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USGS2024

Precariously balanced rocks in northern New York and Vermont, U.S.A.: Ground-motion constraints and implications for fault sources

Precariously balanced rocks (PBRs) and other fragile geologic features have the potential to constrain the maximum intensity of earthquake ground shaking over millennia. Such constraints may be particularly useful in the eastern United States (U.S.), where few earthquake‐source faults are reliably identified, and moderate earthquakes can be felt at great distances due to low seismic attenuation. We describe five PBRs in northern New York and Vermont—a region of elevated seismic hazard associated with historical seismicity. These boulders appear to be among the most fragile PBRs in the region, based on reports from hobbyists. The PBRs are glacial erratics, best evidenced by glacial striations on bedrock pedestals. The pedestals themselves are locally high knobs, often situated on regionally high topography; this setting limits soil development and indicates that any outwash deposits were likely ephemeral. As a result, PBR ages can be reliably established by the retreat of the last continental ice sheet, ∼15–13 ka. To quantify the fragility of the PBRs, we surveyed them with ground‐based light detection and ranging and calculated geometric parameters from the point clouds, field observations, and seismic responses. Preliminary validation of the 2023 time‐independent U.S. National Seismic Hazard Model (NSHM) shows that the existence of PBRs is generally consistent with the median site‐specific hazard curves. Only the Blue Ridge Road site suggests a modest reduction in hazard. To visualize the ensemble of data, we mapped the minimum permissible distance to potential source faults around each PBR site as a function of source magnitude by using the ground‐motion models from the 2023 NSHM. Viewed in this manner, our data are consistent with potential M ∼6.5 earthquake‐source faults in many parts of the Lake Champlain Valley and northern Adirondack Mountains. Our work illustrates a potential pathway for better constraining earthquake‐source faults in regions of cryptic faults.

Bulletin of the Seismological Society of America↗
USGS2026

Re-examining the growing degree day minimum for grass carp spawning initiation in Lake Erie: Have we missed the mark?

Understanding the timing of life history processes of invasive fish species, such as adult aggregations during spawning, allows natural resource managers to optimize targeted population control efforts. Temperature-based estimates of the timing of spawning initiation for grass carp ( Ctenopharyngodon idella ) exist from its native range, but have not previously been developed for grass carp reproduction in its invaded range in the Laurentian Great Lakes of North America. We accounted for differences among methods across studies and calculated cumulative growing degree days (GDD) for the dates of grass carp egg capture in Lake Erie tributaries (Sandusky, Maumee, and Huron rivers) during 2015–2024 and compared these values to the existing GDD base 15°C requirement estimate from the native range (633 GDD–15°C). The earliest egg detection in Lake Erie (Sandusky River) was 19 GDD–15°C or 361 GDD–5°C (latest egg detection was 2285 GDD–5°C from the Sandusky River), indicating that spawning was initiated up to 25 days earlier than would be predicted by the native range GDD. Moreover, spawning in Lake Erie tributaries occurred earlier than predicted for 58% of spawning events examined based on the native range GDD. The GDD values for spawning initiation in Lake Erie tributaries can be used to refine the timing of control efforts targeting pre-spawn and spawning adult fish, inform the timing of egg sampling, and provide linkages to existing early life stage models to infer the length of the growing season available for age-0 fish to reassess tributary suitability.

Lake Erie, Maumee, River, Sandusky river↗
USGS2026

Polystyrene microplastics alter the accumulation and elimination dynamics of silver nanoparticles in Daphnia magna

Rationale Microplastics (MPs) can interact with engineered nanomaterials and alter their environmental fate and bioavailability. However, their influence on the bioaccumulation dynamics of silver nanoparticles (AgNPs) in aquatic filter feeders under environmentally relevant conditions remains poorly understood. We hypothesized that polystyrene microplastics (PS-MPs) alter the uptake, elimination and overall bioaccumulation dynamics of AgNPs in Daphnia magna . Methodology Adult D. magna were exposed to isotopically labeled citrate-coated 109 AgNPs in the presence and absence of PS-MPs. Waterborne uptake, dietary uptake, assimilation efficiency, food ingestion and elimination were quantified experimentally and incorporated into a biodynamic model to predict steady-state silver (Ag) concentrations under environmentally relevant exposure scenarios. Results PS-MPs increased waterborne Ag accumulation by approximately eightfold compared with AgNPs exposure alone. However, Ag elimination was substantially faster, with 98% of accumulated Ag eliminated after five days of depuration compared with 66% without PS-MPs. PS-MPs also reduced food ingestion rates (IRs), while assimilation efficiency remained largely unchanged. Biodynamic modeling predicted that steady-state Ag accumulation was approximately fivefold greater in the presence of PS-MPs, with waterborne exposure becoming the dominant accumulation pathway. Discussion These findings suggest that PS-MPs alter bioaccumulation dynamics of AgNPs in filter-feeding organisms by enhancing organism-associated Ag during waterborne exposure while accelerating Ag elimination, likely through particle-associated transport and gut egestion. Collectively, these results underscore the complexity of Ag bioaccumulation processes when MPs and AgNPs interact and highlight the importance of studies conducted under environmentally relevant conditions.

Environmental Chemistry↗
USGS2026

Relating glassy rind thicknesses to ambient air temperatures at the Lost Jim flow field in the Imuruk Lake volcanic field, Alaska

The Lost Jim flow field, in the Imuruk Lake volcanic field, Alaska, extends west ~34 km from a single vent, crossing subarctic tundra and currently touches several lakes and streams. The weighted mean of five 36Cl cosmogenic exposure ages from the Lost Jim pāhoehoe flow is 7.73 ± 0.37 ka, indicating this eruption occurred substantially after the eruption of the underlying Camille flow, which was emplaced at 39.7 ± 1.3 ka. Paleoclimate records indicate the period when the Lost Jim flow field was emplaced was after deglaciation, and the climate was similar to today. We propose that the emplacement of lava in these cold subarctic conditions can lead to faster cooling of the lava surface compared to lava emplaced in warmer locations such as mid- latitude cold deserts. Glass abundance in the outermost rinds at the Lost Jim flow field was on average 74 % with 6.4 mm thick rims, compared to 60 % with 2.9 mm rims for cold mid-latitude desert samples. We interpret increased glass content as a proxy for rapid cooling likely occurring partly during winter. Glassiness values varied less across vent, margin, and mid-flow locations when compared to the mid-latitude flows suggesting the Lost Jim flow field was broadly impacted by the subarctic climate as opposed to responding to local microclimates. Our results indicate that lava glassiness may be a useful environmental indicator of cooler (in this case subarctic) conditions.

Alaska↗
USGS2025

Divide and conquer: Separating the two probabilities in seismic phase picking

There are two fundamental probabilities in the seismic phase picking process – the probability of the existence of a seismic phase (detection probability) and the probability of correctly identifying the phase arrival time (timing probability). The nearly ubiquitous approach in developing deep learning phase picking models is to use a kernel, such as a truncated Gaussian, to mask the labeled phase arrival time, and train a segmentation model. Once a model is trained, the times of the peaks in the output are taken as phase arrival times (picks) and the height of the peaks are taken as “probability” of the picks. Here, we show that this “probability” represents neither the detection nor the timing probabilty because this approach forces the output to follow the shape of the kernel. We introduce an approach using two models to estimate these two distinct probabilities. We use a binary classifier with a calibrated confidence to address the detection probability and a multi-class classifier to obtain a probability mass function to address the timing probability. This new approach makes the deep learning-based phase picking process more interpretable and gives us options to logically control seismic monitoring workflows.

Geophysical Journal International↗
USGS2000

Method for estimating water use and interbasin transfers of freshwater and wastewater in an urbanized basin

Techniques for management of drainage basins that use water budgets to balance available water resources with actual or anticipated water use require accurate and precise estimates of basin withdrawals, interbasin transfers of freshwater, unaccounted-for use, water use, consumptive use, inflow and infiltration, basin return flow, and interbasin transfers of wastewater. Frequently, interbasin transfers of freshwater and wastewater are not included in basin water budgets because they occur within public water-delivery and wastewater-collection systems. A new 10-step method was developed to improve estimates of inflow and infiltration and interbasin transfers using readily available statewide data. The accuracy and precision of water-use estimates determined by this method are improved through careful application of coefficients for small users and the use of metered values for large users. The method was developed and tested with data for the Ten Mile River Basin in southeastern Massachusetts. This report uses examples from the basin to illustrate each step of the method.

Massachusetts↗
USGS2026

Prioritizing resource protection and understanding potential susceptibility of springs to surficial changes in a low-temperature geothermal system

Geothermal systems are vulnerable to changes in water budget and composition, requiring science-based management. This study uses a dataset of spring water temperatures, time series of groundwater residence time tracers (tritium and carbon-14), and stable isotopes of water to understand geothermal flow in a low-temperature geothermal system in north west Colorado, United States (Steamboat Springs). The geothermal system is bisected by the Yampa River, necessitating a stream mass balance approach to quantify total discharge. Time series analysis of water temperature data provides a ranked list of features more susceptible to surficial changes, which is corroborated using time series of tritium which indicate spatially distinct patterns of mixing between modern and pre-modern groundwater. All springs contain a portion of pre-modern groundwater that is thousands to tens of thousands of years old, a period coinciding with melting of extensive Pleistocene glaciers that was likely one of the recharge sources to the geothermal system. Stream mass balance indicates that greater than 80% of the total geothermal discharge is derived from diffuse or small springs, highlighting the extensive nature of the geothermal outflow zone and the association with local geologic structures. This study provides baseline data to support management of the Steamboat Springs geothermal system and indicates the utility of these approaches in developing science-based geothermal management.

Colorado↗
USGS2026

Reassessing water availability in the Nile River Basin using satellite-based irrigation water use accounting

Existing estimates of irrigation areas and water use in the Nile River Basin vary widely and are based on inconsistent data and methodologies. This study leverages advances in remote sensing to provide an up-to-date and consistent basin-wide reassessment of water use in the Nile River Basin. Land cover and actual evapotranspiration data from 2013 to 2022 were used to quantify irrigated areas, irrigation water use, and the average naturalized water yield. Across the basin, 7.1 million hectares of irrigated land consume an average of 72.5 ± 2.6 billion cubic meters (BCM) of blue water annually. Egypt and Sudan together account for 92% of the irrigated area and 97% of the irrigation water use. The basin’s average naturalized yield, evaluated at Dongola station, is determined to be between 108 and 114.4 ± 3.2 BCM. Although conservative, this updated analysis indicates the basin’s average naturalized yield is 14%–20% higher than the previous naturalized yield estimate (95 BCM) and 29%–36% higher than the commonly cited observed flow of 84 BCM, which is frequently treated as the total basin-wide available water. Importantly, the study underscores that the 84 BCM represents flow at the Aswan gauging station after upstream consumptive uses, not the total water available in the basin under naturalized conditions. This distinction is critical for accurate water accounting, planning, and governance in this water-scarce basin. This study demonstrates the value of open-source remote sensing resources in data-scarce regions while emphasizing the need for region specific validation and bias correction for improved accuracy.

Nile River Basin↗
USGS2026

Cotton farming pesticides affect ileal microbiota activity expressions of virulome but not resistome or metabolic pathways in a sedentary wild passerine

The increased use of agrochemicals to enhance crop production has had detrimental environmental effects including implication in the sharp decline of North American farmland-breeding birds. Here, using a combination of deep shotgun metatranscriptomics and pesticide exposure data, we sought to assess whether exposure to cotton ( Gossypium spp.) production had a differential effect on ileum multi-kingdom microbial activity, metabolism, anti-microbial resistance, and virulence factors of sedentary northern mockingbirds ( Mimus polyglottos ) sampled from two cotton-producing areas (16 birds in total) and one uncultivated area (7 birds) in Texas, USA. Both Shannon Index values (Adj. r 2 = 0.174, F (1,21) = 5.633, p = 0.027) and a Mantel test (Spearman ρ = 0.184, p = 0.013) supported a relationship between metabolically active microbiota Bray–Curtis dissimilarities and differences in pesticide mixtures among study areas. Virulence factor richness (Adj. r 2 = 0.182, F (1,21) = 5.890, p = 0.024), Shannon Index (Adj. r 2 = 0.231, F (1,21) = 7.612, p = 0.012), and load (sum of virulence factor abundances; Adj. r 2 = 0.160, F (1,21) = 5.194, p = 0.033) were related to total pesticide load (total quantity of pesticides). We found no pesticide effects on expression of either antimicrobial resistance genes or metabolic pathways.

Texas↗
USGS2026

Insights into Mountain Pass carbonatite formation from in-situ sulfur isotopes and geochemistry of sulfate and sulfide minerals

The Mountain Pass carbonatite stock hosts a world-class rare earth element deposit and may be classified as a carbonate-sulfate igneous rock, as it contains on average > 50 volume percent carbonate minerals and 20 to 30 volume percent sulfate minerals. The sulfates range in composition from barite to celestine and locally occur with sparse sulfide minerals. We investigate the origin of sulfur enrichment and the occurrence of sulfur-bearing minerals in the Mountain Pass carbonatite with in-situ sulfur isotope and mineral chemistry. Barite cores with δ 34 S of 1 to 3‰ do not coexist with sulfides, whereas celestine rims with δ 34 S of > 3‰ are associated with sulfides with δ 34 S < -10‰. We propose a model in which sulfur-bearing sediments were subducted during episodes of plate convergence in the Mojave Province that preceded Mountain Pass magmatism. Metasomatism of the overlying mantle by melts derived from the subducted sediments generated an unusually carbon- and sulfur-rich source to yield carbonatite magmas. Sulfur from primary carbonatite magmas and ~ 1 to 7% sulfur from subducted sediment melts yielded a slightly enriched δ 34 S composition (relative to depleted mantle δ 34 S of -1‰) for early crystallizing barite. Celestine rims on magmatic barite cores formed at low, hydrothermal temperatures (< 350 °C) based on S isotope thermometry for equilibrium celestine-galena and celestine-pyrite pairs. The sparse sulfides in the carbonatite stock are not in equilibrium with the primary barite cores and therefore do not permit S isotope thermometry estimates of magmatic temperatures. The S/Se ratios of sulfide minerals (> 3,400) typically exceed primitive mantle values (S/Se of 3,340), also consistent with their derivation from hydrothermal fluids. Trace occurrences of sulfide and sulfate minerals in alkaline silicate stocks related to the carbonatite stock have similar δ 34 S compositions and yield similarly low formation temperatures, suggesting regionally extensive and chemically similar sulfur-bearing hydrothermal fluids that imparted lithologically diverse rocks with a consistent sulfur isotope fingerprint.

California, Nevada↗
USGS2024

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

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

California↗
USGS2025

Cascading land surface hazards as a nexus in the Earth system

Earth’s surface is sculpted by numerous processes that move sediment, ranging from gradual and benign to abrupt and catastrophic. Although infrequent, high-magnitude sediment mobilization events can be hazardous to people and infrastructure, leaving topographic imprints on the landscape and remarkable narratives in the historical record. Hazardous events such as fires, storms, and earthquakes accelerate erosion and sediment transport, increasing landscape sensitivity to subsequent perturbations, thus forming a cascading hazard. Although the redistribution of sediment across Earth’s landscape can result in higher risks to vulnerable populations, cascading processes are commonly unaccounted for in hazard assessments. Cascading hazards can occur almost immediately after triggering events, such as coseismic landslides, or over months, years, or even decades after an initial perturbation, such as debris flows after wildfires or flooding in channels alluviated by volcanic debris. Sediment cascades span Earth’s surface, from mountaintops to river valleys, where erosion, deposition, and aggradation can lead to a myriad of hazardous processes, including decreased river conveyance capacity, which increases the likelihood of downstream flooding. An improved understanding of the magnitude, frequency, and persistence of cascading hazards is critical given the rapid changes in the frequency and severity of storms, fires, sea-level change, and cryospheric melting, as well as the expansion of high-population-density urban footprints in regions susceptible to solid Earth hazards. Understanding the full consequences and underlying physics of Earth’s cascading land surface hazards can help minimize future human and economic losses.

California↗
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↗
USGS2025

Assessing nonpoint-source uranium pollution in an irrigated stream-aquifer system

Uranium (U) in rocks and soils of arid and semi-arid environments can be mobilized by irrigation and fertilization, posing environmental and health risks. Elevated U, along with selenium (Se) and nitrate (NO 3 ) co-constituents, necessitates careful monitoring and management. We developed a distributed-parameter numerical model to assess U pollution in an irrigated stream-aquifer system, applying it to a 552 km 2 region in Colorado's Lower Arkansas River Valley (LARV) over 14 years. A MODFLOW model, describing groundwater and stream flow, was coupled with an RT3D-OTIS model to portray reactive U transport. Calibration using the PESTPP-iES iterative ensemble smoother (iES) software indicated good agreement with observed U concentrations. The model revealed substantial and variable U levels across the LARV, highlighting potential hotspots and possible contributing factors, such as geological composition of the bedrock and near-surface shale and aquifer sediments derived from them, irrigation practices, and riparian landscape. U levels exceed the chronic standard (85th percentile = 30 μg/L, set by the US Environmental Protection Agency), which is the permissible regulatory threshold, in groundwater across 44 % of the region and along the river by an average factor of 2.9. Simulated average U concentrations in the non-riparian aquifer and river are 124 μg/L and 60 μg/L, respectively, compared with 112 μg/L and 62 μg/L for measured values. The average 85th percentile U concentration is 222 μg/L in the aquifer and 82 μg/L in the river. Average simulated U mass loading to the river is 0.17 kg/day per km, compared to an estimated 0.23 kg/day per km. Findings provide a baseline for comparing future simulated outcomes of alternative best management practices (BMPs) for U pollution mitigation and offer a methodology applicable to other irrigated regions.

Colorado↗
USGS2026

Suitability of ground-motion models for seismic hazard assessment in Puerto Rico and the U.S. Virgin Islands

We perform linear mixed-effects analyses with a ground-motion dataset to evaluate how well ground-motion models (GMMs) fit active crustal, subduction interface, and subduction intraslab earthquakes in Puerto Rico and the US Virgin Islands. Most of the GMMs reproduce the spatial variation in peak ground motions with earthquake magnitude and rupture distance but predict ground motions 0.3–1.0 natural log units (35%–270%) greater than observations. Two GMMs developed for Puerto Rico that are based on ground-motion records from mostly magnitude 4–5 earthquakes do not perform as well. We attribute the period-dependent overprediction in observed ground motions to differences between the observed site response and the linear site response in the GMMs. Consequently, we developed region-specific GMMs by adjusting the period-dependent linear site response coefficients and period-dependent constant coefficients to remove most of the bias between predicted ground motions and observations. For the analysis, we compile ground-motion records and process waveforms to build a dataset with 10,127 records at 72 stations from 849 magnitude 4.0–6.4 earthquakes between 1 January 2006 and 31 March 2024. The earthquakes include active crustal, subduction interface, and subduction intraslab events. We evaluate the GMMs using the time-averaged shear wave speed in the top 30 m ( ), which we compile from site surveys and proxy values computed from horizontal to vertical spectral ratios. Site terms exhibit strong consistency across GMMs and crustal and subduction earthquakes, indicating that the linear mixed-effects analysis successfully isolates the effects of local site response. The event terms show little spatial correlation and more substantial variability than in other regions, which we attribute to uncertainties in the earthquake magnitudes. This analysis guides the selection of the GMMs for the 2025 update of the National Seismic Hazard Model for Puerto Rico and the US Virgin Islands.

Puerto Rico, U.S. Virgin Islands↗
USGS1999

Characterization of selected biological, chemical, and physical conditions at fixed sites in the Upper Colorado River Basin, Colorado, 1995-98

Biological community samples were collected at 15 sites in the Upper Colorado River Basin (UCOL) in Colorado as part of the National Water-Quality Assessment (NAWQA) Program. Sites sampled in two physiographic provinces, the Southern Rocky Mountains and the Colorado Plateau, represented agriculture, mining, urban and recreation, and mixed land uses and background conditions. Nine measures of water quality, which include information on nutrients, specific conductance (a surrogate for salinity), trace elements in streambed sediment, pesticides in fish tissue, fish communities, and macroinvertebrate richness and composition and stream habitat were used for comparisons among sites within the two physiographic provinces. Sampling sites from three other NAWQA study units—the Rio Grande Valley, the South Platte River Basin, and the Upper Snake River Basin study units—were categorized on the basis of land use and stream size in order to develop a larger data set for comparison to sites in the UCOL. Three categories of land use—forested (includes mining, urban and recreation, and background), agriculture, and mixed—were used for comparison to the UCOL fixed sites. Results indicated that all sites other than the Colorado River below Baker Gulch (a background site) showed some water-quality characteristics to be significantly affected. Results indicated that the concentrations of cadmium and zinc in streambed sediment at mining land-use sites in the Southern Rocky Mountains physiographic province generally were orders of magnitude higher than streambed-sediment concentrations at the background site. Streambed-sediment concentrations at mining land-use sites in the UCOL were greater than the 75 th percentile of concentrations from sites in the three other NAWQA study units. Fish communities and habitat conditions were degraded at mining land-use sites compared to the background site. Ephemeroptera, Plecoptera, and Trichoptera (EPT) richness and the percentage of EPT were lower at mining land-use sites than at the background site and were less than the 50 th percentile of those for sites from the three other NAWQA study units. Nutrient concentrations at urban and recreation sites in the Southern Rocky Mountain physiographic province generally were greater than concentrations at the background site and generally were between the 25 th and 90 th percentile of concentrations for sites from the three other NAWQA study units. Habitat conditions and fish communities at urban and recreation sites were slightly degraded compared to the background site. EPT richness and the percentage of EPT were lower at urban and recreation sites than at the background site and were between the 25 th and 75 th percentile of those for sites from the three other NAWQA study units. The percentage of Chironomidae, which may be indicative of pollutant-tolerant organisms, was higher at urban and recreation sites than at the background site. Mixed land-use sites in the Southern Rocky Mountains physiographic province had similar nutrient concentrations and similar cadmium and zinc streambed-sediment concentrations. Fish-community degradation index values were very different among the three mixed land-use sites in the Southern Rocky Mountains physiographic province. Larger percentages of omnivores and anomalies such as lesions and deformities at two mixed land-use sites resulted in higher degradation values of the fish community. Agriculture land-use sites had higher concentrations of nutrients and selenium than the background site in the Colorado Plateau physiographic province. Concentrations of p,p '-DDE in fish tissue at agriculture sites were higher than the 75 th percentile of concentrations for sites from the three other NAWQA study units. Fish communities had degradation values near the 75 th percentile for agriculture sites. The percentage of EPT was low at agriculture sites when compared to the background site. Two mixed land-use sites in the Colorado Plateau physiographic province had similar concentrations of nutrients, selenium, and p,p '-DDE, and similar EPT richness and composition. These two sites were located downstream from agricultural and urban activities. Some water-quality measures at these two sites indicated degradation compared to a mixed land-use site upstream from most of the agriculture and urban activities in the Colorado Plateau physiographic province.

Colorado↗
USGS2026

Hazard potential of compound flooding from rainfall, storm surge, and groundwater in coastal New York and Connecticut

Compound flood events, the co-occurrence of multiple flood drivers, can result in flood hazard potential exceeding that of any single driver alone. To evaluate compound flooding in a semi-urbanized coastal area, historical records dating back to 1970 are used to study the co-occurrences of high precipitation, storm surge, and shallow groundwater conditions along the coastlines of New York and Connecticut. Joint return periods for coincident precipitation-surge events were computed using statistical dependence models and compared to the assumption of independence as a ratio, referred to here as a return period adjustment. Results indicate distinct seasonality where compound events in the area disproportionately occur in the cold season between October and April. Return period adjustments range from a factor of 1 to almost 9, demonstrating the range in precipitation-storm surge dependence across the study area. Across all 24 station triad locations, groundwater levels were elevated during times of precipitation- surge co-occurrence, reflecting the tendency for coastal storms and shallow groundwater conditions to co-occur seasonally. The result is a pseudo-trivariate compound flood hazard score and corresponding hazard map that integrates dependence between daily precipitation-surge events and overall monthly groundwater levels (as a precondition) into a relative compound hazard score. The location with the highest compound flood hazard score is on the south shore of Long Island, as well as locations across coastal Connecticut where groundwater levels compound the co-occurrence of heavy precipitation and storm surge.

Connecticut, New York↗
USGS2025

Approximate inland extent of saltwater intrusion at the base of the Biscayne aquifer, Miami-Dade County, Florida, 2022

Miami-Dade County is part of a densely populated urban corridor in southeastern Florida. The Biscayne aquifer serves as Miami-Dade County’s primary drinking water source and is characterized by highly permeable karstic limestone and carbonate sand. The aquifer’s coastal location and permeable nature make it susceptible to saltwater intrusion. Monitoring the current inland extent and the rate of movement of the saltwater front in the aquifer can inform management strategies for conserving the long-term sustainability of the county’s water supply. In the 1950s, the U.S. Geological Survey published a map of the inland extent of saltwater intrusion in the Biscayne aquifer and has continued to update this map to monitor changes over time, with the most recent update published in 2018. An updated map has been created showing the approximate inland extent of saltwater intrusion in the Biscayne aquifer in eastern Miami-Dade County in 2022, with the 2018 extent shown for comparison. The inland extent of saltwater intrusion was mapped through the interpretation of borehole electromagnetic induction logs and measurements of chloride and specific conductance in groundwater samples. The location of the saltwater interface at the base of the Biscayne aquifer was represented by the 1,000-milligram-per-liter isochlor. This report describes changes in the location of the saltwater interface from 2018 to 2022. By 2022, the saltwater interface had moved farther inland in both the northern and southern parts of the county, advancing by as much as 0.3 kilometer in the north and up to 0.8 kilometer in the Model Land Area to the south. However, it remained relatively unchanged from its 2018 position in the east-central part of the county.

Florida↗