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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 145 records · Page 8Linked to original sources
USGS2015

Vulnerabilities and opportunities at the nexus of electricity, water and climate

The articles in this special issue examine the critical nexus of electricity, water, and climate, emphasizing connections among resources; the prospect of increasing vulnerabilities of water resources and electricity generation in a changing climate; and the opportunities for research to inform integrated energy and water policy and management measures aimed at reducing vulnerability and increasing resilience. Here, we characterize several major themes emerging from this research and highlight some of the uptake of this work in both scientific and public spheres. Underpinning much of this research is the recognition that water resources are expected to undergo substantial changes based on the global warming that results primarily from fossil energy-based carbon emissions. At the same time, the production of electricity from fossil fuels, nuclear power, and some renewable technologies (biomass, geothermal and concentrating solar power) can be highly water-intensive. Energy choices now and in the near future will have a major impact not just on the global climate, but also on water supplies and the resilience of energy systems that currently depend heavily on them.

Environmental Research Letters↗
USGS2013

Land use and carbon dynamics in the southeastern United States from 1992 to 2050

Land use and land cover change (LUCC) plays an important role in determining the spatial distribution, magnitude, and temporal change of terrestrial carbon sources and sinks. However, the impacts of LUCC are not well understood and quantified over large areas. The goal of this study was to quantify the spatial and temporal patterns of carbon dynamics in various terrestrial ecosystems in the southeastern United States from 1992 to 2050 using a process-based modeling system and then to investigate the impacts of LUCC. Spatial LUCC information was reconstructed and projected using the FOREcasting SCEnarios of future land cover (FORE-SCE) model according to information derived from Landsat observations and other sources. Results indicated that urban expansion (from 3.7% in 1992 to 9.2% in 2050) was expected to be the primary driver for other land cover changes in the region, leading to various declines in forest, cropland, and hay/pasture. The region was projected to be a carbon sink of 60.4 gC m −2 yr −1 on average during the study period, primarily due to the legacy impacts of large-scale conversion of cropland to forest that happened since the 1950s. Nevertheless, the regional carbon sequestration rate was expected to decline because of the slowing down of carbon accumulation in aging forests and the decline of forest area.

Environmental Research Letters↗
USGS2014

Performance of several low-cost accelerometers

Several groups are implementing low‐cost host‐operated systems of strong‐motion accelerographs to support the somewhat divergent needs of seismologists and earthquake engineers. The Advanced National Seismic System Technical Implementation Committee (ANSS TIC, 2002), managed by the U.S. Geological Survey (USGS) in cooperation with other network operators, is exploring the efficacy of such systems if used in ANSS networks. To this end, ANSS convened a working group to explore available Class C strong‐motion accelerometers (defined later), and to consider operational and quality control issues, and the means of annotating, storing, and using such data in ANSS networks. The working group members are largely coincident with our author list, and this report informs instrument‐performance matters in the working group’s report to ANSS. Present examples of operational networks of such devices are the Community Seismic Network (CSN; csn.caltech.edu), operated by the California Institute of Technology, and Quake‐Catcher Network (QCN; Cochran et al., 2009; qcn.stanford.edu; November 2013), jointly operated by Stanford University and the USGS. Several similar efforts are in development at other institutions. The overarching goals of such efforts are to add spatial density to existing Class‐A and Class‐B (see next paragraph) networks at low cost, and to include many additional people so they become invested in the issues of earthquakes, their measurement, and the damage they cause.

Seismological Research Letters↗
USGS2017

A proposal for amending administrative law to facilitate adaptive management

In this article we examine how federal agencies use adaptive management. In order for federal agencies to implement adaptive management more successfully, administrative law must adapt to adaptive management, and we propose changes in administrative law that will help to steer the current process out of a dead end. Adaptive management is a form of structured decision making that is widely used in natural resources management. It involves specific steps integrated in an iterative process for adjusting management actions as new information becomes available. Theoretical requirements for adaptive management notwithstanding, federal agency decision making is subject to the requirements of the federal Administrative Procedure Act, and state agencies are subject to the states' parallel statutes. We argue that conventional administrative law has unnecessarily shackled effective use of adaptive management. We show that through a specialized 'adaptive management track' of administrative procedures, the core values of administrative law—especially public participation, judicial review, and finality— can be implemented in ways that allow for more effective adaptive management. We present and explain draft model legislation (the Model Adaptive Management Procedure Act) that would create such a track for the specific types of agency decision making that could benefit from adaptive management.

Environmental Research Letters↗
USGS2023

MLAAPDE: A machine learning dataset for determining global earthquake source parameters

The Machine Learning Asset Aggregation of the Preliminary Determination of Epicenters (MLAAPDE) dataset is a labeled waveform archive designed to enable rapid development of machine learning (ML) models used in seismic monitoring operations. MLAAPDE consists of more than 5.1 million recordings of 120 s long three‐component broadband waveform data (raw counts) for P , Pn , Pg , S , Sn , and Sg arrivals. The labeled catalog is collected from the U.S. Geological Survey National Earthquake Information Center’s (NEIC) Preliminary Determination of Epicenters bulletin, which includes local to teleseismic observations for earthquakes ∼ M 2.5 and larger. Each arrival in the labeled dataset has been manually reviewed by NEIC staff. An accompanying Python module enables users to develop customized training datasets, which includes different time‐series lengths, distance ranges, sampling rates, and/or phase lists. MLAAPDE is distinct from other publicly available datasets in containing local (14%), regional (36%), and teleseismic (50%) observations, in which local, regional, and teleseismic distance are 0°–3°, 3°–30°, and 30°+, respectively. A recent version of the dataset is publicly available (see Data and Resources ), and user‐specific versions can be generated locally with the accompanying software. MLAAPDE is an NEIC supported, curated, and periodically updated dataset that can contribute to seismological ML research and development.

Seismological Research Letters↗
USGS2023

Comparison of co-recorded analog and digital systems for characterization of responses and uncertainties

One of the most prominent challenges related to legacy seismic data is determining how these data can be appropriately used in modern research applications. The wide variety of instrumentation used in the analog era, the format of recording on paper wrapped around a helicorder drum, and limited metadata information introduces ambiguities that are not typical of modern digital data. Therefore, techniques must be developed to help characterize uncertainties in legacy data. This article presents an analysis that compares corecorded signals from two instruments—a Trillium Compact or Press‐Ewing (PE) seismometer for sensing ground motion and two recording systems: a modern Q330 digitizer or heated‐stylus system. Analyses of the recordings in both time and frequency domains indicate time uncertainty on the order of one second, identify a flat response in a 10–60 s band for the PE and drum recorder, and highlight how specific features of scans and paper seismograms (e.g., repeated portions of scans and line thickness) can cause timing jumps or reduced trace amplitude.

Seismological Research Letters↗
USGS2016

Reply to “Comment on ‘Ground motions from the 2015 Mw 7.8 Gorkha, Nepal, earthquake constrained by a detailed assessment of macroseismic data’ by Stacey S. Martin, Susan E. Hough, and Charleen Hung” by Andrea Tertulliani, Laura Graziani, Corrado Castellano, Alessandra Maramai, and Antonio Rossi

We thank Andrea Tertulliani and his colleagues for their interest in our article on the 2015 Gorkha earthquake (Martin, Hough, et al., 2015), and for their comments pertaining to our study (Tertulliani et al., 2016). Indeed, as they note, a comprehensive assessment of macroseismic effects for an earthquake with far‐reaching effects as that of Gorkha is not only critically important but is also an extremely difficult undertaking. In the absence of a widely known web‐based system, employing a well‐calibrated algorithm with which to collect and systematically assess macroseismic information (e.g., Wald et al., 1999; Coppola et al., 2010; Bossu et al., 2015) in the Indian subcontinent, one is left with two approaches to characterize effects of an event such as the Gorkha earthquake: a comprehensive ground‐based survey such as the one undertaken in India following the 2001 Bhuj earthquake (Pande and Kayal, 2003), or an assessment such as Martin, Hough, et al. (2015) akin to other contemporary studies (e.g., Nuttli, 1973; Sieh, 1978; Meltzner and Wald, 1998; Martin and Szeliga, 2010; Ambraseys and Bilham, 2012; Mahajan et al., 2012; Gupta et al., 2013; Singh et al., 2013; Hough and Martin, 2015; Martin and Hough, 2015; Martin, Bradley, et al., 2015; Ribeiro et al., 2015), based primarily upon media reports and other available documentary accounts.

Seismological Research Letters↗
USGS2018

Candidate products for operational earthquake forecasting illustrated using the HayWired planning scenario, including one very quick (and not‐so‐dirty) hazard‐map option

In an effort to help address debates on the usefulness of operational earthquake forecasting (OEF), we illustrate a number of OEF products that could be automatically generated in near‐real time. To exemplify, we use an M "> M 7.1 mainshock on the Hayward fault, which is very similar to the U.S. Geological Survey (USGS) HayWired earthquake planning scenario. Given that there is always some background level of hazard or risk, we emphasize that probability gains (the ratio of short‐term to long‐term‐average estimates) might be of particular interest to users. We also illustrate how such gains are highly sensitive to forecast duration and latency, with the latter representing how long it takes to generate the forecast and/or to take action. The influence of fault‐based information, which has traditionally been ignored in OEF, is also evaluated using the newly developed the third Uniform California Earthquake Rupture Forecast epidemic‐type aftershock sequence (UCERF3‐ETAS) model. We find that the inclusion of faults only makes a difference for hazard and risk metrics that are dominated by large‐event likelihoods. We also show how the ShakeMap of a mainshock represents a decent estimate of the ground motions that have a 6% chance of being exceeded due to aftershocks in the week that follows. The ultimate value of these types of OEF products can only be determined in the context of specific uses, and because these vary widely, institutions responsible for providing OEF products will depend heavily on user feedback, especially when making resource‐allocation decisions.

Seismological Research Letters↗
USGS2000

Geology in the 1996 USGS seismic-hazard maps, central and eastern United States

The current (1996) national probabilistic seismic-hazard maps utilize information about geologic structure and tectonics of the central and eastern U.S. to compensate for uncertainty that arises from the short seismicity record. Geology was incorporated into the maps mainly as seven source zones that are delineated in three distinct ways. The North American stable continental region is divided into two large zones, the sparsely seismic Precambrian craton and the more active Phanerozoic rim. Five other source zones are much smaller - the Wabash Valley source zone is within the craton, whereas the Reelfoot Rift, eastern Tennessee, Charleston, and Charlevoix source zones are in the Phanerozoic rim of the continent. We document these zones and explain and justify their use. The seven zones provide a foundation from which we suggest a criterion for including more geology in future maps.

Seismological Research Letters↗
USGS2023

Earthquake scenarios for Quito, Ecuador; Cali, Colombia; and Santiago De Los Caballeros, Dominican Republic

Earthquake risk associated with Quito, Ecuador; Cali, Colombia; and Santiago de los Caballeros, Dominican Republic is examined by generating a set of hypothetical earthquake scenarios considering seismic sources, recent seismicity, and major historical earthquakes recorded in the vicinity. In this study, particular focus is given to the development of earthquake scenarios for use in emergency planning in each city as well as stimulating discussion with respect to addressing the gaps in current understanding of built stock inventory and their vulnerability when subjected to strong shaking. Exposure and vulnerability models from the Global Earthquake Model foundation, hazard and local site information available for the cities, and the U.S. Geological Survey near‐real‐time products are utilized to estimate potential consequences for postearthquake response planning. Results showed that the historic city centers remain the most susceptible to experiencing severe damage resulting in widespread casualties. Similarly, the scenarios highlight areas susceptible to shaking induced ground failure hazards, which may pose additional challenges when responding to such earthquakes. Moderate earthquakes originating from nearby seismic sources, for example, Quito fault system for Quito or the Septentrional fault zone in the case of Santiago de Los Caballeros, could potentially be of greater consequence in terms of direct economic impact and disruption to the city when compared to very large distant subduction interface earthquakes.

Cali, Santiago De Los Caballeros, Quito↗
USGS2026

A ground-motion model derived using a generalized mean rupture distance for large slab interface earthquakes

Source–station distance is a central input to ground‐motion models (GMMs) for predicting seismic shaking. GMM development uses distance metrics including the Joyner–Boore distance, which is the shortest distance from an observation point to the surface projection of the earthquake rupture, and R rup the shortest distance to the rupture in three dimensions. Thompson and Baltay (2018) proposed the generalized mean rupture distance R p to address observed near‐fault ground‐motion saturation. R p accounts for the contribution to the shaking of all parts of the rupture and provides a simple method for incorporating spatially variable slip. They used R p to develop a GMM for shallow crustal earthquakes, assuming uniform slip. Here, we investigate the improvement offered by an R p ‐based GMM for large subduction interface earthquakes by recalibrating the path term for a published GMM ( Parker et al. , 2022 ) using R p derived from distributed slip models (DSMs). Inspection of within‐event and total residuals indicates that the recalibrated model fits the data at least as well as an alternative in which the path term was recalibrated using R rup and the same dataset. Incorporating slip information in its entirety or trimming the DSM geometry is preferable to assuming uniform moment release on a prescribed model fault that extends beyond the actual ruptured area. R p tuned to minimize model uncertainty is closer to the maximum distance to rupture for peak ground velocity (PGV) than acceleration, possibly reflecting the contribution to high‐frequency shaking of slip on local asperities. However, when the moment is concentrated far from stations, PGV is fit adequately with R p closer to R rup ⁠ . Our results suggest incorporating slip‐derived moment release through R p could improve GMMs for slab interface events, especially if the implementation of R p ‐based models is refined using a larger dataset of earthquakes with greater geographic diversity to account for regional ground‐motion variations.

Seismological Research Letters↗
USGS2021

Modeling seismic network detection thresholds using production picking algorithms

Estimating the detection threshold of a seismic network (the minimum magnitude earthquake that can be reliably located) is a critical part of network design and can drive network maintenance efforts. The ability of a station to detect an earthquake is often estimated by assuming the spectral amplitude for an earthquake of a given size, assuming an attenuation relationship, and comparing the predicted amplitude with the average station background noise level. This approach has significant uncertainty because of unknown regional attenuation and complications in computing small event power spectra, and it fails to account for the specific capabilities of the automatic seismic phase picker used in monitoring. We develop a data‐driven approach to determine network detection thresholds using a multiband phase picking algorithm that is currently in use at the U.S. Geological Survey National Earthquake Information Center. We apply this picking algorithm to cataloged earthquakes to determine an empirical relationship of the observability of earthquakes as a function of magnitude and distance. Using this relationship, we produce maps of detection threshold using station spatial configuration and station noise levels. We show that quiet, well‐sited stations significantly increase the detection capabilities of a network compared with a network composed of many noisy stations. Because our method is data driven, it has two distinct advantages: (1) it is less dependent on theoretical assumptions of source spectra and models of regional attenuation, and (2) it can easily be applied to any seismic network. This tool allows for an objective approach to the management of stations in regional seismic networks.

Seismological Research Letters↗
USGS2022

High‐precision characterization of seismicity from the 2022 Hunga Tonga‐Hunga Ha'apai volcanic eruption

The earthquake swarm accompanying the January 2022 Hunga Tonga‐Hunga Ha'apai (HTHH) volcanic eruption includes a large number of posteruptive moderate‐magnitude seismic events and presents a unique opportunity to use remote monitoring methods to characterize and compare seismic activity with other historical caldera‐forming eruptions. We compute improved epicentroid locations, magnitudes, and regional moment tensors of seismic events from this earthquake swarm using regional to teleseismic surface‐wave cross correlation and waveform modeling. Precise relative locations of 91 seismic events derived from 59,047 intermediate‐period Rayleigh‐ and Love‐wave cross‐correlation measurements collapse into a small area surrounding the volcano and exhibit a southeastern time‐dependent migration. Regional moment tensors and observed waveforms indicate that these events have a similar mechanism and exhibit a strong positive compensated linear vector dipole component. Precise relative magnitudes agree with regional moment tensor moment magnitude ( ⁠ M w "> M w ⁠ ) estimates while also showing that event sizes and frequency increase during the days after the eruption followed by a period of several weeks of less frequent seismicity of a similar size. The combined information from visual observation and early geologic models indicate that the observed seismicity may be the result of a complex series of events that occurred after the explosive eruption on 15 January, possibly involving rapid resupply of the magma chamber shortly after the eruption and additional faulting and instability in the following weeks. In addition, we identify and characterize an M w "> M w 4.5 event five days before the paroxysmal explosion on 15 January, indicating that additional seismic events preceding the main eruption could have been identified with improved local monitoring. Our analysis of the HTHH eruption sequence demonstrates the value of potentially utilizing teleseismic surface‐wave cross correlation and waveform modeling methods to assist in the detailed analysis of remote volcanic eruption sequences.

Futuna↗
USGS2020

California Historical Intensity Mapping Project (CHIMP): A consistently reinterpreted dataset of seismic intensities for the past 162 years and implications for seismic hazard maps

Historical seismic intensity data are useful for myriad reasons, including assessment of the performance of Probabilistic Seismic Hazard Assessment (PSHA) models and corresponding hazard maps by comparing their predictions to a dataset of historically observed intensities in the region. To assess PSHA models for California, a long and consistently interpreted intensity record is necessary. For this purpose, the California Historical Intensity Mapping Project (CHIMP) has compiled a dataset that combines and reinterprets intensity information that has been stored in disparate and sometimes hard-to-access locations. The CHIMP dataset also includes new observations of intensity from archival research and oral history collection. Version 1 of the dataset includes 46,502 intensity observations for 62 earthquakes with estimated magnitudes ranging from 4.7 to 7.9. The 162 years of shaking data show observed shaking lower than expected from seismic hazard models. This discrepancy is reduced, but persists, if historical intensity data for the largest earthquakes are smoothed to reduce the effects of spatial under-sampling. Possible reasons for this discrepancy include other limitations of the CHIMP dataset, the hazard models, and the possibility that California seismicity throughout the historical period has been lower than the long-term average. Some of these issues may also explain similar discrepancies observed for Italy and Japan.

California↗
USGS2003

The nature of earthquake prediction

Earthquake prediction is inherently statistical. Although some people continue to think of earthquake prediction as the specification of the time, place, and magnitude of a future earthquake, it has been clear for at least two decades that this is an unrealistic and unreasonable definition. The reality is that earthquake prediction starts from long-term forecasts of place and magnitude, with very approximate time constraints, and progresses, at least in principle, to a gradual narrowing of the time window as data and understanding permit. The analogy to catching a rabbit in an overgrown confined field may be appropriate. You do not just start out looking for the rabbit, you instead build a fence dividing the field in two and then decide which half the rabbit is in, thereby gaining one bit of information. You iterate this process until you have located the rabbit “close enough for practical purposes.” This is approximately how earthquake prediction proceeds in the real world, with time and position along a fault comprising the two dimensions of the search. (I assume here that we are considering for the moment only large earthquakes, that is those capable of inflicting serious damage on a regional scale; in California this means events of about M 6.7 and larger.) This more realistic perspective on the problem lays to rest the “red herring” that “earthquake predictions might do more harm than earthquakes.” These imaginary concerns are predicated on the fantasy of a prediction that precisely specifies time, place, and magnitude; in the real world a progression of probabilities that narrows the space-time window in small steps clearly carries no such threat.

Seismological Research Letters↗
USGS2016

Detecting spatial regimes in ecosystems

Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological potential (i.e. potential vegetation), and often fail to account for ongoing changes due to stressors such as land use change and climate change and their effects on plant and animal communities. We use Fisher information, an information theory-based method, on both terrestrial and aquatic animal data (U.S. Breeding Bird Survey and marine zooplankton) to identify ecological boundaries, and compare our results to traditional early warning indicators, conventional ecoregion maps and multivariate analyses such as nMDS and cluster analysis. We successfully detected spatial regimes and transitions in both terrestrial and aquatic systems using Fisher information. Furthermore, Fisher information provided explicit spatial information about community change that is absent from other multivariate approaches. Our results suggest that defining spatial regimes based on animal communities may better reflect ecological reality than do traditional ecoregion maps, especially in our current era of rapid and unpredictable ecological change.

Ecology Letters↗
USGS2013

Linkages between lake shrinkage/expansion and sublacustrine permafrost distribution determined from remote sensing of interior Alaska, USA

[1] Linkages between permafrost distribution and lake surface-area changes in cold regions have not been previously examined over a large scale because of the paucity of subsurface permafrost information. Here, a first large-scale examination of these linkages is made over a 5150 km 2 area of Yukon Flats, Alaska, USA, by evaluating the relationship between lake surface-area changes during 1979–2009, derived from Landsat satellite data, and sublacustrine groundwater flow-path connectivity inferred from a pioneering, airborne geophysical survey of permafrost. The results suggest that the shallow (few tens of meters) thaw state of permafrost has more influence than deeper permafrost conditions on the evolving water budgets of lakes on a multidecadal time scale. In the region studied, these key shallow aquifers have high hydraulic conductivity and great spatial variability in thaw state, making groundwater flow and associated lake level evolution particularly sensitive to climate change owing to the close proximity of these aquifers to the atmosphere.

Alaska↗
USGS2012

Rapid determination of global moment-tensor solutions

In an effort to improve data services, the National Earthquake Information Center has begun a program, in cooperation with the Incorporated Research Institutions for Seismology Data Management Center (IRIS DMC), to produce rapid estimates of the seismic moment tensor for most earthquakes with a body-wave magnitude of 5.8 or greater. Although this program is still undergoing testing and fine-tuning, an estimate of the moment tensor can usually be produced within 20 minutes of the arrival of the broadband P -waveform data from the IRIS DMC. Although the speed with which this data can be obtained varies, in many cases a solution can be obtained within two hours of the earthquake. These solutions do not vary significantly from the final solutions determined using the entire network. Because of the manner in which the data and the synthetic seismograms are aligned, the method is insensitive to the effects of timing errors, epicentral mislocation, and lateral heterogeneity in earth structure. This procedure was implemented in May 1993; the results from that month are presented here.

Geophysical Research Letters↗