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Source-linked reports with geographic coverage including United States.

At least 1,387 records · Page 77Linked to original sources

Site response and wave propagation effects in the eastern United States

Fourier amplitude spectra from regional earthquakes in the eastern United States are used in a parametric inversion for source, path, and site effects. Five earthquakes are selected for analysis during the installation of the United States National Seismic Network (US), Earthscope’s USArray Transportable Array (TA), and other temporary arrays to maximize station coverage. A global search algorithm is used to solve for site response from 0.1 to 15 Hz, corner frequency, geometrical spreading ( r - γ ), and frequency dependent anelastic attenuation in the form Q(f) = Q o f α . Tradeoff between moment and geometric spreading is handled by fixing the moment. The tradeoff between corner frequency and Q(f) is solved by selecting the value of corner frequency that minimizes an objective function defined over all stations. Values of site response and attenuation parameters show a strong spatial correlation with the physiographic provinces of the eastern United States. Site response for the Atlantic Coastal Plain is consistent with previous work using spectral ratios relative to a reference site, defined by strong resonance peaks correlated with the thickness of sediments. Site response for the other physiographic provinces is markedly different from the coastal plain, with a lack of distinct resonance peaks and a broad moderate high at frequences from 0.1 to 0.5 Hz consistent with the hard-rock geology of the regions. Like site response, Q(f) has a strong correlation with physiographic province, showing lower values on the coastal plain and higher values inland. Geometric spreading exponent, γ, decreases with increasing hypocenter distance from just above 1 at a few tens of kilometers to 0.9 at 500 km. The limited range in geometric spreading values is attributed to starting the Fourier transform window at the S ‐wave arrival for all distances and averaging over multiple wave types.

eastern United States↗

Applying U.S. Geological Survey science to understand effects to water supply in the Upper Colorado River Basin

Introduction The Colorado River Basin is a vital source of water to more than 40 million people in the Western United States and Mexico, including in major cities like Denver, Las Vegas, Phoenix, Tucson, Los Angeles, and San Diego, and supports irrigation for about 16,000 square kilometers of agricultural land. Since 2000, the southwestern United States has been unusually dry due to low precipitation and warm air temperatures, contributing to extreme water level declines of the two large reservoirs on the Colorado River, Lake Mead and Lake Powell. In 2021, these reservoirs reached their lowest levels on record, resulting in unprecedented restrictions on water usage in the basin. As much as 90 percent of the annual runoff in the Colorado River Basin originates in areas upstream from Lake Powell (hereafter, these areas will be referred to collectively as the “Upper Basin”). Consequently, understanding the processes that can affect water supply in the Upper Basin could be crucial for supporting human, agricultural, and ecological needs across a large spatial scale. The U.S. Geological Survey (USGS) does a wide variety of science in cooperation with resource managers, municipalities, tribes, and local, State, and Federal agencies to help improve understanding of processes, such as streamflow and water quality, potentially affecting water supply in the Upper Basin. This fact sheet describes three key potential factors affecting water supply in the Upper Basin—snow processes and water storage, wildfire and basin hydrology, and salinity concentrations and water quality—and highlights associated USGS research activities in the basin.

Arizona, Colorado, New Mexico, Utah, Wyoming↗

Three decades of declines restructure butterfly communities in the Midwestern United States

Insects are declining worldwide, yet gaps remain in our understanding of how declines are distributed across species within communities. Using three decades of butterfly monitoring data aggregated from the Midwestern United States, we found that no butterfly species increased in abundance from 1992 to 2023. 59 out of 136 species declined (annual mean trend: −1.2 to −6.9% per year) with losses distributed across all functional groups including residents, migrants, rare, and common species. Community composition changed such that abundance is now more even across species, driven by more severe losses in abundance—but not richness—of common species compared to rare species. These widespread declines are likely cascading across ecosystems. Conservation efforts that focus on entire communities could mitigate butterfly biodiversity loss.

Illinois, Indiana, Iowa, Michigan, Minnesota, Miss↗

The U.S. Geological Survey National Water Quality Network—Groundwater, 2024

The U.S. Geological Survey (USGS) operates a National Water Quality Network (NWQN) to monitor trends in groundwater quality and assess emerging contaminants of concern. It is a “network of networks” with 81 subnetworks being sampled on a decadal time scale. Each year, 8 of the subnetworks are sampled. Subnetworks have 20–30 wells each and include studies of domestic supply wells or shallow groundwater (20–50 feet deep) underlying urban land use or agricultural land use. Currently there are 2,089 wells in the network. All wells are sampled for physical properties, nutrients, major ions, trace elements, per- and polyfluoroalkyl substances (PFAS), and a subset of wells are sampled for pesticides, volatile organic compounds, radionuclides, and microbiological contaminants.

Contiguous United States↗

The U.S. Geological Survey National Atmospheric Deposition Program, National Trends Network, 2023

The U.S. Geological Survey (USGS) has been a National Atmospheric Deposition Program (NADP) partner agency since 1981. NADP is composed of five atmospheric monitoring networks that verify Clean Air Act effectiveness and provide essential data to protect human health and preserve ecosystems for current and future generations. Stakeholders include land management agencies overseeing sensitive habitats (the National Park Service, Bureau of Land Management, U.S. Forest Service, and Tribes), Federal and State regulatory agencies, and the public.

Contiguous United States↗

Evaluating trends using total impervious cover as a metric for degree of urbanisation

Impervious cover (IC) is a common metric for assessing the degree of urbanisation in watersheds. However, there are different methods for determining IC, and use of IC correlation with urban watershed response to hydrologic and geochemical inputs can be strongly influenced by the end members (IC below 10% and above 40%). The resolution of the imagery (e.g., 1 m vs. 30 m) used to measure IC can influence the estimate of IC, with differences up to 15% observed between these two resolutions for 21 watersheds along the east coast of the United States. The differences are greatest in the middle range between 10% and 40% IC. When using IC for correlation with urban watershed responses such as discharge flashiness or median solute concentrations, fits with R 2 between 0.4 and 0.78 were obtained when including end members of IC from 0% to 50%. However, when trying to distinguish behaviour between urban watersheds that fall in the middle ranges of IC, these same parameters do not correlate well with IC. Correlations fail significance tests, can switch direction, and fall below an R 2 of 0.1 without the end members of very low or very high IC. Because of improved accuracy, the finest resolution is preferred when available, and mixing IC estimation methods should be avoided. Furthermore, using regressions that include end members may not contribute to differentiating how IC in the 10%–40% range impacts hydrologic and geochemical responses in urban watersheds. Understanding this middle range of IC is important for comparing urban and suburban watersheds or planning watershed development to minimise impacts.

Delaware, Georgia, Maryland, New Jersy, New York, ↗

Forecast, monitor, adapt: A multi-agency strategy to protect people from postfire debris flows

In 2020, a wildfire burned across Glenwood Canyon in Colorado, USA. A history of postfire debris flows in the region and a hazard assessment for the burn area indicated that potentially life-threatening debris flows could be triggered by rainfall within months of a wildfire. As a result, four government agencies evaluated strategies to help mitigate hazards, including the loss of human life, that may be associated with debris-flow events. After the fire, 26 large debris flows occurred in the summer of 2021 and three sediment-laden flows occurred in the summer of 2023, but there were no major injuries or fatalities reported. We found that integrating hazard assessment/ forecasting, monitoring, and adaptation scenarios was a successful strategy for reducing postfire debris-flow risks to human life (including injuries and fatalities). Weather forecasts and estimates of debris-flow triggering rainfall thresholds, likelihood, and volume were used to anticipate the timing, location, and magnitude of debris-flow events. Rainfall monitoring and detailed recordkeeping of storms that triggered debris flows were used to validate and update debris-flow warning thresholds that varied with time following the wildfire. Although the governmental agencies working in this burn area had distinct and differing agency mandates, they were able to integrate information to reduce the risk of debris-flow events to human life.

Colorado↗

Representing 3-dimensional fuels for physics-based fire behavior models: A general framework and case study in a type-converted post-fire shrubfield

Background Physics-based three-dimensional (3D) fire behavior models improve planning for prescribed fire application and wildfire mitigation, but require high spatial resolution 3D fuel models as inputs. While multiple methods and data sources for realistically representing 3D, heterogeneous fuels are available, no unifying framework exists to guide the use of these tools to create 3D fuel models across gradients of vegetation characteristics and data availability. Existing data and methods are most uncertain for mid-level fuels (e.g., shrubs and small trees), due to canopy obstruction of remotely sensed data and a relative lack of modeling efforts. Yet, mid-level fuels are especially important as potential ladder fuels and increasingly common as the dominant fuel in type-converted, post-fire, shrub-dominated landscapes. Results Here we introduce the Framework for Representing 3D Fuels (FR3D), a general framework for combining multiple data sources and methods to construct 3D fuel models for forested and unforested landscapes. We then demonstrate FR3D in a case study to build a 3D fuelbed model in a post-fire, shrub-dominated landscape using three new methods for deriving mid-level shrub fuels from: (1) Airborne Laser Scanning (ALS), (2) imputation of Terrestrial Laser Scanning (TLS), and (3) generative modeling of TLS. We compare the resulting fuel models and examine how they affected simulated 3D fire behavior using QUIC-Fire. While each method represented the broad landscape patterning of shrubs, differences in shrub loading, height, and cover highlighted advantages and drawbacks of the different methods. Modeled fire behavior was realistic for all fuel representation methods, but rate of spread and fine fuel consumption was sensitive to the different arrangements of shrubs. Conclusions The sensitivity of fire behavior to shrub modeling methods emphasizes the need for fuel models that faithfully represent local fuelbed characteristics and conditions, and highlights the value in testing a range of modeled fuels to understand the potential range of prescribed fire outcomes. FR3D and novel methods of modeling mid-level fuel provide a foundation for tool integration efforts and increased site-specificity of fuel representation for physics-based fire models.

New Mexico↗

Decision-support modeling and research priorities for establishing baseline conditions for outstandingly remarkable values, Obed Wild and Scenic River, Tennessee

The Obed River is the last undammed river in Tennessee. The Obed Wild and Scenic River is managed by the National Park Service and covers a protected area of the Obed River headwaters (including four contributing tributaries). The Obed Wild and Scenic River supports a unique ecosystem with eight federally listed species. The National Park Service is responsible for preserving the baseline free-flowing condition of the river and associated outstandingly remarkable values (ORVs). Previous studies have been mostly project-based with differing methods, thus complicating efforts to quantify long-term changes in environmental conditions. This report presents a science plan summarizing (1) ORV conditions, (2) recent results of a decision-support hydrologic model for OBRI, and (3) possible future research priorities. The decision-support model was created to model streamflow conditions and changes in the ORVs since park establishment in 1976 and during three additional time periods. Established baseline conditions could help with management of ORVs not dependent on streamflow.

Tennessee↗

Random forest regression models for estimating low-streamflow statistics at ungaged locations in New York, excluding Long Island

This report is currently being updated with re‑calibrated random‑forest models for StreamStats implementation. The basin‑characteristic inputs were modified to align with StreamStats requirements. Abstract Models to estimate low-streamflow statistics at ungaged locations in New York, excluding Long Island and including hydrologically connected basins from bordering States, were developed for the first time by the U.S. Geological Survey, in cooperation with the New York State Department of Environmental Conservation. A total of 224 basin characteristics were developed for 213 unaltered streamgages (locations where the human effects on streamflow were limited), across the following categories: basin geometry, climate, land cover, soils, surficial geology, and other characteristics. The basins with unaltered streamgages were evaluated for potential redundancy, and streamgages in close proximity and with similar drainage areas were flagged and removed from the testing and cross-validation datasets to prevent data leaking from the training dataset to the testing dataset. Random forest regression models were created by using basin characteristics as predictor variables and by developing a workflow to train, tune, and test the model. Models were developed to estimate the ungaged lowest annual 7-day and 30-day average streamflow that occurs (on average) once every 10 years (7Q10 and 30Q10). The top four basin characteristics used for the 7Q10 and 30Q10 models were drainage area, total stream length, perimeter of the basin, and length of the longest flow path. Results for the 7Q10 and 30Q10 models had coefficients of determination ( R 2 ) of 0.796 and 0.853, respectively. The output model results were bias-corrected for ungaged locations across New York and are available within the interactive StreamStats tool.

New York↗

Analysis of summer water temperatures of the lower Virgin River near Mesquite, Nevada, 2019–21

The lower Virgin River is a sandy, shallow reach of the Virgin River that flows from northern Arizona to Lake Mead in Nevada. The Virgin River hosts several native fish species, including two endangered fish, woundfin ( Plagopterus argentissimu ) and Virgin River chub ( Gila seminuda ). All native fish species in the lower Virgin River have experienced reductions in population sizes in the last several decades. Reduced stream flow (especially during summer low-flow conditions) often results in increased water temperatures, which can increase mortality, reduce breeding, limit population connectivity, and favor non-native fish species. This study investigated summer water temperatures and flow in the lower Virgin River near Mesquite, Nev., between Littlefield, Ariz., and Bunkerville, Nev., to evaluate how hydrologic conditions could be affecting native fish species. The 3-year monitoring project involved collection of continuous temperature and discrete discharge measurements at 15 sites from 2019 to 2021 during the summer months from June to September. Results indicate that the lower Virgin River is often greater than 5 degrees Celsius (°C) above the established critical thermal maximum of 31 °C, that the cooling effect of the Littlefield springs dissipates quickly downstream, and that water temperature is affected primarily by atmospheric conditions. Discharge and water temperature are poorly related at normal stable flow conditions.

Arizona, Nevada↗

Evidence for marine-driven, cyclical fluctuations in burrow-nesting seabird habitat on the Oregon Coast

Seabirds are among the most threatened birds globally, with the loss or deterioration of coastal breeding habitats posing a severe threat. Natural and anthropogenic disturbances substantially influence coastal ecosystems through erosion and vegetation loss, altering habitat for the wildlife species that depend on them. In addition to these disturbances, oceanographic processes may play an important role in shaping the vegetation at breeding habitats; however, there is limited information on how vegetative conditions for burrow nesting seabirds have changed over time, and whether these changes are related to specific oceanographic or climatic factors. The Oregon Coast National Wildlife Refuge Complex, USA (NWRC) is home to a diverse suite of 1.3 million nesting seabirds from 14 species, which provide valuable ecological, economic, and cultural services, including nutrient transfer to terrestrial habitats and ecotourism for local communities. Over the last 30 years, populations of several burrow nesting seabird species including tufted puffin ( Fratercula cirrhata ) and rhinoceros auklet ( Cerorhinca monocerata ), which breed on offshore islands, have sharply declined along the Oregon Coast. To better understand the potential factors driving these declines, we conducted a spatiotemporal analysis of an aspect of burrow nesting seabird habitat, vegetation cover, within the Oregon Coast NWRC. Specifically, we quantified vegetative cover on 16 islands from 1992 to 2022 using a combination of empirical data, historical aerial photography (1992–2005), and aerial photography from the National Agriculture Imagery Program (2005–2022). Results showed cyclical fluctuations in vegetation cover coast-wide, which were closely related to large scale oceanographic oscillations. Specifically, vegetation cover was negatively correlated with the winter Pacific Decadal Oscillation and positively correlated with the spring El Nino Southern Oscillation. We did not directly compare seabird population trends to vegetation trends; however, quantifying these long-term changes in vegetation at breeding habitats can contribute to our comprehensive understanding of the myriad factors influencing seabird population dynamics and conservation.

Oregon↗

Land-based nutrient flux to a fringing reef: Insights from Ofu Island, American Samoa

Submarine groundwater discharge (SGD) is a critical driver of nutrient transport in coral reef ecosystems, shaping water quality, primary productivity, and overall reef health. This study quantifies SGD fluxes and associated nutrient dynamics in two reef flat pools within the Ofu Unit of the National Park of American Samoa: Papaloloa and Fatuana. A multi-method approach integrating unoccupied aerial system-based thermal infrared (UAS-TIR) surveys, radon-based SGD measurements, multichannel electrical resistivity tomography (ERT), and discrete water sampling was used to assess SGD rates and nutrient contributions. UAS-TIR imagery revealed cooler sea surface temperatures in both pools, indicative of SGD, with the higher fluxes observed in Papaloloa. Radon measurements revealed a strong inverse correlation between SGD rates and tidal stage, with a more immediate SGD response at Papaloloa due to its highly permeable calcareous sand and gravel substrate. In contrast, a 2–3-hour lag in SGD response at Fatuana suggests discharge from a more inland aquifer that has lower diffusivity. Nutrient concentrations correlated with temperature and salinity, confirming SGD as the dominant nutrient transport mechanism, whereas isotopic analyses indicated inputs from both groundwater and potential anthropogenic sources. Despite lower SGD flux at Fatuana, higher algal cover suggests additional factors influencing algal proliferation, including substrate availability and hydrodynamic conditions. Excess nutrient inputs from SGD may contribute to algal overgrowth, which threatens Ofu’s thermally tolerant corals by increasing competition for space and light. These findings underscore the complexity of SGD-mediated nutrient dynamics in reef environments and emphasize the need for integrated hydrological and ecological assessments to support effective reef conservation and management strategies.

American Samoa, Ofu Island, Olosega Island↗

Evidence of red fox (Vulpes vulpes) depredating a Saltmarsh Sparrow (Ammospiza caudacuta) nest

Saltmarsh Sparrows ( Ammospiza caudacuta ), a tidal-marsh specialist, face severe population declines due to habitat loss, sea-level rise, and predation. While previous research suggests that predation pressure increases at the southern extent of the species’ breeding range, data on local predator communities remain limited. To address this, we deployed game cameras at 16 Saltmarsh Sparrow nests across four salt marshes on Virginia’s eastern shore, the southern-most extent of their breeding range. Our study provides camera-documented evidence of red fox ( Vulpes vulpes ) predation on Saltmarsh Sparrow nests. We detected a suspected predation event by white-tailed deer ( Odocoileus virginianus ) and four other potential nest predators. Additionally, we detected a Willet ( Tringa semipalmata ) aggressively displacing a nesting female, suggesting interspecific interactions may contribute to nest failure.

Virginia↗

Food habits of Yellow Perch, Smallmouth Bass, and Northern Pikeminnow in Lake Cascade, Idaho

Objective Yellow Perch Perca flavescens was first encountered in Lake Cascade, Idaho, in 1957. Since its introduction, the abundance of Yellow Perch in Lake Cascade has been highly variable. Historically, declines in Yellow Perch abundance were attributed to predation by Northern Pikeminnow Ptychocheilus oregonensis . In the 1990s, Smallmouth Bass Micropterus dolomieu became established in Lake Cascade. Although Yellow Perch abundance has been high and currently supports a world-class fishery, the Idaho Department of Fish and Game has documented poor Yellow Perch recruitment in recent years, concerning regional managers. An investigation into the food habits of Yellow Perch, Smallmouth Bass, and Northern Pikeminnow was conducted to better understand the importance of juvenile Yellow Perch to predator diets. Methods In Lake Cascade, gill nets were deployed monthly from April 2022 to May 2023. Ageing structures and stomach contents were removed from Yellow Perch, Smallmouth Bass, and Northern Pikeminnow. Diet composition was quantified and then summarized by species, cohort, and season. Bioenergetics modeling, coupled with estimates of predator abundance, was used to evaluate overall consumption of Yellow Perch. Results In total, stomach contents were extracted from 1,099 Yellow Perch, 440 Smallmouth Bass, and 980 Northern Pikeminnow. Food habits varied by season and predator length, but Yellow Perch was a primary prey item of all study species. The energetic contribution of Yellow Perch to Yellow Perch varied from 10% to 80% across seasons. Smallmouth Bass consumed fewer Yellow Perch than either Yellow Perch or Northern Pikeminnow. The highest average per capita consumption of Yellow Perch (i.e., across seasons) was observed for 500–600-mm Northern Pikeminnow (five Yellow Perch/Northern Pikeminnow). Energetic contribution of Yellow Perch to Northern Pikeminnow diets was highest in spring 2023, yet Northern Pikeminnow consumed the highest average number of Yellow Perch in July. Bioenergetics modeling estimated that per-capita annual consumption of Yellow Perch was 6.0 kg for Yellow Perch, 3.4 kg for Smallmouth Bass, and 9.9 kg for Northern Pikeminnow. In total, estimated consumption of all study species was as high as 37% of the estimated total number age-0 Yellow Perch produced. Conclusions Yellow Perch was an important prey item for all three species, particularly Yellow Perch and Northern Pikeminnow. Results from this study provide important information on the predation of Yellow Perch in Lake Cascade. Further, this work will bolster a growing body of research on the food habits of and interactions between native and nonnative predators in western reservoir systems.

Idaho↗

The influence of human presence and footprint on animal space use in US national parks

Given the importance of protected areas for biodiversity, the growth of visitation to many areas has raised concerns about the effects of humans on wildlife. In 2020, the COVID-19 pandemic led to temporary closure of national parks in the United States, offering a pseudonatural experiment to tease apart the effects of permanent infrastructure and transient human presence on animals. We compiled GPS tracking data from 229 individuals of 10 mammal species in 14 parks and used third-order hierarchical resource selection functions to evaluate the influence of the human footprint on animal space use in 2019 and 2020. Averaged across all parks and species, animals avoided the human footprint, whether the park was open or closed. However, although animals in remote areas showed consistent avoidance, on average those in more developed areas switched from avoidance to selection when protected areas were closed. Findings varied across species: some responded consistently negatively to the footprint (wolves, mountain goats), some positively (mule deer, red fox) and others had a strong exposure-mediated response (elk, mountain lion). Furthermore, some species responded more strongly to the park closure (black bear, moose). This study advances our understanding of complex interactions between recreation and wildlife in protected areas.

western United States↗

Hydroclimatic and land-use factors affecting peak streamflow in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin

Flood-frequency analysis provides the basis for flood risk estimates used by water-resource managers in land-use planning, and it informs the design of essential infrastructure such as bridges and culverts. Federal guidelines for flood-frequency analysis do not offer guidance on addressing changing climate and land-use conditions when estimating floods. However, failing to consider climatic and land-use changes that cause abrupt or gradual changes in flood regimes can result in a poor representation of the true flood risk. In response to concerns about changing flood regimes, the U.S. Geological Survey, in cooperation with nine State agencies (Illinois Department of Transportation, Iowa Department of Transportation, Michigan Department of Transportation, Minnesota Department of Transportation, Missouri Department of Transportation, Montana Department of Natural Resources and Conservation, North Dakota Department of Water Resources, South Dakota Department of Transportation, and Wisconsin Department of Transportation) began a study to examine variability and change in hydrology and climate and the effects of urbanization and tile drainage on flooding. The analyses of patterns and changes in hydrology and climate were reported in a multichapter Scientific Investigations Report, the findings of which are summarized in this U.S. Geological Survey Circular. Additional analyses documenting changes in seasonality of flooding and the effects of urbanization and tile drainage were completed and published as separate studies and are also summarized in this Circular. These studies provide extensive exploratory analysis of peak streamflow, daily streamflow, and climate data, setting the stage for advancements in flood-frequency analysis.

Illinois, Iowa, Michigan, Minnesota, Missouri, Mon↗

The 3D Elevation Program—Supporting Tennessee’s economy

Introduction The State of Tennessee has an area of approximately 42,100 square miles and includes six physiographic regions: Blue Ridge, Valley and Ridge, Appalachian Plateaus, Highland Rim, Nashville Basin, and the Gulf Coastal Plains. Up-to-date elevation data support key activities across the State, such as economic development, infrastructure and construction management, agriculture and precision farming, forest resources management, natural resources conservation, flood risk management, emergency management, and urban and regional planning. The State experiences frequent landslides affecting major roadways. High-resolution elevation data can help identify potential landslide-prone areas. Critical applications that meet the State’s management needs depend on light detection and ranging (lidar) data that provide a highly detailed three-dimensional (3D) model of the Earth’s surface and aboveground features. The 3D Elevation Program (3DEP; refer to sidebar) is managed by the U.S. Geological Survey (USGS) in partnership with Federal, State, Tribal, U.S. territorial, and local agencies to acquire consistent lidar coverage at qual-ity level 2 or better to meet the many needs of the Nation and Tennessee. The status of available and in-progress 3DEP baseline lidar data in Tennessee is shown in figure 1. 3DEP baseline lidar data include quality level 2 or better, 1-meter or better digital elevation models, and lidar point clouds, and must meet the Lidar Base Specification version 1.2 ( https://www.usgs.gov/3dep/lidarspec ) or newer requirements. The National Enhanced Elevation Assessment identified user requirements and conservatively estimated that availability of lidar data would result in at least $6.32 million in new benefits annually to the State. The top 10 Tennessee business uses for 3D elevation data, which are based on the estimated annual conservative benefits of 3DEP, are shown in table 2.

Fact Sheet↗