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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 469 records · Page 26Linked to original sources
USGS2014

Limnogeology, news in brief

We've invited Michael R. Rosen, water quality specialist within the USGS Water Science Field Team in Carson City and Elizabeth Gierlowski-Kordesch, professor of geology at Ohio University, to take a look at the intriguing new developments that are emerging in limnogeologic studies. These studies are increasing our understanding of how climate and movements of the Earth's surface influence terrestrial environments, as well as how contaminants are distributed and retained in the environment. They present a selection of recent significant research on sediments, rock, and biota that have been preserved in modern and ancient lake basins.

Environmental Earth Sciences↗
USGS2022

GSPy: A new toolbox and data standard for Geophysical Datasets

The diversity of geophysical methods and datatypes, as well as the isolated nature of various specialties (e.g., electromagnetic, seismic, potential fields) leads to a profusion of separate data file formats and documentation conventions. This can hinder cooperation and reduce the impact of datasets researchers have invested in heavily to collect and prepare. An open, portable, and well-supported community data standard could greatly improve the interoperability, transferability, and long-term archival of geophysical data. Airborne geophysical methods particularly need an open and accessible data standard, and they exemplify the complexity that is common in geophysical datasets where critical auxiliary information on the survey and system parameters are required to fully utilize and understand the data. Here, we propose a new Geophysical Standard, termed the GS convention, that leverages the well-established and widely used NetCDF file format and builds on the Climate and Forecasts (CF) metadata convention. We also present an accompanying open-source Python package, GSPy, to provide methods and workflows for building the GS-standardized NetCDF files, importing and exporting between common data formats, preparing input files for geophysical inversion software, and visualizing data and inverted models. By using the NetCDF format, handled through the Xarray Python package, and following the CF conventions, we standardize how metadata is recorded and directly stored with the data, from general survey and system information down to specific variable attributes. Utilizing the hierarchical nature of NetCDF, GS-formatted files are organized with a root Survey group that contains global metadata about the geophysical survey. Data are then organized into subgroups beneath Survey and are categorized as Tabular or Raster depending on the geometry and point of origin for the data. Lastly, the standard ensures consistency in constructing and tracking coordinate reference systems, which is vital for accurate portability and analysis. Development and adoption of a NetCDF-based data standard for geophysical surveys can greatly improve how these complex datasets are shared and utilized, making the data more accessible to a broader science community. The architecture of GSPy can be easily transferred to additional geophysical datatypes and methods in future releases.

Frontiers in Earth Science - Environmental Informa↗
USGS2026

Guidelines for producing integrated 210Pb and 14C age-models

Accurate reconstructions of past environmental changes are crucial in paleoecological research and require reliable chronologies of sedimentary archives. Establishing robust age-models and obtaining the most appropriate proxies for analysis is a complex scientific endeavor, requiring extensive resources and collaboration among specialists, including radiochronologists. Radiometric dating methods, such as 210 Pb and radiocarbon ( 14 C), are frequently employed to establish chronologies in aquatic sedimentary deposits and peat bogs. In this study, we review key aspects of sampling, analysis, and the principles underlying 210 Pb and 14 C age-models, focusing on methods for developing robust joint chronologies for paleoenvironmental research. Drawing largely from the authors' experiences and group discussions during and after a scientific workshop in 2022, we discuss important considerations for site selection, sampling strategies, and radiometric dating to construct integrated 210 Pb and 14 C age-models. Using expert consensus, this group – called Paleostats – aims to provide a set of best practices for other geochronologists with this methods paper. Among our conclusions, we emphasize the importance of accounting for site-specific factors such as prior information on sedimentation rates to establish appropriate sampling and analytical strategies. The use of appropriate coring devices can minimize disturbance to sediments and ensure the core surface remains intact and preserved until sectioning. Where excess 210 Pb is expected, sectioning at intervals of ≤1 cm provides an adequate sampling resolution for 210 Pb dating. Exceptions are possible, allowing for ~2–3 cm sections in areas with confirmed high sedimentation rates (e.g., > 1 cm yr −1 ). Recovering deeper core sections for 14 C dating with sufficient overlap allows for accounting errors in depth estimates made in the field. Special attention is advised during time intervals where validation proxies, such as the human-made radionuclides 137 Cs or post-bomb 14 C, are expected, and to determine the depth of secular equilibrium between 210 Pb and 226 Ra. Radiocarbon analyses are commonly performed by accelerator mass spectrometry, and age models are constructed mainly using Bayesian statistics with Markov Chain Monte Carlo techniques (e.g., Bacon ). A Bayesian approach ( Plum ) is now available for producing 210 Pb age-models, which infers the 210 Pb ex flux, eliminates the need for selecting an equilibrium depth, and allows dating cores with incomplete 210 Pb ex inventory. Plum offers improved chronologies by integrating raw 210 Pb and 14 C data, and these age-models can be enriched with other dating methodologies, such as identifying tephras and other well-recorded historical events. Harmonized reporting would contribute to making radiometric age-models reproducible, which would benefit from an international effort. Using 210 Pb and 14 C to produce integrated age-models may yield better insights into the interplay between natural and recent anthropogenic forcings on ecosystems. This can enhance our understanding of environmental processes and their impacts on climate change, ultimately supporting science-based assessments and decisions.

Earth-Science Reviews↗
USGS2024

Rainfall as a driver of post-wildfire flooding and debris flows: A review and synthesis

The increasing threat of post-wildfire hazards creates an imperative for improved post-wildfire flooding and debris flow prediction capabilities. Because rainfall is a primary driver of predictive hydrology and debris flow initiation and inundation models, recent efforts have emphasized the need for interdisciplinary collaboration between meteorology and post-wildfire hazard science that develops more accurate rainfall estimates with longer lead times. In this work, we identified critical knowledge gaps for developing rainfall estimates and filled those gaps by reviewing recent literature and synthesizing pre-existing datasets. Gap areas were organized into the following general topics: a) rainfall intensity-duration-frequency relations, b) time-varying rainfall, c) spatially varying rainfall, and d) rainfall regimes. Recent key research advances include the increasing availability of gridded quantitative rainfall estimates, the expanded use of distributed hydrologic and erosion models that incorporate spatial and temporal variability in rainfall, and the linking of concepts and modeling from the atmospheric and climate sciences with post-wildfire hazard science. We prototype a rainfall regime regionalization schema that captures self-similar properties of rainfall intensity ( k , the maximum rainfall intensity) and temporal scaling ( n , the decay rate). Our k - n relations schema could serve as a framework for organizing, interpreting, and predicting post-wildfire hydrologic and erosional responses. Finally, we summarize salient gaps for implementing spatiotemporally varying rainfall as the driver of post-wildfire hydrologic models designed to improve the prediction of flooding and debris flow hazards to the built environment for emergency managers.

Earth-Science Reviews↗
USGS2019

Growing pains of crowdsourced stream stage monitoring using mobile phones: The development of CrowdHydrology

Citizen science-based approaches to monitor the natural environment tend to be bimodal in maturity. Older and established programs such as the Audubon’s Christmas bird count and Community Collaborative Rain, Hail, and Snow Network (CoCoRaHS) have thousands of participants across decades of observations, while less mature citizen science projects have shorter lifespans often focused on local or regional observations with tens or hundreds of participants. For the latter, it can be difficult to transition into a more mature and sustainable citizen science-based research program. This paper focuses on this transition by evaluating CrowdHydrology (ca. 2010), a citizen science project that has transitioned from a regional to national network. It evaluates the data accuracy, citizen participation, and station popularity. The CrowdHydrology network asks citizens to send in text messages of water levels in streams and lakes, which has resulted in 16,294 observations submitted by over 8,000 unique participants at 120 unique locations. Using water level data and participation records from CrowdHydrology, we analyze the expansion and citizen participation from a regional to national citizen science network. We identify barriers to participation and evaluate why some citizen science observation stations are popular while others are not. We explore our chosen contributory program model for CrowdHydrology and the influence this model has had on long-term participation. Results demonstrate a highly variable rate of contributions of citizen scientists. This paper proposes hypotheses on why many of our observations are from one-time participants and why some monitoring stations are more popular than others. Finally, we address the future expansion of the CrowdHydrology network by evaluating successful monitoring locations and growing interest of watershed groups to expand the network of gauges.

Frontiers in Earth Science↗
USGS2010

Evolution of Ore Deposits and Technology Transfer Project: Isotope and Chemical Methods in Support of the U.S. Geological Survey Science Strategy, 2003-2008

Principal functions of the U.S. Geological Survey (USGS) Mineral Resources Program are providing assessments of the location, quantity, and quality of undiscovered mineral deposits, and predicting the environmental impacts of exploration and mine development. The mineral and environmental assessments of domestic deposits are used by planners and decisionmakers to improve the stewardship of public lands and public resources. Assessments of undiscovered mineral deposits on a global scale reveal the potential availability of minerals to the United States and other countries that manufacture goods imported to the United States. These resources are of fundamental relevance to national and international economic and security policy in our globalized world economy. Performing mineral and environmental assessments requires that predictions be made of the likelihood of undiscovered deposits. The predictions are based on geologic and geoenvironmental models that are constructed for the diverse types of mineral deposits from detailed descriptions of actual deposits and detailed understanding of the processes that formed them. Over the past three decades the understanding of ore-forming processes has benefited greatly from the integration of laboratory-based geochemical tools with field observations and other data sources. Under the aegis of the Evolution of Ore Deposits and Technology Transfer Project (referred to hereinafter as the Project), a 5-year effort that terminated in 2008, the Mineral Resources Program provided state-of-the-art analytical capabilities to support applications of several related geochemical tools to ore-deposit-related studies. The analytical capabilities and scientific approaches developed within the Project have wide applicability within Earth-system science. For this reason the Project Laboratories represent a valuable catalyst for interdisciplinary collaborations of the type that should be formed in the coming years for the United States to meet its natural-resources and natural-science needs. This circular presents an overview of the Project. Descriptions of the Project laboratories are given first including descriptions of the types of chemical or isotopic analyses that are made and the utility of the measurements. This is followed by summaries of select measurements that were carried out by the Project scientists. The studies are grouped by science direction. Virtually all of them were collaborations with USGS colleagues or with scientists from other governmental agencies, academia, or the private sector.

Circular↗
USGS1986

Guidelines to classification and nomenclature of Arabian felsic plutonic rocks

Well-defined procedures for classifying the felsic plutonic rocks of the Arabian Shield on the basis of petrographic, chemical and lithostratigraphic criteria and mineral-resource potential have been adopted and developed in the Saudi Arabian Deputy Ministry for Mineral Resources over the past decade. A number of problems with conventional classification schemes have been identified and resolved; others, notably those arising from difficulties in identifying precise mineral compositions, continue to present difficulties. The petrographic nomenclature used is essentially that recommended by the International Union of Geological Sciences. Problems that have arisen include the definition of: (1) rocks with sodic, zoned or perthitic feldspar, (2) trondhjemites, and (3) alkali granites. Chemical classification has been largely based on relative molar amounts of alumina, lime and alkalis, and the use of conventional variation diagrams, but pilot studies utilizing univariate and multivariate statistical techniques have been made. The classification used in Saudi Arabia for stratigraphic purposes is a hierarchy of formation-rank units, suites and super-suites as defined in the Saudi Arabian stratigraphic code. For genetic and petrological studies, a grouping as ‘associations’ of similar and genetically related lithologies is commonly used. In order to indicate mineral-resource potential, the felsic plutons are classed as common, precursor, specialized or mineralized, in order of increasing exploration significance.

Journal of African Earth Sciences↗
USGS2019

A review of machine learning applications to coastal sediment transport and morphodynamics

A range of computer science methods under the heading of machine learning (ML) enables the extraction of insight and quantitative relationships from multidimensional datasets. Here, we review some common ML methods and their application to studies of coastal morphodynamics and sediment transport. We examine aspects of ‘what’ and ‘why’ ML methods contribute, such as ‘what’ science problems ML tools have been used to address, ‘what’ was learned when using ML, and ‘why’ authors used ML methods. We find a variety of research questions have been addressed, ranging from small-scale predictions of sediment transport to larger-scale sand bar morphodynamics and coastal overwash on a developed island. We find various reasons justify the use of ML, including maximize predictability, emulation of model components, smooth and continuous nonlinear regression through data, and explicit inclusion of uncertainty. Overall the expanding use of ML has allowed for an expanding set of questions to be addressed. After reviewing the studies we outline a set of ‘best practices’ for coastal researchers using machine learning methods. Finally we suggest possible areas for future research, including the use of novel machine learning techniques and exploring ‘open data’ that is becoming increasingly available.

Earth-Science Reviews↗
USGS2022

On the documentation, independence, and stability of widely used seismological data products

Earthquake scientists have traditionally relied on relatively small data sets recorded on small numbers of instruments. With advances in both instrumentation and computational resources, the big-data era, including an established norm of open data-sharing, allows seismologists to explore important issues using data volumes that would have been unimaginable in earlier decades. Alongside with these developments, the community has moved towards routine production of interpreted data products such as seismic moment tensor catalogs that have provided an additional boon to earthquake science. As these products have become increasingly familiar and useful, it is important to bear in mind that they are not data, but rather interpreted data products. As such, they differ from data in ways that can be important, but not always appreciated. Important - and sometimes surprising - issues can arise if methodology is not fully described, data from multiple sources are included, or data products are not versioned (time-stamped). The line between data and data products is sometimes blurred, leading to an underappreciation of issues that affect data products. This note illustrates examples from two widely used data products: moment tensor catalogs and Did You Feel It? (DYFI) macroseismic intensity values. These examples show that increasing a data product’s documentation, independence, and stability can make it even more useful. To ensure the reproducibility of studies using data products, time-stamped products should be preserved, for example as electronic supplements to published papers, or, ideally, a more permanent repository.

Frontiers in Earth Science↗
USGS2020

USGS “Did You Feel It?” — Science and lessons from twenty years of citizen science-based macroseismology

The U.S. Geological Survey (USGS) “Did You Feel It?” (DYFI) system is an automatic method for rapidly collecting macroseismic intensity data from Internet users’ shaking and damage reports and for generating intensity maps immediately following felt earthquakes. DYFI has been in operation for nearly two decades (1999-2019) in the United States, and for nearly 15 years globally. During that period the amount of data collected is astounding: Over 5 million individual DYFI intensity reports—spanning all magnitude and distance ranges—have been amassed and archived. DYFI allows for macroseismic data collection at rates and quantities never before imagined, and thus high-quality macroseismic intensity maps can be made almost immediately, and with more complete coverage at higher resolution than in the past. DYFI also allows for valuable positive interactions of the citizenry with a Federal science agency. In essence, the widespread adoption of DYFI—along with ShakeMap—has facilitated the general acceptance of the very concept of shaking intensity, fundamentally improving our agency’s ability to communicate both hazard and risk to the population. DYFI effectively confirms the importance of reporting and inculcating the public’s understanding of intensity—in addition to magnitude—for a proper perspective of earthquake risk-related decision-making. Furthermore, the vast amount of DYFI data allow for data-rich analyses of otherwise intractable seismological, sociological, and earthquake impact studies that range from quantifying the shaking due to induced earthquakes, to human response and risk perception, to relating recorded shaking metrics to macroseismic effects, and the attenuation of intensity with magnitude and distance. Naturally, web-based data collection also poses challenges. After two decades of experience acquiring data with the DYFI system, we address some of these hallenges by documenting refinements to our algorithmic and operational procedures that have evolved over that time. Lastly, we outline new opportune research and development directions for our DYFI approach to citizen seismology.

Frontiers in Earth Science↗
USGS2020

Aeolian remobilisation of volcanic ash: Outcomes of a workshop in the Argentinian Patagonia

During explosive volcanic eruptions, large quantities of tephra can be dispersed and deposited over wide areas. Following deposition, subsequent aeolian remobilisation of ash can potentially exacerbate primary impacts on timescales of months to millennia. Recent ash remobilisation events (e.g., following eruptions of Cordón Caulle 2011; Chile, and Eyjafjallajökull 2010, Iceland) have highlighted this to be a recurring phenomenon with consequences for human health, economic sectors, and critical infrastructure. Consequently, scientists from observatories and Volcanic Ash Advisory Centers (VAACs), as well as researchers from fields including volcanology, aeolian processes and soil sciences, convened at the San Carlos de Bariloche headquarters of the Argentinian National Institute of Agricultural Technology to discuss the “state of the art” for field studies of remobilised deposits as well as monitoring, modeling and understanding ash remobilisation. In this article, we identify practices for field characterisation of deposits and active processes, including mapping, particle characterisation and sediment traps. Furthermore, since forecast models currently rely on poorly-constrained dust emission schemes, we call for laboratory and field measurements to better parameterise the flux of volcanic ash as a function of friction velocity. While source area location and extent are currently the primary inputs for dispersion models, once emission schemes become more sophisticated and better constrained, other parameters will also become important (e.g., source material volume and properties, effective precipitation, type and distribution of vegetation cover, friction velocity). Thus, aeolian ash remobilisation hazard and associated impact assessment require systematic monitoring, including the development of a regularly-updated spatial database of resuspension source areas.

Frontiers in Earth Science↗
USGS2024

Editorial: Enabling people-centered risk communication for geohazards

In the field of natural hazards, communicating science with the public and stakeholders (i.e., interested parties) involves entering the challenging and complex world of hazard and risk communication, the ultimate purpose of which is to reduce the impact of impending hazards on people and property at risk. Hazard and risk communication are adequate if they reach people with the information that they need, at the right time, and in a form that they can use. This task appears to be particularly difficult when decisions by the public and stakeholders have to be made in the presence of uncertainty about what could happen, as is often the case with geohazards. Moreover, decision-making is complex when there are time pressures, human and economic resources are limited, and multiple sources of information need to be considered. This poses several challenges for the development of two-way and people-centered risk communication for geohazards. The “Enabling People-Centered Risk Communication for Geohazards” Research Topic analyses these challenges and identifies innovative pathways to address them. More precisely, it draws together 13 state-of-the-art articles from around the world on improving communication practices, strategies, and understandings relating to a range of various geohazards and weather-related hazards.

Frontiers in Earth Science↗
USGS2024

Using open-science workflow tools to produce SCEC CyberShake physics-based probabilistic seismic hazard models

The Statewide (formerly Southern) California Earthquake Center (SCEC) conducts multidisciplinary earthquake system science research that aims to develop predictive models of earthquake processes, and to produce accurate seismic hazard information that can improve societal preparedness and resiliency to earthquake hazards. As part of this program, SCEC has developed the CyberShake platform, which calculates physics-based probabilistic seismic hazard analysis (PSHA) models for regions with high-quality seismic velocity and fault models. The CyberShake platform implements a sophisticated computational workflow that includes over 15 individual codes written by 6 developers. These codes are heterogeneous, ranging from short-running high-throughput serial CPU codes to large, long-running, parallel GPU codes. Additionally, CyberShake simulation campaigns are computationally extensive, typically producing tens of terabytes of meaningful scientific data and metadata over several months of around-the-clock execution on leadership-class supercomputers. To meet the needs of the CyberShake platform, we have developed an extreme-scale workflow stack, including the Pegasus Workflow Management System, HTCondor, Globus, and custom tools. We present this workflow software stack and identify how the CyberShake platform and supporting tools enable us to meet a variety of challenges that come with large-scale simulations, such as automated remote job submission, data management, and verification and validation. This platform enabled us to perform our most recent simulation campaign, CyberShake Study 22.12, from December 2022 to April 2023. During this time, our workflow tools executed approximately 32,000 jobs, and used up to 73% of the Summit system at Oak Ridge Leadership Computing Facility. Our workflow tools managed about 2.5 PB of total temporary and output data, and automatically staged 19 million output files totaling 74 TB back to archival storage on the University of Southern California's Center for Advanced Research Computing systems, including file-based relational data and large binary files to efficiently store millions of simulated seismograms. CyberShake extreme-scale workflows have generated simulation-based probabilistic seismic hazard models that are being used by seismological, engineering, and governmental communities.

Frontiers Earth Science Journal↗
USGS2024

A benchmark dataset and workflow for landslide susceptibility zonation

Landslide susceptibility shows the spatial likelihood of landslide occurrence in a specific geographical area and is a relevant tool for mitigating the impact of landslides worldwide. As such, it is the subject of countless scientific studies. Many methods exist for generating a susceptibility map, mostly falling under the definition of statistical or machine learning. These models try to solve a classification problem: given a collection of spatial variables, and their combination associated with landslide presence or absence, a model should be trained, tested to reproduce the target outcome, and eventually applied to unseen data. Contrary to many fields of science that use machine learning for specific tasks, no reference data exist to assess the performance of a given method for landslide susceptibility. Here, we propose a benchmark dataset consisting of 7360 slope units encompassing an area of about 4,100 km 2 "> 4,100 km 2 in Central Italy. Using the dataset, we tried to answer two open questions in landslide research: (1) what effect does the human variability have in creating susceptibility models; (2) how can we develop a reproducible workflow for allowing meaningful model comparisons within the landslide susceptibility research community. With these questions in mind, we released a preliminary version of the dataset, along with a “call for collaboration,” aimed at collecting different calculations using the proposed data, and leaving the freedom of implementation to the respondents. Contributions were different in many respects, including classification methods, use of predictors, implementation of training/validation, and performance assessment. That feedback suggested refining the initial dataset, and constraining the implementation workflow. This resulted in a final benchmark dataset and landslide susceptibility maps obtained with many classification methods. Values of area under the receiver operating characteristic curve obtained with the final benchmark dataset were rather similar, as an effect of constraints on training, cross–validation, and use of data. Brier score results show larger variability, instead, ascribed to different model predictive abilities. Correlation plots show similarities between results of different methods applied by the same group, ascribed to a residual implementation dependence. We stress that the experiment did not intend to select the “best” method but only to establish a first benchmark dataset and workflow, that may be useful as a standard reference for calculations by other scholars. The experiment, to our knowledge, is the first of its kind for landslide susceptibility modeling. The data and workflow presented here comparatively assess the performance of independent methods for landslide susceptibility and we suggest the benchmark approach as a best practice for quantitative research in geosciences.

Earth-Science Reviews↗
USGS2018

Patterns, pace and processes of water-quality variability: Examples from a long-studied estuary

Environmental time series have rich information content that is invaluable for measuring and understanding changes over time and guiding policies to manage change. I extracted information from measurements of 10 water‐quality constituents in upper San Francisco Bay from 1975 to 2016, one of the longest observational records in a U.S. estuary. Changes were detected at every time scale captured by monthly sampling. Long‐term trends included increased ammonium (+53%), nitrate + nitrate (+50%), silicate (+14%), Secchi depth (+42%), and decreased chlorophyll a (Chl a ) (−74%) and suspended particulate matter (−45%). Changes at the decadal scale included abrupt shifts (Chl a , nitrate + nitrite) and oscillations between shorter trends of increase and decrease (Secchi depth, phosphate). Long‐term trends were not expressed equally across all seasons, and seasonal patterns of change varied across constituents. These examples illustrate key features of environmental variability at the land–sea interface: (1) water‐quality components change continually at time scales from months to decades; (2) patterns of seasonal, multiyear, and multidecadal change are complex and vary across constituents; (3) primary drivers of change are freshwater inflow, the master regulator of estuarine dynamics, and human activities such as river damming, water diversions, wastewater discharge, environmental policies, and species introductions; (4) extracting the full information content of time series requires multiple analyses, each revealing a different layer of insight into how changes develop over time; (5) water‐quality variability is nonstationary, so future changes cannot be forecast reliably; (6) repeated observation is an essential method of Earth system science with applications in the design and performance measures of environmental policies.

California↗
USGS2015

Timescale

No abstract available.

Encyclopedia of Earth Sciences Series↗