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Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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At least 973 records · Page 54Linked to original sources

USGS2021

Landscape characterization of floral resources for pollinators in the Prairie Pothole Region of the United States

Across agricultural areas of the Prairie Pothole Region (PPR), floral resources are primarily found on public grasslands, roadsides, and private grasslands used as pasture or enrolled in federal conservation programs. Little research has characterized the availability of flowers across the region or identified the primary stakeholders managing lands supporting pollinators. We explored spatial and temporal variability in flower abundance and richness across multiple grassland categories (i.e. general grassland, conservation grassland, and engineered pollinator habitat) in the PPR from 2015 to 2018 and used these data to estimate the number of flowering stems present across the region on private and public land holdings. Both flowering plant abundance and richness were greatest on engineered pollinator habitat, but this land category encompassed <0.01% of the total grassland area in the PPR. There was a steady decrease in flower abundance over the growing season across all land categories. We detected considerable variation in flower abundance and richness across grassland categories, indicating that not all natural or semi-natural covers provide similar value to pollinators. At a landscape scale, large land holdings such as privately-owned grasslands and Conservation Reserve Program lands contributed the greatest number of flowers by an order of magnitude, though these lands collectively did not support the greatest abundance of flowers per unit area. Our research depicts spatial and temporal variation in pollinator resources across the region. Further, our research will assist managers and policy makers in understanding the role of public and private lands and conservation programs in supporting pollinators.

Minnesota, North Dakota, South Dakota↗

USGS2013

The role of airborne mineral dusts in human disease

Exposure to fine particulate matter (PM) is generally acknowledged to increase risk for human morbidity and mortality. However, particulate matter (PM) research has generally examined anthropogenic (industry and combustion by-products) sources with few studies considering contributions from geogenic PM (produced from the Earth by natural processes, e.g., volcanic ash, windborne ash from wildfires, and mineral dusts) or geoanthropogenic PM (produced from natural sources by processes that are modified or enhanced by human activities, e.g., dusts from lakebeds dried by human removal of water, dusts produced from areas that have undergone desertification as a result of human practices). Globally, public health concerns are mounting, related to potential increases in dust emission from climate related changes such as desertification and the associated long range as well as local health effects. Recent epidemiological studies have identified associations between far-traveled dusts from primary sources and increased morbidity and mortality in Europe and Asia. This paper provides an outline of public health research and history as it relates to naturally occurring inorganic mineral dusts. We summarize results of current public health research and describe some of the many challenges related to understanding health effects from exposures to dust aerosols.

Aeolian Research↗

USGS2018

Ask not what nature can do for you: A critique of ecosystem services as a communication strategy

Given the urgent need to raise public awareness on biodiversity issues, we review the effectiveness of “ecosystem services” as a frame for promoting biodiversity conservation. Since its inception as a communications tool in the 1970s, the concept of ecosystem services has become pervasive in biodiversity policy. While the goal of securing ecosystem services is absolutely legitimate, we argue that it has had limited success as a vehicle for securing public interest and support for nature, which is crucial to securing long-term social mandates for protection. Emerging evidence suggests that focusing on ecosystem services rather than the intrinsic value of nature is unlikely to be effective in bolstering public support for nature conservation. Theory to guide effective communication about nature is urgently needed. In the mean-time, communicators should reflect on their objectives and intended audience and revisit the way nature is framed to ensure maximum resonance.

Biological Conservation↗

USGS2021

Social identity, values, and trust in government: How stakeholder group, ideology, and wildlife value orientations relate to trust in a state agency for wildlife management

Our objective was to understand how social identity and values influenced general public and stakeholder trust in a state wildlife management agency (SWMA). In particular, we wanted to examine how stakeholder group, political ideology, and wildlife value orientation influenced trust in a SWMA. Data were derived from a study of state residents, hunters and livestock producers related to wolf management. Results suggest differences in agency trust correlated with all three factors and the interaction between stakeholder group and wildlife value orientation. Livestock producers reported lower levels of trust in the agency, compared to hunters and the general public. Individuals with conservative or middle-of-the-road ideologies reported less trust in the agency than individuals with a liberal ideology did. Respondents with traditional wildlife values also had less trust in the agency compared to mutualist, pluralist, and distanced respondents. Results suggested similarities in the ideologies and wildlife value orientations of livestock producers and hunters, although these groups differed significantly in their trust in the agency. Agencies face the challenge of managing common-pool, public-trust resources for stakeholders who hold different values and ideologies, and who are differentially affected by management decisions.

Minnesota↗

USGS2024

The US COVID-19 and Influenza Scenario Modeling Hubs: Delivering long-term projections to guide policy

Between December 2020 and April 2023, the COVID-19 Scenario Modeling Hub (SMH) generated operational multi-month projections of COVID-19 burden in the US to guide pandemic planning and decision-making in the context of high uncertainty. This effort was born out of an attempt to coordinate, synthesize and effectively use the unprecedented amount of predictive modeling that emerged throughout the COVID-19 pandemic. Here we describe the history of this massive collective research effort, the process of convening and maintaining an open modeling hub active over multiple years, and attempt to provide a blueprint for future efforts. We detail the process of generating 17 rounds of scenarios and projections at different stages of the COVID-19 pandemic, and disseminating results to the public health community and lay public. We also highlight how SMH was expanded to generate influenza projections during the 2022–23 season. We identify key impacts of SMH results on public health and draw lessons to improve future collaborative modeling efforts, research on scenario projections, and the interface between models and policy.

Epidemics↗

USGS2020

Developing post-alert messaging for ShakeAlert, the earthquake early warning system for the West Coast of the United States of America

As ShakeAlert, the earthquake early warning system for the West Coast of the U.S., begins its transition to operational public alerting, we explore how post-alert messaging might represent system performance. Planned post-alert messaging can provide timely, crucial information to both emergency managers and ShakeAlert operators as well as calibrate expectations among various publics or public user groups and inform their responses to future alerts. There is a concern among the scientists and emergency managers that false alerts may negatively impact trust in the system, so quickly disseminated post-alert messages are necessary. For a new early warning system, such as ShakeAlert, this is particularly relevant given that the potentially affected population is likely to be unfamiliar with this system. We address this concern in six steps: (1) assessment of ShakeAlert performance to date, (2) characterization of human behavior and response to earthquake alerts, (3) presentation of a decision tree for issuing post-alert messages, (4) design of a critical set of post-alert messaging scenarios, (5) elaboration of these scenarios with message templates for a variety of communication channels, and (6) development of a typology of earthquake alerts. We further explore methods for monitoring and evaluating ShakeAlert post-alert messaging, for continuous improvement to the system.

California, Oregon, Washington, Idaho, Nevada, Uta↗

USGS2023

Perceptions of volcanic air pollution and exposure reduction practices on the Island of Hawai‘i: Working towards socially relevant risk communication

Kīlauea volcano, on the Island of Hawai‘i, is one of the most active volcanoes in the world. Over the past four decades it has released large amounts of volcanic gases and aerosols which form volcanic air pollution known as ‘vog’. Communities downwind of Kīlauea have been chronically or episodically exposed to this potentially harmful air pollution and have raised concerns about the hazards of vog exposure. Public health and civil protection agencies have offered a range of advice, information, and mitigation strategies for living with vog. In this mixed-methods social study, we investigate the translation of official advice into practice in Island of Hawai‘i communities and assess how risk communication could be improved by considering public input, preferences, and community relevance. Given the paucity of information on the long-term effects of chronic vog exposure, assessing the effectiveness of public health and risk communication is vital.

Hawaii↗

USGS2019

Factors affecting 1,2,3-trichloropropane contamination in groundwater in California

1,2,3-Trichloropropane (1,2,3-TCP) is a volatile organic chemical of eminent concern due to its carcinogenic, mutagenic, and reproductive effects, and its frequent occurrence at concentrations of concern worldwide. In California, 1,2,3-TCP was detected in 6.5% of 1237 wells sampled by the U. S. Geological Survey (USGS). About 8% of domestic wells had a detection of 1,2,3-TCP, compared to 5% of public-supply wells. 1,2,3-TCP was detected in 5.5% of most recent samples from 7787 public-supply well sources of the California State Water Resources Control Board Division of Drinking Water (DDW). Concentrations ranged from <0.005 to 2.7 μg/L. The California maximum contaminant level (MCL) is 0.005 μg/L. Most of the detections occurred in the San Joaquin Valley, where 1,2,3-TCP was detected above the MCL in 16% of USGS sampled wells and 18% of DDW wells. 1,2,3-TCP occurrence and concentrations are related to legacy fumigant use and hydrogeologic factors. Understanding factors affecting 1,2,3-TCP will aid in determining vulnerability and long term persistence in the San Joaquin Valley, which can help focus efforts to manage drinking water resources on the most vulnerable areas and also inform efforts in other areas of the state and worldwide. Widespread occurrence of 1,2,3-TCP is related to nonpoint source agricultural contaminant inputs. High concentrations of 1,2,3-TCP are in young, shallow, oxic groundwater beneath primarily orchard/vineyard crops. These areas are in coarse-grained sediments that promote rapid recharge, related to proximal alluvial fan sediments deposited by large streams that drain glaciated watersheds of the Sierra Nevada. 1,2,3-TCP co-occurs with 1,2-dibromo-3-chloropropane (DBCP) and 1,2-dichloropropane (1,2-DCP) throughout modern age groundwater, indicating its long term persistence with little degradation. The highest concentrations of 1,2,3-TCP were observed at point source cleanup sites in urban areas; depending on the age and source of groundwater to nearby public-supply wells, these areas may see increasing concentrations of 1,2,3-TCP.

California↗

USGS2023

Latency and geofence testing of wireless emergency alerts intended for the ShakeAlert® earthquake early warning system for the West Coast of the United States of America

ShakeAlert, the earthquake early warning (EEW) system for the West Coast of the United States, attempts to provides crucial warnings before strong shaking occurs. However, because the alerts are triggered only when an earthquake is already in progress, and the alert latencies and delivery times are platform dependent, the time between these warnings and the arrival of shaking is variable. The ShakeAlert system uses, among other public alerting platforms like a mobile phone operating system, smartphone apps, and the Federal Emergency Management Agency Integrated Public Alert & Warning System (IPAWS). IPAWS sends Wireless Emergency Alerts (WEAs) informing people via their smartphones and other mobile devices about various events, such as natural hazards, child abductions, or public health information about COVID-19. However, little is known about the IPAWS delivery latencies. Given that people may have only a few seconds of notice after they receive an alert to take a protective action before they feel earthquake shaking, quantifying latencies is critical to understanding whether the IPAWS system is useful for EEW. In this study, we developed new methods to test the IPAWS distribution system's performance, both with devices in a controlled environment and as well as with a 2019 community-based feedback form, in Oakland and San Diego County, California, respectively. The controlled environment test used mobile phones (including smart and non-smart phones) and associated devices to determine alert receipt times; the community research form had participants self-report their receipt times. By triangulating the data between the controlled test environment and the community research, we determined the latency statistics as well as whether the geofence (the geographic area where the alert was intended to be sent) held broadly. We found that the latencies were similar between the two tests despite the large differences in population sizes. WEA messages were received within a median time frame of 6–12 s, and the geofence held with only a few exceptions. We use this latency to assess how the system would have performed in two large earthquakes, the 1989 M6.9 Loma Prieta and 2019 M7.1 Ridgecrest earthquakes, which both occurred near our WEA test locations. Our analysis revealed that had IPAWS been available during those earthquakes, particularly Loma Prieta, it would have provided crucial seconds of notice that damaging shaking was imminent in some locations relatively far from the epicenter. Further, we find affordable non-smart phones can receive WEAs as fast as smartphones. Finally, our new method can be used for latency and geospatial testing going forward for IPAWS and other similar alerting systems.

California↗

USGS2021

Machine learning models of arsenic in private wells throughout the conterminous United States as a tool for exposure assessment in human health studies

Arsenic from geologic sources is widespread in groundwater within the United States (U.S.). In several areas, groundwater arsenic concentrations exceed the U.S. Environmental Protection Agency maximum contaminant level of 10 μg per liter (μg/L). However, this standard applies only to public-supply drinking water and not to private-supply, which is not federally regulated and is rarely monitored. As a result, arsenic exposure from private wells is a potentially substantial, but largely hidden, public health concern. Machine learning models using boosted regression trees (BRT) and random forest classification (RFC) techniques were developed to estimate probabilities and concentration ranges of arsenic in private wells throughout the conterminous U.S. Three BRT models were fit separately to estimate the probability of private well arsenic concentrations exceeding 1, 5, or 10 μg/L whereas the RFC model estimates the most probable category (≤5, >5 to ≤10, or >10 μg/L). Overall, the models perform best at identifying areas with low concentrations of arsenic in private wells. The BRT 10 μg/L model estimates for testing data have an overall accuracy of 91.2%, sensitivity of 33.9%, and specificity of 98.2%. Influential variables identified across all models included average annual precipitation and soil geochemistry. Models were developed in collaboration with public health experts to support U.S.-based studies focused on health effects from arsenic exposure.

Environmental Science and Technology↗

USGS2024

Estimating lithium concentrations in groundwater used as drinking water for the conterminous United States

Lithium (Li) concentrations in drinking-water supplies are not regulated in the United States; however, Li is included in the 2022 U.S. Environmental Protection Agency list of unregulated contaminants for monitoring by public water systems. Li is used pharmaceutically to treat bipolar disorder, and studies have linked its occurrence in drinking water to human-health outcomes. An extreme gradient boosting model was developed to estimate geogenic Li in drinking-water supply wells throughout the conterminous United States. The model was trained using Li measurements from ∼13,500 wells and predictor variables related to its natural occurrence in groundwater. The model predicts the probability of Li in four concentration classifications, ≤4 μg/L, >4 to ≤10 μg/L, >10 to ≤30 μg/L, and >30 μg/L. Model predictions were evaluated using wells held out from model training and with new data and have an accuracy of 47–65%. Important predictor variables include average annual precipitation, well depth, and soil geochemistry. Model predictions were mapped at a spatial resolution of 1 km 2 and represent well depths associated with public- and private-supply wells. This model was developed by hydrologists and public-health researchers to estimate Li exposure from drinking water and compare to national-scale human-health data for a better understanding of dose–response to low (<30 μg/L) concentrations of Li.

conterminous United States↗

USGS2022

Tapwater exposures, effects potential, and residential risk management in Northern Plains Nations

In the United States (US), private-supply tapwater (TW) is rarely monitored. This data gap undermines individual/community risk-management decision-making, leading to an increased probability of unrecognized contaminant exposures in rural and remote locations that rely on private wells. We assessed point-of-use (POU) TW in three northern plains Tribal Nations, where ongoing TW arsenic (As) interventions include expansion of small community water systems and POU adsorptive-media treatment for Strong Heart Water Study participants. Samples from 34 private-well and 22 public-supply sites were analyzed for 476 organics, 34 inorganics, and 3 in vitro bioactivities. 63 organics and 30 inorganics were detected. Arsenic, uranium (U), and lead (Pb) were detected in 54%, 43%, and 20% of samples, respectively. Concentrations equivalent to public-supply maximum contaminant level(s) (MCL) were exceeded only in untreated private-well samples (As 47%, U 3%). Precautionary health-based screening levels were exceeded frequently, due to inorganics in private supplies and chlorine-based disinfection byproducts in public supplies. The results indicate that simultaneous exposures to co-occurring TW contaminants are common, warranting consideration of expanded source, point-of-entry, or POU treatment(s). This study illustrates the importance of increased monitoring of private-well TW, employing a broad, environmentally informative analytical scope, to reduce the risks of unrecognized contaminant exposures.

North Dakota, South Dakota↗

USGS2012

Factors associated with sources, transport, and fate of chloroform and three other trihalomethanes in untreated groundwater used for drinking water

Multiple lines of evidence for indicating factors associated with the sources, transport, and fate of chloroform and three other trihalomethanes (THMs) in untreated groundwater were revealed by evaluating low-level analytical results and logistic regression results for THMs. Samples of untreated groundwater from wells used for drinking water were collected from 1996-2007 from 2492 wells across the United States and analyzed for chloroform, bromodichloromethane, dibromochloromethane, and bromoform by a low-level analytical method implemented in April 1996. Using an assessment level of 0.02 μg/L, chloroform was detected in 36.5% of public-well samples and 17.6% of domestic-well samples, with most concentrations less than 1 μg/L. Brominated THMs occurred less frequently than chloroform but more frequently in public-well samples than domestic-well samples. For both public and domestic wells, THMs occurred most frequently in urban areas. Logistic regression analyses showed that the occurrence of THMs was related to nonpoint sources such as urban land use and to point sources like septic systems. The frequent occurrence and concentration distribution pattern of THMs, as well as their frequent co-occurrence with other organic compounds and nitrate, all known to have anthropogenic sources, and the positive associations between THM occurrence and dissolved oxygen and recharge indicate the recycling of water that contains THMs and other anthropogenic contaminants.

Environmental Science & Technology↗

USGS2021

Commentary: The role of geodetic algorithms for earthquake early warning in Cascadia

The ShakeAlert earthquake early warning (EEW) system issues public alerts in California and will soon extend to Oregon and Washington. The Cascadia subduction zone presents significant new challenges and opportunities for EEW. Initial publications suggested that EEW algorithms based on Global Navigation Satellite System (GNSS) data could provide improved warning for intraslab events and dramatically improved warning for offshore megathrust events, both of which contribute significantly to hazard in Cascadia. We find that some expectations in these publications were unrealistic, and we demonstrate that in general geodetic algorithms would not produce timely warnings for intraslab events nor warning times of two minutes or more for severe shaking from megathrust earthquakes. Nonetheless, lessons from recent earthquakes in Japan and California, for which alerts from seismic algorithms suffered from magnitude saturation and high data latencies, demonstrate the urgent need for rigorous testing of geodetic EEW as a potential complement to seismic EEW.

California, Oregon, Washington↗

USGS2014

Report of the committee on chemistry of natural waters, 1935–36

The membership of this Committee was not changed during the past year. A publication has appeared during the year giving the analytical data assembled for and used as a basis for Bulletin 40 of the Department of Public Works, California. This new publication, printed as 40‐A, is entitled “Detailed analyses showing qualities of irrigation‐waters.” Analyses are given for both surface‐ and ground‐waters.

Eos, Transactions, American Geophysical Union↗

USGS2020

A continuously updated, geospatially rectified database of utility-scale wind turbines in the United States

Nearly 60,000 utility-scale wind turbines are installed in the United States as of July, 2019, representing over 97 gigawatts of electric power capacity; US wind turbine installations continue to grow at a rapid pace. Yet, until April 2018, no publicly-available, regularly updated data source existed to describe those turbines and their locations. Under a cooperative research and development agreement, analysts from three organizations collaborated to develop and release the United States Wind Turbine Database (USWTDB) - a publicly available, continuously updated, spatially rectified data source of locations and attributes of utility-scale wind turbines in the United States. Technical specifications and wind facility data, incorporated from five sources, undergo rigorous quality control. The location of each turbine is visually verified using high-resolution aerial imagery. The quarterly-updated data are available in a variety of formats, including an interactive web application, comma-separated values (CSV), shapefile, and application programming interface (API). The data are used widely by academic researchers, engineers and developers from wind energy companies, government agencies, planners, educators, and the general public.

Scientific Data↗

USGS2015

Onshore industrial wind turbine locations for the United States up to March 2014

Wind energy is a rapidly growing form of renewable energy in the United States. While summary information on the total amounts of installed capacity are available by state, a free, centralized, national, turbine-level, geospatial dataset useful for scientific research, land and resource management, and other uses did not exist. Available in multiple formats and in a web application, these public domain data provide industrial-scale onshore wind turbine locations in the United States up to March 2014, corresponding facility information, and turbine technical specifications. Wind turbine records have been collected and compiled from various public sources, digitized or position verified from aerial imagery, and quality assured and quality controlled. Technical specifications for turbines were assigned based on the wind turbine make and model as described in public literature. In some cases, turbines were not seen in imagery or turbine information did not exist or was difficult to obtain. Uncertainty associated with these is recorded in a confidence rating.

Scientific Data↗

USGS2003

The challenge and opportunity of recovering wolf populations

The gray wolf once inhabited a wide variety of habitats throughout most of the northern hemisphere north of 20°N latitude. Because the animal preyed on livestock and competed with humans for wild prey, it was extirpated from much of its range outside of wilderness areas. Environmental awareness in the late 1960s brought for the wolf legal protection, increased research, and favorable media coverage. The species has increased in both Europe and North America, is beginning to reoccupy semiwilderness and agricultural land, and is causing increased damage to livestock. Because of the wolf's high reproductive rate and long dispersal tendencies, the animal can recolonize many more areas. In most such areas control will be necessary, but the same public sentiments that promoted wolf recovery reject control. If wolf advocates could accept control by the public rather than by the government, wolves could live in far more places. Insistence on government control discourages some officials and government agencies from promoting recovery. The use of large- or small-scale zoning for wolf management may help resolve the issue. Public education is probably the most effective way to minimize the problem and maximize wolf recovery, but the effort must begin immediately.

Conservation Biology↗