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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 973 records · Page 54Linked to original sources
USGS2011

Migratory flyway and geographical distance are barriers to the gene flow of influenza virus among North American birds

Despite the importance of migratory birds in the ecology and evolution of avian influenza virus (AIV), there is a lack of information on the patterns of AIV spread at the intra‐continental scale. We applied a variety of statistical phylogeographic techniques to a plethora of viral genome sequence data to determine the strength, pattern and determinants of gene flow in AIV sampled from wild birds in North America. These analyses revealed a clear isolation‐by‐distance of AIV among sampling localities. In addition, we show that phylogeographic models incorporating information on the avian flyway of sampling proved a better fit to the observed sequence data than those specifying homogeneous or random rates of gene flow among localities. In sum, these data strongly suggest that the intra‐continental spread of AIV by migratory birds is subject to major ecological barriers, including spatial distance and avian flyway.

California, Oregon, Washington↗
USGS2024

Regional seismic velocity model for the U.S. Atlantic and Gulf Coastal Plains based on measured shear wave velocity, sediment thickness, and surface geology

The Atlantic and Gulf Coastal Plains (CPs) are characterized by widespread accumulations of low-velocity sediments and sedimentary rock that overlay high-velocity bedrock. Geology and sediment thickness greatly influence seismic wave propagation, but current regional ground motion amplification and seismic hazard models include limited characterization of these site conditions. In this study, a new regional seismic velocity model for the CPs is created by integrating shear wave velocity (V S ) measurements, surface geology, and a sediment thickness model recently developed for the CPs. A reference rock V S of 3000 m/s has been assumed at the bottom of the sedimentary columns, which corresponds to the base of Cretaceous and Mesozoic sediments underlying the Atlantic CP and the Gulf CP, respectively. Measured V S profiles located throughout the CPs are sorted into five geologic groups of varying age, and median V S profiles are developed for each group by combining measured V S values within layer thicknesses defined by an assumed layering ratio. Statistical analyses are also conducted to test the appropriateness of the selected groups. A power law model with geology-informed coefficients is used to extend the median velocity models beyond the depths where measured data were available. The median V S profiles provide reasonable agreement with other generic models applicable for the region, but they also incorporate new information that enables more advanced characterizations of site response at regional scales and their effective incorporation into seismic hazard models and building codes. The proposed median velocity profiles can be assigned within a grid-based model of the CPs according to the spatial distribution of geologic units at the surface.

Earthquake Spectra↗
USGS2024

Forecasting storm-induced coastal flooding for 21st century sea-level rise scenarios in the Hawaiian, Mariana, and American Samoan Islands

Oceanographic, coastal engineering, ecologic, and geospatial data and tools were combined to evaluate the increased risks of storm-induced coastal flooding in the populated Hawaiian, Mariana, and American Samoan Islands as a result of climate change and sea-level rise. We followed a hybrid (dynamical and statistical) downscaling approach to map flooding due to waves and storm surge at 10-square meter resolution along all 1,870 kilometers of these islands’ coastlines for annual (1-year), 20-year, and 100-year return-interval storm events and +0.00 meter (m), +0.25 m, +0.50 m, +1.00 m, +1.50 m, +2.00 m, and +3.00 m sea-level rise scenarios. We quantified the coastal flood depths and extents using the latest climate forcing from Intergovernmental Panel for Climate Change’s Sixth Assessment Report Coupled Model Intercomparison Project. The data generated using these methods provide stakeholders and decision makers with a spatially explicit, rigorous valuation of how, where, and when climate change and sea-level rise increase coastal storm-induced flooding to help identify areas where management and (or) restoration could potentially help reduce the risk to, and increase the resiliency of, the coastal communities in the populated Hawaiian, Mariana, and American Samoan Islands.

Hawaii↗
USGS2014

Delineation of marsh types of the Texas coast from Corpus Christi Bay to the Sabine River in 2010

Coastal zone managers and researchers often require detailed information regarding emergent marsh vegetation types for modeling habitat capacities and needs of marsh-reliant wildlife (such as waterfowl and alligator). Detailed information on the extent and distribution of marsh vegetation zones throughout the Texas coast has been historically unavailable. In response, the U.S. Geological Survey, in cooperation and collaboration with the U.S. Fish and Wildlife Service via the Gulf Coast Joint Venture, Texas A&M University-Kingsville, the University of Louisiana-Lafayette, and Ducks Unlimited, Inc., has produced a classification of marsh vegetation types along the middle and upper Texas coast from Corpus Christi Bay to the Sabine River. This study incorporates approximately 1,000 ground reference locations collected via helicopter surveys in coastal marsh areas and about 2,000 supplemental locations from fresh marsh, water, and “other” (that is, nonmarsh) areas. About two-thirds of these data were used for training, and about one-third were used for assessing accuracy. Decision-tree analyses using Rulequest See5 were used to classify emergent marsh vegetation types by using these data, multitemporal satellite-based multispectral imagery from 2009 to 2011, a bare-earth digital elevation model (DEM) based on airborne light detection and ranging (lidar), alternative contemporary land cover classifications, and other spatially explicit variables believed to be important for delineating the extent and distribution of marsh vegetation communities. Image objects were generated from segmentation of high-resolution airborne imagery acquired in 2010 and were used to refine the classification. The classification is dated 2010 because the year is both the midpoint of the multitemporal satellite-based imagery (2009–11) classified and the date of the high-resolution airborne imagery that was used to develop image objects. Overall accuracy corrected for bias (accuracy estimate incorporates true marginal proportions) was 91 percent (95 percent confidence interval [CI]: 89.2–92.8), with a kappa statistic of 0.79 (95 percent CI: 0.77–0.81). The classification performed best for saline marsh (user’s accuracy 81.5 percent; producer’s accuracy corrected for bias 62.9 percent) but showed a lesser ability to discriminate intermediate marsh (user’s accuracy 47.7 percent; producer’s accuracy corrected for bias 49.5 percent). Because of confusion in intermediate and brackish marsh classes, an alternative classification containing only three marsh types was created in which intermediate and brackish marshes were combined into a single class. Image objects were reattributed by using this alternative three-marsh-type classification. Overall accuracy, corrected for bias, of this more general classification was 92.4 percent (95 percent CI: 90.7–94.2), and the kappa statistic was 0.83 (95 percent CI: 0.81–0.85). Mean user’s accuracy for marshes within the four-marsh-type and three-marsh-type classifications was 65.4 percent and 75.6 percent, respectively, whereas mean producer’s accuracy was 56.7 percent and 65.1 percent, respectively. This study provides a more objective and repeatable method for classifying marsh types of the middle and upper Texas coast at an extent and greater level of detail than previously available for the study area. The seamless classification produced through this work is now available to help State agencies (such as the Texas Parks and Wildlife Department) and landscape-scale conservation partnerships (such as the Gulf Coast Prairie Landscape Conservation Cooperative and the Gulf Coast Joint Venture) to develop and (or) refine conservation plans targeting priority natural resources. Moreover, these data may improve projections of landscape change and serve as a baseline for monitoring future changes resulting from chronic and episodic stressors.

Texas↗
USGS1994

Permeability of soils in Mississippi

The permeability of soils in Mississippi was determined and mapped using a geographic information system (GIS). Soil permeabilities in Mississippi were determined to range in value from nearly 0.0 to values exceeding 5.0 inches per hour. The U.S. Soil Conservation Service's State Soil Geographic Data Base (STATSGO) was used as the primary source of data for the determination of area-weighted soil permeability. STATSGO provides soil layer properties that are spatially referenced to mapped areas. These mapped areas are referred to as polygons in the GIS. The polygons arc boundaries of soils mapped as a group and are given unique Map Unit Identifiers (MUIDs). The data describing the physical characteristics of the soils within each polygon are stored in a tabular data base format and are referred to as attributes. The U.S. Soil Conservation Service developed STATSGO to be primarily used as a guide for regional resource planning, management, and monitoring. STATSGO was designed so that soil information could be extracted from properties tables at the layer level, combined by component, and statistically expanded to cover the entire map unit. The results of this study provide a mapped value for permeability which is representative of the vertical permeability of soils in that area. The resultant permeability map provides a representative vertical soil permeability for a given area sufficient for county, multi- county, and area planning, and will be used as the soil permeability data component in the evaluation of the susceptibility of major aquifers to contami- nation in Mississippi.

Water-Resources Investigations Report↗
USGS2023

Initial comparison of pollen counting methods using precipitation and ambient air samples and automated artificial intelligence to support national monitoring objectives

Given the endemic nature of pollen throughout the environment, the impact upon human health, and the need for more extensive and better measurements of pollen in the USA, a preliminary project within the National Atmospheric Deposition Program’s (NADP) National Trends Network (NTN) was developed. Pollen was measured in ambient air by several methods and in precipitation wet deposition samples at three monitoring sites in the NTN. A method for counting pollen on filters was developed and provided pollen counts for NADP atmospheric wet-deposition samples and high-volume ambient air samplers (HVAS) for comparison with co-located traditional National Allergy Bureau microscopy samples and a commercially available pollen sensor (PS) counting method during the 2021 pollen season. The goals of this project were to test the potential of available air-monitoring infrastructures to obtain improved spatial measurements of aeroallergens, compare pollen counting results from the various methods, and to determine the suitability of using wet deposition samples for pollen collection. The onset and senescence of pollen seasons for general categories of genera compared favorably for each method at each site, indicating that pollen monitoring using wet-deposition and ambient air sampling filters could provide useful information to inform scientific studies, but not likely for public health objectives. Pollen counts were log transformed for Pearson product moment correlation. Tree pollen counts were correlated at all sites for daily PS data and traditional counting data ( R = 0.69–0.84), but statistical correlations between methods for grass and weed pollen were weak (0.40 < R < 0.60) or considered not correlated ( R < 0.40). Total pollen counts in NADP precipitation samples were correlated with traditional and PS counts at only one of three sites. Pollen counts for the weekly HVAS filter samples were correlated with PS counts for trees ( R = 0.62) and with NAB counts for trees ( R = 0.68) and weeds ( R = 0.72). Correlations in the data between methods suggest that, given further methods development, a variety of techniques could be integrated to expand and enhance existing pollen monitoring networks. Improved ambient air and atmospheric deposition sampling methods specifically targeted for pollen capture and analysis could support the collection of accurate and efficient meaningful aeroallergen data from existing atmospheric monitoring networks.

Aerobiologia↗
USGS2016

Low soil moisture during hot periods drives apparent negative temperature sensitivity of soil respiration in a dryland ecosystem: A multi-model comparison

Arid and semiarid ecosystems (drylands) may dominate the trajectory of biosphere-to-atmosphere carbon (C) exchange, and understanding dryland CO 2 efflux is important for C cycling at the global-scale. However, unknowns remain regarding how temperature and moisture interact to regulate dryland soil respiration ( R s ), while ‘islands of fertility’ in drylands create spatially heterogeneous R s . At a site in southeastern Utah, USA we added or removed litter (0–650 % of control) in plots associated with either shrubs or biological soil crust-dominated interspaces between vascular plants. We measured R s , soil temperature (T s ), and water content (θ) repeatedly from October 2013 to November 2014. R s was highest following rain in late summer at T s ~30 °C, and lowest mid-summer at T s > 40 °C, resulting in apparent negative temperature sensitivity of R s at high temperatures, and positive temperature sensitivity at low-moderate temperatures. We used Bayesian statistical methods to compare models capturing a range of hypothesized relationships between T s , θ, and R s . The best model indicates that apparent negative temperature sensitivity of R s at high T s reflects the control of water content, not high temperatures. Modeled Q 10 ranged from 2.7 to 1.4 between 5 and 45 °C. Litter addition had no effect on Q 10 or reference respiration ( R ref = R s at 20 °C and optimum θ) beneath shrubs, and little effect on R ref in interspaces, yet R ref was 1.5 times higher beneath shrubs than in interspaces. Altogether, these results suggest reduced R s often observed at high T s in drylands is dominated by the control of θ, and, on shorter-timescales, variable litter inputs exert minimal control over R s .

Biogeochemistry↗
USGS1985

Interspecific competition among Hawaiian forest birds

The object of this study was to determine whether interspecific competition modified local geographic distribution, after taking into account the effect of habitat structure. The tendencies for 14 passerine birds to have positive or negative associations were examined, using 7861 sample points in seven native forests on the islands of Hawaii, Maui, and Kauai. All birds were at least partly insectivorous and were fairly common in forested areas, although some fed chiefly on nectar or fruit. Species—pairs were classified as primary or secondary potential competitors based on general dietary similarity. To evaluate the association between species and to account for the effect of individual species habitat preferences, partial correlations were computed for each species—pair in a study area from the simple correlations between the species and 26 habitat variables plus two quadratic terms to represent nonlinearity. The partial correlations represented a short—term ("instantaneous") assessment of the strength of competitive interactions, and did not reflect the accumulation of competitive displacement through time. Of 170 partial correlations in the analysis, only 10 indicated significant negative association. The general pattern was of positive association (76 significantly positive partials), which probably resulted from flocking and from attraction of birds to areas of resource superabundance. Two species showed consistent patterns of negative partial correlations over several adjacent study areas, the Japanese White—eye/Iiwi in montane Hawaii, and the Japanese White—eye/Elepaio in windward Hawaii; both patterns could be reasonably attributed to direct competition. Species—pairs were grouped by the native or exotic status of the component species. Native/exotic pairs had a significantly greater proportion of negative partial correlations (37%) than either native/native pairs (8%) or exotic/exotic pairs (0%). This pattern was consistent across the seven study areas and appeared to reflect the occurrence of interspecific competition along a broad and diffuse ecological "front" between a co—evolved native avifauna and recently introduced exotic species. The role of competition in the pattern was corroborated by the significantly higher proportion of negative partial correlations among species—pairs of primary potential competitors than among those of secondary potential competitors. Our results suggested that °47% of the primary potential competitors among native/exotic species—pairs may experience at least small depressions in local population density due to competition. Although the negative correlations were for the most part small (average negative r = 0.06), one species could eventually replace another as spatial displacement accumulated through time. The Japanese White—eye appeared to have a principal role in native/exotic interactions, with 62% of the partial correlations between it and native primary potential competitor species being negative. Noteworthy implications were that (1) it was important to account for the habitat responses of individual species when studying the role of interspecific competition in modifying small—scale geographic distribution; (2) competition was frequently sporadic in its geographic occurrence and in the species affected, thus supporting Wiens' (1977) theory of competition; and (3) as a consequence, the role of interspecific competition in modifying distribution may be difficult to detect statistically with small data sets.

Hawaii↗
USGS2009

Trends in Streamflow and Nutrient and Suspended-Sediment Concentrations and Loads in the Upper Mississippi, Ohio, Red, and Great Lakes River Basins, 1975-2004

Many actions have been taken to reduce nutrient and suspended-sediment concentrations and the amount of nutrients and sediment transported in streams as a result of the Clean Water Act and subsequent regulations. This report assesses how nutrient and suspended-sediment concentrations and loads in selected streams have changed during recent years to determine if these actions have been successful. Flow-adjusted and overall trends in concentrations and trends in loads from 1993 to 2004 were computed for total nitrogen, dissolved ammonia, total organic nitrogen plus ammonia, dissolved nitrite plus nitrate, total phosphorus, dissolved phosphorus, total suspended material (total suspended solids or suspended sediment), and total suspended sediment for 49 sites in the Upper Mississippi, Ohio, Red, and Great Lakes Basins. Changes in total nitrogen, total phosphorus, and total suspended-material loads were examined from 1975 to 2003 at six sites to provide a longer term context for the data examined from 1993 to 2004. Flow-adjusted trends in total nitrogen concentrations at 19 of 24 sites showed tendency toward increasing concentrations, and overall trends in total nitrogen concentrations at 16 of the 24 sites showed a general tendency toward increasing concentrations. The trends in these flow-adjusted total nitrogen concentrations are related to the changes in fertilizer nitrogen applications. Flow-adjusted trends in dissolved ammonia concentrations from 1993 to 2004 showed a widespread tendency toward decreasing concentrations. The widespread, downward trends in dissolved ammonia concentrations indicate that some of the ammonia reduction goals of the Clean Water Act are being met. Flow-adjusted and overall trends in total organic plus ammonia nitrogen concentrations from 1993 to 2004 did not show a distinct spatial pattern. Flow-adjusted and overall trends in dissolved nitrite plus nitrate concentrations from 1993 to 2004 also did not show a distinct spatial pattern. Flow-adjusted trends in total phosphorus concentrations were upward at 24 of 40 sites. Overall trends in total phosphorus concentrations were mixed and showed no spatial pattern. Flow-adjusted and overall trends in dissolved phosphorus concentrations were consistently downward at all of the sites in the eastern part of the basins studied. The reduction in phosphorus fertilizer use and manure production east of the Mississippi River could explain most of the observed trends in dissolved phosphorus. Flow-adjusted trends in total suspended-material concentrations showed distinct spatial patterns of increasing tendencies throughout the western part of the basins studied and in Illinois and decreasing concentrations throughout most of Wisconsin, Iowa, and in the eastern part of the basins studied. Flow-adjusted trends in total phosphorus were strongly related to the flow-adjusted trends in suspended materials. The trends in the flow-adjusted suspended-sediment concentrations from 1993 to 2004 resembled those for suspended materials. The long-term, nonmonotonic trends in total nitrogen, total phosphorus, and suspended-material loads for 1975 to 2003 were described by local regression, LOESS, smoothing for six sites. The statistical significance of those trends cannot be determined; however, the long-term changes found for annual streamflow and load data indicate that the monotonic trends from 1993 to 2004 should not be extrapolated backward in time.

Scientific Investigations Report↗
USGS2011

An evaluation of the Bayesian approach to fitting the N-mixture model for use with pseudo-replicated count data

The N-mixture model proposed by Royle in 2004 may be used to approximate the abundance and detection probability of animal species in a given region. In 2006, Royle and Dorazio discussed the advantages of using a Bayesian approach in modelling animal abundance and occurrence using a hierarchical N-mixture model. N-mixture models assume replication on sampling sites, an assumption that may be violated when the site is not closed to changes in abundance during the survey period or when nominal replicates are defined spatially. In this paper, we studied the robustness of a Bayesian approach to fitting the N-mixture model for pseudo-replicated count data. Our simulation results showed that the Bayesian estimates for abundance and detection probability are slightly biased when the actual detection probability is small and are sensitive to the presence of extra variability within local sites.

Journal of Statistical Computation and Simulation↗
USGS1998

Assemblage organization in stream fishes: Effects of environmental variation and interspecific interactions

We assessed the relative importance of environmental variation, interspecific competition for space, and predator abundance on assemblage structure and microhabitat use in a stream fish assemblage inhabiting Coweeta Creek, North Carolina, USA. Our study encompassed a 10–yr time span (1983–1992) and included some of the highest and lowest flows in the last 58 years. We collected 16 seasonal samples which included data on: (1) habitat availability (total and microhabitat) and microhabitat diversity, (2) assemblage structure (i.e., the number and abundances of species comprising a subset of the community), and (3) microhabitat use and overlap. We classified habitat availability data on the basis of year, season, and hydrologic period. Hydrologic period (i.e., pre–drought [PR], drought [D], and post–drought [PO]) represented the temporal location of a sample with respect to a four–year drought that occurred during the study. Hydrologic period explained a greater amount of variance in habitat availability data than either season or year. Total habitat availability was significantly greater during PO than in PR or D, although microhabitat diversity did not differ among either seasons or hydrologic periods. There were significantly fewer high–flow events (i.e., ≥2.1 m 3 /s) during D than in either PR or PO periods. We observed a total of 16 species during our investigation, and the total number of species was significantly higher in D than in PR samples. Correlation analyses between the number of species present (total and abundant species) and environmental data yielded limited results, although the total number of species was inversely correlated with total habitat availability. A cluster analysis grouped assemblage structure samples by hydrologic period rather than season or year, supporting the contention that variation in annual flow had a strong impact on this assemblage. The drought had little effect on the numerical abundance of benthic species in this assemblage; however, a majority of water–column species increased in abundance. The increased abundances of water–column species may have been related to the decrease in high-flow events observed during the drought. Such high–flow events are known to cause mortality in stream fishes. Microhabitat use data showed that species belonged to one of three microhabitat guilds: benthic, lower water column, and mid water column. In general, species within the same guild did not exhibit statistically distinguishable patterns of microhabitat use, and most significant differences occurred between members of different guilds. However, lower water–column guild species frequentlywere not separable from all members of either benthic or mid–water–column species. Variations in the abundance of potential competitors or predators did not produce strong shifts in microhabitat use by assemblage members. Predators were present in the site in only 9 of 16 seasonal samples and never were abundant (maximum number observed per day was 2). In conclusion, our results demonstrate that variability in both mean and peak flows had a much stronger effect on the structure and use of spatial resources within this assemblage then either interspecific competition for space or predation. Consequently, we suspect that the patterns in both assemblage structure and resource use displayed by fishes in Coweeta Creek arose from the interaction between environmental variation and species–specific evolutionary constraints on behavior, morphology, and physiology.

North Carolina↗
USGS2008

Summary of mercury and trace element results in precipitation from the Culpeper, Virginia, Mercury Deposition Network Site (VA-08), 2002-2006

The VA-08 Mercury Deposition Network (MDN) site, southwest of Culpeper, Virginia, was established in autumn of 2002. This site, along with nearby VA-28 (~31 km west) at Big Meadows in Shenandoah National Park, fills a spatial gap in the Mid-Atlantic region of the MDN network and provides Hg deposition data immediately west of the Washington, D.C., metropolitan area. Results for the Culpeper site from autumn of 2002 to the end of 2006 suggest that the highest mercury (Hg) deposition (up to 5.0 µg/m 2 per quarter of the 6.5-12.6 µg/m 2 annual Hg deposition) is measured during the second and third quarters of the year (April-September). This is a result of both elevated Hg precipitation concentrations (up to 27 ng/L) and greater precipitation during these months. The data also exhibit a general statistically significant (p<0.05) negative correlation between weekly total precipitation and Hg concentrations, suggesting a dilution effect during larger precipitation events, especially during winter and spring. Comparison of results between the Culpeper and Big Meadows sites indicates that although quarterly Hg deposition was not significantly different (p<0.05) between sites, quarterly volume-averaged Hg precipitation concentrations were statistically larger (p<0.05) and precipitation was significantly lower (p<0.05) at VA-08. Lower Hg concentrations at the VA-28 site relative to VA-08 are likely a result of greater total precipitation and thus additional dilution of Hg in precipitation. Results from concomitant trace elements in precipitation collected from July, 2005, to December, 2006, were used to better identify possible sources of Hg at the Culpeper MDN site. Principal component analysis of the Hg and trace metal data identified 3 primary source categories, each with large loadings of characteristic elements: 1) Ca, Al, Mg, Sr, La, and Ce (crustal sources); 2) V, Na, and Ni (local wintertime heating oil); and 3) Zn, Cd, Mn, and Hg (regional anthropogenic emission sources). HYSPLIT air mass trajectory modeling and enrichment factor calculations are consistent with this interpretation. A preliminary source attribution model suggests that ~51% of the Hg in wet deposition is due to regional anthropogenic sources, while crustal sources and local oil combustion account for 9.5% and <1%, respectively. This calculation implies that the global Hg burden accounts for ~40% of the Hg in wet deposition.

Virginia↗
USGS2022

Seasonal movements and spatial overlap of juvenile and adult lake sturgeon in Lake Champlain

The lake sturgeon Acipenser fulvescens is a large, long-lived, potamodromous species that is widely distributed throughout freshwater systems in the central part of North America. In this study, we used acoustic telemetry to examine seasonal distribution and movement patterns of endangered Lake Sturgeon in Lake Champlain, Vermont. Acoustic tags were implanted in 29 juvenile Lake Sturgeon (453–874 mm TL) and 19 adults (1,215–1,615 mm TL) from the Winooski River and nearby areas of Lake Champlain between 2015 and 2019; tags were detected with 23 passive acoustic receivers deployed in the river and delta area and an additional 34 receivers deployed throughout Lake Champlain. Home range analysis using a lattice-based density estimator indicated that juvenile home range sizes were the same as adult home range sizes in spring and summer but were statistically larger than adult home ranges in winter. Cumulative home range analysis showed that juvenile and adult home ranges overlapped in shallow (<10-m) water in the summer and fall. In winter and spring, cumulative home ranges from juveniles included deepwater sites (>25 m), while adults remained in shallow water near the mouth of their spawning river. Seven juveniles made long-range movements (18–34 km) during the winter and spring months, and 13 juveniles moved back into the lower section of their natal river after overwintering in Lake Champlain. This study is the first to directly compare adult and juvenile Lake Sturgeon distribution, home range size, movements, and habitat use in a large lake system and provides a baseline for further research on the movement ecology of Lake Sturgeon in Lake Champlain.

Vermont↗
USGS2007

A global search inversion for earthquake kinematic rupture history: Application to the 2000 western Tottori, Japan earthquake

[1] We present a two-stage nonlinear technique to invert strong motions records and geodetic data to retrieve the rupture history of an earthquake on a finite fault. To account for the actual rupture complexity, the fault parameters are spatially variable peak slip velocity, slip direction, rupture time and risetime. The unknown parameters are given at the nodes of the subfaults, whereas the parameters within a subfault are allowed to vary through a bilinear interpolation of the nodal values. The forward modeling is performed with a discrete wave number technique, whose Green's functions include the complete response of the vertically varying Earth structure. During the first stage, an algorithm based on the heat-bath simulated annealing generates an ensemble of models that efficiently sample the good data-fitting regions of parameter space. In the second stage (appraisal), the algorithm performs a statistical analysis of the model ensemble and computes a weighted mean model and its standard deviation. This technique, rather than simply looking at the best model, extracts the most stable features of the earthquake rupture that are consistent with the data and gives an estimate of the variability of each model parameter. We present some synthetic tests to show the effectiveness of the method and its robustness to uncertainty of the adopted crustal model. Finally, we apply this inverse technique to the well recorded 2000 western Tottori, Japan, earthquake ( Mw 6.6); we confirm that the rupture process is characterized by large slip (3-4 m) at very shallow depths but, differently from previous studies, we imaged a new slip patch (2-2.5 m) located deeper, between 14 and 18 km depth.

Tottori↗
USGS2007

Surface-Water Conditions in Georgia, Water Year 2005

INTRODUCTION The U.S. Geological Survey (USGS) Georgia Water Science Center-in cooperation with Federal, State, and local agencies-collected surface-water streamflow, water-quality, and ecological data during the 2005 Water Year (October 1, 2004-September 30, 2005). These data were compiled into layers of an interactive ArcReaderTM published map document (pmf). ArcReaderTM is a product of Environmental Systems Research Institute, Inc (ESRI?). Datasets represented on the interactive map are * continuous daily mean streamflow * continuous daily mean water levels * continuous daily total precipitation * continuous daily water quality (water temperature, specific conductance dissolved oxygen, pH, and turbidity) * noncontinuous peak streamflow * miscellaneous streamflow measurements * lake or reservoir elevation * periodic surface-water quality * periodic ecological data * historical continuous daily mean streamflow discontinued prior to the 2005 water year The map interface provides the ability to identify a station in spatial reference to the political boundaries of the State of Georgia and other features-such as major streams, major roads, and other collection stations. Each station is hyperlinked to a station summary showing seasonal and annual stream characteristics for the current year and for the period of record. For continuous discharge stations, the station summary includes a one page graphical summary page containing five graphs, a station map, and a photograph of the station. The graphs provide a quick overview of the current and period-of-record hydrologic conditions of the station by providing a daily mean discharge graph for the water year, monthly statistics graph for the water year and period of record, an annual mean streamflow graph for the period of record, an annual minimum 7-day average streamflow graph for the period of record, and an annual peak streamflow graph for the period of record. Additionally, data can be accessed through the layer's link to the National Water Inventory System Web (NWISWeb) Interface.

Georgia↗
USGS2016

Modeling the effects of land cover and use on landscape capability for urban ungulate populations

Expanding ungulate populations are causing concerns for wildlife professionals and residents in many urban areas worldwide. Nowhere is the phenomenon more apparent than in the eastern US, where urban white-tailed deer (Odocoileus virginianus) populations are increasing. Most habitat suitability models for deer have been developed in rural areas and across large (>1000 km2) spatial extents. Only recently have we begun to understand the factors that contribute to space use by deer over much smaller spatial extents. In this study, we explore the concepts, terminology, methodology and state-of-the-science in wildlife abundance modeling as applied to overabundant deer populations across heterogeneous urban landscapes. We used classified, high-resolution digital orthoimagery to extract landscape characteristics in several urban areas of upstate New York. In addition, we assessed deer abundance and distribution in 1-km2 blocks across each study area from either aerial surveys or ground-based distance sampling. We recorded the number of detections in each block and used binomial mixture models to explore important relationships between abundance and key landscape features. Finally, we cross-validated statistical models of abundance and compared covariate relationships across study sites. Study areas were characterized along a gradient of urbanization based on the proportions of impervious surfaces and natural vegetation which, based on the best-supported models, also distinguished blocks potentially occupied by deer. Models performed better at identifying occurrence of deer and worse at predicting abundance in cross-validation comparisons. We attribute poor predictive performance to differences in deer population trajectories over time. The proportion of impervious surfaces often yielded better predictions of abundance and occurrence than did the proportion of natural vegetation, which we attribute to a lack of certain land cover classes during cold and snowy winters. Merits and limitations of our approach to habitat suitability modeling are discussed in detail.

Book chapter↗
USGS2020

Units recovery methods in compositional data analysis

Compositional data carry relative information. Hence, their statistical analysis has to be performed on coordinates with respect to a log-ratio basis. Frequently, the modeler is required to back-transform the estimates obtained with the modeling to have them in the original units such as euros, kg or mg/liter. Approaches for recovering original units need to be formally introduced and its properties explored. Here, we formulate and analyze the properties of two procedures: a simple approach consisting of adding a residual part to the composition and an approach based on the use of an auxiliary variable. Both procedures are illustrated using a geochemical data set where the original units are recovered when spatial models are applied.

Natural Resources Research↗
USGS2019

Agricultural cropland extent and areas of South Asia derived using Landsat satellite 30-m time-series big-data using random forest machine learning algorithms on the Google Earth Engine cloud

The South Asia (India, Pakistan, Bangladesh, Nepal, Sri Lanka and Bhutan) has a staggering 900 million people (~43% of the population) who face food insecurity or severe food insecurity as per United Nations, Food and Agriculture Organization’s (FAO) the Food Insecurity Experience Scale (FIES). The existing coarse-resolution (>250-m) cropland maps lack precision in geo-location of individual farms and have low map accuracies. This also results in uncertainties in cropland areas calculated from such products. Thereby, the overarching goal of this study was to develop high spatial resolution (30-m or better) baseline cropland extent product of South Asia for the year 2015 using Landsat satellite time-series big-data and machine learning algorithms (MLAs) on the Google Earth Engine (GEE) cloud computing platform. To eliminate the impact of clouds, ten time-composited Landsat bands (blue, green, red, NIR, SWIR1, SWIR2, Thermal, EVI, NDVI, NDWI) were derived for each of the 3 time-periods over 12 months (monsoon: Julian days 151-300; winter: Julian days 301-365 plus 1-60; and summer: Julian days 61-150), taking the every 8-day data from Landsat-8 and 7 for the years 2013-2015, for a total of 30-bands plus global digital elevation model (GDEM) derived slope band. This 31-band mega-file big data-cube was composed for each of the 5 agro-ecological zones (AEZ’s) of South Asia and formed a baseline data for image classification and analysis. Knowledge-base for the Random Forest (RF) MLAs were developed using spatially well spread-out reference training data (N=2179) in 5 AEZs. Classification was performed on GEE for each of the 5 AEZs using well-established knowledge-based and RF MLAs on the cloud. Map accuracies were measured using independent validation data (N=1185). The survey showed that the South Asia cropland product had a producer’s accuracy of 89.9% (errors of omissions of 10.1%), user’s accuracy of 95.3% (errors of commission of 4.7%) and an overall accuracy of 88.7%. The National and sub-national (districts) areas computed from this cropland extent product explained 80-96% variability when compared with the National statistics of the South Asian Countries. The full resolution imagery can be viewed at full-resolution, by zooming-in to any location in South Asia or the world, at www.croplands.org and the cropland products of South Asia downloaded from The Land Processes Distributed Active Archive Center (LP DAAC) of National Aeronautics and Space Administration (NASA) and the United States Geological Survey (USGS): https://lpdaac.usgs.gov/products/gfsad30saafgircev001/

GIScience and Remote Sensing↗