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At least 235 records · Page 13Linked to original sources
USGS2017

Pinyon and juniper encroachment into sagebrush ecosystems impacts distribution and survival of greater sage-grouse

In sagebrush ( Artemisia spp.) ecosystems, encroachment of pinyon ( Pinus spp.) and juniper ( Juniperus spp.; hereafter, “pinyon-juniper”) trees has increased dramatically since European settlement. Understanding the impacts of this encroachment on behavioral decisions, distributions, and population dynamics of greater sage-grouse (Centrocercus urophasianus) and other sagebrush obligate species could help benefit sagebrush ecosystem management actions. We employed a novel two-stage Bayesian model that linked avoidance across different levels of pinyon-juniper cover to sage-grouse survival. Our analysis relied on extensive telemetry data collected across 6 yr and seven subpopulations within the Bi-State Distinct Population Segment (DPS), on the border of Nevada and California. The first model stage indicated avoidance behavior for all canopy cover classes on average, but individual grouse exhibited a high degree of heterogeneity in avoidance behavior of the lowest cover class (e.g., scattered isolated trees). The second stage modeled survival as a function of estimated avoidance parameters and indicated increased survival rates for individuals that exhibited avoidance of the lowest cover class. A post hoc frailty analysis revealed the greatest increase in hazard (i.e., mortality risk) occurred in areas with scattered isolated trees consisting of relatively high primary plant productivity. Collectively, these results provide clear evidence that local sage-grouse distributions and demographic rates are influenced by pinyon-juniper, especially in habitats with higher primary productivity but relatively low and seemingly benign tree cover. Such areas may function as ecological traps that convey attractive resources but adversely affect population vital rates. To increase sage-grouse survival, our model predictions support reducing actual pinyon-juniper cover as low as 1.5%, which is lower than the published target of 4.0%. These results may represent effects of pinyon-juniper cover in areas with similar ecological conditions to those of the Bi-State DPS, where populations occur at relatively high elevations and pinyon-juniper is abundant and widespread.

Rangeland Ecology and Management↗
USGS2025

Landslide-channel feedbacks amplify channel widening during floods

Channel widening is a major hazard during floods, particularly in confined mountainous catchments. However, channel widening during floods is not well understood and not always explained by hydraulic variables alone. Floods in mountainous regions often coincide with landslides triggered by heavy rainfall, yet landslide-channel interactions during a flood event are not well known or documented. Here we demonstrate with an example from the Great Colorado Flood in 2013, a 1000 year precipitation event, how landslide-channel feedbacks can substantially amplify channel widening and flood risk. We use a combination of DEM differencing, field analysis, and multiphase flow modeling to document landslide-channel interaction during the flood event in which sediment delivered by landslides temporarily dammed the channel before failing and generating substantial channel widening. We propose that such landslide-flood interactions will become increasingly important to account for in flood hazard assessment as flooding and landsliding both increase with extreme rainfall under climate change.

Colorado↗
USGS1998

Nitrate in Ground Waters of the United States--Assessing the Risk

Using data compiled by the National Water Quality Assessment Program (NAWQA), the USGS has evaluated the potential for nitrate contamination of ground waters in the United States. Soil-drainage characteristics and the amount of nitrogen contributed by fertilizer, manure, and atmospheric sources were found to markedly influence the concentration of nitrate in ground water. These two characteristics were compiled in a national map that shows patterns of risk for nitrate contamination of ground water. Areas with well-drained soils and high nitrogen input have the highest risk. Ground-water nitrate data generally verified the risk patterns shown on the national map. The verification analysis is based on over 10,000 samples collected through 1992.

Fact Sheet↗
USGS2012

Estimated probability of arsenic in groundwater from bedrock aquifers in New Hampshire, 2011

Probabilities of arsenic occurrence in groundwater from bedrock aquifers at concentrations of 1, 5, and 10 micrograms per liter (µg/L) were estimated during 2011 using multivariate logistic regression. These estimates were developed for use by the New Hampshire Environmental Public Health Tracking Program. About 39 percent of New Hampshire bedrock groundwater was identified as having at least a 50 percent chance of containing an arsenic concentration greater than or equal to 1 µg/L. This compares to about 7 percent of New Hampshire bedrock groundwater having at least a 50 percent chance of containing an arsenic concentration equaling or exceeding 5 µg/L and about 5 percent of the State having at least a 50 percent chance for its bedrock groundwater to contain concentrations at or above 10 µg/L. The southeastern counties of Merrimack, Strafford, Hillsborough, and Rockingham have the greatest potential for having arsenic concentrations above 5 and 10 µg/L in bedrock groundwater. Significant predictors of arsenic in groundwater from bedrock aquifers for all three thresholds analyzed included geologic, geochemical, land use, hydrologic, topographic, and demographic factors. Among the three thresholds evaluated, there were some differences in explanatory variables, but many variables were the same. More than 250 individual predictor variables were assembled for this study and tested as potential predictor variables for the models. More than 1,700 individual measurements of arsenic concentration from a combination of public and private water-supply wells served as the dependent (or predicted) variable in the models. The statewide maps generated by the probability models are not designed to predict arsenic concentration in any single well, but they are expected to provide useful information in areas of the State that currently contain little to no data on arsenic concentration. They also may aid in resource decision making, in determining potential risk for private wells, and in ecological-level analysis of disease outcomes. The approach for modeling arsenic in groundwater could also be applied to other environmental contaminants that have potential implications for human health, such as uranium, radon, fluoride, manganese, volatile organic compounds, nitrate, and bacteria.

New Hampshire↗
USGS1995

Water withdrawals in the Black Warrior-Tombigbee basin in Alabama, 1985-87

Public-supply, industrial, and power generation water withdrawals were inventoried for the Black Warrior-Tombigbee basin in Alabama for 1987. A water source capacity analysis was done for each facility to assess the risk of the future water demand exceeding the capacity of the current source. Approximately 96 percent of all water withdrawn in the study area was surface water. Surface water accounted for 88 percent of withdrawals by public suppliers and 99 percent of withdrawals by self- supplied industries.

Alabama↗
USGS2016

Application of decision science to resilience management in Jamaica Bay

This book highlights the growing interest in management interventions designed to enhance the resilience of the Jamaica Bay socio-ecological system. Effective management, whether the focus is on managing biological processes or human behavior or (most likely) both, requires decision makers to anticipate how the managed system will respond to interventions (i.e., via predictions or projections). In systems characterized by many interacting components and high uncertainty, making probabilistic predictions is often difficult and requires careful thinking not only about system dynamics, but also about how management objectives are specified and the analytic method used to select the preferred action(s). Developing a clear statement of the problem(s) and articulation of management objectives is often best achieved by including input from managers, scientists and other stakeholders affected by the decision through a process of joint problem framing (Marcot and others 2012; Keeney and others 1990). Using a deliberate, coherent and transparent framework for deciding among management alternatives to best meet these objectives then ensures a greater likelihood for successful intervention. Decision science provides the theoretical and practical basis for developing this framework and applying decision analysis methods for making complex decisions under uncertainty and risk.

Book chapter↗
USGS2013

Tsunami mitigation and preparedness activities in California

Scenario planning and final results associated with the U.S. Geological Survey Science Application for Risk Reduction (SAFRR) tsunami project are providing great benefits to the ongoing tsunami risk-reduction efforts of the California Tsunami Preparedness and Hazard Mitigation Program. This program, led by the California Governor’s Office of Emergency Services and the California Geological Survey, works with coastal communities to improve tsunami preparedness and mitigation at the local level through various efforts, such as improving tsunami hazard analysis, establishing consistent evacuation communications and planning, and leveraging national risk-reduction efforts associated with the National Tsunami Hazard Mitigation Program. The recent 2010 Chilean and 2011 Tohoku tsunamis did not cause notable inundation of dry land in California, but dozens of harbors sustained damages totaling nearly $100 million (Wilson and others, 2012a). Estimates associated with the SAFRR distant tsunami scenario suggest socioeconomic and environmental losses could be even larger. Information gathered from these events and the SAFRR scenario is guiding the development and implementation of new strategies for emergency response, maritime planning, and land-use planning, including a reassessment of the tsunami threat along the California coast; scenario-specific, tsunami evacuation “playbook” maps and guidance in-harbor hazard maps and offshore safety zones for potential boat evacuation during future distant source events; “probability-based” products for land-use planning under the California Seismic Hazard Mapping Act; and an expansion of real-time and post-tsunami field reconnaissance teams and information sharing through a state-wide clearinghouse. The state tsunami program has benefitted greatly from participation in the SAFRR tsunami scenario process, and hopes to continue this relationship with the U.S. Geological Survey to help improve tsunami preparedness in California.

California↗
USGS2026

Challenges and opportunities for Sendai framework disaster loss reporting in the United States

The Sendai Framework for Disaster Risk Reduction provides quantitative indicators for nations to measure progress in the reduction of disaster losses. The collection and analysis of disaster loss data under the Sendai Framework improves our understanding of the effectiveness of national disaster risk reduction strategies and interventions. The Sendai Framework has enhanced cooperation among Federal agencies to collect and track disaster loss data in the U.S., yet challenges remain for reporting disaster losses. Based on our experiences collecting and reporting U.S. data to the Sendai Monitor, we identify opportunities to improve disaster loss reporting in the U.S.

Progress in Disaster Science↗
USGS2023

Groundwater quality near the Montebello Oil Field, Los Angeles County, California

Groundwater quality and potential sources and migration pathways of chemical constituents associated with hydrocarbon-bearing formations were assessed by the U.S. Geological Survey for the California State Water Resources Control Board Oil and Gas Regional Monitoring Program (RMP). Groundwater samples were collected as part of the RMP from 21 preexisting wells used for public supply, monitoring, or irrigation in and near the Montebello Oil Field and analyzed for constituents associated with hydrocarbon-bearing formations and constituents used to identify recently recharged groundwater and older groundwater. The newly collected RMP data were supplemented with historical sample data from 849 groundwater wells and analyzed with respect to explanatory factors that have the potential to influence water quality. Potential sources and migration pathways of fluids (water, gas, or oil) from hydrocarbon-bearing formations that could affect groundwater quality in the Montebello Oil Field include large volumes of recycled produced water (water withdrawn from an oil well and brought to the surface that may include oil, water, and gas from the geologic formation and water or gas injected for enhanced recovery) that have been reinjected since the 1960s to enhance oil production, oil and gas wells with well-integrity issues, and oil and gas wells with an uncemented annulus that intersects groundwater resource zones. Trace amounts of dissolved petroleum hydrocarbons, thermogenic gas (propane through pentane range), or both, were detected in seven groundwater samples collected in 2014 and 2018 as part of the RMP. Five of those samples also contained manufactured volatile organic compounds and at least some modern-age groundwater (recharged during or after 1953), indicating that the hydrocarbons could have originated from surficial, or shallow, sources unrelated to oil and gas development. Two samples contained low concentrations of petroleum hydrocarbons (less than 0.1 microgram per liter) and did not contain detections of manufactured volatile organic compounds in pre-modern groundwater. These samples were collected from relatively deep wells (greater than 140 meters below land surface) with perforations completed in marine sediments that may contain water with similar compositions to produced water. The RMP sample results and available historical data in and near the Montebello Oil Field did not provide conclusive evidence that oil and gas development has adversely affected groundwater resources. All samples with detectable petroleum hydrocarbons, thermogenic gases, or both, were collected from sites that also are within 500 meters of anthropogenic hydrocarbon sources not associated with oil and gas development or sources. In addition, naturally occurring sources of hydrocarbons that exist at intervals shallower than, or are in areas outside of, economically productive oil- and gas-producing zones could affect groundwater quality. A definitive analysis of relations of groundwater quality to potential anthropogenic and natural explanatory factors was not possible because of the low density of new and historical sampling data, particularly in parts of the Montebello Oil Field where the largest relative risks to groundwater from hydrocarbon-bearing formations exist. Areas to consider for more detailed monitoring and analysis in the future that may present the largest relative potential risks to groundwater quality include (1) areas downgradient from historical surface ponds and sumps and (2) areas with co-located high net injection (oil reservoir injection exceeds production), old oil and gas wells that may be more likely to develop well-integrity issues than newer wells, and oil and gas wells with uncemented boreholes intersecting groundwater zones. To help fill gaps resulting from sparse groundwater wells, temperature and resistivity borehole log data could be analyzed to locate anomalies that identify potential areas where relatively warm or saline water from deeper hydrocarbon-bearing formations is present in groundwater.

California↗
USGS2022

Interagency Flood Risk Management (InFRM) watershed hydrology assessment for the Neches River basin. Appendix A: Statistical hydrology

Statistical analysis of the observational record from U.S. Geological Survey (USGS) streamgaging stations and other historical information provides an informative means of estimating flood flow frequency. Flood flow frequency is defined by values or quantiles of discharge for selected annual exceedance probabilities (AEPs) (England and others, 2018). The annual peak discharge data as part of systematic operation of a streamgaging station provides the foundation for a detailed analysis of peak discharge, but additional historical information pertaining to peak discharges also can be used. An annual peak discharge is defined as the maximum instantaneous discharge for a streamgaging station for a given water year, and annual peak discharge data for USGS streamgaging stations can be acquired through the USGS National Water Information System (NWIS) database (USGS, 2018). The statistical analyses are based on water-year increments. A water year is the 12-month period from October 1 of a given year through September 30 of the following year designated by the calendar year in which it ends. For the statistical hydrology portion of the multi-layered analysis, InFRM team members from the USGS analyzed annual peak discharge records for the 15 USGS streamgaging stations (gages) shown on Figure A.1. Information on the period of record data for those USGS gages are listed in Table A.1.

Texas↗
USGS2008

Assessment of nonpoint source chemical loading potential to watersheds containing uranium waste dumps associated with uranium exploration and mining, San Rafael Swell, Utah

During July and August of 2006, 117 solid-phase samples were collected from abandoned uranium waste dumps, geologic background sites, and adjacent streambeds in the San Rafael Swell, in southeastern Utah. The objective of this sampling program was to assess the nonpoint source chemical loading potential to ephemeral and perennial watersheds from uranium waste dumps on Bureau of Land Management property. Uranium waste dump samples were collected using solid-phase sampling protocols. After collection, solid-phase samples were homogenized and extracted in the laboratory using a field leaching procedure. Filtered (0.45 micron) water samples were obtained from the field leaching procedure and were analyzed for Ag, As, Ba, Be, Cd, Cr, Cu, Fe, Mn, Mo, Ni, Pb, Sb, Se, U, V, and Zn at the Inductively Coupled Plasma-Mass Spectrometry Metals Analysis Laboratory at the University of Utah, Salt Lake City, Utah and for Hg at the U.S. Geological Survey National Water Quality Laboratory, Denver, Colorado. For the initial ranking of chemical loading potential of suspect uranium waste dumps, leachate analyses were compared with existing aquatic life and drinking-water-quality standards and the ratio of samples that exceeded standards to the total number of samples was determined for each element having a water-quality standard for aquatic life and drinking-water. Approximately 56 percent (48/85) of the leachate samples extracted from uranium waste dumps had one or more chemical constituents that exceeded aquatic life and drinking-water-quality standards. Most of the uranium waste dump sites with elevated trace-element concentrations in leachates were along Reds Canyon Road between Tomsich Butte and Family Butte. Twelve of the uranium waste dump sites with elevated trace-element concentrations in leachates contained three or more constituents that exceeded drinking-water-quality standards. Eighteen of the uranium waste dump sites had three or more constituents that exceeded trace-element concentrations for aquatic life water-quality standards. The proximity of the uranium waste dumps in the Tomsich Butte area near Muddy Creek, coupled with the elevated concentration of trace elements, increases the offsite impact potential to water resources. Future assessment and remediation priority of these areas may be done by using GIS-based risk-mapping techniques, such as Sensitive Catchment Integrated Mapping and Analysis Project.

Utah↗
USGS2014

Chemical mixtures in potable water in the U.S.

In recent years, regulators have devoted increasing attention to health risks from exposure to multiple chemicals. In 1996, the US Congress directed the US Environmental Protection Agency (EPA) to study mixtures of chemicals in drinking water, with a particular focus on potential interactions affecting chemicals' joint toxicity. The task is complicated by the number of possible mixtures in drinking water and lack of toxicological data for combinations of chemicals. As one step toward risk assessment and regulation of mixtures, the EPA and the Agency for Toxic Substances and Disease Registry (ATSDR) have proposed to estimate mixtures' toxicity based on the interactions of individual component chemicals. This approach permits the use of existing toxicological data on individual chemicals, but still requires additional information on interactions between chemicals and environmental data on the public's exposure to combinations of chemicals. Large compilations of water-quality data have recently become available from federal and state agencies. This chapter demonstrates the use of these environmental data, in combination with the available toxicological data, to explore scenarios for mixture toxicity and develop priorities for future research and regulation. Occurrence data on binary and ternary mixtures of arsenic, cadmium, and manganese are used to parameterize the EPA and ATSDR models for each drinking water source in the dataset. The models' outputs are then mapped at county scale to illustrate the implications of the proposed models for risk assessment and rulemaking. For example, according to the EPA's interaction model, the levels of arsenic and cadmium found in US groundwater are unlikely to have synergistic cardiovascular effects in most areas of the country, but the same mixture's potential for synergistic neurological effects merits further study. Similar analysis could, in future, be used to explore the implications of alternative risk models for the toxicity and interaction of complex mixtures, and to identify the communities with the highest and lowest expected value for regulation of chemical mixtures.

Book chapter↗
USGS2006

Integrating human impacts and ecological integrity into a risk-based protocol for conservation planning

Conservation planning aims to protect biodiversity by sustainng the natural physical, chemical, and biological processes within representative ecosystems. Often data to measure these components are inadequate or unavailable. The impact of human activities on ecosystem processes complicates integrity assessments and might alter ecosystem organization at multiple spatial scales. Freshwater conservation targets, such as populations and communities, are influenced by both intrinsic aquatic properties and the surrounding landscape, and locally collected data might not accurately reflect potential impacts. We suggest that changes in five major biotic drivers—energy sources, physical habitat, flow regime, water quality, and biotic interactions—might be used as surrogates to inform conservation planners of the ecological integrity of freshwater ecosystems. Threats to freshwater systems might be evaluated based on their impact to these drivers to provide an overview of potential risk to conservation targets. We developed a risk-based protocol, the Ecological Risk Index (ERI), to identify watersheds with least/most risk to conservation targets. Our protocol combines risk-based components, specifically the frequency and severity of human-induced stressors, with biotic drivers and mappable land- and water-use data to provide a summary of relative risk to watersheds. We illustrate application of our protocol with a case study of the upper Tennessee River basin, USA. Differences in risk patterns among the major drainages in the basin reflect dominant land uses, such as mining and agriculture. A principal components analysis showed that localized, moderately severe threats accounted for most of the threat composition differences among our watersheds. We also found that the relative importance of threats is sensitive to the spatial grain of the analysis. Our case study demonstrates that the ERI is useful for evaluating the frequency and severity of ecosystemwide risk, which can inform local and regional conservation planning.

Tennessee↗
USGS2025

Sources and risk factors for nitrate, pathogens, and fecal contamination of private wells in rural southwestern Wisconsin, USA

Household well water can be degraded by contaminants from the land's surface, but private well owners lack means to protect the source water from neighboring disturbances. Rural residents of southwestern Wisconsin, USA, rely on private well water, and the combination of land use and fractured carbonate bedrock makes groundwater vulnerable to contamination. To identify the extent, sources, and risk factors of private well contamination, randomly selected wells sampled during two-day periods in fall (n = 301) and spring (n = 529) were analyzed for nitrate and indicator bacteria, and a subset (n = 138) was sampled across four seasonal events for analysis of pathogens and microbial source tracking markers by quantitative polymerase chain reaction. Risk factors representing land use, hydrology, geology, and well construction were analyzed for associations with contamination in multivariable models. The importance of risk factors varied by contaminant, illustrating the multifaceted nature of rural groundwater quality. Nitrate contamination was associated with agricultural land use, and wells with casings that extended below a shale aquitard accessed less contaminated water than those drawing water from above it. Human fecal microbes were detected in 64 wells (46%), and rainfall was the key risk factor for contamination, indicating that wastewater from septic systems was available to contaminate wells when transport conditions were favorable. Manure microbes from cattle/ruminants and pigs were detected in 33 and 13 wells, respectively, and concentrations increased with the hectarage of cultivated land near wells. Pathogen genes for viruses, bacteria, and protozoa were detected in 66 wells (48%), including more detections of zoonotic than human-specific pathogens, and human Bacteroides , an indicator of wastewater, was an equivocal predictor of pathogen presence in private wells. Characterizing important elements of the setting, like geology, and identifying sources and risk factors for contaminants can inform landscape-level policies to protect groundwater quality.

Wisconsin↗
USGS2023

Wide-area debris field and seabed characterization of a deep ocean dump site surveyed by autonomous underwater vehicles

Disposal of industrial and hazardous waste in the deep ocean was a pervasive global practice near coastlines in the 20th century. Uncertainty in the quantity, location, and contents of dumped materials at historical disposal sites underscores ongoing risks to marine ecosystems and human health. This study presents analysis of a 150-km2 wide-area sidescan sonar survey conducted in March 2021 with two autonomous underwater vehicles (AUVs) at an offshore dumpsite in San Pedro Basin, California. Previous camera surveys located 60 barrels and other debris; sediment analysis in the region showed varying concentrations of the insecticidal chemical Dichlorodiphenyl-trichloroethane (DDT), for which an estimated 350-700 metric tons was discarded in the San Pedro Basin between 1947 and 1961. A lack of primary historical documents from Montrose Chemical or California Salvage Company that specify the DDT acid waste disposal method has contributed to the ambiguity surrounding whether the dumping method was via bulk discharge or containerized units. Barrels and debris visually detected during previous surveys by Remotely Operated Vehicles (ROVs) Jason and SuBastian and AUV Sentry served as the basis for ground truth testing and object classification using size and acoustic intensity characteristics. Target detection and classification algorithms were developed using image and signal processing techniques that resulted in the identification of over 74,000 debris targets within the survey region. Statistical, spectral, and machine learning techniques are used to characterize seabed variability and for bottom-type classification. These analytical techniques combined with the survey capabilities of AUVs provide a framework for efficient mapping and characterization of uncharted deep-water disposal sites.

California↗
USGS2022

A framework for integrating inferred movement behavior into disease risk models

Movement behavior is an important contributor to habitat selection and its incorporation in disease risk models has been somewhat neglected. The habitat preferences of host individuals affect their probability of exposure to pathogens. If preference behavior can be incorporated in ecological niche models (ENMs) when data on pathogen distributions are available, then variation in such behavior may dramatically impact exposure risk. Here we use data from the anthrax endemic system of Etosha National Park, Namibia, to demonstrate how integrating inferred movement behavior alters the construction of disease risk maps. We used a Maximum Entropy (MaxEnt) model that associated soil, bioclimatic, and vegetation variables with the best available pathogen presence data collected at anthrax carcass sites to map areas of most likely Bacillus anthracis (the causative bacterium of anthrax) persistence. We then used a hidden Markov model (HMM) to distinguish foraging and non-foraging behavioral states along the movement tracks of nine zebra ( Equus quagga ) during the 2009 and 2010 anthrax seasons. The resulting tracks, decomposed on the basis of the inferred behavioral state, formed the basis of step-selection functions (SSFs) that used the MaxEnt output as a potential predictor variable. Our analyses revealed different risks of exposure during different zebra behavioral states, which were obscured when the full movement tracks were analyzed without consideration of the underlying behavioral states of individuals. Pathogen (or vector) distribution models may be misleading with regard to the actual risk faced by host animal populations when specific behavioral states are not explicitly accounted for in selection analyses. To more accurately evaluate exposure risk, especially in the case of environmentally transmitted pathogens, selection functions could be built for each identified behavioral state and then used to assess the comparative exposure risk across relevant states. The scale of data collection and analysis, however, introduces complexities and limitations for consideration when interpreting results.

Etosha National Park↗
USGS1996

Reflected seismic waves and their effect on strong shaking during the 1989 Loma Prieta, California, earthquake

Our data indicate that critical and postcritical reflections from crustal layers and the Moho produced increased shaking at discrete distances along the San Francisco Peninsula during the 1989 Loma Prieta earthquake. These reflections may have produced an increase in amplitude that is as much as 10 times greater than that of the direct arrival. Peak amplitude-distance patterns measured from explosive sources, synthetic seismograms, aftershocks, and the mainshock of the 1989 Loma Prieta earthquake indicate that (1) point sources, such as explosions, produce similar peak amplitude-distance relations as distributed, double-couple sources when the crustal structure is approximately a Poisson solid; (2) peak amplitudes from smaller point sources (explosions) may be scaled to those of larger sources (earthquakes); and (3) reflections caused a pattern of high amplitudes at specific distances along the San Francisco Peninsula that geographically correlates with areas of reported damage following from the Loma Prieta mainshock. Our study indicates that critical and postcritical reflections were stronger influences on the locations of strong shaking than local geology because a number of sites around the San Francisco Bay that are underlain by unconsolidated sediments experienced much less shaking than sites that were underlain by hard rock. Furthermore, some severely shaken hard-rock sites were farther from the epicenter than many of the less severely shaken “soft-sediment” sites. Models of the regional crustal structure and seismic-wave propagation paths may be useful in identifying sites around the San Francisco Bay region that are at risk due to reflected seismic energy, and this type of analysis may be useful in other seismically active regions.

California↗
USGS2013

Report of geomagnetic pulsation indices for space weather applications

The phenomenon of ultra-low frequency geomagnetic pulsations was first observed in the ground-based measurements of the 1859 Carrington Event and has been studied for over 100 years. Pulsation frequency is considered to be “ultra” low when it is lower than the natural frequencies of the plasma, such as the ion gyrofrequency. Ultra-low frequency pulsations are considered a source of noise in some geophysical analysis techniques, such as aeromagnetic surveys and transient electromagnetics, so it is critical to develop near real-time space weather products to monitor these geomagnetic pulsations. The proper spectral analysis of magnetometer data, such as using wavelet analysis techniques, can also be important to Geomagnetically Induced Current risk assessment.

Open-File Report↗