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1,658 records · Page 60Linked to original sources
USGS2025

Evidence for fluid pressurization of fault zones and persistent sensitivity to injection rate beneath the Raton Basin

Subsurface wastewater injection has increased the seismicity rate within the Raton Basin over more than two decades, with the basin-wide injection rate peaked between 2009-2015. To understand the evolution of injection-induced earthquakes, we systematically analyzed 2016-2024 broadband recordings with a machine-learning-based phase picker and constructed a catalog with 95,993 earthquakes (-1≤ M L ≤4.3). We then inverted for full centroid moment tensors (CMT) for 90 M L ≥ 2 events, with a special interest in constraining the non-double-couple components via probabilistic metrics. Both relocations and CMT solutions support basement-rooted normal faults, including graben and half-graben structures. Furthermore, we observe the non-double-couple components that imply elevated pore pressure in the fault zones. An earthquake cluster emerged in the north-central basin in 2023, preceded by ~1-yr of increased injection volume from wells within 15km. Despite a basin-wide decrease in the injection volume, we highlights the persistence of seismicity that remains to sensitive to injection rates within the Raton Basin.

Colorado, New Mexico↗
USGS2025

Beyond optimality: Dryland ecosystems infrequently use water efficiently for carbon gain

Optimality theory assumes plants maximize carbon gain per unit water lost and is often implemented to scale leaf-level carbon gain and water use to regional and global scales. Optimality theory is often mathematically represented by assuming plant water-use efficiency (WUE) scales with VPD k , where k = ½ represents expected optimal behavior. It is unclear, however, if this relationship holds in arid and semi-arid ecosystems that are strongly impacted by soil and atmospheric moisture status. We used data from seven flux tower sites along an aridity gradient in New Mexico to answer: how does the relationship between WUE and VPD compare to expectations based on optimality theory? To address this question, we integrated the Dynamic Evapotranspiration Partitioning Approach for Rapid Timescales with a stochastic antecedent model to estimate ecosystem-level WUE (GPP/T) and the net sensitivity of WUE to VPD, or k Dynamic , which we compare to the theoretical optimal sensitivity of k = ½. Our results show that optimality theory is not always appropriate, and k Dynamic often deviates from ½, especially at some of the more arid sites or during periods of low soil moisture. At less arid, higher elevation sites, k Dynamic is most consistent with optimality theory at moderate VPD levels, but not at high VPD. In general, the sensitivity of WUE to VPD is highly variable such that k Dynamic exhibits notable daily and seasonal variability, suggesting highly dynamic stomatal behavior. These results emphasize that representing plant water-use strategies as dynamic in time and space is critical to improving large-scale estimates of plant water use.

New Mexico↗
USGS2025

Mine waste as a potential source of critical minerals and other commodities: Examples from the Four Corners states, USA

The growing demand for critical minerals and other mineral resources has raised concerns about possible supplies of these essential commodities. Mine waste is a potential source of these essential commodities. We compiled a geospatial database of publicly available data of the largest non-fuel mine waste features (>200,000 m 2 in areal extent) in the Four Corners states of the United States, where most of those features are from porphyry Cu deposits. The combined volume of those large porphyry Cu mine waste features is approximately 17 cubic kilometers, 60% of which is ore-related material such as tailings. Using publicly available data on density, grade, and previous recovery values, we estimate the contained endowments of Ag, As, Au, Bi, Cu, Mo, Re, S, Sb, Se, Te, and W. These estimates indicate endowments within ore-related mine wastes are collectively comparable to endowments of giant to supergiant deposits. If fully recovered, these commodities could meet current global demand from less than 1 year (Sb) to more than 200 years (Re), underscoring the enormous untapped resource potential of mine waste.

Arizona, Colorado, New Mexico, Utah↗
USGS2025

Hydrogeologic investigation, framework, and conceptual flow model of the Antlers aquifer, southeastern Oklahoma, 1980–2022

The 1973 Oklahoma Groundwater Law (Oklahoma Statute §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. Every 20 years, the Oklahoma Water Resources Board is required to update the hydrologic investigation on which the maximum annual yield determinations were based. The maximum annual yield allocated per acre of land is used to set the equal-proportionate share pumping rate. The maximum annual yield of 5,913,600 acre-feet per year and equal-proportionate-share of 2.1 acre-feet per acre per year currently (2025) in place for the Antlers aquifer were issued by the Oklahoma Water Resources Board on February 14, 1995. Because more than 20 years have elapsed since the 1995 final order for the Antlers aquifer was issued, the U.S. Geological Survey, in cooperation with the Oklahoma Water Resources Board, completed an in-depth hydrologic study that included a hydrogeologic framework and conceptual groundwater-flow model for the 1980–2022 study period. The results of an analysis of land use, long-term climate patterns, streamflow and base-flow patterns, historical groundwater use, as well as groundwater-level fluctuations across the Antlers aquifer are described. In addition, groundwater quality was analyzed for total dissolved solids concentrations and major ions for the Antlers aquifer. An updated hydrogeologic framework was developed that included refining the aquifer boundary in Oklahoma, the creation of new potentiometric surface and saturated thickness of fresh groundwater maps, one multiple-well aquifer test, slug tests, and an analysis of lithologic logs across the aquifer. A conceptual groundwater flow model and water budget were developed by incorporating estimates of recharge from precipitation, saturated-zone evapotranspiration, streambed seepage, lateral groundwater flows, vertical leakage, and withdrawals from groundwater wells.

Oklahoma, Texas↗
USGS2025

Introduction to the special section on improving measurements of earthquake source parameters

Earthquake source parameters such as magnitude, seismic moment, source dimension, stress drop, and radiated energy are fundamental to understanding earthquake physics, and are also key ingredients in earthquake ground‐motion modeling, rupture simulation, and statistical seismology. However, the uncertainties in these parameters estimated from the radiated seismic wavefield are large due to variability in approaches, including site and attenuation characterizations, and so estimates for an individual earthquake made by different studies can vary greatly. Estimating spectral source parameters remains a popular topic, due to a combination of their intrinsic importance and their apparent ease of measurement, but also a controversial one, due to many sources of variability and large uncertainty. The available methods coupled with necessary parameter choices and assumptions in the analysis make it challenging for researchers to apply methods or understand the reliability in results or reported source parameters. This Special Section on Improving Measurements of Earthquake Source Parameters showcasing comparisons between methods and studies seeks to alleviate some of these difficulties to help the community identify the important components and trade‐offs of decomposing recorded seismograms into their source, path, and site components.

Bulletin of the Seismological Society of America↗
USGS2000

Pesticides in surface waters of the Upper Colorado River Basin, Colorado, 1996-98

Forty-four river, stream, and drain sites in the Upper Colorado River Basin in Colorado were sampled during 1996-98 to determine the occurrence and distribution of pesticides in the basin. In a fixed-station study, 57 surface-water samples were collected from October 1996 through January 1998 at four sites. Each site was sampled approximately monthly for up to a year, with more frequent sampling during the spring and summer growing season. In a synoptic study, surface-water samples were collected at 43 sites in the agricultural areas of the Grand Valley and the Uncompahgre River Valley in May 1998. Each site was sampled once. Pesticide concentrations generally were low and varied seasonally and across land uses. Thirty-five pesticides were detected at least once in the two studies, and 11 pesticides accounted for almost 82 percent of the detections. Herbicides were more commonly detected than insecticides, and only the herbicides alachlor and atrazine were detected in more than 50 percent of the samples. Carbofuran was the most commonly detected insecticide and was detected in 19 percent of the samples. Pesticide detections increased and were measured at higher concentrations in the summer months and at the agriculture sites. All pesticide concentrations were less than drinking-water standards, and most complied with human-health advisories and criteria for the protection of freshwater aquatic life. Pesticides in the Upper Colorado River Basin in Colorado were detected slightly less frequently and generally at lower concentrations than in 20 National Water-Quality Assessment Program study-unit basins that collected water-quality data from 1992 through 1996. Results from surface-water sampling conducted during 1996?98 in the Upper Colorado River Basin in Colorado indicate that beneficial uses of water were not being impaired by the presence of pesticides in surface waters in the basin.

Colorado↗
USGS1996

Magnitude and frequency of low flows in the Suwannee River Water Management District, Florida

Low-flow frequency statistics for 20 gaging stations having at least 10 years of continuous record and 31 other stations having less than 10 years of continu ous record or a series of at least two low- flow measurements are presented for unregulated streams in the Suwannee River Water Management District in north-central Florida. Statistics for the 20 continuous-record stations included are the annual and monthly minimum consecutive-day average low- flow magnitudes for 1, 3, 7, 14, and 30 consecutive days for recurrence intervals of 2, 5, 10, 20, and, for some long-term stations, 50 years, based on records available through the 1994 climatic year.Only theannual statistics are given for the 31 other stations; these are for the 7- and 30-consecutive day periods only and for recurrence intervals of 2 and 10 years only. Annual low-flow frequency statistics range from zero for many small streams to 5,500 cubic feet per second for the annual 30- consecutive-day average flow with a recurrenceinterval of 2 years for the Suwannee River near Wilcox (station 02323500). Monthly low-flow frequency statistics range from zero for many small streams to 13,800 cubic feet per second for the minimum 30-consecutive-day average flow with a 2-year recurrence interval for the month of March for the same station. Generally, low-flow characteristics of streams in the Suwannee River Water Management District are controlled by climatic, topographic, and geologic fac tors. The carbonate Floridan aquifer system underlies, or is at the surface of, the entire District. The terrane's karstic nature results in many sinkholes and springs. In some places, springs may contribute greatly to low streamflow and the contributing areas of such springs may include areas outside the presumed surface drainage area of the springs. In other places, water may enter sinkholes within a drainage basin, then reappear in springs downstream from a gage. Many of the smaller streams in the District go dry or have no flow for several months in many years. In addition to the low-flow statistics, four synoptic low-flow measurement surveys were conducted on 161 sites during 1990, 1995, and 1996. The measurements were made to provide "snapshots" of flow conditions of streams throughout the Suwannee River Water Management District. Magnitudes of low flows during the 1990 series of measurements were in the range associated with minimum 7-consecutive-day 50-year recurrence interval to the minimum 7-consecutive-day 20-year recurrence interval, except in Taylor and Dixie Counties, where the magnitudes ranged from the minimum 7-consecutive-day 5-year flow level to the7-consecutive-day 2-year flow level. The magnitudes were all greater than the minimum 7- consecutive-day 2-year flow level during 1995 and 1996. Observations of no flow were recorded at many of the sites for all four series of measurements.

Florida↗
USGS2025

Invasion of perennial sagebrush steppe by shallow-rooted exotic cheatgrass reduces stable forms of soil carbon in a warmer but not cooler ecoregion

Soil organic carbon ('SOC') in drylands comprises nearly a third of the global SOC pool and has relatively rapid turnover and thus is a key driver of variability in the global carbon cycle. SOC is also a sensitive indicator of longer-term directional change and disturbance-responses of ecosystem C storage. Biome-scale disruption of the dryland carbon cycle by exotic annual grass invasions (mainly Bromus tectorum, 'Cheatgrass') threatens carbon storage and corresponding benefits to soil hydrology and nutrient retention. Past studies on cheatgrass impacts mainly focused on total C, and of the few that evaluated SOC, none compared the very different fractions of SOC, such as relatively unstable particulate organic carbon (POC) or relatively stable, mineral-associated organic carbon (MAOC). We measured SOC and its POC and MAOC constituents in the surface soils of sites that had sagebrush canopies but differed in whether their understories had been invaded by cheatgrass or not, in both warm and relatively colder ecoregions of the western USA. MAOC stocks were 36.1% less in the 0–10 cm depth and 46.1% less in the 10–20 cm depth in the cheatgrass-invaded stands compared to the uninvaded stands of the warmer Colorado Plateau, but not in the cooler and more carbon-rich Wyoming Basin ecoregion. In plots where cheatgrass increased SOC, it was via unstable POC. These findings indicate that cheatgrass effects on the distribution of soil carbon among POC and MAOC fractions may vary among ecoregions, and that cheatgrass can reduce forms of carbon that are otherwise considered stable and 'secure', i.e. sequestered.

Environmental Research Communications↗
USGS2026

Complex carbonate ore mineralogy in the Mountain Pass carbonatite rare earth element deposit, USA

Economic concentrations of rare earth element (REE) minerals are uncommon in the Earth’s crust, with most occurring in carbonatites. Unlike most igneous rocks composed of silicate minerals, carbonatites are dominated by carbonate minerals, some of which can incorporate significant light REEs (LREEs; La, Ce, Pr, Nd). Technological applications of REEs are numerous and they have been identified as some of the most critical mineral commodities to the global economy. The Mountain Pass carbonatite stock in the Mojave Desert of California is the most economically significant REE deposit in the USA and contains a few to tens of percent (by volume) of the carbonate REE ore mineral bastnäsite. Despite the economic significance of the Mountain Pass deposit, studies of its ore mineralogy are limited. Here we present new carbonate ore mineralogy data for a compositionally diverse suite of carbonatitic rocks from the Mountain Pass stock and related dikes. Whole-rock geochemical data are integrated with mineral-scale textural and chemical data obtained by scanning electron microscopy (SEM), electron probe microanalysis (EPMA), and microRaman spectroscopy. Our results document a complex spectrum of REE-bearing carbonate minerals and intermediate mixed-layer structures. Mineral species include bastnäsite [REE(CO 3 )F], hydroxylbastnäsite [REE(CO 3 )OH], parisite [Ca(REE) 2 (CO 3 ) 3 F 2 ], synchysite [Ca(REE)(CO 3 ) 2 F], röntgenite [Ca 2 (Ce,La) 3 (CO 3 ) 5 F 3 ], and sahamalite [(Mg,Fe 2+ )(REE) 2 (CO 3 ) 4 ]. Carbonate ore mineralogy is heterogeneous within and between samples, including at the intracrystal scale. Complexly zoned crystals exhibit as many as five to six different compositional domains and syntaxial intergrowths, commonly with the more Ca-rich varieties (parisite, synchysite) forming crystal rims that surround relict bastnäsite cores. We attribute the phenocryst variability to changes in the chemistry and temperature of primary carbonatite magmas and evolved/exsolved fluids. Cross-cutting vein textures of calcite, celestine and various REE carbonate minerals, interstitial bastnäsite crystallization, breccia blocks lined by fine-grained bastnäsite, and the presence of hydroxylbastnäsite and partially hydroxylated bastnäsite point to the role of secondary hydrothermal processes in REE mineralization. Fluorcarbonate mineral compositions demonstrate that La and Ce are more structurally abundant in bastnäsite, whereas the more Ca-rich species (parisite, synchysite) contain a greater proportion of REE heavier than Pr (Nd, Sm, Eu, Gd) and Y. Atomic ratios of Pr/(Nd + Pr) are likewise variable, with the highest average value for bastnäsite (0.25) compared to parisite (0.22) and sychysite (0.21). This finding has geometallurgical implications, given that current mining operations are focused on recovery of Nd and Pr for high field strength permanent magnets and the Nd/Pr ratios are a critical factor in ore processing and magnet manufacture.

California↗
USGS2024

Nitrogen deposition weakens soil carbon control of nitrogen dynamics across the contiguous United States

Anthropogenic nitrogen (N) deposition is unequally distributed across space and time, with inputs to terrestrial ecosystems impacted by industry regulations and variations in human activity. Soil carbon (C) content normally controls the fraction of mineralized N that is nitrified ( ƒ nitrified ), affecting N bioavailability for plants and microbes. However, it is unknown whether N deposition has modified the relationships among soil C, net N mineralization, and net nitrification. To test whether N deposition alters the relationship between soil C and net N transformations, we collected soils from coniferous and deciduous forests, grasslands, and residential yards in 14 regions across the contiguous United States that vary in N deposition rates. We quantified rates of net nitrification and N mineralization, soil chemistry (soil C, N, and pH), and microbial biomass and function (as beta-glucosidase (BG) and N -acetylglucosaminidase (NAG) activity) across these regions. Following expectations, soil C was a driver of ƒ nitrified across regions, whereby increasing soil C resulted in a decline in net nitrification and ƒ nitrified . The ƒ nitrified value increased with lower microbial enzymatic investment in N acquisition (increasing BG:NAG ratio) and lower active microbial biomass, providing some evidence that heterotrophic microbial N demand controls the ammonium pool for nitrifiers. However, higher total N deposition increased ƒ nitrified , including for high soil C sites predicted to have low ƒ nitrified , which decreased the role of soil C as a predictor of ƒ nitrified . Notably, the drop in contemporary atmospheric N deposition rates during the 2020 COVID-19 pandemic did not weaken the effect of N deposition on relationships between soil C and ƒ nitrified . Our results suggest that N deposition can disrupt the relationship between soil C and net N transformations, with this change potentially explained by weaker microbial competition for N. Therefore, past N inputs and soil C should be used together to predict N dynamics across terrestrial ecosystems.

contiguous United States↗
USGS1998

Stream habitat characteristics at selected sites in the Georgia-Florida coastal plain

Habitat characterization is part of a multidisciplinary approach to water-quality assessment implemented by the National Water-Quality Assessment Program. Habitat data were collected in the Georgia-Florida Coastal Plain study unit at 24 sites during 1993-95. Data were collected for habitat characteristics at three spatial scales: basin, segment, and reach. Basin data include physiography, land resource provinces, and land use, providing a description of the environmental setting at each site. Segment data include length, gradient, and sinuosity. A Kendall correlation analysis performed on segment characteristics and the log-of-basin area showed a correlation between segment gradient and the log-of-basin area and a correlation between sinuosity and segment length. Reach data consist of field-collected measurements of both instream and riparian habitats. Sand and detritus were the most common channel-bed substrates among the sampled sites. Measurements of channel width, water depth, and bank width and height were used to create cross-sectional profiles of each sampled area. Elevations of selected durations plotted on cross sections illustrated the percentage of time that the banks were inundated at each site. Sites were divided into two groups based on duration of bank inundation (less than or equal to 1 percent and greater than 1 percent). Bank woody vegetation was also sampled and a clustering algorithm known as Two-Way INdicator SPecies ANalysis (TWINSPAN) was used to analyze these data. TWINSPAN divided the sites into two groups based on their vegetation composition. A statistical comparison of the two types of site groups (duration of bank inundation and vegetation) was performed. The significant association between these groups was consistent with the hypothesis that inundation frequency affected riparian vegetation.

Florida, Georgia↗
USGS2024

Characterization of change in tree cover state and condition over the conterminous United States

Variability in the effects of disturbances and extreme climate events can lead to changes in tree cover over time, including partial or complete loss, with diverse ecological consequences. It is therefore critical to identify in space and time the change processes that lead to tree cover change. Studies of change are often hampered by the lack of data capable of consistently detecting different types of change. Using the Landsat satellite record to create a long time-series of land cover and land cover change, the U.S. Geological Survey Land Change Monitoring Assessment and Projection (LCMAP) project has made an annual time series of land cover across the conterminous United States for the period 1985 to 2018. Multiple LCMAP products analyzed together with map validation reference plots provide a robust basis for understanding tree cover change. In LCMAP (Collection 1.2), annual change detection is based on harmonic model breaks calculated at each Landsat pixel from the Continuous Change Detection and Classification (CCDC) algorithm. The results showed that the majority of CCDC harmonic model breaks (signifying change) indicated partial tree cover loss (associated with management practices such as tree cover thinning) as compared to complete tree cover loss (associated with practices like clearcut harvest or fire disturbance). Substantially fewer occurrences of complete tree cover loss were associated with change in land cover state. The area of annual tree cover change increased after the late 1990s and stayed high for the rest of the study period. The reference data showed that tree harvest dominated across the conterminous United States. The majority of tree cover change occurred in evergreen forests. Large estimates of disturbance-related tree cover change indicated that tree cover loss may have previously been underreported due to omission of partial tree cover loss in prior studies. This has considerable implications for forest carbon accounting along with tracking ecosystem goods and services.

Forests↗
USGS2024

Methods to evaluate and improve the modeling of rupture directivity in assessment of seismic hazard

In recent years, there have been several advancements related to the modelling of near-source effects of earthquake rupture on strong ground shaking, leading to an improved characterization of ground motions and resulting seismic hazard. Some of these modifications have stemmed from physics-based numerical modelling of the earthquake rupture process, using physics-based dynamic rupture simulations. These contributions have led to a better understanding of how fault rupture characteristics, geometry, and the style of faulting can interact with the hypocenter-dependence on the path from source to site that may ultimately guide the development of seismic directivity models. Moving forward, the application of modern techniques can be used to incorporate these source characteristics and near-fault ground motion behavior that contribute to the azimuthally varying effects that result in rupture directivity. One example is the application of machine learning methods to support more automated integration of new predictor variables in model development and open more evaluation opportunities to access residuals. Here, we utilize several techniques to take advantage of the plethora of synthetic data and its ability to supplement preexisting trends observed in data. We showcase two examples of how models can be either developed, expanded upon, or constrained using artificial neural network model (ANNs). We evaluate the performance of the ANN with existing methods, comparing misfit, potential limitations, and ability to continue to improve upon these methods in the future. One approach uses a set of simulations with corresponding synthetic ground motions from the Southern California Earthquake Center (SCEC) CyberShake study to develop a ground motion model adapted to incorporate seismic directivity information using an ANN. This large database (TBs) enables us to train the model to capture magnitude, period, and distance variations and how these parameters relate to amplification from hypocenters located along finite-faults. In some cases, there is reduced misfit from better representing source features that aren’t included in base ground motion models that neglect hypocenter location (e.g. azimuthal variation, source-to-site terms). Another ANN method uses a shallow-layered neural network model to better fit a hypocenter-independent model. This method adjusts the median and aleatory variability to account for the averaged impact of various hypocenter distributions to fit the underlying directivity adjustment model. This method serves as a template to apply to other directivity models, improving computational efficiency and more readily enabling integration in hazard codes.

California↗
USGS2025

Water resources related to breccia pipe uranium mining in the Grand Canyon region

Introduction In the arid Grand Canyon region, water resources are limited to primarily the Colorado River and associated tributaries and to groundwater in the form of seeps and springs. Groundwater resources in the region supply water for human use and support diverse and rich ecosystems in the locations immediately surrounding the seeps and springs. Throughout the region, uranium resources occur and may interact with water resources in both mined and unmined uranium deposits. There is a need to better understand groundwater in the region and the effects from uranium mining in order to better manage the limited water resources in the area. This Fact Sheet summarizes results from U.S. Geological Survey studies that were conducted on this topic from 2012 to 2023.

Arizona↗
USGS2026

Localization of spatiotemporally heterogeneous subsurface flows using autoencoder-based deep learning framework for time-lapse self-potential tomography

Self-potential (SP) monitoring has emerged as a valuable method for characterizing subsurface hydrogeological features and processes due to its sensitivity to fluid-induced electrokinetic effects. Despite advancements in SP inversion, challenges remain in imaging groundwater dynamics from SP activities due to complex hydrological settings and transient noise. In this study, a deep learning autoencoder (AE)-based framework is proposed for the spatiotemporal localization of subsurface fluid movement from time-lapse SP tomography. Temporal segments of time-lapse numerical inversions were first derived from long-term SP monitoring conducted from a floodplain site in Oak Ridge, Tennessee, known for active hyporheic exchange. Subsequently, AE models based on vision transformer (ViT), convolutional long short-term memory (ConvLSTM), convolutional neural network, and temporal convolutional network were individually trained and compared on the SP tomography segments for reconstruction performance. Finally, the reconstruction error over time serves as an anomaly score to identify moments of active SP variation, whereas spatial distributions of errors within these moments are analyzed to image and localize regions associated with anomalous subsurface fluid movement. The results demonstrate that ConvLSTM- and ViT-AE are most capable for the localization task with contrasting error distributions and consistent delineation of anomalies. Applying the method to both SP arrays parallel and perpendicular to the stream produced consistent anomaly zones near a fault or karst feature, validating the robustness and generalization of the approach. These results demonstrate the potential of the proposed framework as a scalable and interpretable tool for spatiotemporal analysis of subsurface flow dynamics in complex hydrogeological systems.

Tennessee↗
USGS2025

Simulation of the impacts of spring diversions on streamflow in the Strawberry Creek watershed, San Bernardino County, California, using an integrated hydrological model

The Strawberry Creek watershed, situated in the San Bernardino Mountains of southern California, features a group of natural springs known as Arrowhead Springs that have been augmented with diversions in the form of sub-horizontal borings and tunnels. Understanding the impact of these structures on streamflow through groundwater capture is crucial for managing surface-water resources in this watershed. In this study we constructed the Strawberry Creek integrated hydrological model (SCIHM) to increase this understanding. The SCIHM is an integrated surface runoff and groundwater model that uses the coupled groundwater and surface-water flow model (GSFLOW), which is based on the integration of the precipitation-runoff modeling system (PRMS) and the modular groundwater flow model commonly called MODFLOW, version MODFLOW-2005 software to simulate surface runoff and infiltration and groundwater flow. The model has three layers, 263 rows, and 176 columns. The model area includes the Strawberry Creek and four adjacent watersheds. The PRMS model was calibrated using two streamflow gaging stations and the GSFLOW model was calibrated to reported spring diversion discharge and a sparse number of groundwater-level measurements. The SCIHM was run with and without diversions active and simulated streamflow was compared, finding that in the headwaters of Strawberry Creek about 35 percent of the diversion flow was captured from base flow.

EarthArXiv↗
USGS2026

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

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

Oregon↗
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↗