Search USGS⌕ Search

SEARCH · Search USGS

Results for “Interfaces”

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

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 721 records · Page 40Linked to original sources
USGS2016

Soil amplification with a strong impedance contrast: Boston, Massachusetts

In this study, we evaluate the effect of strong sediment/bedrock impedance contrasts on soil amplification in Boston, Massachusetts, for typical sites along the Charles and Mystic Rivers. These sites can be characterized by artificial fill overlying marine sediments overlying glacial till and bedrock, where the depth to bedrock ranges from 20 to 80 m. The marine sediments generally consist of organic silts, sand, and Boston Blue Clay. We chose these sites because they represent typical foundation conditions in the city of Boston, and the soil conditions are similar to other high impedance contrast environments. The sediment/bedrock interface in this region results in an impedance ratio on the order of ten, which in turn results in a significant amplification of the ground motion. Using stratigraphic information derived from numerous boreholes across the region paired with geologic and geomorphologic constraints, we develop a depth-to-bedrock model for the greater Boston region. Using shear-wave velocity profiles from 30 locations, we develop average velocity profiles for sites mapped as artificial fill, glaciofluvial deposits, and bedrock. By pairing the depth-to-bedrock model with the surficial geology and the average shear-wave velocity profiles, we can predict soil amplification in Boston. We compare linear and equivalent-linear site response predictions for a soil layer of varying thickness over bedrock, and assess the effects of varying the bedrock shear-wave velocity (V Sb ) and quality factor (Q). In a moderate seismicity region like Boston, many earthquakes will result in ground motions that can be modeled with linear site response methods. We also assess the effect of bedrock depth on soil amplification for a generic soil profile in artificial fill, using both linear and equivalent-linear site response models. Finally, we assess the accuracy of the model results by comparing the predicted (linear site response) and observed site response at the Northeastern University (NEU) vertical seismometer array during the 2011 M 5.8 Mineral, Virginia, earthquake. Site response at the NEU vertical array results in amplification on the order of 10 times at a period between 0.7-0.8 s. The results from this study provide evidence that the mean short-period and mean intermediate-period amplification used in design codes (i.e., from the F a and F v site coefficients) may underpredict soil amplification in strong impedance contrast environments such as Boston.

Massachusetts↗
USGS2023

Nitrogen isotopes indicate vehicle emissions and biomass burning dominate ambient ammonia across Colorado's Front Range urban corridor

Urban ammonia (NH 3 ) emissions contribute to poor local air quality and can be transported to rural landscapes, impacting sensitive ecosystems. The Colorado Front Range urban corridor encompasses the Denver Metropolitan Area, rural farmland/rangeland and montane forest between the city and the Rocky Mountains. Reactive nitrogen emissions from the corridor are partly responsible for increased N deposition to the wildland-urban interface (WUI) in this region. To determine the significance of individual NH 3 sources to WUI ecosystems, we measured the concentration and isotopic composition (δ 15 N–NH 3 ) of ambient NH 3(g) from April to October 2018 across a five-site urban to rural gradient in the corridor. The urban sites had higher NH 3 concentrations and δ 15 N–NH 3 values than the rural/suburban sites. Based on isotope mixing models, NH 3 emission source contributions for all sites were fertilizer (12 ± 5.7%), livestock waste (18 ± 12%), vehicles (37 ± 23%), and biomass burning (34 ± 20%). Vehicle contributions were consistent across all months with an average of 35% and summer months showed a peak in biomass burning contributions (40%). As wildfires are projected to increase due to climate change, we stress a need for constraints on the isotopic signature of NH 3 emitted from wildfires. Vehicle emissions contributed the greatest amount of NH 3 (40%) at the urban sites while rural/suburban sites had higher agricultural contributions (41%). Had 2018 not had an anomalously high wildfire season, 46% and 60% of the NH 3 would have been attributed to vehicle emissions at the WUI site and urban sites, respectively. NH 3 emissions have historically been ascribed to agricultural activities but these findings illustrate the universal significance of vehicle emissions and the potential for sustained wildfire activity to be a primary contributor to NH 3 . Air quality (e.g., particulate matter) and nitrogen deposition reduction plans may benefit by including management practices that address vehicle NH 3 emissions.

Colorado↗
USGS2025

Effects of chronic metal exposure and metamorphosis on the microbiomes of larval and adult insects and riparian spiders through the aquatic-riparian food web

The macroinvertebrate microbiome controls various aspects of the host's physiology, from regulation of environmental contaminants to reproductive output. Aquatic insects provide critical nutritional subsidies linking aquatic and riparian food webs while simultaneously serving as a contaminant pathway for riparian insectivores in polluted ecosystems. Previous studies have characterized the transport and transfer of contaminants from aquatic to riparian ecosystems through insect metamorphosis, but both contaminant exposure and metamorphosis are energetically intensive processes that may cause host microbiomes to undergo radical transformation in structure and function, potentially affecting the host's physiology. We collected arthropods from three sites within Torch Lake, a historical copper mine in the Keweenaw Peninsula, Michigan, USA, and three sites within a nearby reference lake. Our objectives were to: 1) characterize the variation in microbiome communities and predicted metagenomic functions with legacy copper mining activity across space, among host types and family-level host taxonomy, 2) characterize how insect metamorphosis alters the microbiome community, including the degree of endosymbiotic infection, and predicted metagenomic function. We field-collected organisms, extracted their DNA, and sequenced the 16S region of the rRNA gene to characterize microbiome communities, then predicted metagenomic function. Site, lake, and host taxonomy affected the host microbiome community composition. Copper exposure increased the abundance of xenobiotic and lipid metabolism pathways in the Araneidae spider microbiome. Insect metamorphosis reduced the alpha diversity, altered the community composition, and predicted metagenomic function. We observed a bioconcentration of endosymbiotic bacteria in adult insects, especially holometabolous insects. Through metamorphosis, we observed a transition in function from xenobiotic degradation pathways to carbohydrate metabolism. Overall, contaminant exposure alters the microbiome composition in aquatic insects and riparian spiders and alters the function of the microbiome across the aquatic-riparian interface. Furthermore, metamorphosis is a critical element in shaping the aquatic insect microbiome across its life history.

Michigan↗
USGS2005

Parallel Fortran-MPI software for numerical inversion of the Laplace transform and its application to oscillatory water levels in groundwater environments

A parallel Fortran-MPI (Message Passing Interface) software for numerical inversion of the Laplace transform based on a Fourier series method is developed to meet the need of solving intensive computational problems involving oscillatory water level's response to hydraulic tests in a groundwater environment. The software is a parallel version of ACM (The Association for Computing Machinery) Transactions on Mathematical Software (TOMS) Algorithm 796. Running 38 test examples indicated that implementation of MPI techniques with distributed memory architecture speedups the processing and improves the efficiency. Applications to oscillatory water levels in a well during aquifer tests are presented to illustrate how this package can be applied to solve complicated environmental problems involved in differential and integral equations. The package is free and is easy to use for people with little or no previous experience in using MPI but who wish to get off to a quick start in parallel computing. ?? 2004 Elsevier Ltd. All rights reserved.

Environmental Modelling and Software↗
USGS2013

An integrated multi-criteria scenario evaluation web tool for participatory land-use planning in urbanized areas: The Ecosystem Portfolio Model

Land-use land-cover change is one of the most important and direct drivers of changes in ecosystem functions and services. Given the complexity of the decision-making, there is a need for Internet-based decision support systems with scenario evaluation capabilities to help planners, resource managers and communities visualize, compare and consider trade-offs among the many values at stake in land use planning. This article presents details on an Ecosystem Portfolio Model (EPM) prototype that integrates ecological, socio-economic information and associated values of relevance to decision-makers and stakeholders. The EPM uses a multi-criteria scenario evaluation framework, Geographic Information Systems (GIS) analysis and spatially-explicit land-use/land-cover change-sensitive models to characterize changes in important land-cover related ecosystem values related to ecosystem services and functions, land parcel prices, and community quality-of-life (QoL) metrics. Parameters in the underlying models can be modified through the interface, allowing users in a facilitated group setting to explore simultaneously issues of scientific uncertainty and divergence in the preferences of stakeholders. One application of the South Florida EPM prototype reported in this article shows the modeled changes (which are significant) in aggregate ecological value, landscape patterns and fragmentation, biodiversity potential and ecological restoration potential for current land uses compared to the 2050 land-use scenario. Ongoing refinements to EPM, and future work especially in regard to modifiable sea level rise scenarios are also discussed.

Environmental Modelling and Software↗
USGS2017

Simple, efficient allocation of modelling runs on heterogeneous clusters with MPI

In scientific modelling and computation, the choice of an appropriate method for allocating tasks for parallel processing depends on the computational setting and on the nature of the computation. The allocation of independent but similar computational tasks, such as modelling runs or Monte Carlo trials, among the nodes of a heterogeneous computational cluster is a special case that has not been specifically evaluated previously. A simulation study shows that a method of on-demand (that is, worker-initiated) pulling from a bag of tasks in this case leads to reliably short makespans for computational jobs despite heterogeneity both within and between cluster nodes. A simple reference implementation in the C programming language with the Message Passing Interface (MPI) is provided.

Environmental Modelling and Software↗
USGS2017

Shallow water benthic imaging and substrate characterization using recreational-grade sidescan-sonar

In recent years, lightweight, inexpensive, vessel-mounted ‘recreational grade’ sonar systems have rapidly grown in popularity among aquatic scientists, for swath imaging of benthic substrates. To promote an ongoing ‘democratization’ of acoustical imaging of shallow water environments, methods to carry out geometric and radiometric correction and georectification of sonar echograms are presented, based on simplified models for sonar-target geometry and acoustic backscattering and attenuation in shallow water. Procedures are described for automated removal of the acoustic shadows, identification of bed-water interface for situations when the water is too turbid or turbulent for reliable depth echosounding, and for automated bed substrate classification based on singlebeam full-waveform analysis. These methods are encoded in an open-source and freely-available software package, which should further facilitate use of recreational-grade sidescan sonar, in a fully automated and objective manner. The sequential correction, mapping, and analysis steps are demonstrated using a data set from a shallow freshwater environment.

Environmental Modelling and Software↗
USGS2018

A tool for efficient, model-independent management optimization under uncertainty

To fill a need for risk-based environmental management optimization, we have developed PESTPP-OPT, a model-independent tool for resource management optimization under uncertainty. PESTPP-OPT solves a sequential linear programming (SLP) problem and also implements (optional) efficient, “on-the-fly” (without user intervention) first-order, second-moment (FOSM) uncertainty techniques to estimate model-derived constraint uncertainty. Combined with a user-specified risk value, the constraint uncertainty estimates are used to form chance-constraints for the SLP solution process, so that any optimal solution includes contributions from model input and observation uncertainty. In this way, a “single answer” that includes uncertainty is yielded from the modeling analysis. PESTPP-OPT uses the familiar PEST/PEST++ model interface protocols, which makes it widely applicable to many modeling analyses. The use of PESTPP-OPT is demonstrated with a synthetic, integrated surface-water/groundwater model. The function and implications of chance constraints for this synthetic model are discussed.

Environmental Modelling and Software↗
USGS2021

Towards improved environmental modeling outcomes: Enabling low-cost access to high-dimensional, geostatistical-based decision-support analyses

Computer models of environmental systems routinely inform decision making for water resource management. In this context, quantifying uncertainty in the important simulated outputs, and reducing uncertainty through assimilating historic system-state observations, is as important as the numerical model. However, implementing high-dimensional and stochastic workflows are challenging, often requiring that practitioners have theoretical and practical understanding of several advanced topics. Worse, implementing these important analyses can take substantial time and effort. This additional effort is often cited as justification for postponing, or even forgoing, these analyses. Herein, we present scripting tools to facilitate the efficient and repeatable construction of high-dimensional, geostatistical-based PEST interfaces, including uncertainty analyses. As demonstrated, these tools can be applied with minimal effort to a model with varied temporal and spatial discretization. Ultimately, these tools can enable low-cost access to valuable decision-support analyses earlier and more frequently during the modeling workflow.

Environmental Modelling & Software↗
USGS2021

Supporting cost-effective watershed management strategies for Chesapeake Bay using a modeling and optimization framework

Extensive efforts to adaptively manage nutrient pollution rely on Chesapeake Bay Program's (Phase 6) Watershed Model, called Chesapeake Assessment Scenario Tool (CAST), which helps decision-makers plan and track implementation of Best Management Practices (BMPs). We describe mathematical characteristics of CAST and develop a constrained nonlinear BMP-subset model, software, and visualization framework. This represents the first publicly available optimization framework for exploring least-cost strategies of pollutant load control for the United States' largest estuary . The optimization identifies implementation options for a BMP subset modeled with load reduction effectiveness factors, and the web interface facilitates interactive exploration of >30,000 solutions organized by objective, nutrient control level, and for ~200 counties. We assess framework performance and demonstrate modeled cost improvements when comparing optimization-suggested proposals with proposals inspired by jurisdiction plans. Stakeholder feedback highlights the framework's current utility for investigating cost-effective tradeoffs and its usefulness as a foundation for future analysis of restoration strategies.

Chesapeake Bay watershed↗
USGS2022

A scalable model-independent iterative data assimilation tool for sequential and batch estimation of high dimensional model parameters and states

Ensemble-based data assimilation (DA) methods have displayed strong potential to improve model state and parameter estimation across several disciplines due to their computational efficiency, scalability, and ability to estimate uncertainty in the dynamic states and the parameters. However, a barrier to adoption of ensemble DA methods remains. Namely, there is currently a lack of available tools that enable efficient and scalable DA in a non-intrusive fashion and that support implementation flexibility. This paper presents an open-source software tool (PESTPP-DA) that implements a range of data assimilation methods—Ensemble Kalman filter, Ensemble Kalman Smoother and Ensemble Smoother—using the widely known PEST model-interface protocols, to interact with any model. Two iterative solutions can be used for nonlinear and/or non-Gaussian assimilation problems. To demonstrate the broad range of PESTPP-DA applications, two synthetic case studies are presented: (1) the Lorenz model and (2) a groundwater pumping test in the presence of a non-Gaussian hydraulic conductivity field.

Environmental Modelling & Software↗
USGS2022

A model-independent tool for evolutionary constrained multi-objective optimization under uncertainty

An open-source tool has been developed to facilitate constrained single- and multi-objective optimization under uncertainty (CMOU) analyses. The tool uses the well-known PEST interface protocols to communicate with the underlying forward simulation, making it non-intrusive. The tool contains a built-in parallel run manager to make use of heterogeneous and distributed computing resources. Several popular and well-known evolutionary algorithms are implemented and can be combined with a range of approaches to represent uncertainty in model-derived constraint/objective values. These attributes serve to address the current barrier to adopt advanced CMOU analyses for a wide range of decision-support problems across the environmental modeling spectrum. We demonstrate the capabilities of the CMOU tool on a well-known analytical benchmark problem that we augmented to include uncertainty, as well as on a synthetic density-dependent coastal groundwater management benchmark problem. Both demonstrations highlight the importance of explicitly accounting for uncertainty to convey risk and reliability in pareto-optimal design.

Environmental Modelling & Software↗
USGS2022

Increasing the uptake of ecological model results in policy decisions to improve biodiversity outcomes

Models help decision-makers anticipate the consequences of policies for ecosystems and people; for instance, improving our ability to represent interactions between human activities and ecological systems is essential to identify pathways to meet the 2030 Sustainable Development Goals. However, use of modeling outputs in decision-making remains uncommon. We share insights from a multidisciplinary National Socio-Environmental Synthesis Center working group on technical, communication, and process-related factors that facilitate or hamper uptake of model results. We emphasize that it is not simply technical model improvements, but active and iterative stakeholder involvement that can lead to more impactful outcomes. In particular, trust- and relationship-building with decision-makers are key for knowledge-based decision making. In this respect, nurturing knowledge exchange on the interpersonal (e.g., through participatory processes), and institutional level (e.g., through science-policy interfaces across scales), represent promising approaches. To this end, we offer a generalized approach for linking modeling and decision-making.

Environmental Modelling & Software↗
USGS2024

An open-source workflow for scaling burn severity metrics from drone to satellite to support post-fire watershed management

Wildfires are increasing in size and severity across much of the western United States, exposing vulnerable wildland-urban interfaces to post-fire hazards. The Mediterranean chaparral region of Northern California contains many high sloping watersheds prone to hazardous post-fire flood events and identifying watersheds at high risk of soil loss and debris flows is a priority for post-fire response and management. Uncrewed Aerial Systems (UAS; aka drones) offer post-fire management teams the ability to quickly mobilize and survey burned areas with very high-resolution imagery (∼1 cm), facilitating emergency management and post-fire hazard assessment. However, adoption of this technology by hazard response teams may be hindered by complicated workflows for UAS data acquisition, image processing and analysis. We present an open-source workflow using mature Geographic Information Systems (GIS) software and Python packages in a Jupyter Notebook environment that guides users through classification of true-color UAS imagery to generate high resolution burn severity maps which can then be scaled across larger watersheds using Sentinel-2 normalized burn ratio (NBR) images. Soil burn severity classifications using a weighted brightness (WB) image and Char Index (CI) generated from UAS imagery were validated with in-situ data and random stratified points, resulting in the CI having the highest overall accuracy of 87.5%. CI also displayed a marginally stronger relationship over the WB with the post-fire Sentinel-2 NBR, R 2 = 0.79 and R 2 = 0.78 respectively. Our methods offer the unique opportunity to standardize GIS workflows, promoting replication through transparency, while improving the user's understanding of scientific GIS functionality.

California↗
USGS2024

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

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

Epidemics↗
USGS2016

Insights into methane dynamics from analysis of authigenic carbonates and chemosynthetic mussels at newly-discovered Atlantic Margin seeps

The recent discovery of active methane venting along the US northern and mid-Atlantic margin represents a new source of global methane not previously accounted for in carbon budgets from this region. However, uncertainty remains as to the origin and history of methane seepage along this tectonically inactive passive margin. Here we present the first isotopic analyses of authigenic carbonates and methanotrophic deep-sea mussels, Bathymodiolus sp., and the first direct constraints on the timing of past methane emission, based on samples collected at the upper slope Baltimore Canyon (∼385 m water depth) and deepwater Norfolk (∼1600 m) seep fields within the area of newly-discovered venting. The authigenic carbonates at both sites were dominated by aragonite, with an average signature of −47‰ , a value consistent with microbially driven anaerobic oxidation of methane-rich fluids occurring at or near the sediment–water interface. Authigenic carbonate U and Sr isotope data further support the inference of carbonate precipitation from seawater-derived fluids rather than from formation fluids from deep aquifers. Carbonate stable and radiocarbon ( and ) isotope values from living Bathymodiolus sp. specimens are lighter than those of seawater dissolved inorganic carbon, highlighting the influence of fossil carbon from methane on carbonate precipitation. U–Th dates on authigenic carbonates suggest seepage at Baltimore Canyon between 14.7±0.6 ka to 15.7±1.6 ka , and at the Norfolk seep field between 1.0±0.7 ka to 3.3±1.3 ka , providing constraint on the longevity of methane efflux at these sites. The age of the brecciated authigenic carbonates and the occurrence of pockmarks at the Baltimore Canyon upper slope could suggest a link between sediment delivery during Pleistocene sea-level lowstand, accumulation of pore fluid overpressure from sediment compaction, and release of overpressure through subsequent venting. Calculations show that the Baltimore Canyon site probably has not been within the gas hydrate stability zone (GHSZ) in the past 20 ka, meaning that in-situ release of methane from dissociating gas hydrate cannot be sustaining the seep. We cannot rule out updip migration of methane from dissociation of gas hydrate that occurs farther down the slope as a source of the venting at Baltimore Canyon, but consider that the history of rapid sediment accumulation and overpressure may play a more important role in methane emissions at this site.

Baltimore Canyon seep fields, Norfolk seep fields↗
USGS2017

Evidence for strong lateral seismic velocity variation in the lower crust and upper mantle beneath the California margin

Regional seismograms from earthquakes in Northern California show a systematic difference in arrival times across Southern California where long period (30–50 seconds) SH waves arrive up to 15 seconds earlier at stations near the coast compared with sites towards the east at similar epicentral distances. We attribute this time difference to heterogeneity of the velocity structure at the crust-mantle interface beneath the California margin. To model these observations, we propose a fast seismic layer, with thickness growing westward from the San Andreas along with a thicker and slower continental crust to the east. Synthetics generated from such a model are able to match the observed timing of SH waveforms better than existing 3D models. The presence of a strong upper mantle buttressed against a weaker crust has a major influence in how the boundary between the Pacific plate and North American plate deforms and may explain the observed asymmetric strain rate across the boundary.

California↗
USGS2018

Stress rotation across the Cascadia megathrust requires a weak subduction plate boundary at seismogenic depths

The Mendocino Triple Junction region is the most seismically active part of the Cascadia Subduction Zone. The northward moving Pacific plate collides with the subducting Gorda plate causing intense internal deformation within it. Here we show that the stress field rotates rapidly with depth across the thrust interface from a strike-slip regime within the subducting plate, reflecting the Pacific plate collision, to a thrust regime in the overriding plate. We utilize a dense focal mechanism dataset, including observations from the Cascadia Initiative ocean bottom seismograph experiment, to constrain the stress orientations. To quantify the implications of this rotation for the strength of the plate boundary, we designed an inversion that solves for the absolute stress tensors in a three-layer model subject to assumptions about the strength of the subducting mantle. Our results indicate that the shear stress on the plate boundary fault is likely no more than about ∼50 MPa at ∼20 km depth. Regardless of the assumed mantle strength, we infer a relatively weak megathrust fault with an effective friction coefficient of ∼0 to 0.2 at seismogenic depths. Such a low value for the effective friction coefficient requires a combination of high fluid pressures and/or fault-zone minerals with low inherent friction in the region where a great earthquake is expected in Cascadia.

California↗