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USGS2026

Evaluating the U.S. Geological Survey’s earthquake shaking hazard forecasts and their implications on seismic risk

We analyze the last six update cycles of the long-term probabilistic earthquake shaking hazard forecast from the U.S. Geological Survey (USGS) and discuss the changes in hazard estimates from the 1996 to the latest 2023 update of the National Seismic Hazard Model (NSHM) for the conterminous U.S. We summarize how our understanding of earthquake hazards has evolved over the last two decades and quantify the implications of changing hazards on people, buildings, and lifeline infrastructure. The net effect of changes in hazard estimates, with reference to the mean hazard from the 2023 NSHM update that has 2% probability of exceedance in 50 years, suggests an overall increase in total geographic areas facing very strong shaking levels (modified Mercalli Intensity (MMI) of VII or more) when compared with any of the previous cycles. This increase puts ~159.2 million people (an increase from 111.8 million when using the 2018 NSHM), ~47.3 million residential buildings (an increase from 32.5 million with the 2018 NSHM), and ~$25.6 trillion of economic exposure of all buildings (an increase from $17.4 trillion when using the 2018 NSHM) at risk from earthquakes. We demonstrate that small changes in hazard estimates do not necessarily imply small changes in risk estimates. Therefore, changes in risk estimates can be used to highlight key USGS NSHM updates for improving risk mitigation efforts.

Earthquake Spectra Journal↗

USGS2026

Ringtail (Bassariscus astutus) survival in southwestern Oregon

The effective conservation and management of small carnivore populations requires understanding species’ life-history traits and identifying important vital rates that drive population trajectories. However, many of these species are rare or elusive and of state or federal conservation concern, and demographic information is often lacking and difficult to obtain. At the northern limit of their range in Oregon, USA, ringtail ( Bassariscus astutus ) occupy mid-elevation forests and are a species of conservation concern because of their limited distribution and suspected low density. We initiated a radio-telemetry study in 2020 to estimate monthly and annual survival of ringtail in southwest Oregon. We monitored 26 ringtail from November 2020 to October 2022 and estimated survival rates using a known-fate framework and Program MARK. Model-averaged monthly survival estimates ranged from lows of 0.963 (SE = 0.022, 95% CI = 0.887–0.988) in spring (Feb–May) of 2021 to highs of 0.980 (SE = 0.018, 95% CI = 0.889–0.997) in summer (Jun–Oct) of 2022. Model-averaged estimates of annual survival were 0.695 (SE = 0.176, 95% CI = 0.310–0.920) during 2020–2021 and 0.728 (SE = 0.168, 95% CI = 0.336–0.934) during 2021–2022. Predation was the leading cause of mortality, but notably, no mortalities could be attributed to avian predation. Survival rates were much higher within forested landscapes in Oregon than for populations in the southwestern United States, which may have implications for regional conservation and management strategies.

Oregon↗

USGS2024

A benchmark dataset and workflow for landslide susceptibility zonation

Landslide susceptibility shows the spatial likelihood of landslide occurrence in a specific geographical area and is a relevant tool for mitigating the impact of landslides worldwide. As such, it is the subject of countless scientific studies. Many methods exist for generating a susceptibility map, mostly falling under the definition of statistical or machine learning. These models try to solve a classification problem: given a collection of spatial variables, and their combination associated with landslide presence or absence, a model should be trained, tested to reproduce the target outcome, and eventually applied to unseen data. Contrary to many fields of science that use machine learning for specific tasks, no reference data exist to assess the performance of a given method for landslide susceptibility. Here, we propose a benchmark dataset consisting of 7360 slope units encompassing an area of about 4,100 km 2 "> 4,100 km 2 in Central Italy. Using the dataset, we tried to answer two open questions in landslide research: (1) what effect does the human variability have in creating susceptibility models; (2) how can we develop a reproducible workflow for allowing meaningful model comparisons within the landslide susceptibility research community. With these questions in mind, we released a preliminary version of the dataset, along with a “call for collaboration,” aimed at collecting different calculations using the proposed data, and leaving the freedom of implementation to the respondents. Contributions were different in many respects, including classification methods, use of predictors, implementation of training/validation, and performance assessment. That feedback suggested refining the initial dataset, and constraining the implementation workflow. This resulted in a final benchmark dataset and landslide susceptibility maps obtained with many classification methods. Values of area under the receiver operating characteristic curve obtained with the final benchmark dataset were rather similar, as an effect of constraints on training, cross–validation, and use of data. Brier score results show larger variability, instead, ascribed to different model predictive abilities. Correlation plots show similarities between results of different methods applied by the same group, ascribed to a residual implementation dependence. We stress that the experiment did not intend to select the “best” method but only to establish a first benchmark dataset and workflow, that may be useful as a standard reference for calculations by other scholars. The experiment, to our knowledge, is the first of its kind for landslide susceptibility modeling. The data and workflow presented here comparatively assess the performance of independent methods for landslide susceptibility and we suggest the benchmark approach as a best practice for quantitative research in geosciences.

Earth-Science Reviews↗

USGS2025

Anatectic origin of Mississippian spodumene-bearing pegmatites in western Maine during orogenic plateau collapse

Spodumene pegmatites are an important lithium source, but the processes and tectonic settings in which they form are poorly understood. The Rumford pegmatite district surrounding Plumbago Mountain, western Maine, is host to numerous spodumene pegmatites, including the Plumbago North pegmatite (a world-class spodumene resource). Competing petrogenetic models for these spodumene pegmatites include (1) highly fractionated melts of the Mooselookmeguntic igneous complex and (2) anatexis. We tested these hypotheses by constraining the geologic, magmatic, metamorphic, and tectonic history of the Plumbago Mountain area with detailed geologic mapping and U-(Th)-Pb geochronology. The Silurian Rangeley Formation records initial isoclinal folding prior to, and contact-related metamorphism synchronous with, the intrusion of the 417 ± 4 Ma Plumbago Mountain pluton. Peak amphibolite facies metamorphism and crustal melting occurred during the ca. 410 to 400 Ma Acadian orogeny. Pulsed emplacement of the Mooselookmeguntic igneous complex occurred between ca. 389 and 356 Ma. Cassiterite U-Pb dates of spodumene pegmatites (333–327 Ma) are ≥23 m.y. younger than nearby granitic plutons, strongly arguing against the fractional crystallization model. Metamorphic monazite and xenotime (346–328 Ma) and 330 to 308 Ma 40 Ar/ 39 Ar hornblende dates indicate metamorphism coeval with spodumene pegmatite emplacement, supporting anatectic models. Reheating, anatexis, and spodumene pegmatite emplacement occurred during collapse of the 380 to 330 Ma Acadian orogenic plateau. Lithium enrichment may be linked to one or more stages of partial melting of metasedimentary and plutonic rocks during the formation, tenure, and collapse of the Acadian altiplano and emphasizes the role of anatexis in producing spodumene pegmatites of economic significance.

Maine↗

USGS2026

Core microbiomes as a potential fingerprinting method of Western USA dust sources

Introduction: Changing frequency and intensity of dust emissions impacts ecosystems and human health. Dust carries microbes, nutrients, heavy metals, and other materials that may change environmental biogeochemistry at deposition sites. Identifying dust sources provides key information on where and when mitigation strategies should be employed. However, commonly used geochemical or isotopic tracers are often not capable of distinguishing between geographic regions. Methods: We explored whether soil bacterial communities may provide distinct fingerprints of dust sources in the western United States. We identified bacterial core communities of dust from ten locations monitored by the National Wind Erosion Research Network (NWERN) with varied land use (cropland, rangeland, and playa), and compared communities to location, soil, and regional characteristics. Samples were collected monthly from Modified Wilson and Cooke (MWAC) samplers, composited by season (spring, summer, and fall), and analyzed using 16S rRNA sequencing. Results: We found distinct bacterial core communities that reflected dust source characteristics. In order of importance, precipitation levels ( p = 0.0001), location ( p = 0.0001), soil texture ( p = 0.0001), seasonality ( p = 0.0001), and elevation (p = 0.0002) were correlated with bacterial community composition. Discussion: Distinct bacterial core communities were associated with site characteristics such as biocrusts, playas, and military base proximity. Our results suggest that the use of core microbiomes may offer a fingerprinting method to identify dust source regions.

Colorado, Nevada, New Mexico, North Dakota, Oklaho↗

USGS2026

Seismic characteristics of the April 2024 eruption of Ruang Volcano, North Sulawesi, Indonesia

The two most recent eruptions of Ruang volcano, in 2002 and 2024, have been large (VEI 4) with very short precursory periods, 3 and 6 days, respectively. Background seismicity at Ruang volcano is generally low with 0–2 volcano-tectonic (VT) earthquakes per day. The 2024 eruptions were preceded by a notable increase in VT earthquakes from 11 to 15 April with a rapid escalation from 16 to 17 April in the form of increased VT swarms, and the appearance of low frequency earthquakes and short bursts of VT drumbeats shortly before the eruption. Similar VT seismic unrest was recorded in March 2015, May 2016, and April 2022, although none of these episodes culminated in an eruption. A comparison of seismic energy release between April 2022 and April 2024 shows distinct differences. In 2024, cumulative seismic energy reached its peak within 5 days, just before the onset of eruption on 17 April. In contrast, during the 2022-episode, energy release followed a more gradual increase over 8 days peaking on 16 April, then declining gradually without leading to eruption. Notably, low frequency (LF) and drumbeat earthquakes were absent in non-eruptive unrest episodes. The transition to proximal LFs in 2024 likely signals pressure fluctuations, intensified magma degassing, and conduit formation, acting as an important precursor to eruption. Additionally, the occurrence of short bursts of drumbeat seismicity likely reflects the onset of the shallow magma ascent and was an important short-term precursor to the eruption. Finally, we examine the potential influence of regional tectonic earthquakes on the escalation of precursory unrest in 2024.

North Sulawesi, Ruang volcano↗

USGS2000

Assessment of potential for natural attenuation of chlorinated ethenes and ethanes in ground water at a petrochemical reclamation site, Harris County, Texas

Redox conditions in the Numerous Sand Channels Zone beneath a petrochemical reclamation site in Harris County, Texas, range from sulfate reducing to methanogenic as indicated by the presence of methane in ground water and the range of molecular hydrogen concentrations. Assessment of the potential for reductive dechlorination using BIOCHLOR as a screening tool indicated conditions favoring anaerobic degradation of chlorinated organic compounds in the Numerous Sand Channels Zone. Evidence supporting reductive dechlorination includes apparently biogenic cis -1,2-dichloroethene; an increased ratio of 1,2-dichloroethane to 1,1,2-trichloroethane downgradient from the assumed contaminant source area; ethene and methane concentrations greater than background concentrations within the area of the contaminant plume; and a positive correlation of the ratio of ethene to vinyl chloride as a function of methane concentrations. The body of evidence presented in this report argues for hydrogenolysis of trichloroethene to cis -1,2-dichloroethene; of 1,1,2-trichloroethane to 1,2-dichloroethane; and of vinyl chloride to ethene within the Numerous Sand Channels Zone. Simulations using BIOCHLOR yielded apparent first-order decay constants for reductive dechlorination in the sequence tetrachloroethene trichloroethene cis -1,2-dichloroethene vinyl chloride ethene within the range of literature values reported for each compound and apparent first-order decay constants for reductive dechlorination in the sequence 1,1,2-trichloroethane 1,2-dichloroethane slightly greater than literature values reported for each compound along the upgradient segment of a simulated ground-water flowpath. Except for vinyl chloride, apparent rates of reductive dechlorination for all simulated species show a marked decrease along the downgradient segment of the simulated ground-water flowpath. Evidence for reductive dechlorination of chlorinated ethenes within the Numerous Sand Channels Zone indicates potential for natural attenuation of chlorinated ethenes. Reductive dechlorination of chlorinated ethanes apparently occurs to a lesser extent, indicating relatively less potential for natural attenuation of chlorinated ethanes. Additional data are needed on the concentrations and distribution of chlorinated ethenes and ethanes in individual fine sand intervals of the Numerous Sand Channels Zone. This information, combined with lower minimum reporting levels for future chloroethane analyses, might enable a more complete and quantitative assessment of the potential for natural attenuation at the site.

Texas↗

USGS2026

Using a temporary emigration model to estimate abundance of stream fishes from hybrid removal surveys with and without block nets

Monitoring programs are often faced with a decision to allocate resources into either robust spatiotemporal coverage to estimate a population index (e.g., not true abundance) or confirming closed sampling conditions (e.g., with block nets) for an unbiased population estimate at the cost of spatiotemporal coverage. However, making accurate and precise abundance estimates at robust spatiotemporal scales is possible when combining open and closed sampling designs with integrated modeling techniques. We used simulations and a case study of backpack electrofishing surveys in the Santa Ana River, California to test the efficacy of an integrated abundance model (temporary emigration model, TE) to estimate abundance of fishes using removal sampling methods with a hybrid sampling design (sampling with and without block nets during removal sampling). We found that the TE model performed well under most modeling scenarios (sample size, amount of closure violation, number of samples collected during closure), although at least a few samples with block nets were necessary for all parameters to be estimable. When applied to fish surveys in the Santa Ana River, we found that catch of the fishes fit to the TE model (Santa Ana Sucker, Arroyo Chub, Channel Catfish, Largemouth Bass, Yellow Bullhead) showed little evidence that the closure assumption was violated when block nets were not used. Additionally, we found that the abundance of non-native fishes negatively affected the abundance of the native Santa Ana Sucker, which was also found to adversely affect the native fish’s access to critical habitat consisting of gravel and cobble substrate. Our results indicate that the TE model presents a viable solution to common sampling problems that impact many monitoring programs, where precise and accurate population estimates can be made at large spatiotemporal scales even when most samples violate the closure assumption.

California↗

USGS2025

Earthquake stress-drop values delineate spatial variations in maximum shear stress in the Japanese forearc lithosphere

Earthquake stress drop (Δσ) may increase with depth and stress in the brittle lithosphere. However, the range of uncertainty in Δσ and the lack of constraints on absolute stress make it difficult to establish whether they are correlated. Here, we investigate Δσ dependence on depth and maximum shear stress ( τ max ) based on ~11 years of seismicity in the northeastern Japanese forearc following the 2011 Tohoku-Oki megathrust earthquake. We interpret Δσ estimates computed using both individual spectra and spectral-ratio methods and find that Δσ exhibits a clear depth dependence within the seismically active upper ~60 km of the forearc lithosphere ( ~ 0.8 MPa per 10 km). We further compare Δσ values with quantitative τ max estimates from finite-element models of force balance. We find that median Δσ values increase with τ max in the brittle forearc lithosphere and that earthquake stress release is proportional to τ max . The dependence of Δσ on τ max explains the apparent depth dependence of Δσ and suggests that average Δσ values provide a relative measure of the stress at failure. In the northeastern Japanese forearc, Δσ values remained roughly constant in the decade following the Tohoku-Oki earthquake, suggesting negligible changes in failure stress in the forearc since the mainshock.

Communications Earth and Environment↗

USGS2025

PEST++IES how many iterations & realizations, finding the point of diminishing returns

PEST++IES (White 2018; White et al. 2020) is widely used in the groundwater modeling community for its ability to perform computationally efficient history matching and uncertainty analysis in a highly parameterized context. One primary advantage of using an iterative ensemble smoother is that the number of model runs required per iteration depends on the number of realizations in an ensemble, not the number of parameters in each realization. However, this raises the question: what is the optimal number of realizations and iterations to use for any one model before the point of diminishing returns? Using a modified version of the Freyberg model (Freyberg 1988; Hunt et al. 2020), different parameter and observation scenarios were evaluated for four iterations and ensembles of 10, 25, 50, 100, 250, 500, 1000, and 2000 realizations. To match observations, PEST++IES altered hydraulic conductivity ( k ), both globally across the model and locally at three different pilot point densities, as well as global recharge (via a single multiplier), global river conductance, and individual well flow rates. Risk-based well capture zone results (Fienen et al. 2022a) and estimated hydraulic conductivity fields from each scenario were quantitatively and qualitatively compared against the “truth” model and its outputs. Across the cases examined, ensemble sizes of 100 to 250 realizations and two PEST++IES iterations were generally sufficient to achieve good results.

Groundwater↗

USGS2025

The Hardscrabble Creek complex: A newly discovered, mostly buried, Mesoproterozoic mafic-ultramafic pluton in the Wet Mountains, Colorado, USA

The origin of prolific ca. 1.4 Ga ferroan magmatism between the southwestern USA and eastern Canada is enigmatic and has been explained by various models, including extensional, mantle plume, and convergent plate-margin models. Rare mafic plutons are associated with the ferroan plutons, which may help constrain their mantle source and tectonic setting. In the southwestern USA, only two such mafic plutons are known to exist. We present the first evidence for a third, mostly buried, potentially layered, mafic-ultramafic Mesoproterozoic pluton, informally referred to as the Hardscrabble Creek complex, in the central Wet Mountains of Colorado, USA. Recent geophysical data show an elliptical magnetic and gravity high spatially coincident with local gabbroic outcrops. New field and petrographic analyses of these exposed rocks reveal that they consist of ultramafic to mafic cumulates, including orthopyroxenite, olivine norite, norite, and anorthosite. High-precision U-Pb dating of zircon from orthopyroxenite and norite yield weighted mean 206 Pb/ 238 U dates of 1352.36 ± 1.60 Ma and 1352.37 ± 1.71 Ma, respectively. These dates indicate that the complex formed over a narrow timeframe, after the adjacent 1362 ± 7 Ma ferroan San Isabel Granite, and during the waning stages of the regional ca. 1.4 Ga ferroan magmatism. Whole-rock geochemistry and Nd-Sr-Pb isotope compositions of samples from the Hardscrabble Creek complex are similar to those of the San Isabel Granite, suggesting that they were derived from the same or a similar mantle source. The mineral chemistry of the samples is comparable to Proterozoic massif-type anorthosites and related mafic intrusions, indicating that the Hardscrabble Creek complex and San Isabel Granite together represent a rare anorthosite-mangerite-charnockite-granite (AMCG) suite in the southwestern USA. The Hardscrabble Creek complex is unique because it formed ~80 m.y. after the other few mafic plutons in the southwestern USA, and it contains an ultramafic section that is absent from these plutons and rare to the AMCG suite in general. A combination of arc-like whole-rock geochemistry, chondrite uniform reservoir-like Nd-Sr-Pb isotopes, and ocean island basalt (OIB)-like zircon trace element chemistry suggests that the complex was derived from a partial melt of OIB-like mantle and interacted with metasomatically enriched lithospheric mantle. The enriched lithospheric mantle signature, combined with the long ~160 m.y. duration of magmatism in the region, is consistent with a period of protracted convergent tectonism.

Colorado↗

USGS2024

Constraining the earthquake recording threshold of intraslab earthquakes with turbidites in southcentral Alaska’s lakes and fjords

Strong ground motion from intraslab earthquakes, which do not produce primary paleoseismic evidence, may initiate gravity-driven turbidity flows in subaqueous basins. The resulting deposits (turbidites) can provide a paleoseismic proxy if the conditions that initiate these flows are known. To better constrain the initiating conditions, we use two recent intraslab earthquakes in southcentral Alaska, the M w 7.1 30 November 2018 Anchorage earthquake and the M w 7.1 24 January 2016 Iniskin earthquake, as calibration events. Through a multilake investigation, we document the occurrence, or the absence, of earthquake-generated turbidity flows from these two events. Both earthquakes are recorded by centimeter-scale turbidites that can be differentiated from climatically generated deposits, as well as other seismic sources based on deposit thickness, sedimentological properties, and deposit age. We show that a Modified Mercalli Intensity (MMI) of ∼V–V1/2 is the minimum shaking intensity required to generate localized sediment remobilization from deltaic slopes, and an MMI of ∼V1/2 is required to produce a deposit of sufficient thickness that a seismic origin can be confidently assigned. The documentation of seismically generated deposits in quick succession (∼2 years) with diagnostic features highlights the utility of using recent earthquakes as calibration events to investigate the subaqueous response to strong ground motion.

Alaska↗

USGS2025

Case study of deep learning image segmentation for the purposes of rapid 2D petrographic analysis in volcanic rocks

Automation using deep learning methods is a useful alternative to manual methods of petrographic segmentation, but often requires user familiarity with coding and/or algorithms. We examine the Dragonfly TM program's deep learning tools for application by users with a variety of skill levels as a method for petrographic image segmentation. An image processing methodology, bimodal image stacking, was created for low-input-data, high-efficacy training of models which can then be applied to varied samples. Using backscatter electron images we show that the resulting model segmentations agree with manual segmentation total and modal crystallinity values within 5%, and calculated plagioclase crystal size distribution (CSD) values within 2σ, despite limitations in discriminating mafic phases. Model creation and training takes <24 hours, 1–3 hours of which are supervised, and the resultant model can then be applied to new uncharacterized samples in <15 minutes per image. This allows for non-experts to create and utilize deep learning models to segment images of variable brightness and texture, at low user-time cost and resulting in size and shape data which are within uncertainty of manual segmentation. While some limitations are noted (for example, sieve-textured phases may need manual correction, and different minerals with similar BSE intensity may not be resolved as separate phases), this methodology can be utilized for general application of models to wide ranges of volcanic crystalline and bubble textures, and to create a library of models for rapid petrological analysis during volcanic eruptions.

Alaska↗

USGS2024

2024 Crustal Deformation Modeling Workshop report

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

Conference Paper↗

USGS2024

Streamflow depletion caused by groundwater pumping: Fundamental research priorities for management-relevant science

Reductions in streamflow caused by groundwater pumping, known as “streamflow depletion,” link the hydrologic process of stream-aquifer interactions to human modifications of the water cycle. Isolating the impacts of groundwater pumping on streamflow is challenging because other climate and human activities concurrently impact streamflow, making it difficult to separate individual drivers of hydrologic change. In addition, there can be lags between when pumping occurs and when streamflow is affected. However, accurate quantification of streamflow depletion is critical to integrated groundwater and surface water management decision making. Here, we highlight research priorities to help advance fundamental hydrologic science and better serve the decision-making process. Key priorities include (a) linking streamflow depletion to decision-relevant outcomes such as ecosystem function and water users to align with partner needs; (b) enhancing partner trust and applicability of streamflow depletion methods through benchmarking and coupled model development; and (c) improving links between streamflow depletion quantification and decision-making processes. Catalyzing research efforts around the common goal of enhancing our streamflow depletion decision-support capabilities will require disciplinary advances within the water science community and a commitment to transdisciplinary collaboration with diverse water-connected disciplines, professions, governments, organizations, and communities.

Water Resource Research↗

USGS1992

Nonpoint-source pollutant discharges of the three major tributaries to Reelfoot Lake, west Tennessee, October 1987-September 1989

An investigation of the concentration and loads of nitrogen, phosphorus, and suspended sediment in storm runoff to Reelfoot Lake, in western Tennessee, was conducted from October 1987 through September 1989. Concentrations of selected herbicides also were defined. Reelfoot Lake, with a surface area of about 15,500 acres, is the largest natural lake in Tennessee and an important recreation and fisheries resource. Previous studies showed that the lake is hypereutrophic, a condition caused by high concentrations of nutrients in water and sediments discharged from the three principal tributaries (South Reelfoot Creek, North Reelfoot Creek, and Running Slough) to the lake. Pesticides, including herbicides, have been detected in the lake's bottom sediments. Storm runoff contributed about 87percent of the total water discharge of the three main tributaries to Reelfoot Lake. South Reelfoot Creek contributed about 4.7 tons per acre per year of suspended sediment, while North Reelfoot Creek contributed about 1.9 tons per acre per year. Running Slough contributed only about 0.31 ton per acre per year of suspended sediment. Most of the suspended sediment was transported by storm runoff between October and March. About 80 percent of the annual streamflow of the three tributaries occurs during these months. The North Reelfoot Creek basin contributed 8.2 pounds per acre per year of total nitrogen and 2.4 pounds per acre per year of total phosphorus. South Reelfoot Creek basin contributed about 6.5 and 1.3 pounds per acre per year of total nitrogen and phosphorus, respectively, while Running Slough basin contributions were 3.4 and 0.86 pounds per acre per year, respectively. The differences in nutrient yields appear to result from more row-crop agriculture and the relatively steeply sloping agricultural land in the North Reelfoot Creek basin. Ninety-one percent of the total nitrogen load and 95 percent of the total phosphorus load in the three streams was transported by storm runoff. Significant differences in the mean concentrations of nutrients in runoff were defined between the active agricultural months (April through September) and the inactive months (October through March). Storm-runoff samples were analyzed for II selected triazine herbicides. Alachlor and atrazine were the most commonly detected herbicides. Thirty-two percent of the samples contained detectable levels of alachlor and 93 percent of the samples contained detectable levels of atrazine. Ninety percent of the samples collected during the active agricultural months contained detectable leveki of alachlor and all 29 samples contained detectable levels of atrazine. Sixteen samples exceeded lifetime health-advisory levels for atrazine in drinking water (3 micrograms per liter); two samples collected from the April IS, 1988, storm at North Reelfoot Creek and South Reelfoot Creek contained 42 and 57 micrograms per liter of atrazine, respectively. Concentrations of the other nine triazine herbicides were generally less than the level of detection (0.1 microgram per liter).

Tennessee↗

USGS2000

Water quality of the Quaternary and Ada-Vamoosa aquifers on the Osage Reservation, Osage County, Oklahoma, 1997

The project was to provide information on the quality of ground water from rural-domestic-water wells within the Osage Reservation and compare the water-quality to proximity to oil wells. About 38,500 oil wells have been drilled in the Reservation since drilling began in 1896. About 1,480 square miles or 64 percent of the Reservation is within a quarter mile of an oil well. The unconfined Quaternary sand aquifer covers about 315 square miles or about 14 percent of the Reservation and the confined Ada-Vamoosa sandstone aquifer covers about 800 square miles or about 35 percent of the Reservation. Fifty-eight percent of the Quaternary aquifer and 69 percent of the outcrop area of the Ada-Vamoosa aquifer are within a quarter mile of an oil well. One hundred twenty domestic ground-water wells were sampled from the Quaternary and Ada-Vamoosa aquifers. Forty-nine percent of the Reservation is underlain by the aquifers. Ground-water quality is good on most of the Reservation, but the use of domestic-water-supply wells tend to minimize water-quality problems. Existing water-supply wells commonly are located in areas that produce usable volumes of potable water. Several constituents in samples from the Ada-Vamoosa aquifer within a quarter mile of an oil well were significantly greater than from the aquifer not near oil wells. The constituents include specific conductance, dissolved solids, sodium, sulfate, chloride, bromide, and silica. These ions are probably derived from brine water. In the Ada-Vamoosa aquifer subgroups, 57 percent of the samples near oil wells and 24 percent of the samples not near oil wells had dissolved-solids concentrations greater than 500 milligrams per liter. The water quality in the Quaternary and Ada-Vamoosa aquifers is similar in areas where no oil wells have been drilled but is significantly different for several constituents. Median concentrations of major constituents from the Ada-Vamoosa aquifer not near oil wells were less than or equal to values from the Quaternary aquifer. Sixty-four percent of the water-quality samples from the Quaternary and 51 percent from the Ada-Vamoosa aquifers have dissolved-solids concentrations less than the secondary drinking water regulations of 500 milligrams per liter. Fifty-nine percent of the aquifer samples in the Quaternary aquifer subgroups not near oil wells and 70 percent of the samples near oil wells had dissolved solids less than 500 milligrams per liter. Areas in the Ada-Vamoosa aquifer near Hominy, Pershing, and Hula Lake have dissolved-solids concentrations greater than the secondary drinking water regulations. Water-quality samples from the Quaternary aquifer in these areas also have dissolved-solids concentrations greater than 500 milligrams per liter.

Oklahoma↗

USGS2025

Late Pleistocene kinematics of the Great Southern Puerto Rico Fault Zone, Puerto Rico

Several onshore faults in southern Puerto Rico have recently been recognized as Quaternary active. However, the kinematics of these faults, particularly any lateral component, remain largely unconstrained. It is difficult to characterize low strain‐rate faults, partially due to extensive erosional and anthropogenic landscape modification, steep relief, and frequent landsliding, limiting the preservation of geomorphic features that could serve as recorders of fault motion. Here, we constrain the kinematics along sections of the Great Southern Puerto Rico Fault Zone (GSPRFZ) on the southern coastal plain of Puerto Rico. We integrate ∼1‐m‐resolution light detection and ranging (lidar)‐derived topography, historical air photos, and field mapping to identify a series of ∼50–1200‐m‐long fault scarps and lineaments that trend northwest–southeast and extend for ≥25 km across the southern coastal plain. Fault scarps are primarily south facing, cut across topography, and displace Quaternary deposits and landforms. We document multiple offset geomorphic markers, including channel thalwegs and interfluves formed in deposits previously mapped as Quaternary piedmont alluvial plain. We observe both vertical (south‐side‐down) and right‐lateral meter‐scale displacements, which indicate that the GSPRFZ accommodates right‐lateral oblique motion in the late Pleistocene, consistent with northeast motion of the Puerto Rico and the Virgin Islands microplate away from the Hispaniola block.

Puerto Rico↗