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USGS2025

Magnitude, depth and methodological variations of spectral stress drop within the SCEC/USGS Community Stress Drop Validation Study using the 2019 Ridgecrest Earthquake Sequence

We present the first ensemble analysis of the 56 different sets of results submitted to the ongoing Community Stress Drop Validation Study using the 2019 Ridgecrest, California, earthquake sequence. Different assumptions and methods result in different estimation of the source contribution to recorded seismograms, and hence to the source parameters (principally corner frequency, f c ⁠ , spectral stress drop, Δσ, and seismic moment, M 0 ⁠ ) obtained from modeling calculated source spectra. For earthquakes smaller than magnitude (M) 2.5 there is negligible correlation between the f c values obtained by different studies, implying that no present method is reliable using available data. For larger magnitude events, correlation between f c measurements of different studies, within even a small M range is always higher than spectral ⁠Δσ , because the f c measurements simply reflect the underlying physical decrease in f c with increasing M. We model the observed trends of submitted f c with both magnitude and depth. Most methods report an increase in spectral Δσ with M, although a magnitude‐invariant spectral Δσ is within the confidence limits. The depth dependence is smaller and depends on whether a study allows attenuation to vary with source depth; a combination of depth‐dependent attenuation correction, and depth‐dependent shear‐wave velocity can compensate for reported depth trends. We model the submitted values to remove differing M and depth variation to investigate the relative interevent variability. We find consistent relative variation between individual events, and also lower relative spectral Δσ in the northwest of the aftershock sequence, and higher on the cross fault and in the region of main fault intersection. This large‐scale comparison implies that absolute spectral Δσ estimates are dependent on the methods used; studies of different regions or using different methods should not be directly compared and improved constraints on path and site corrections are needed to resolve these absolute spectral Δσ differences.

California↗
USGS2025

Time-varying rates of organic and inorganic mass accumulation in southeast Louisiana marshes: Relationships to sea-level anomalies and tropical storms

Louisiana's coastal wetlands are complex systems that require a continuous input of organic and inorganic material to keep pace with relative sea-level rise. Coastal restoration projects such as sediment diversions are being implemented to mitigate land loss and increase availability of inorganic sediment to coastal wetlands, and marshes specifically rely on organic material to build soil volume and maintain surface elevation. Interannual-to-decadal sea-level anomalies such as hurricanes can affect marsh accretion, mineral deposition, and plant productivity. In this light, complex ecogeomorphic feedback controls whether a marsh surface is sustainable or eroded/drowns. This study performs some of the first differential vertical accretion rates (VARs) and organic and inorganic mass accumulation rates (MARs) over time in SE Louisiana marshes determined from the 210 Pb Constant Rate of Supply model, coupled with standard 137 Cs VARs. These accumulation rates over the past ∼100 years were measured from a total of six brackish and salt marsh locations in Barataria Basin near the proposed Mid-Barataria Sediment Diversion. They were then related to interannual sea-surface elevations at Grand Isle, Louisiana, over the last ∼60 years and recorded hurricane activity in the delta. Results show VARs range from 0.63 cm/y to 1.69 cm/y and total MARs range from 0.11 to 0.43 g/cm 2 /y. Temporally, VARs and MARs (total, inorganic, and organic) are characterized by gradual increases in rates with decreasing age along with episodic peaks in VARs and MARs. The findings of this study indicate that no relationship occurs between sea-level anomalies and VARs or organic and inorganic MARs; however, a strong relationship appears to occur between major hurricanes to VAR and MAR contributions. Furthermore, high water content (81 ± 8%) and organic-rich soils in the sediment cores highlight the significance of belowground biomass and associated pore volume in maintaining marsh elevation in the study area.

Louisiana↗
USGS2026

ShakeAlert Earthquake Early Warning System performance during the Mw 7.0 offshore Cape Mendocino earthquake

The 5 December 2024 M w 7.0 Offshore Cape Mendocino earthquake was a challenging test of the U.S. West Coast ShakeAlert earthquake early warning system due to its offshore epicenter and limited near‐source station coverage. We analyzed real‐time performance of all components of the ShakeAlert system, including the seismic algorithms (earthquake point‐source integrated code [EPIC] and Finite‐fault rupture Detector [FinDer]), the geodetic algorithm (Geodetic First Approximation of Size and Time–peak ground displacement [GFAST‐PGD]), and network telemetry during the event. EPIC created the first solution for this earthquake 15 s after origin time with an initial magnitude estimate of M 5.6 and location error of 10 km from the Advanced National Seismic System epicenter. An early spurious trigger from station CE.89101 fortuitously maintained location accuracy and, correspondingly, magnitude accuracy. FinDer contributed its first solution at 18 s with a location estimate closer to the seismic network and produced two distinct rupture geometries, leading to minor fluctuations in estimated intensity contours. GFAST‐PGD did not meet alerting thresholds but otherwise performed as expected. Network latencies were <2 s for most stations, supporting the rapid detection of this earthquake by the system. Roughly five million alerts were delivered to cell phone devices in California and Oregon during this event. This was also the first instance of a school district‐wide ShakeAlert‐powered system being activated. Comparisons to recorded seismograms demonstrate that the maximum warning times before potentially damaging shaking (intensity 6+) were in the range of 5–55 s. Although the ShakeAlert system provided accurate solutions and useful alert delivery, this earthquake raised awareness of potential issues within the system, including the need for improved offshore location estimates, a combination of solutions from ShakeAlert servers, and handling of spurious triggers.

California↗
USGS2024

Comparing subduction ground-motion models to observations for Cascadia

We evaluate Cascadia subduction ground-motion models (GMMs), considered for the 2023 US National Seismic Hazard Model (NSHM) update, by comparing observations to model predictions. The observations comprise regional recordings from intraslab earthquakes, including contributions from 2021 and 2022 events in southern Cascadia and global records from interface earthquakes. Since the 2018 NSHM update, new GMMs for Cascadia have been published by the Next Generation Attenuation (NGA)-Subduction Project that require independent evaluation. In the regional intraslab comparisons, we highlight a characteristic frequency dependence for Cascadia data, with short periods having lower ground motions and longer periods being comparable to other subduction zones. We evaluate differences in northern and southern Cascadia and find that the NGA-Subduction GMMs developed using southern Cascadia data perform better in this region than the model that did not consider these data. We compare ground-motion variability in Cascadia with the NGA-Subduction model predictions and find differences at short periods ( T = 0.1 s) due to the use of global versus regional data in the development of these models. Moreover, the within-event component of aleatory variability from the GMMs overpredicts the standard deviation of Cascadia recordings at very short periods ( T < 0.05 s). Using global interface earthquakes as a proxy to evaluate the Cascadia GMMs, we find long-period overprediction from a simulation-based GMM and some of the empirical GMMs. When comparing recent observations, we find a similar misfit to GMMs and the 2010 and 2022 Ferndale earthquakes. Finally, we observe different basin amplification factors arising in different subsets of the data, which indicate that differences in basin factors between empirical GMMs could arise from the data selection choices by the developers. As part of evaluating the regional basin terms, we apply basin amplification factors from the magnitude 9 Cascadia earthquake simulations to the empirical GMMs for interface earthquakes. The comparisons presented in this study indicate that the NGA-Subduction GMMs for Cascadia perform well relative to observations and older subduction GMMs.

British Columbia, California, Oregon, Washington↗
USGS2025

The δ13C signature of dissolved organic and inorganic carbon reveals complex carbon transformations within a salt marsh

Coastal wetlands have high rates of atmospheric CO 2 uptake, which is subsequently respired back to the atmosphere, stored as organic matter within flooded, anoxic soils, or exported to the coastal ocean. Transformation of fixed carbon occurs through a variety of subsurface aerobic and anaerobic microbial processes, and results in a large inventory of dissolved carbon. Carbon source and the roles of aerobic respiration, sulfate reduction, and methane cycling were evaluated within salt marsh peat and the underlying sandy subterranean estuary. There is a large increase in dissolved inorganic carbon (DIC, 7,350 ± 3,900 μmol L −1 ), dissolved organic carbon (DOC, 1,040 ± 1,480 μmol L −1 ) and CH 4 (14.5 ± 33.3 μmol L −1 ) within the marsh porewaters compared to creek waters. Alkalinity production (5,730 ± 2,170 μeq L −1 ) and sulfate removal (1,810 ± 1,970 μmol L −1 ) indicate anaerobic respiration, however, relative contributions from the various decomposition pathways cannot be identified due to overlapping geochemical signatures. The δ 13 C of the DOC (−29.0 ± 3.7‰) and DIC (−11.2 ± 1.1‰) produced within the marsh differed from the bulk soil organic matter δ 13 C (−14.5 ± 0.2‰). We explore a variety of mechanisms that could result in co-occurring depleted δ 13 C-DOC and enriched δ 13 C-DIC compared to the bulk soil organic carbon pool and salt marsh vegetation, including selective mineralization, production of δ 13 C-depleted bacterial biomass, and methane-derived DOC. While important questions remain about carbon cycling pathways, we found evidence of a cryptic methane cycle. Alteration of the δ 13 C of carbon species complicates source attribution in solid and dissolved phases and careful consideration should be used when carbon is partitioned between in situ salt marsh production and external marine and terrestrial sources.

Massachusetts↗
USGS2026

Determination of baseline water-quality conditions using continuous specific conductance and discrete measurements of total dissolved solids and selected major ions, Arkansas River Basin, Colorado

From 2022 through 2024, the U.S. Geological Survey (USGS) in cooperation with the Regional Resources Planning Group (Southeastern Colorado Water Conservancy District, Colorado Springs Utilities, Pueblo Water, Lower Arkansas Valley Water Conservancy District, Aurora Water, and Upper Arkansas Water Conservancy District) established a basinwide water-quality monitoring network in the Arkansas River Basin in Colorado. The study leveraged ongoing continuous measurements of streamflow and specific conductance (SC) at 13 sites along the main stem Arkansas River and Fountain Creek from the USGS 07108600 Arkansas River at Granite, Colo., (Ark Granite) site to the USGS 07137500 Arkansas River near Coolidge, Kansas, (Ark Coolidge) site. Baseline water-quality conditions were established using data from October 1989 through September 2022 to help identify changes in water quality that could result from changes in land and water use. Total dissolved solids (TDS) concentration was the main indicator of general water quality in this study because it can be accurately estimated from SC and is sensitive to changes in streamflow, water operations, and source contributions. Median TDS concentrations in Arkansas River samples (October 1989 through December 2023) ranged from 75 milligrams per liter (mg/L) at Ark Granite near the headwaters to 3,660 mg/L at Ark Coolidge near the Colorado–Kansas State line. Distinct seasonal differences in median streamflow and TDS were apparent during the winter and summer months. Seasonal Kendall tests showed no significant trends in monthly mean streamflow (October 1995 through September 2022) at Arkansas River sites upstream from Pueblo Reservoir. Upward trends in TDS concentrations and loads occurred only at Ark Granite. Downward trends in streamflow, TDS concentrations, and TDS loads occurred at Arkansas River sites from USGS 07109500 Arkansas River near Avondale, Colo., to Ark Coolidge. Downward trends in streamflow and SC (surrogate for TDS) were more prevalent during winter base flow months and may indicate changes in groundwater quantity, and possibly groundwater quality, potentially affecting the river water-quality condition.

Colorado↗
USGS2025

Groundwater flowpath characteristics drive variability in per- and polyfluoroalkyl substances (PFAS) loading across a stream-wetland system

Groundwater-dependent ecosystems in areas with industrial land use are at risk of exposure to a PFAS chemicals. We investigated one such system with several known PFAS source areas, where high and low permeability sediments (glacial) coupled with groundwater-lake and groundwater/surface-water interactions created complex ‘source to seep’ dynamics. Using heat-tracing and chemical methods, numerous preferential groundwater discharge zones were identified and sampled across the upper Quashnet River stream-wetland system in Mashpee, MA, USA, downgradient of Joint Base Cape Cod (JBCC). Surface-water and groundwater samples were analyzed for 40 PFAS compounds between March and October 2022. Samples were collected from groundwater seeps identified as preferential discharge points (PDPs), wells upgradient of the stream-wetland system, contributing flow-through kettle lakes, and along Quashnet River surface-waters. PFAS from sampled waters contained perfluorinated carboxylates (PFPea, PFHxA, PFNA), perfluorinated sulfonates (PFBS, PFPeS, PFHxS, PFOS), fluorotelomer sulfonates (6:2, 8:2 FtS), and perfluoroalkyl sulfonamides (PFOSA). Samples from PDPs and wells had measured PFAS concentrations ranging from non-detect to 4677 ng/L ng/L (mean = 418 ng/L, std. = 709 ng/L), and a range of deuterium excess values (3.2 to 15.9 per mil) indicative of varying degrees of groundwater-lake interaction prior to groundwater flowpath emergence at PDPs. Correlations ( p < 0.01) between deuterium excess, %PFAS precursors, and terminal PFAS compounds highlighted potential precursor transformations associated with lake-groundwater exchange along flowpaths sourcing PDPs. However, some seepages had higher total PFAS concentrations (>1000 ng/L) than upgradient kettle lakes despite showing lake (evaporative) isotopic signatures, indicating the potential for groundwater flowpath convergence at wetland discharge zones and the influence of lakebed PFAS precursor reactions. Results from these synoptic surveys address gaps in the existing PFAS literature by demonstrating the importance of subsurface fate and transport on PFAS compound concentrations and mass loading in preferential groundwater discharge zones.

Massachusetts↗
USGS2026

Evaluating machine learning approaches to identify and predict oil and gas produced water lithium concentrations

Recently, the demand for battery-grade lithium has substantially increased, largely due to electrification of the transportation sector. The search for new lithium sources has turned to produced waters (frequently brines), a large-volume wastewater by-product of oil and gas extraction. Geochemical analysis indicates the presence of varying concentrations of lithium from produced water samples collected across the United States and represented in the U.S. Geological Survey’s National Produced Water Geochemical Database, as well as mixtures of Marcellus Shale produced water included in the Pennsylvania Department of Environmental Protection’s Oil and Gas Well Waste Reports. We first examined whether the geochemical signature of the lithium-bearing produced waters is sufficiently distinct so that machine learning (ML) can be used to correctly classify samples to the formation of origin. The produced water sample data used to assess classification accuracy were from the Marcellus Shale, Utica Shale and Point Pleasant Formation (Utica), and Smackover Formation oil and gas wells. Further, we evaluated the potential for ML to accurately classify Marcellus Shale produced water spatially (i.e., northeast versus southwest Pennsylvania). We then investigated whether ML algorithms applied to a suite of geochemical concentration data (i.e. Ba, Br, Cl, K, Mg, Sr) may be used to predict the lithium concentration of an unknown sample. Finally, we applied an estimated economic lithium grade cutoff of 150 milligrams per liter (mg/l) and assessed the utility of ML to predict whether a produced water sample would fall above or below the grade cutoff based on the suite of geochemical parameters. Four machine learning algorithms—Random Forest (RF), Gradient Boosting Trees (GBT), Extreme Boosting (XGBoost), and Deep Neural Networks (DNN) were assessed. This study successfully demonstrates that all four machine learning methods can precisely and accurately estimate lithium concentrations and geologic formation classification. The products of this study contribute to the growing body of knowledge aimed at expanding the lithium resource base within the United States.

Alabama, Arkansas, Florida, Georgia, Louisiana, Mi↗
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↗
USGS2025

Submarine groundwater discharge creates cold‐water refugia that can mitigate exposure of heat stress in nearshore corals

Coral reef mortality around the world is accelerating due to human activities and rising sea temperatures that cause bleaching, which is expected to become more frequent. Our ability to predict which corals will be most resilient, however, remains limited due to insufficient information characterizing nearshore temperature and habitat conditions. In this study, we examine how submarine groundwater discharge (SGD) reduces nearshore water temperatures and exposure of corals to heat stress, complementing the understanding that SGD can adversely affect coral when it contains elevated nutrient concentrations. Data from fixed nearshore sensors and vertical depth profiles along ~100 km of the western shoreline of the Island of Hawai’i from 2003 to 2014 demonstrate that submarine groundwater discharge (SGD) can reduce nearshore water temperatures by 1 °C–5°C and create estuarine-like conditions with salinities as low as 20 PSU, where the prevalent coral species, Pocillopora meandrina, Porites lobata , and Montipora capitata , thrive. Time-series temperature records reveal that exposure to high ambient ocean temperatures, which are known to initiate bleaching events, are reduced up to 5%–46% of the time. Coral health surveys indicated coral bleaching in response to moderately high annual temperatures in 2010 and 2011, with more colonies affected farther from cold, SGD-fed waters. Synthesis of these results, along with coral response data following the more extreme marine heat wave of 2014–2015, demonstrates lower coral loss and greater coral recovery near groundwater seeps, particularly those with higher flux and influence on reducing nearshore water temperatures. Our results demonstrate that SGD may therefore provide a beneficial ecosystem service and enhance coral reef resilience, particularly where human-related nutrient additions to groundwater can be mitigated. The implications of our findings are relevant across tropical coasts where groundwater inputs can be substantial, such as the Caribbean and Indo-Pacific, and contribute to improving our understanding of coral sensitivity to gradients in temperature and nutrient stress. Improved management of groundwater resources could thus be vital to local–regional strategies for mitigating future heat stress.

Hawaii↗
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

Decomposing the Tea Bag Index and finding slower organic matter loss rates at higher elevations and deeper soil horizons in a minerogenic salt marsh

Environmental gradients can affect organic matter decay within and across wetlands and contribute to spatial heterogeneity in soil carbon stocks. We tested the sensitivity of decay rates to tidal flooding and soil depth in a minerogenic salt marsh using the Tea Bag Index (TBI). Tea bags were buried at 10 and 50 cm depths across an elevation gradient in a subtropical Spartina alterniflora marsh in Georgia (USA). Plant and animal communities and soil properties were characterized once, while replicate tea bags and porewaters were collected several times over 1 year. TBI decay rates were faster than prior litterbag studies in the same marsh, largely due to rapid green tea loss. Rooibos tea decay rates were more comparable to natural marsh litter, potentially suggesting that is more useful as a standardized organic matter proxy than green tea. Decay was slowest at higher marsh elevations and not consistently related to other biotic (e.g., plants, crab burrows) or abiotic factors (e.g., porewater chemistry), indicating that local hydrology strongly affected organic matter loss rates. TBI rates were 32 %–118 % faster in the 10 cm horizon than at 50 cm. Rates were fastest in the first 3 months and slowed 54 %–60 % at both depths between 3 and 6 months. Rates slowed further between 6 and 12 months, but this was more muted at 10 cm (17 %) compared to 50 cm (50 %). Slower rates at depth and with time were unlikely due to the TBI stabilization factor, which was similar across depths and decreased from 6 to 12 months. Slower decay at 50 cm demonstrates that rates were constrained by environmental conditions in the deeper horizon rather than the composition of this highly standardized litter. Overall, these patterns suggest that hydrological setting, which affects oxidant introduction and reactant removal and is often overlooked in marsh decomposition studies, may be a particularly important control on organic matter loss in the short term (3–12 months).

Georgia↗
USGS2025

Forecasting water levels using the ConvLSTM algorithm in the Everglades, USA

Forecasting water levels in complex ecosystems like wetlands can support effective water resource management, ecological conservation, and understanding surface and groundwater hydrology. Predictive models can be used to simulate the complex interactions among natural processes, hydrometeorological factors, and human activities. The Greater Everglades in the USA is a well-known example of an ecosystem where complexity has motivated adoption of machine learning algorithms in water level prediction studies. This paper aims to contribute to extending existing machine learning algorithms by integrating spatiotemporal data with deep-learning algorithms in the forecasting process. In this study, a deep-learning model is developed to predict water levels on a regional scale, covering a large area of approximately 9,138 square kilometers in the Everglades ecosystem. This model has the architecture of Convolutional Long Short-Term Memory which can deal with spatiotemporal data by capturing both spatial and temporal dependencies in the training data. The forecasting capabilities of this model (referred to as the global model) are assessed by comparing the global model to two Artificial Neural Networks developed at two different gaging stations, referred to here as local models. One local model is developed at a gaging station directly influenced by nearby water control structures, whereas the other is developed at a gaging station located farther away from these structures. By leveraging data from the Everglades Depth Estimation Network spanning from January 2002 to May 2023, the global and local models were trained to forecast water levels with a two-day lead time. Our findings suggest that both the global and local models perform with approximately the same level of accuracy, with Mean Absolute Relative Error values ranging from 0.38% to 1.4% at the selected stations. The developed global model has demonstrated strong potential as a standalone forecasting tool for the entire study area in the Everglades and could eliminate the need for developing multiple local models. This finding also highlights how machine learning can capture complex spatial and temporal relationships to generate accurate water level predictions on a regional scale.

Florida↗
USGS2024

Application of non-stationary shear-wave velocity randomization approach to predict 1D seismic site response and its variability at two downhole array recordings

Accounting for uncertainties in seismic site response is crucial to improving the performance of one-dimensional (1D) ground response analyses (GRAs) at downhole array recording sites. In addition to site effects, uncertainties in 1D-GRAs can also be contributed from the seismic source and/or path. Though often representing not more than one percent of the distance (path) from the source, site conditions are known to have an enormous influence on ground shaking. In this study, we focus on the site shear-wave velocity ( V S ) structure, which is the main ingredient for estimating the variability of site response. As such, V S can manifest aleatory uncertainties related to the effects of small-scale spatial heterogeneities within the near surface, thus V S can substantially modify ground shaking during earthquakes. We apply a novel V S randomization approach to propagate the small-scale heterogeneities of V S to estimate seismic site response within a non-stationary probabilistic framework. The randomization approach generates samples of V S profiles that are used to perform several 1D-GRAs and obtain an averaged site response and related variability. The proposed method is implemented on data recorded at two downhole array sites with different subsurface soil conditions: a soft soil site on Treasure Island (California, United States of America) and a rock outcrop site in Cadarache (South-East France). We show that synthetic surface-to-borehole transfer functions from 1D-GRAs provide an acceptable fit to the empirical transfer functions from low-motion earthquake records and succeed in reproducing most of the site-specific seismic response variability. The remaining mismatch between transfer functions is likely due to insufficient precision on the seismic bedrock and the impedance contrast. The variability in site response is discussed with emphasis on the role of V S small-scale heterogeneities, attenuation, and input motion incidence angle in ground motion variability for the site and soil conditions at both locations.

California↗
USGS2025

Leveraging wildfire to augment forest management and amplify forest resilience

Successive catastrophic wildfire seasons in western North America have escalated the urgency around reducing fire risk to communities and ecosystems. In historically frequent-fire forests, fuel buildup as a result of fire exclusion is contributing to increased fire severity. The probability of high-severity fire can be reduced by active forest management that reduces fuels, prompting federal and state agencies to commit significant resources to increase the pace and scale of fuel reduction treatments. However, lower severity areas of wildfires also have the potential to act as “treatments,” and even catastrophic fires with large areas of high severity can still have substantial areas of lower severity fire that may be improving forest conditions locally. We quantified active management and wildfire severity across yellow pine and mixed conifer (YPMC) forests in the Sierra Nevada of California over a 22-year period (2001–2022). We did not detect increases in the area treated through time, but the area of beneficial wildfire (low to moderate severity) increased substantially, exceeding active treatment area in 8 of 22 years. Overall, beneficial wildfire treated ~17% more area than all treatments combined, and roughly four times more area than fire-related treatments alone. We then used disturbance history to evaluate resistance to high-severity wildfire and forest loss across the YPMC range. Of the 2.3 million ha YPMC of forests in 2001, 20% lost mature forests due to high-severity fire by 2022, which is nearly half of all YPMC area burned. Most of the landscape (47%) remains at risk of high-severity fire because it had no restorative disturbances, but 33% of the study area has some level of resistance to high-severity wildfire. In these areas, resistance will need to be enhanced and maintained over time via active management or managed wildfire, but these treatment needs will likely outpace capacity even under optimistic implementation scenarios. Given limited resources for implementing active management and the likelihood of a more fiery future, incorporating beneficial wildfire into landscape-level treatment planning has the potential to amplify the impact of active management treatments.

California, Nevada↗
USGS2024

Assessment of long-term changes in surface-water extent within Klamath Marsh, south-central Oregon, 1985–2021

The annual maximum extent of surface water in Klamath Marsh has naturally fluctuated in response to periods of wet and dry conditions in the surrounding basin. Field observations during the 2010s indicate that the annual maximum extent of surface water has been declining and the marsh is not responding to hydrologic inputs as it had historically. This report describes the results of a hydrologic evaluation of Klamath Marsh to characterize and understand multi-year declines in the surface-water extent and increased intermittency of streamflow exiting the marsh. Landsat imagery collected during 1985–2021 was processed to create a time series of annual maximum surface-water extent to assess changes in surface-water inundation within the marsh. A 50-percent decrease in the mean surface area of annual total open-water extent (TOWE) during the latter half of the study period (2003–21) compared to the first half (1985–2003) was observed in this 37-year time-series dataset. The change in open-water extent was offset by a corresponding increase in dry land in the marsh. Time series of streamflow, groundwater level, total annual precipitation, annual mean temperature, and anthropogenic water use and water management were compiled and evaluated to improve understanding of the factors affecting TOWE. Statistically significant downward trends in the regional groundwater table and streamflow into and out of the marsh were identified as well as statistically significant upward trends in annual mean temperature. Statistically significant correlations among TOWE, streamflow, and groundwater level also were identified. The decreasing trends could not be attributed to changes in total annual precipitation or changing anthropogenic groundwater use within the study area. Declines in the open-water extent of Klamath Marsh since 2000 principally are due to a decoupling of the groundwater and surface-water system beneath the marsh because of regional declines in groundwater level. Regional increases in air temperature and the reestablishment of more than 55,000 acres of forested land within the study area have likely contributed to increasing evapotranspiration, leaving less water available for groundwater recharge and stream base flow and resulting in basin-wide declines in streamflow and groundwater levels.

Oregon↗
USGS1996

Technique for estimating magnitude and frequency of peak flows in Maryland

A convenient and reliable technique for estimating flood magnitudes is required for effective flood-plain management and for the efficient design of bridges, culverts, embankments, and flood-protection structures. Methods are presented for estimating peak-flow magnitudes of selected frequencies, ranging from 2 to 500 years, for all nontidal drainage basins in Maryland. The methods were developed by generalized least-squares regression techniques using data from 219 gaged basins in and near Maryland. The State is divided into five hydrologic regions: the Appalachian Plateaus and Allegheny Ridges region, the Blue Ridge and Great Valley region, the Piedmont region, the Western Coastal Plain region, and the Eastern Coastal Plain region. These regions correspond to the physiographic provinces of the State, with the exceptions that (1) the Coastal Plain Province is divided into two hydrologic regions, and (2) there is no distinct hydrologic region corresponding to the Valley and Ridge Province as it is divided into its constituent Allegheny Ridges and Great Valley subdivisions. Sets of equations for calculating peak discharges based on physical basin characteristics are provided for each of the regions. Based on the peak-flow equations, methods for estimating peak flows are presented for ungaged and gaged streams in Maryland. The methods and equations are supported by generalized least-squares analysis of basin and flood-frequency characteristics data from 219 drainage basins in and near Maryland. estimates for each of the five regions are calculated using combinations of the fol-lowing basin characteristics: drainage area, forest cover, basin relief, carbonate rock coverage, storage, and runoff-curve number. Drainage area contributes to the estimate in all five study regions. Carbonate rock coverage is used only in the Blue Ridge and Great Valley region. Storage and runoff-curve number are used solely in the Eastern Coastal Plain region. All other basin characteristics are used in two or more regions. Standard errors of estimate for the regression equations range from 19 to 31 percent in the Appalachian Plateaus and Allegheny Ridges region, 34 to 47 percent in the Blue Ridge and Great Valley region, 33 to 48 percent in the Piedmont region, 45 to 64 percent in the Western Coastal Plain region, and 36 to 42 percent in the Eastern Coastal Plain region.

Maryland↗
USGS2024

Geological context and significance of the clay-sulfate transition region in Mount Sharp, Gale crater, Mars: An integrated assessment based on orbiter and rover data

On Mars, phyllosilicate (“clay”) minerals are often associated with older terrains, and sulfate minerals are associated with younger terrains, and this dichotomy is taken as evidence that Mars’ surface dried up over time. Therefore, in situ investigation of the Mount Sharp strata in Gale crater, which record a shift from dominantly clay-bearing to sulfate-bearing minerals, as seen in visible−near-infrared orbital reflectance spectra, is a key science objective for the Mars Science Laboratory (MSL) Curiosity rover mission. Here, we present regional (orbiter-based) and in situ (rover-based) evidence for a low-angle erosional unconformity that separates the lacustrine and marginal lacustrine deposits of the Carolyn Shoemaker formation from the dominantly eolian deposits of the lower Mirador formation within the orbitally defined clay-sulfate transition region. The up-section record of wetter (Carolyn Shoemaker formation) to drier (lower Mirador formation) depositional conditions is accompanied by distinct changes in diagenesis. Clay minerals occur preferentially within the Carolyn Shoemaker formation and are absent within the lower members of the Mirador formation. At and above the proposed unconformity, strata are characterized by an increase in diagenetic nodules enriched in X-ray amorphous Mg-sulfate. Early clay formation in the Carolyn Shoemaker formation may have created a hydraulic barrier such that later migrating magnesium- and sulfur-rich fluids accumulated preferentially within the lower members of the Mirador formation. The proposed unconformity may have also acted as a fluid conduit to further promote Mg-sulfate nodule formation at the Carolyn Shoemaker−Mirador formation boundary. These results confirm an association of the clay-sulfate transition with the drying of depositional environments, but they also suggest that at least some orbital sulfate signatures within the region are not time-congruent with the environmental signals extracted from primary sedimentology. Our findings highlight that complex interactions among primary depositional environment, erosion, and diagenesis contribute to the transition in clay-sulfate orbital signatures observed in the stratigraphy of Mount Sharp.

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