation of OpenET performance at six almond sites covering a large range in soils, age, and variety. It also compares OpenET ensemble evapotranspiration (ET) data with applied irrigation and precipitation records over an additional 148 almond orchards located in the Central Valley of California. Results show OpenET models, including the ensemble ET value, produced reasonable and actionable ET values, with overall coefficient of determination (R 2 ) and mean absolute error values of 0.73- and 0.95-mm d −1 at the daily time step, respectively. However, given the temporal sampling of Landsat (8-day revisit) and the interpolation methods used, the assessed ET models had difficulty in capturing short-term variability in almond ET; for example, the rapid decline in measured ET observed as a response to lack of irrigation preceding and during almond harvest. The study also drew attention to the spatial complexity in scenarios where irrigated orchards are surrounded by hot/dry areas, causing discrepancies between measured and modeled ET values. In comparison with irrigation records, OpenET ensemble ET was capable of quantifying water input (applied irrigation + precipitation) in almond orchards to within 13 % when evaluating monthly data. Initial results presented here reinforce the idea that RSET models, such as in OpenET, are powerful tools, yet their application requires nuanced understanding and careful consideration of local conditions.

California↗
USGS2025

Groundwater structures fish growth and production across a riverscape

Landscapes are composed of habitat patches and conditions that vary across space and time. While habitat variability and complexity can support important ecological processes and ecosystem services, the dynamic nature of habitats can also constrain organismal growth and production as optimal conditions are fleeting. In riverine ecosystems, groundwater discharge to streams stabilises water temperature and flow regimes, thus mediating how habitat complexity is expressed. Yet, how stable habitats structure growth and production within the broader landscape matrix is not well understood. In this study, we explored the effects of groundwater on spatiotemporal variation in growth and production for juvenile Yellowstone cutthroat trout ( Oncorhynchus virginalis bouvieri ) across the upper Snake River catchment, Wyoming, USA. We combined machine learning techniques and remotely sensed landscape data to estimate groundwater availability across the river network, which we linked to stream temperature regimes and conspecific density. We then used Bayesian hierarchical models to quantify the effects of temperature, density and groundwater on spatiotemporal variation in fish growth and production in 52 focal reaches. Finally, we predicted body size trajectories and trends in total production continuously over both space and time to understand the effect of groundwater at the riverscape scale. Groundwater discharged to streams where topography changes abruptly in valley-bottom areas underlain by coarse glacial deposits. Groundwater stabilised temperature regimes and was associated with high trout densities. Temperature and density, in turn, interacted to influence growth rates: growth increased strongly with temperature, but this effect was reduced when density was high. Accordingly, variation in groundwater availability among stream reaches diversified growth and production regimes. In reaches with low groundwater availability, growth and production declined over time from summer maxima. In contrast, in reaches with high groundwater availability, temporal trends in growth and production were hump-shaped—peaking in autumn—and mean production was greater. At the riverscape scale, temporal asynchrony in growth rates generated convergent spatial variation in growth capacity, but—when combined with density—led to the formation of distinct hotspots of production. Our results demonstrate how groundwater, an important driver of aquatic ecosystem heterogeneity, structures trout growth and production across space and time. Importantly, rare, but stable habitats may disproportionately affect ecological processes and serve as key sources of population diversity at larger spatial scales.

Wyoming↗
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↗
USGS2024

Reference 1D seismic velocity models for volcano monitoring and imaging: Methods, models, and applications

Seismic velocity models of the crust are an integral part of earthquake monitoring systems at volcanoes. 1D models that vary only in depth are typically used for real‐time hypocenter determination and serve as critical reference models for detailed 3D imaging studies and geomechanical modeling. Such models are usually computed using seismic tomographic methods that rely on P ‐ and S ‐wave arrival‐time picks from numerous earthquakes recorded at receivers around the volcano. Traditional linearized tomographic methods that jointly invert for source locations, velocity structure, and station corrections depend critically on having reasonable starting values for the unknown parameters, are susceptible to local misfit minima and divergence, and often do not provide adequate uncertainty information. These issues are often exacerbated by sparse seismic networks, inadequate distributions of seismicity, and/or poor data quality common at volcanoes. In contrast, modern probabilistic global search methods avoid these issues only at the cost of increased computation time. In this article, we review both approaches and present example applications and comparisons at several volcanoes in the United States, including Mount Hood (Oregon), Mount St. Helens (Washington), the Island of Hawai’i, and Mount Cleveland (Alaska). We provide guidance on the proper usage of these methods as relevant to challenges specific to volcano monitoring and imaging. Finally, we survey‐published 1D P ‐wave velocity models from around the world and use them to derive a generic stratovolcano velocity model, which serves as a useful reference model for comparison and when local velocity information is sparse.

Seismological Research Letters↗
USGS2024

Cross-fade sampling: Extremely efficient Bayesian inversion for a variety of geophysical problems

This paper introduces cross-fade sampling, a computationally efficient Markov Chain Monte Carlo simulation method that uses a semi-analytical approach to quickly solve Bayesian inverse problems that do not themselves have an analytical solution. Cross-fading is efficient in two ways. First, it requires fewer samples to obtain the same quality simulation of the target probability density function (PDF). Secondly, it is much faster to evaluate the posterior probability of each sample than conventional sampling methods for simulating Bayesian posterior PDFs. Conventional methods require evaluating the prior probability (which describes your a priori constraints) and data likelihood (which describes the fit between the observations and the predictions of the model) for each sample model. However, cross-fading does not require evaluating the data likelihood, meaning that ‘big data’ can be fit with zero additional computational cost. Further, the cross-fading approach can be used to calculate the marginal likelihood associated with a model design, facilitating model comparison and Bayesian model averaging. Topics covered in this paper include derivation of the cross-fade approach and how it can be used to simulate Bayesian posterior PDFs and compute the marginal likelihood, discussion of the class of problems to which cross-fading can be applied (with examples from earthquake statistics, earthquake ground motion modelling, volcanic eruption forecasting, and finite fault slip modelling), demonstration of efficiency relative to existing sampling methods and discussion of how cross-fading can be used to account for prediction errors (i.e. epistemic errors) as part of the geophysical inverse problem.

Geophysical Journal International↗
USGS2024

Three-dimensional temperature maps of the Williston Basin, USA: Implications for deep hot sedimentary and enhanced geothermal resources

As part of U.S. Geological Survey's (USGS) efforts to identify and assess geothermal energy resources of the US, a three-dimensional (3D) geologic and thermal model has been constructed for the Williston Basin, USA. The geologic model consists of all sedimentary units above the Proterozoic and Archean crystalline rock (called basement herein), with a total sedimentary thickness of up to 5 km near the basin center. Twenty-nine geologic units were mapped from interpreted formation tops from 16,465 wells. A 3D temperature model was constructed to a depth of 7 km by constructing a 3D heat flow model for the sedimentary units, followed by estimating underlying temperature using a one-dimensional (1D) analytic solution for heat flow within the underlying crystalline basement. Using the sedimentary basin model, heat flow was simulated in 3D and was calibrated using three temperature datasets: 1) 24 high-confidence static temperature logs (equilibrium thermal profiles), 2) more than15,000 drill stem test (DST) measurements from >7,000 wells, and 3) more than 45,000 bottomhole temperature (BHT) measurements from >14,000 wells. The DST and BHT datasets provide broad spatial coverage, but are lower confidence, primarily because measurements were made prior to attaining thermal equilibrium. DST and BHT measurements were binned regionally to develop representative thermal profiles that generally agree with these lower quality data (hereafter called pseudowell temperature profiles). Layer properties (primarily thermal conductivity and compaction curves) were set to best estimate values, then the heat flow model was calibrated to fit pseudowell and static temperature logs primarily by adjusting basal heat flow to approximate the overall temperature profile. Minor adjustments to thermal conductivity allowed adjusting changes in slope at lithologic contacts. Resulting maps include 3D temperature and basal (bottom of sedimentary units) heat flow estimates, which are used as input for the temperature model of the basement. The crystalline basement temperature model uses an analytic 1D solution to the heat flow equation that requires estimates of heat flow and temperature at the upper boundary (i.e., the sediment/basement contact), radiogenic heat production within the crystalline basement, and reference thermal conductivity (i.e., uncorrected for temperature). Two regions of high heat flow are identified: 1) in western North Dakota along the North American Central Plains Conductivity Anomaly and 2) in eastern Montana near the Poplar dome. Within the sedimentary column in the center of the basin of the basin, an area of approximately 100,000 km2 is predicted to have moderate- to high-temperature geothermal resources (>90 °C) under the thickest sequences of sediments. Where thick insulation and high heat flow coincide, electric-grade resources can be less than 4 km deep. Assuming a maximum feasible drilling depth of 7 km, temperatures are predicted to be as high as 175 °C. The geologic model may be used to identify strata at sufficient temperatures that may have natural permeability or that may have conditions that favor development of enhanced/engineered geothermal systems resources.

Montana, North Dakota, South Dakota↗
USGS2025

Near-fault amplification and ground motion variability during the 2019 Ridgecrest, California sequence

We estimate ground-motion variability near the 2019 M 7.1 Ridgecrest earthquake sequence. Accurate seismic hazard estimation requires understanding ground-motion spatial correlations, yet many studies lack the dense station coverage needed to resolve small-scale variability. The 2019 M 7.1 Ridgecrest earthquake sequence presents a unique opportunity to examine ground motions and their spatial correlations at a range of interstation distances. The permanent seismic network was augmented with hundreds of temporary stations including several fault-crossing nodal arrays. We compute the event ( δE i ) and within-event ( δW ij ) residuals from the observed peak ground velocity and peak ground acceleration data to isolate potential sources of ground-motion variability. We then compare δW ij between station pairs that record an event to understand the semivariance of the ground motion versus interstation distance. By fitting an exponential model to the semivariances, we determine a correlation range of 25 km for the Ridgecrest region. Although the exponential model fits the broad-scale increase of semivariance with interstation distance, we also observe smaller-scale trends. We find that ground motions are less correlated for station pairs that are near or across faults that ruptured during the 2019 Ridgecrest sequence. We also find large, positive median δW ij with relative values 2–3 times larger than nearby stations for individual stations’ near-fault traces. Near-fault amplification and greater ground-motion variability can delineate fault zones and may locally increase the seismic hazard.

California↗
USGS2025

Hydrogeologic framework and conceptual model of the Red River alluvial aquifer east of Lake Texoma, southeastern Oklahoma, 1980–2022

The 1973 Oklahoma Groundwater Law (Oklahoma Statutes §82-1020.5) requires that the Oklahoma Water Resources Board conduct hydrologic investigations of the State’s groundwater basins to support a determination of the maximum annual yield for each groundwater basin. At present (2025), the Oklahoma Water Resources Board has not established a maximum annual yield for the Red River alluvial aquifer east of Lake Texoma. To support the evaluation and determination of a maximum annual yield, a hydrogeologic framework and conceptual groundwater-flow model were developed to assess groundwater availability in the Red River alluvial aquifer east of Lake Texoma. The scope of this hydrologic investigation is the alluvium and terrace containing the Red River alluvial aquifer in Oklahoma between Lake Texoma, the Texas State line, and the Arkansas State line, an extent referred to in this report as “the eastern part of the Red River alluvial aquifer.” Parts of the alluvium and terrace extent in Arkansas and Texas are included in some analyses to address hydrologic influences from outside the aquifer’s boundaries in Oklahoma. The eastern part of the Red River alluvial aquifer in southeastern Oklahoma consists of approximately 401,280 acres of Quaternary alluvium and terrace deposits associated with the Red River and its major tributaries. Mean annual recharge to the aquifer for the 1980–2022 study period was estimated to be 8.62 inches per year, or 17.98 percent of the mean annual precipitation over the same period (47.94 inches). This mean annual recharge rate is equivalent to an inflow of approximately 288,250 acre-feet per year for the eastern part of the Red River alluvial aquifer. Recharge estimated using the Soil-Water-Balance code accounts for 98.7 percent of the conceptual-model inflows to the eastern part of the Red River alluvial aquifer. Saturated-zone evapotranspiration accounts for 11.9 percent and net streambed seepage accounts for 87.4 percent of the outflows in the conceptual model.

Arkansas, Oklahoma, Texas↗
USGS2024

Onset of aftershocks: Constraints on the Rate-and-State model

Aftershock rates typically decay with time t after the mainshock according to the Omori–Utsu law, R (t)=K(c+t) −p ⁠ , with parameters K , c , and p . The rate‐and‐state (RS) model, which is currently the most popular physics‐based seismicity model, also predicts an Omori–Utsu decay with p = 1 and a c ‐value that depends on the size of the coseismic stress change. Because the mainshock‐induced stresses strongly vary in space, the c ‐value should vary accordingly. Short‐time aftershock incompleteness (STAI) in earthquake catalogs has prevented a detailed test of this prediction so far, but the newly developed a ‐positive method for reconstructing the true earthquake rate now allows its testing. Using previously published slip models, we calculate the coseismic stress changes for the six largest mainshocks in Southern California in recent decades and estimate the maximum shear as a scalar proxy of the coseismic stress tensor. Aftershock rates reconstructed for events in different stress ranges show that the rates follow a power law with p = 1 independent of stress with no clear sign of a c ‐value. The onset of the power‐law decay is abrupt and more delayed in areas with smaller stress changes. The observations do not necessarily contradict the RS model, as STAI limits the resolution for early aftershocks, and the RS model can reproduce the observations for specific Aσ values. However, the observations lead to strong constraints, namely Aσ <10 kPa and a power‐law decay of the background rate with distance to the fault, with exponent 2.7.

Seismological Research Letters↗
USGS2025

Collaborative drought science planning in the Colorado River Basin

The U.S. Geological Survey (USGS) is using collaborative, interdisciplinary planning to develop data and tools needed to optimize the management of water resources and land use by resource management agencies during an ongoing, multidecadal drought in the Colorado River Basin. The USGS Actionable and Strategic Integrated Science and Technology team works to build relationships with resource management agencies and other stakeholders who can benefit from the use of USGS data and products. In 2023, the Actionable and Strategic Integrated Science and Technology team hosted a series of collaborative workshops to bring together representatives of resource management agencies and other stakeholders (any person or entity with interests in a resource or location) with USGS program managers, scientists, and multidisciplinary subject matter experts to codevelop concepts for interdisciplinary drought science and technology projects to address pressing needs related to drought in the Colorado River Basin. Workshop participants identified current and recent scientific data that could be shared through a centralized online data portal. Workshop participants also identified drought science and technology needs and developed project concepts to address those science needs. Participants categorized project concepts based on their potential to develop short-, mid-, and long-term drought science data and tools, provide for the spatial or temporal expansion of ongoing USGS science projects, and address high-priority science needs. Participants developed nine project concepts: (1) understanding shifting ecohydrologic baselines, (2) San Juan River Basin synthesis, (3) incorporating dynamic land cover into hydrologic models, (4) aridification compared to drought, (5) surface water-groundwater interactions, (6) cascading effects of drought on dust, (7) cascading effects of drought on water availability, (8) cascading effects of drought on socioeconomic factors, and (9) the value of water in the Colorado River Basin. This report provides an overview of the 2023 Codesign Workshop Series, synthesized outcomes from workshop materials and discussions, and science project concepts that emerged from the collaborative meetings that will continue to be refined into science project proposals through codevelopment processes. This report also highlights lessons learned and next steps needed to receive feedback and testing of the USGS Science Collaboration Portal, continue collaboration to develop detailed specifics and steps for short-term wins, develop interdisciplinary project proposals, and implement science planning and studies.

Arizona, California, Colorado, Nevada, New Mexico,↗
USGS2024

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

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

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