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Research about Continental United States

Source-linked reports with geographic coverage including Continental United States.

At least 19 recordsLinked to original sources

Machine learning generated streamflow drought forecasts for the Conterminous United States (CONUS): Developing and evaluating an operational tool to enhance sub-seasonal to seasonal streamflow drought early warning for gaged locations

Forecasts of streamflow drought, when streamflow declines below typical levels, are notably less available than for floods or meteorological drought, despite widespread impacts. To address this gap, we apply machine learning (ML) models to forecast streamflow drought 1-13 weeks into the future at > 3,000 streamgage locations across the conterminous United States (CONUS). We applied two ML methods (Long short-term memory (LSTM) neural networks; Light Gradient-Boosting Machine - LightGBM) and two benchmark model approaches (persistence; Autoregressive Integrated Moving Average - ARIMA) to predict weekly streamflow percentiles with independent models for each forecast horizon. To explore whether a training focus on dry weeks improved performance, both ML models were trained using all percentiles (LSTM-all, LightGBM-all) and only percentiles below 30% (LSTM<30, LightGBM<30). We evaluated model performance regionally and nationally for drought occurrence (the classification performance for a future date) and for drought onset/termination (performance identifying drought starts and ends). ML models generally performed worse than the persistence model for discrete classification (moderate, severe, extreme drought) of drought occurrence but exceeded the benchmark models for onset/termination. ML models outperformed benchmarks in predicting continuous streamflow percentiles below 30%. Occurrence performance was better for less intense droughts and shorter forecast horizons, with the ML models having predictive power at 1-4 week horizons for severe droughts (10th percentile threshold). All models struggled to forecast onset, though the best ML model was the LSTM<30 (sensitivity of 22%). Termination performance was greater, with the drought termination performance greatest for the LightGBM-all model. When estimating model uncertainty, the LSTM<30 model had the narrowest 90% percentile interval with closest to optimal capture. This work highlights the challenges and opportunities to further advance hydrological drought forecasting and supports an experimental operational streamflow drought assessment and forecast tool.

Continental United States↗

Enhancing mineral systems exploration through geochronology, thermochronology, and isotope analysis: USGS Geochron and USGS Isotope databases

A mineral systems approach to mineral exploration provides a comprehensive framework for understanding ore deposit formation by examining the geodynamic, magmatic, hydrothermal, and sedimentary processes responsible for mineralization, alteration, and remobilization of economic mineral deposits. Temporal and thermal constraints on ore genesis are crucial for refining mineral system models and guiding predictive exploration strategies. Geochronology and thermochronology offer invaluable insights into the timing and thermal evolution of ore-forming processes, whereas isotopic analyses provide critical information on the source and geochemical history of ore-forming fluids. Combining these methodologies have proven highly effective for mineral exploration in regions like Australia, however, their combined application has been limited in the United States. To apply these tools to mineral systems-based exploration, the U.S. Geological Survey (USGS) has developed two products: (1) The USGS Geochron Database, and (2) the USGS Isotope Database. These databases provide centralized repositories of geo/thermochronological dates and data (Geochron Database) and both radiogenic and stable isotope data (Isotope Database) generated by the USGS and partners over the past decades. Integrating these datasets together and with traditional exploration approaches provides the mineral exploration community with powerful tools for determining the temporal and thermal histories of ore systems and identifying metallogenic source provinces.

Continental United States↗

Declining reservoir reliability and increasing reservoir vulnerability: Long-term observations reveal longer and more severe periods of low reservoir storage for major United States reservoirs

Hydrological drought is a pervasive and reoccurring challenge in managing water resources. Reservoirs are critical for lessening the impacts of drought on water available for many uses. We use a novel and generalized approach to identify periods of unusually low reservoir storage—via comparisons to operational rule curves and historical patterns—to investigate how droughts affect storage in 250 reservoirs across the conterminous U.S. (CONUS). We find that the maximum amount of water stored in reservoirs is decreasing, and that periods of unusually low storage are becoming longer, more severe, and more variable in (a) western and central CONUS reservoirs, and (b) reservoirs with primarily over-year storage. Results suggest that reservoir storage has become less reliable and more vulnerable to larger deviations from desired storage patterns. These changes have coincided with ongoing shifts to the hydroclimate of CONUS, and with sedimentation further reducing available reservoir storage.

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Forecasting the long-term spatial distribution of earthquakes for the 2023 US National Seismic Hazard Model using gridded seismicity

Probabilistic seismic hazard analyses such as the U.S. National Seismic Hazard Model (NSHM) typically rely on declustering and spatially smoothing an earthquake catalog to estimate a long‐term time‐independent (background) seismicity rate to forecast future seismicity. In support of the U.S. Geological Survey’s (USGS) 2023 update to the NSHM, we update the methods used to develop this background or gridded seismicity model component of the NSHM. As in 2018, we use a combination of fixed and adaptive kernel Gaussian smoothing. However, we implement two additional declustering methods to account for the fact that declustering is a nonunique process. These new declustering methods result in different forecasts for the locations of future seismicity, as represented by spatial probability density functions that are later combined with a rate model to produce a full gridded earthquake rate forecast. The method updates, particularly in the separation of the spatial and rate models as well as revised regional boundaries, in some places cause substantive changes to the seismic hazard forecast compared to the previous 2018 NSHM. Additional updates to catalog processing and induced seismicity zones also contribute to changes in the gridded seismicity hazard since 2018. However, these changes are well understood and reflect improvements in our modeling of gridded seismicity hazard.

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Testing the hierarchy of predictability in grassland restoration across a gradient of environmental severity

Ecological restoration is critical for recovering degraded ecosystems but is challenged by variable success and low predictability. Understanding which outcomes are more predictable and less variable following restoration can improve restoration effectiveness. Recent theory asserts that the predictability of outcomes would follow an order from most to least predictable from coarse to fine community properties (physical structure > taxonomic diversity > functional composition > taxonomic composition) and that predictability would increase with more severe environmental conditions constraining species establishment. We tested this “hierarchy of predictability” hypothesis by synthesizing outcomes along an aridity gradient with 11 grassland restoration projects across the United States. We used 1829 vegetation monitoring plots from 227 restoration treatments, spread across 52 sites. We fit generalized linear mixed-effects models to predict six indicators of restoration outcomes as a function of restoration characteristics (i.e., seed mixes, disturbance, management actions, time since restoration) and used variance explained by models and model residuals as proxies for restoration predictability. We did not find consistent support for our hypotheses. Physical structure was among the most predictable outcomes when the response variable was relative abundance of grasses, but unpredictable for total canopy cover. Similarly, one dimension of taxonomic composition related to species identities was unpredictable, but another dimension of taxonomic composition indicating whether exotic or native species dominated the community was highly predictable. Taxonomic diversity (i.e., species richness) and functional composition (i.e., mean trait values) were intermittently predictable. Predictability also did not increase consistently with aridity. The dimension of taxonomic composition related to the identity of species in restored communities was more predictable (i.e., smaller residuals) in more arid sites, but functional composition was less predictable (i.e., larger residuals), and other outcomes showed no significant trend. Restoration outcomes were most predictable when they related to variation in dominant species, while those responding to rare species were harder to predict, indicating a potential role of scale in restoration predictability. Overall, our results highlight additional factors that might influence restoration predictability and add support to the importance of continuous monitoring and active management beyond one-time seed addition for successful grassland restoration in the United States.

Continental United States↗

CONUS404: The NCAR-USGS 4-km long-term regional hydroclimate reanalysis over the CONUS

A unique, high-resolution, hydroclimate reanalysis, 40-plus-year (October 1979–September 2021), 4 km (named as CONUS404), has been created using the Weather Research and Forecasting Model by dynamically downscaling of the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis of the global climate dataset (ERA5) over the conterminous United States. The paper describes the approach for generating the dataset, provides an initial evaluation, including biases, and indicates how interested users can access the data. The motivation for creating this National Center for Atmospheric Research (NCAR)–U.S. Geological Survey (USGS) collaborative dataset is to provide research and end-user communities with a high-resolution, self-consistent, long-term, continental-scale hydroclimate dataset appropriate for forcing hydrological models and conducting hydroclimate scientific analyses over the conterminous United States. The data are archived and accessible on the USGS Black Pearl tape system and on the NCAR supercomputer Campaign storage system.

Continental United States↗

Operational assessment tool for forest carbon dynamics for the United States: A new spatially explicit approach linking the LUCAS and CBM-CFS3 models

Background Quantifying the carbon balance of forested ecosystems has been the subject of intense study involving the development of numerous methodological approaches. Forest inventories, processes-based biogeochemical models, and inversion methods have all been used to estimate the contribution of U.S. forests to the global terrestrial carbon sink. However, estimates have ranged widely, largely based on the approach used, and no single system is appropriate for operational carbon quantification and forecasting. We present estimates obtained using a new spatially explicit modeling framework utilizing a “gain–loss” approach, by linking the LUCAS model of land-use and land-cover change with the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3). Results We estimated forest ecosystems in the conterminous United States stored 52.0 Pg C across all pools. Between 2001 and 2020, carbon storage increased by 2.4 Pg C at an annualized rate of 126 Tg C year −1 . Our results broadly agree with other studies using a variety of other methods to estimate the forest carbon sink. Climate variability and change was the primary driver of annual variability in the size of the net carbon sink, while land-use and land-cover change and disturbance were the primary drivers of the magnitude, reducing annual sink strength by 39%. Projections of carbon change under climate scenarios for the western U.S. find diverging estimates of carbon balance depending on the scenario. Under a moderate emissions scenario we estimated a 38% increase in the net sink of carbon, while under a high emissions scenario we estimated a reversal from a net sink to net source. Conclusions The new approach provides a fully coupled modeling framework capable of producing spatially explicit estimates of carbon stocks and fluxes under a range of historical and/or future socioeconomic, climate, and land management futures.

Continental United States↗

National assessment of carbon dioxide enhanced oil recovery and associated carbon dioxide retention resources — Results

In 2020, the U.S. Geological Survey (USGS) completed a probabilistic assessment of the volume of technically recoverable oil resources available if current carbon dioxide enhanced oil recovery (CO 2 -EOR) technologies were applied to amenable oil reservoirs underlying the onshore and State waters areas of the conterminous United States. The assessment also includes estimates of the mass of CO 2 that could be stored (retained) as a result of CO 2 -EOR activities. The USGS assessment team evaluated more than 3,500 oil reservoirs that were miscible to injected CO 2 . The assessed reservoirs are in 185 previously defined USGS plays in 33 petroleum provinces of 7 national regions. The assessment team estimated that the technically recoverable oil associated with CO 2 -EOR ranges from approximately 25,000 million barrels (MMbbl) at the P 5 percentile to as much as 32,000 MMbbl at the P 95 percentile, with a mean of 29,000 MMbbl. The associated CO 2 retention ranges from approximately 7,400 million metric tons (Mt) at the P 5 percentile to as much as 9,500 Mt at the P 95 percentile, with a mean of 8,400 Mt. The West Texas and Eastern New Mexico region and the Gulf Coast region together contain 60 percent of the mean assessed CO 2 -EOR oil potential and 61 percent of the mean assessed CO 2 retention. Other regions with significant resource potential include the Midcontinent region and Rocky Mountains and Northern Great Plains region.

Continental United States↗

National assessment of carbon dioxide enhanced oil recovery and associated carbon dioxide retention resources — Summary

Introduction In 2020, the U.S. Geological Survey (USGS) completed a probabilistic assessment of the volume of technically recoverable oil resources that might be produced by using current carbon dioxide enhanced oil recovery (CO 2 -EOR) technologies in amenable conventional oil reservoirs underlying the onshore and State waters areas of the conterminous United States. The assessment also includes estimates of the mass of CO 2 that could be stored (retained) in the assessed oil reservoirs following the application of the CO 2 -EOR process. The USGS assessment team evaluated more than 3,500 oil reservoirs that were miscible to injected CO 2 . The assessed reservoirs are in 185 previously defined USGS plays in 33 petroleum provinces of 7 national regions. The team estimated that the total technically recoverable oil resulting from the application of the CO 2 -EOR process ranges from approximately 25,000 million barrels (MMbbl) at the P 5 percentile to as much as 32,000 MMbbl at the P 95 percentile, with a mean of 29,000 MMbbl. The associated CO 2 retention ranges from approximately 7,400 million metric tons (Mt) at the P 5 percentile to as much as 9,500 Mt at the P 95 percentile, with a mean of 8,400 Mt. The results are summarized in this fact sheet and are provided in more detail in the companion data release and circular. The West Texas and Eastern New Mexico region (primarily its Permian Basin) and the Gulf Coast region together contain 60 percent of the mean assessed CO 2 -EOR oil potential and 61 percent of the mean assessed CO 2 retention. Other regions with significant resource potential include the Midcontinent region and the Rocky Mountains and Northern Great Plains region.

Continental United States↗

Pesticides and pesticide degradates in groundwater used for public supply across the United States: Occurrence and human-health context

This is the first assessment of groundwater from public-supply wells across the United States to analyze for >100 pesticide degradates and to provide human-health context for degradates without benchmarks. Samples from 1204 wells in aquifers representing 70% of the volume pumped for drinking supply were analyzed for 109 pesticides (active ingredients) and 116 degradates. Among the 41% of wells where pesticide compounds were detected, nearly two-thirds contained compound mixtures and three-quarters contained degradates. Atrazine, hexazinone, prometon, tebuthiuron, four atrazine degradates, and one metolachlor degradate were each detected in >5% of wells. Detection frequencies were largest for aquifers with more shallow, unconfined wells producing modern-age groundwater. To screen for potential human-health concerns, benchmark quotients (BQs) were calculated by dividing concentrations by the human-health benchmark, when available. For degradates without benchmarks, estimated values (estimated benchmark quotients (BQE)) were first calculated by assuming equimolar toxicity to the most toxic parent; final analysis excluded degradates with likely overestimated toxicity. Six pesticide compounds and 1.6% of wells had concentrations approaching levels of potential concern (individual or summed BQ or BQE values >0.1), and none exceeded these levels (values >1). Therefore, although pesticide compounds occurred frequently, concentrations were low, even accounting for mixtures and degradates without benchmarks.

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Batrachochytrium salamandrivorans (Bsal) not detected in an intensive survey of wild North American amphibians

The salamander chytrid fungus (Batrachochytrium salamandrivorans [Bsal]) is causing massive mortality of salamanders in Europe. The potential for spread via international trade into North America and the high diversity of salamanders has catalyzed concern about Bsal in the U.S. Surveillance programs for invading pathogens must initially meet challenges that include low rates of occurrence on the landscape, low prevalence at a site, and imperfect detection of the diagnostic tests. We implemented a large-scale survey to determine if Bsal was present in North America designed to target taxa and localities where Bsal was determined highest risk to be present based on species susceptibility and geography. Our analysis included a Bayesian model to estimate the probability of occurrence of Bsal given our prior knowledge of the occurrence and prevalence of the pathogen. We failed to detect Bsal in any of 11,189 samples from 594 sites in 223 counties within 35 U.S. states and one site in Mexico. Our modeling indicates that Bsal is highly unlikely to occur within wild amphibians in the U.S. and suggests that the best proactive response is to continue mitigation efforts against the introduction and establishment of the disease and to develop plans to reduce impacts should Bsal establish.

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Identifying important military installations for continental-scale conservation of marsh bird breeding habitat

Degradation of wetland ecosystems has negatively impacted many species, perhaps none more so than marsh birds that breed in vegetative emergent wetlands throughout North America. The U.S. Department of Defense manages approximately 29 million acres of land within the continental U.S., and many military installations contain wetland complexes that may be important for wetland birds. Thus, failure to adequately manage habitat for marsh birds could result in species extirpations and additional listings under the Endangered Species Act, and may result in regulatory burdens that reduce military readiness. We conducted spatial analyses to identify important breeding habitat on > 500 military installations for 12 species of marsh birds, with the goal of identifying installations that are, and are not, likely to harbor breeding habitat for each species. We also sought to assess the local value of military installations for species of greatest concern by comparing habitat suitability within installations to that in areas directly adjacent to those sites. We built range-wide, spatially-explicit models of species distribution to project suitability of breeding habitat for marsh birds within and adjacent to military installations. Our results demonstrate that installations with the best marsh bird habitat are geographically aggregated (both among and within species), primarily at sites along the eastern seaboard and within the southern U.S. In addition, only a few sites appear to contain high-quality habitat for most species. Five or fewer sites contained most of the high-quality habitat for 9 of 12 species, whereas most of the high-quality habitat for remaining species was found at ≤ 10 sites. This work fills an information gap regarding the distribution of breeding habitat for marsh birds on military lands across the U.S., and should facilitate both strategic conservation of habitat over broad scales and the integration of marsh birds into management efforts at the site level. Our analyses also identify installations that are not likely to harbor breeding habitat for priority species, and thus should help minimize conflicts between needs of the military and marsh-bird conservation.

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Paired air-water annual temperature patterns reveal hydrogeological controls on stream thermal regimes at watershed to continental scales

Despite decades of research into air and stream temperature dynamics, paired air-water annual temperature signals have been underutilized to characterize watershed processes. Annual stream temperature dynamics are useful in classifying fundamental thermal regimes and can enhance process-based interpretation of stream temperature controls, including deep and shallow groundwater discharge, when paired with air signals. In this study, we investigated multi-scale variability in annual paired air-water temperature patterns using sine-wave linear regressions of multi-year daily temperature data from streams of various sizes. A total of 311 sites from two spatially intensive regional datasets (Shenandoah National Park and Olympic Experimental State Forest) and a spatially extensive national dataset spanning the contiguous United States (U.S. Geological Survey gages) were evaluated. We calculated three annual air-water thermal metrics (mean ratio, phase lag, and amplitude ratio) to deduce the influence of groundwater and other watershed processes on stream thermal regimes at multiple spatial scales. Site-specific values of the three annual air-water thermal metrics ranged from 0.69 to 5.29 (mean ratio), −9 to 40 days (phase lag), and 0.29 to 1.12 (amplitude ratio). Regional patterns in the annual thermal metrics revealed persistent yet spatially variable influences of shallow groundwater discharge and high levels of thermal variability within watersheds, indicating the importance of local hydrogeological controls on stream temperature. Furthermore, annual thermal metric patterns from the regional datasets were generally concordant with the national dataset suggesting the utility of these annual thermal metrics for analysis at multiple scales. Analysis of the national dataset showed that previously defined thermal regimes based on water temperature alone could be further refined using air-water metrics and these metrics were related to physiographic watershed characteristics such as contributing area, elevation, and slope. This research demonstrates the importance of spatial scale and heterogeneity for inferring hydrological process in streams and provides guidance for the interpretation of annual air-water temperature metrics that can be efficiently applied to the growing database of multi-year temperature records. Results from this research can aid in the prediction of future thermal habitat suitability for coldwater-adapted species at ecologically and management-relevant spatial scales with readily available data.

Continental United States↗

An updated stress map of the continental U.S. reveals heterogeneous intraplate stress

Knowledge of the state of stress in the Earth’s crust is key to understanding the forces and processes responsible for earthquakes. Historically, low rates of natural seismicity in the central and eastern United States have complicated efforts to understand intraplate stress, but recent improvements in seismic networks and the spread of human-induced seismicity have greatly improved data coverage. Here we compile a nationwide stress map based on formal inversions of focal mechanisms that challenges the idea that deformation in continental interiors is driven primarily by broad, uniform stress fields derived from distant plate boundaries. Despite plate-boundary compression, extension dominates roughly half of the continent, and second-order forces related to lithospheric structure appear to control extension directions. We also show that the states of stress in several active eastern United States seismic zones differ significantly from surrounding areas and that these anomalies cannot be explained by transient processes, suggesting that earthquakes are focused by persistent, locally-derived sources of stress. Such spatially variable intraplate stress appears to justify the current, spatially variable estimates of seismic hazard. Future work to quantify sources of stress, stressing-rate magnitudes, and their relationship with strain and earthquake rates could allow prospective mapping of intraplate hazard.

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Multi-regional synthesis of temporal trends in biotic assemblages in streams and rivers of the continental United States

Biotic assemblages in aquatic ecosystems are excellent integrators and indicators of changing environmental conditions within a watershed. Therefore, temporal changes in abiotic environmental variables often can be inferred from temporal changes in biotic assemblages. Algae, macroinvertebrate, and fish assemblage data were collected from 91 sampling sites in 4 geographic regions (northeastern/north-central, southeastern, south-central, and western), collectively encompassing the continental United States, from 1993 to 2009 as part of the U.S. Geological Survey National Water-Quality Assessment Program. This report uses a multivariate approach to synthesize temporal trends in biotic assemblages and correlations with relevant abiotic parameters as a function of biotic assemblage, geographic region, and land use. Of the three groups of biota, algal assemblages had temporal trends at the greatest percentage of sites. Of the regions, a greater percentage of sites in the northeastern/north-central and western regions had temporal trends in biotic assemblages. In terms of land use, a greater percentage of watersheds draining agricultural, urban, and undeveloped areas had significant temporal changes in biota, as compared to watersheds with mixed use. Correlations between biotic assemblages and abiotic variables indicate that, in general, macroinvertebrate assemblages correlated with water quality and fish assemblages correlated with physical habitat. Taken together, results indicate that there are regional differences in how individual biotic assemblages (algae, macroinvertebrates, and fish) respond to different abiotic drivers of change.

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Land subsidence in the United States

This report explores the role of science in defining and understanding subsidence problems, and shows that the optimal use of our land and water resources may depend on improved scientific understanding to minimize subsidence. More than 80 percent of the identified land subsidence in the Nation is a consequence of human impact on subsurface water, and is an often overlooked environmental consequence of our land- and water-use practices. Nine illustrative case studies demonstrate the role of subsurface water in human-induced land subsidence. These studies represent three distinct processes that account for most of the water-related subsidence--compaction of aquifer systems, drainage and subsequent oxidation of organic soils, and dissolution and collapse of susceptible rocks. The compaction of alluvial aquifer systems that can accompany excessive ground-water pumping and resulting ground-water level declines is, by far, the single largest cause of subsidence.

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