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Research about conterminous United States

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

At least 109 records · Page 6Linked to original sources

Assessing direct and indirect long-term economic impacts from earthquakes to the U.S. National Bridge Inventory

Using the 2018 National Seismic Hazard Model and the 2018 National Bridge Inventory, an annualized earthquake loss (AEL) study was conducted for approximately 610,000 bridges in the conterminous United States, quantifying both direct and indirect economic losses. The typical AEL framework has been augmented with new replacement unit cost data and bridge-specific parameters for modifying default fragility curves. Earthquake hazard is defined using spectral acceleration hazard curves that account for location-specific soil conditions. Hazard is integrated with bridge-specific fragility curves to compute annual probabilities of exceeding various damage states. Further, economic loss for each bridge was estimated using the repair costs associated with specific damage states and indirect costs incurred from downtimes. Quantitative assessments of seismic risk, especially those that account for downtime-related impacts, enable us to illustrate the distribution of risk with respect to geographic region, era of construction, or type of bridge.

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Mercury in soils of the conterminous United States: Patterns and pools

Soils account for the largest global mercury reservoirs, but observations are sparse in many regions. The accumulation and turnover of mercury in soils determines whether they act as an atmospheric source or sink. Here, we present a spatial analysis of soil mercury from a large soil survey (three horizons, ∼4800 sites) across the conterminous United States conducted by the U.S. Geological Survey. Soil mercury pools were calculated for 11 layers, cumulatively representing the top 1 m of soil, and totaling 158 ± 2 Gg (±SD) of mercury (20.3 ± 0.2 mg m −2 ). Mercury areal density was greatest in mixed forest (27.3 ± 0.5 mg m −2 ), cropland (25.3 ± 0.3 mg m −2 ), and deciduous forest (25.6 ± 0.5 mg m −2 ) ecosystems and lowest in barren (13.5 ± 0.3 mg m −2 ) and shrubland (12.6 ± 0.2 mg m −2 ) ecosystems. Assessment of the provenance of soil mercury using bedrock titanium normalization suggests that 62%–95% of soil mercury is unexplained by parental sources.

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Strength and memory of precipitation's control over streamflow across the conterminous United States

How precipitation (P) is translated into streamflow (Q) and over what timescales (i.e., “memory”) is difficult to predict without calibration of site-specific models or using geochemical approaches, posing barriers to prediction in ungauged basins or advancement of general theories. Here, we used a data-driven approach to identify regional patterns and exogenous controls on P–Q interactions. We applied an information flow analysis, which quantifies uncertainty reduction, to a daily time series of P and Q from 671 watersheds across the conterminous United States. We first demonstrated that information transfer from P to Q primarily reflects the quickflow component of water-budgets, based on a watershed model. Readily quantifiable information flows show a functional relationship with model parameters, suggesting utility for model calibration. Second, applied to real watersheds, P–Q information flows exhibit seasonally varying behavior within regions in a manner consistent with dominant runoff generation mechanisms. However, the timing and the magnitude of information flows also reflect considerable subregional heterogeneity, likely attributable to differences in watershed size, baseflow contributions, and variation in aerial coverage of preferential flow paths. A regression analysis showed that a combination of climate and watershed characteristics are predictive of P–Q information flows. Though information flows cannot, in most cases, uniquely determine dominant runoff mechanisms, they provide a means to quantify the heterogeneous outcomes of those mechanisms within regions, thereby serving as a benchmarking tool for models developed at the regional scale. Last, information flows characterize regionally specific ways in which catchment connectivity changes from the wet to dry season.

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Assessment of carbon dioxide enhanced oil recovery and associated carbon dioxide retention resources of the United States

In 2020, the U.S. Geological Survey (USGS) completed a probabilistic assessment of the volume of technically recoverable oil resources that could be produced using current carbon dioxide enhanced oil recovery (CO2-EOR) technologies in amenable conventional oil reservoirs underlying onshore and State-owned offshore waters (herein after, onshore and State waters areas) of the conterminous United States. Our assessment also includes estimates of the mass of CO2 that could be stored (retained) in the assessed oil reservoirs following the application of the CO2-EOR process. The USGS assessment team evaluated more than 3,500 oil reservoirs that were amenable to miscible CO2 injection. The assessed reservoirs are located in 185 plays previously defined by a USGS National Oil and Gas Assessment in 33 petroleum provinces of seven national regions. The team estimated that the total technically recoverable oil resulting from the application of the CO2-EOR process ranges from approximately 25,000 million barrels (MMbbl) at the P5 probability percentile to as much as 32,000 MMbbl at the P95 probability percentile, with a mean of 29,000 MMbbl. The associated CO2 retention ranges from approximately 7,400 million metric tons (Mt) at the P5 percentile to as much as 9,500 Mt at the P95 percentile, with a mean of 8,400 Mt.

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A CONUS-scale study of wildfire and evapotranspiration: Spatial and temporal response and controlling factors

Evapotranspiration (ET) accounts for a substantial portion of regional water budgets in much of the southeast and fire-prone western United States (US). Even small changes in ET rates can translate to meaningful shifts in runoff patterns and makes forecasting the direction and magnitude of wildfire-induced ET alteration of critical importance. We use 1 km ET estimates from the operational Simplified Surface Energy Balance (SSEBop) product for the conterminous US (CONUS) to evaluate post-fire ET and evaporation ratio (ET/P) shifts in the first five post-fire years in approximately 5500 unique fires. Pixels with similar ET/P responses to fire are grouped through k-means clustering and the resultant cluster distribution is explored over space and time. The largest changes in post-fire ET/P are observed in the southwestern CONUS where first-year ratios are reduced by 50 to 90% and pre-fire ratios are rarely recovered by post-fire year five. Regional and intra-fire ET/P response variability is also highest in the western CONUS where climatic, topographic, and ecologic gradients are steep. Post-fire ET/P modifications are small to negligible in the east-southeast CONUS, and 18% of all pixels analyzed exhibit small to moderate increases in post-fire year one ET/P. A comparison of burned and unburned pixel pairs confirms the role of fire in the shifts but also indicates a high degree of background variability in the ET and precipitation data. Although the biggest percent ET/P reductions occur in shrub/scrub landscapes in much of the west, the biggest magnitude ET changes often occur in evergreen forests. Higher burn severities are consistently correlated with greater post-fire ET/P reductions, while relationships between post-fire ET/P shifts and numerous other landscape attributes (e.g., pre-fire vegetation type) vary in both direction and magnitude in different parts of the CONUS. Further work can be conducted to refine controlling relationships within more homogeneous sub-regions.

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Earthquake risk of gas pipelines in the conterminous United States and its sources of uncertainty

Relatively little research has been conducted to systematically quantify the nationwide earthquake risk of gas pipelines in the US; simultaneously, national guidance is limited for operators across the country to consistently evaluate the earthquake risk of their assets. Furthermore, many challenges and uncertainties exist in a comprehensive seismic risk assessment of gas pipelines. As a first stage in a systematic nationwide assessment, we quantify the earthquake risk of gas transmission pipelines in the conterminous US due to strong ground shaking, including the associated uncertainties. Specifically, we integrate the US Geological Survey 2018 National Seismic Hazard Model, a logic tree–based exposure model, three different vulnerability models, and a consequence model. The results enable comparison against other risk assessment efforts, encourage more transparent deliberation regarding alternative approaches, and facilitate decisions on potentially assessing localized risks due to ground failures that require site-specific data. Based on the uncertainties approximated herein, the resulting sensitivity analyses suggest that the vulnerability model is the most influential source of uncertainty. Finally, we highlight research needs such as (1) developing more vulnerability models for regional seismic risk assessment of gas pipelines; (2) identifying, prioritizing, and measuring input pipeline attributes that are important for estimating seismic damage; and (3) better quantifying seismic hazards with their uncertainties at the national scale, for both ground failures and ground shaking.

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2018 and 2023 U. S. National Seismic Hazard Models

During 2017-2018, the National Seismic Hazard Model (NSHM) was updated by incorporating (1) new median ground motion models, new estimates of their epistemic uncertainties and aleatory variabilities, and new soil amplification factors for the central and eastern U.S., (2) amplification of long-period ground motions in deep sedimentary basins in the Los Angeles, San Francisco, Seattle, and Salt Lake City areas, (3) an updated seismicity catalog, which includes new earthquakes that occurred between 2012 and 2017, and (4) improved computer code and implementation details. Results show significantly increased ground shaking in many (but not all) locations across the central and eastern U.S., and increased ground shaking in the four urban areas (listed above) that overlie deep sedimentary basins in the western U.S. During 2019-2023, the NSHM will consider additional updates for the 2023 NSHM including: 3D simulations in urban areas of Los Angeles and Seattle, additional soil amplification models for other urban areas (e.g., eastern and southern coastal plains of the U.S., Reno, and Las Vegas), non-ergodic ground motion models that reconsider epistemic and aleatory uncertainty, topographic amplification, and new geological and geodetic models for faults. These maps will be considered by the Building Seismic Safety Council, American Society of Civil Engineers, and International Building Code committees for inclusion in upcoming building codes. Due to population growth, more people live and work in areas of moderate or high seismic hazard than ever before, leading to higher risk of undesirable consequences from future ground shaking.

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Advances in quantifying streamflow variability across continental scales: 1. Identifying natural and anthropogenic controlling factors in the USA using a spatially explicit modeling method

Despite considerable progress in hydrological modeling, challenges remain in the interpretation and accurate transfer of hydrological information across watersheds and scales. In the conterminous United States (CONUS), these limitations are related to spatial inconsistencies and constraints in hydrological model structures, including a lack of spatially explicit process components (streams, reservoirs, and watershed development) and restricted estimation of model parameters across watersheds. Collectively, such limitations can impede identification of the causes of streamflow variations across the diversity of watershed sizes and land uses in the CONUS and contribute to model imprecision and spatial inconsistencies in prediction uncertainties. We addressed these concerns with a new approach, the first hybrid (statistical-mechanistic) SPARROW (SPAtially Referenced Regression On Watershed attributes) model of long-term mean annual streamflow, applied across diverse environmental settings of the CONUS. The hybrid model coupled previous catchment-scale (1 km) water balance predictions of “natural” unit area runoff, which are inclusive of major water cycling processes, with additional explanatory variables (e.g., soils, vegetation, land use, topography, water losses in streams, and reservoirs) that account for the effects of natural and cultural water supply and demand processes that operate over large spatial scales and explain streamflow variability across CONUS river basins. Accounting for these statistically unique effects, including a nonlinear surface area-dependent scaling of water loss in river networks, significantly improved the accuracy of mean streamflow predictions in CONUS basins. Our hybrid modeling approach provides new methods for transferring hydrological information to ungauged locations in river networks, especially those in larger and more culturally diverse CONUS watersheds.

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Estimation of base flow by optimal hydrograph separation for the conterminous United States and implications for national-extent hydrologic models

Optimal hydrograph separation (OHS) uses a two-parameter recursive digital filter that applies specific conductance mass-balance constraints to estimate the base flow contribution to total streamflow at stream gages where discharge and specific conductance are measured. OHS was applied to U.S. Geological Survey (USGS) stream gages across the conterminous United States to examine the range/distribution of base flow inputs and the utility of this method to build a hydrologic model calibration dataset. OHS models with acceptable goodness-of-fit criteria were insensitive to drainage area, stream density, watershed slope, elevation, agricultural or perennial snow/ice land cover, average annual precipitation, runoff, or evapotranspiration, implying that OHS results are a viable calibration dataset applicable in diverse watersheds. OHS-estimated base flow contribution was compared to base flow-like model components from the USGS National Hydrologic Model Infrastructure run with the Precipitation-Runoff Modeling System (NHM-PRMS). The NHM-PRMS variable gwres_flow is most conceptually like a base flow component of streamflow but the gwres_flow contribution to total streamflow is generally smaller than the OHS-estimated base flow contribution. The NHM-PRMS variable slow_flow , added to gwres_flow , produced similar or greater estimates of base flow contributions to total streamflow than the OHS-estimated base flow contribution but was dependent on the total flow magnitude.

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Mapping irrigated cropland extent across the conterminous United States at 30 m resolution using a semi-automatic training approach on Google Earth Engine

Accurate and timely information on the distribution of irrigated croplands is crucial to research on agriculture, water availability, land use, and climate change. While agricultural land use has been well characterized, less attention has been paid specifically to croplands that are irrigated, in part due to the difficulty in mapping and distinguishing irrigation in satellite imagery. In this study, we developed a semi-automatic training approach to rapidly map irrigated croplands across the conterminous United States (CONUS) at 30 m resolution using Google Earth Engine. To resolve the issue of lacking nationwide training data, we generated two intermediate irrigation maps by segmenting Landsat-derived annual maximum greenness and enhanced vegetation index using county-level thresholds calibrated from an existing coarse resolution irrigation map. The resulting intermediate maps were then spatially filtered to provide a training data pool for most areas except for the upper midwestern states where we visually collected samples. We then used random samples extracted from the training pool along with remote sensing-derived features and climate variables to train ecoregion-stratified random forest classifiers for pixel-level classification. For ecoregions with a large training pool, the procedure of sample extraction, classifier training, and classification was conducted 10 times to obtain stable classification results. The resulting 2012 Landsat-based irrigation dataset (LANID) identified 23.3 million hectares of irrigated croplands in CONUS. A quantitative assessment of LANID showed superior accuracy to currently available maps, with a mean Kappa value of 0.88 (0.75–0.99), overall accuracy of 94% (87.5–99%), and producer’s and user’s accuracy of the irrigation class of 97.3% and 90.5%, respectively, at the aquifer level. Evaluation of feature importance indicated that Landsat-derived features played the primary role in classification in relatively arid regions while climate variables were important in the more humid eastern states. This methodology has the potential to produce annual irrigation maps for CONUS and provide insights into the field-level spatial and temporal aspects of irrigation.

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Zinc isotopic signatures in eight lake sediment cores from across the United States

Zinc is an important trace element pollutant in urban environments; however, the extent of Zn contamination and the sources of urban Zn pollution are often unclear. We measured Zn concentrations and isotopes in sediment cores collected from eight lakes or reservoirs across the United States. We paired these data with historical records of land use within each watershed to calculate a mean Zn concentration and δ 66 Zn for natural (less than 5% urban land use; 123 ± 21.7 mg/kg; +0.33 ± 0.08‰, n = 6 lakes) and urban (greater than 70% urban land use; 389 ± 200 mg/kg; +0.14 ± 0.07‰, n = 3 lakes) lake sediments. The relation between Zn concentration data and Zn isotope data allows us to create a mixing model between two end members: natural and urban. The δ 66 Zn of the urban end-member is consistent with Zn pollution from vehicle-related sources (tire wear and emissions). Application of this model to samples collected from lakes recording periods ranging from 5 to 70% urban land use in their surrounding watersheds indicates that the lakes and reservoirs were affected by large amounts of Zn from urban sources.

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The quality of our Nation’s waters--Ecological health in the Nation's streams, 1993-2005

This report summarizes a national assessment of the ecological health of streams done by the U.S. Geological Survey's (USGS) National Water-Quality Assessment Program (NAWQA). Healthy functioning stream ecosystems provide society with many benefits, including water purification, flood control, nutrient recycling, waste decomposition, fisheries, and aesthetics. The value to society of many of these benefits is substantial; for example, sportfishing in the United States generates an estimated annual economic output of $125 billion, including more than 1 million jobs (National Research Council, 2005; American Sportfishing Association, 2008). Continued monitoring and assessment of the Nation’s streams is needed to support informed decisions that will safeguard this important natural and economic resource. The quality of streams and rivers is often assessed with measures of the chemical or physical properties of water. However, a more comprehensive perspective is obtained if resident biological communities are also assessed. Guidelines to protect human health and aquatic life have been established for specific physical and chemical properties of water and have become useful yardsticks with which to assess water quality. Biological communities provide additional crucial information because they live within streams for weeks to years and therefore integrate through time the effects of changes to their chemical or physical environment. In addition, biological communities are a direct measure of stream health—an indicator of the ability of a stream to support aquatic life. Thus, the condition of biological communities, integrated with key physical and chemical properties, provides a comprehensive assessment of stream health.

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County-level estimates of nutrient inputs to the land surface of the conterminous United States, 1982-2001

Nutrient input data for fertilizer use, livestock manure, and atmospheric deposition from various sources were estimated and allocated to counties in the conterminous United States for the years 1982 through 2001. These nationally consistent nutrient input data are needed by the National Water-Quality Assessment Program for investigations of stream- and ground-water quality. For nitrogen, the largest source was farm fertilizer; for phosphorus, the largest sources were farm fertilizer and livestock manure. Nutrient inputs from fertilizer use in nonfarm areas, while locally important, were an order of magnitude smaller than inputs from other sources. Nutrient inputs from all sources increased between 1987 and 1997, but the relative proportions of nutrients from each source were constant. Farm-fertilizer inputs were highest in the upper Midwest, along eastern coastal areas, and in irrigated areas of the West. Nonfarm-fertilizer use was similar in major metropolitan areas throughout the Nation, but was more extensive in the more populated Eastern and Central States and in California. Areas of greater manure inputs were located throughout the South-central and Southeastern States and in scattered areas of the West. Nitrogen deposition from the atmosphere generally increased from west to east and is related to the location of major sources and the effects of precipitation and prevailing winds. These nutrient-loading data at the county level are expected to be the fundamental basis for national and regional assessments of water quality for the National Water-Quality Assessment Program and other large-scale programs.

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Development of a circa 2000 land cover database for the United States

Multi-Resolution Land Characterization 2000 (MRLC 2000) is a second-generation federal consortium to create an updated pool of nation-wide Landsat 7 imagery, and derive a second-generation National Land Cover Database (NLCD 2000). This multi-layer, multisource database will include a suite of 30-meter resolution data that will serve as standardized ingredients for the production of land cover – both nationally and locally. This database will also provide the framework to allow flexibility in developing and applying suites of independent data layers. These nationally standardized independent data layers or components, will be useful not only within the land-cover classification but as data themes for other applications. This database will consist of the following components: (1) normalized tasseled cap (TC) transformations of Landsat 7 imagery for three time periods per scene (early, peak and late), (2) ancillary data layers, including 30m DEM derivatives of slope, aspect and elevation and three STATSCO soil derivatives, (4) image shape and texture information, (5) image derivatives of percent imperviousness and percent tree canopy per-pixel, (6) classified land-cover data derived from the Tassel Capped imagery, ancillary data and derivatives, (7) classification rules and metadata from the land cover classification, allowing future users the potential to modify rules to derive land cover products tailored to their specific local applications. In a pilot study application of the database concept, two mapping zones (Utah and Virginia) were selected for full generation of the above data components. Three derivative layers including, per-pixel imperviousness, per-pixel canopy and land cover were classified from the database. Cross validation accuracies for land cover ranged from 65-82%, and mean absolute error values of 10-15% were reported for percent tree canopy and imperviousness.

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Profiles of gamma-ray and magnetic data from aerial surveys over the conterminous United States

This publication contains images for the conterminous U.S. generated from geophysical data, software for displaying and analyzing the images, and software for displaying and examining the profile data from the aerial surveys flown as part of the National Uranium Resource Evaluation (NURE) Program of the U.S. Department of Energy. The images included are of gamma-ray data (uranium, thorium, and potassium channels), Bouguer gravity data, isostatic residual gravity data, aeromagnetic anomalies, topography, and topography with bathymetry.

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Explaining spatial variability in mean annual runoff in the conterminous United States

The hydrologic concepts needed in a water-balance model to estimate the spatial variation in mean annual runoff for the 344 climate divisions in the conterminous United States (U.S.) were determined. The concepts that were evaluated were the climatic supply of water (precipitation), climatic demand for water (potential evapotranspiration), seasonality in supply and demand, and soil-moisture-storage capacity. Most (91%) of the spatial variability in mean annual runoff for the climate divisions in the conterminous U.S. was explained by the spatial variability of mean annual precipitation minus mean annual potential evapotranspiration. When soil-moisture-storage capacity and seasonality in supply and demand were added to the water balance, the explained variance in mean annual runoff increased slightly, and the error in estimated mean annual runoff decreased significantly. Adding soil-moisture-storage capacity and seasonality in supply and demand provided the most improvement in areas where seasonal supply and demand are out of phase.

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