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At least 793 records · Page 44Linked to original sources
USGS2021

System characterization report on the Gaofen-1

Executive Summary This report addresses system characterization of Gaofen-1 and is part of a series of system characterization reports produced and delivered by the U.S. Geological Survey Earth Resources Observation and Science Cal/Val Center of Excellence in 2020. These reports present the detail methodology and procedures for characterization; present technical and operational information about the specific sensing system being evaluated; and provide a summary of test measurements, data retention practices, data analysis results, and conclusions. Gaofen represents a series of Chinese high-resolution Earth observation satellites. More than 12 satellites have been launched in the Gaofen series, beginning with Gaofen-1 in 2013. Satellites within the series have varying infrared, radar, and optical imaging capabilities. The primary goal for the satellite is to provide near real-time observations for climate change monitoring, geographical mapping, precision agriculture support, environmental and resource surveying, and disaster prevention. More information on Chinese satellites and sensors is available within the “2020 Joint Agency Commercial Imagery Evaluation—Remote Sensing Satellite Compendium” and at http://www.cnsageo.com/#/detailIndex?secondIndex=2&id=3&code=8 . The Earth Resources Observation and Science Cal/Val Center of Excellence System Characterization team completed data analyses to characterize the geometric (interior and exterior), radiometric, and spatial performances. Results of these analyses indicate that Gaofen-1 has an interior geometric performance of −0.48 meter (m) (−0.03 pixel) northing and 0.42 m (0.03 pixel) easting offset for band 1, −0.99 m (−0.06 pixel) northing and −0.38 m (−0.02 pixel) easting offset for band 2, −0.45 m (−0.03) northing and 0.83 m (0.05 pixel) easting offset for band 3, −3.20 m (−0.20 pixel) northing and 1.44 m (0.09 pixel) easting offset for band 4 in band-to-band registration. Similarly, Gaofen-1 has an exterior geometric performance of 7.50 m (0.48 pixel) easting and 109.50 m (7.30 pixels) northing offset in comparison to the Landsat 8 Operational Land Imager; a radiometric performance in the range of −0.014 to 0.149 (absolute reflective difference); and a spatial performance in the range of 1.1 to 2.0 pixels at full width at half maximum, with a modulation transfer function at a Nyquist frequency in the range of 0.040 to 0.250.

Open-File Report↗
USGS2007

Summary of selected U.S. Geological survey data on domestic well water quality for the Centers for Disease Control's National Environmental Public Health Tracking Program

About 10 to 30 percent of the population in most States uses domestic (private) water supply. In many States, the total number of people served by domestic supplies can be in the millions. The water quality of domestic supplies is inconsistently regulated and generally not well characterized. The U.S. Geological Survey (USGS) has two water-quality data sets in the National Water Information System (NWIS) database that can be used to help define the water quality of domestic-water supplies: (1) data from the National Water-Quality Assessment (NAWQA) Program, and (2) USGS State data. Data from domestic wells from the NAWQA Program were collected to meet one of the Program's objectives, which was to define the water quality of major aquifers in the United States. These domestic wells were located primarily in rural areas. Water-quality conditions in these major aquifers as defined by the NAWQA data can be compared because of the consistency of the NAWQA sampling design, sampling protocols, and water-quality analyses. The NWIS database is a repository of USGS water data collected for a variety of projects; consequently, project objectives and analytical methods vary. This variability can bias statistical summaries of contaminant occurrence and concentrations; nevertheless, these data can be used to define the geographic distribution of contaminants. Maps created using NAWQA and USGS State data in NWIS can show geographic areas where contaminant concentrations may be of potential human-health concern by showing concentrations relative to human-health water-quality benchmarks. On the basis of national summaries of detection frequencies and concentrations relative to U.S. Environmental Protection Agency (USEPA) human-health benchmarks for trace elements, pesticides, and volatile organic compounds, 28 water-quality constituents were identified as contaminants of potential human-health concern. From this list, 11 contaminants were selected for summarization of water-quality data in 16 States (grantee States) that were funded by the Environmental Public Health Tracking (EPHT) Program of the Centers for Disease Control and Prevention (CDC). Only data from domestic-water supplies were used in this summary because samples from these wells are most relevant to human exposure for the targeted population. Using NAWQA data, the concentrations of the 11 contaminants were compared to USEPA human-health benchmarks. Using NAWQA and USGS State data in NWIS, the geographic distribution of the contaminants were mapped for the 16 grantee States. Radon, arsenic, manganese, nitrate, strontium, and uranium had the largest percentages of samples with concentrations greater than their human-health benchmarks. In contrast, organic compounds (pesticides and volatile organic compounds) had the lowest percentages of samples with concentrations greater than human-health benchmarks. Results of data retrievals and spatial analysis were compiled for each of the 16 States and are presented in State summaries for each State. Example summary tables, graphs, and maps based on USGS data for New Jersey are presented to illustrate how USGS water-quality and associated ancillary geospatial data can be used by the CDC to address goals and objectives of the EPHT Program.

Scientific Investigations Report↗
USGS2011

Observed and forecast flood-inundation mapping application-A pilot study of an eleven-mile reach of the White River, Indianapolis, Indiana

Near-real-time and forecast flood-inundation mapping products resulted from a pilot study for an 11-mile reach of the White River in Indianapolis. The study was done by the U.S. Geological Survey (USGS), Indiana Silver Jackets hazard mitigation taskforce members, the National Weather Service (NWS), the Polis Center, and Indiana University, in cooperation with the City of Indianapolis, the Indianapolis Museum of Art, the Indiana Department of Homeland Security, and the Indiana Department of Natural Resources, Division of Water. The pilot project showed that it is technically feasible to create a flood-inundation map library by means of a two-dimensional hydraulic model, use a map from the library to quickly complete a moderately detailed local flood-loss estimate, and automatically run the hydraulic model during a flood event to provide the maps and flood-damage information through a Web graphical user interface. A library of static digital flood-inundation maps was created by means of a calibrated two-dimensional hydraulic model. Estimated water-surface elevations were developed for a range of river stages referenced to a USGS streamgage and NWS flood forecast point colocated within the study reach. These maps were made available through the Internet in several formats, including geographic information system, Keyhole Markup Language, and Portable Document Format. A flood-loss estimate was completed for part of the study reach by using one of the flood-inundation maps from the static library. The Federal Emergency Management Agency natural disaster-loss estimation program HAZUS-MH, in conjunction with local building information, was used to complete a level 2 analysis of flood-loss estimation. A Service-Oriented Architecture-based dynamic flood-inundation application was developed and was designed to start automatically during a flood, obtain near real-time and forecast data (from the colocated USGS streamgage and NWS flood forecast point within the study reach), run the two-dimensional hydraulic model, and produce flood-inundation maps. The application used local building data and depth-damage curves to estimate flood losses based on the maps, and it served inundation maps and flood-loss estimates through a Web-based graphical user interface.

Indiana↗
USGS2013

A regional classification of the effectiveness of depressional wetlands at mitigating nitrogen transport to surface waters in the Northern Atlantic Coastal Plain

Nitrogen from nonpoint sources contributes to eutrophication, hypoxia, and related ecological degradation in Atlantic Coastal Plain streams and adjacent coastal estuaries such as Chesapeake Bay and Pamlico Sound. Although denitrification in depressional (non-riparian) wetlands common to the Coastal Plain can be a significant landscape sink for nitrogen, the effectiveness of individual wetlands at removing nitrogen varies substantially due to varying hydrogeologic, geochemical, and other landscape conditions, which are often poorly or inconsistently mapped over large areas. A geographic model describing the spatial variability in the likely effectiveness of depressional wetlands in watershed uplands at mitigating nitrogen transport from nonpoint sources to surface waters was constructed for the Northern Atlantic Coastal Plain (NACP), from North Carolina through New Jersey. Geographic and statistical techniques were used to develop the model. Available medium-resolution (1:100,000-scale) stream hydrography was used to define 33,799 individual watershed catchments in the study area. Sixteen landscape metrics relevant to the occurrence of depressional wetlands and their effectiveness as nitrogen sinks were defined for each catchment, based primarily on available topographic and soils data. Cluster analysis was used to aggregate the 33,799 catchments into eight wetland landscape regions (WLRs) based on the value of three principal components computed for the 16 original landscape metrics. Significant differences in topography, soil, and land cover among the eight WLRs demonstrate the effectiveness of the clustering technique. Results were used to interpret the relative likelihood of depressional wetlands in each WLR and their likely effectiveness at mitigating nitrogen transport from upland source areas to surface waters. The potential effectiveness of depressional wetlands at mitigating nitrogen transport varies substantially over different parts of the NACP. Depressional wetlands are common in three WLRs covering 32 percent of the area, and have a relatively high potential to mitigate nitrogen transport from nonpoint sources. Conversely, 37 percent of the study area includes rolling hills with relatively high slope and relief, and little likelihood of depressional wetlands. The remainder of the Coastal Plain includes relatively flat watersheds with moderate to low relative likelihood of nitrogen mitigation. The delineation of WLRs in this model should be useful for targeting wetland conservation or restoration efforts, and for estimating the effects of depressional wetlands on the regional nitrogen budget, but should be considered in light of limitations and assumptions inherent in the model.

Scientific Investigations Report↗
USGS1995

Techniques of contributing-area delineation for analysis of nonpoint-source contamination of Long Island, New York

Ninety shallow monitoring wells on Long Island, N.Y., were used to test the hypothesis that the correlation between the detection of volatile organic compounds (VOC's) at a well and explanatory variables representing land use, population density, and hydrogeologic conditions around the well is affected by the size and shape of the area defined as the contributing area. Explanatory variables are quantified through overlay of various specified contributing areas on 1:24 000-scale landuse and population-density geographic information system (GIS) coverages. Four methods of contributing-area delineation were used: (a) centering a circle of selected radius on the well site, (b) orienting a triangular area along the direction of horizontal ground-water flow to the well, (c) generating a shaped based on direction and magnitude of horizontal flow to the well, and (d) generating a shape based on three-dimensional particle pathlines backtracked from the well screen to the water table. The strongest correlations with VOC detections were obtained from circles of 400- to 1 000-meter radius. Improvement in correlation through delineations based on ground-water flow would require geographic overlay on more highly detailed GIS coverages than those used in the study.

Models for assessing and monitoring groundwater qu↗
USGS2009

Vegetation classification and distribution mapping report: Mesa Verde National Park

The classification and distribution mapping of the vegetation of Mesa Verde National Park (MEVE) and surrounding environment was achieved through a multi-agency effort between 2004 and 2007. The National Park Service’s Southern Colorado Plateau Network facilitated the team that conducted the work, which comprised the U.S. Geological Survey’s Southwest Biological Science Center, Fort Collins Research Center, and Rocky Mountain Geographic Science Center; Northern Arizona University; Prescott College; and NatureServe. The project team described 47 plant communities for MEVE, 34 of which were described from quantitative classification based on f eld-relevé data collected in 1993 and 2004. The team derived 13 additional plant communities from field observations during the photointerpretation phase of the project. The National Vegetation Classification Standard served as a framework for classifying these plant communities to the alliance and association level. Eleven of the 47 plant communities were classified as “park specials;” that is, plant communities with insufficient data to describe them as new alliances or associations. The project team also developed a spatial vegetation map database representing MEVE, with three different map-class schemas: base, group, and management map classes. The base map classes represent the fi nest level of spatial detail. Initial polygons were developed using Definiens Professional (at the time of our use, this software was called eCognition), assisted by interpretation of 1:12,000 true-color digital orthophoto quarter quadrangles (DOQQs). These polygons (base map classes) were labeled using manual photo interpretation of the DOQQs and 1:12,000 true-color aerial photography. Field visits verified interpretation concepts. The vegetation map database includes 46 base map classes, which consist of associations, alliances, and park specials classified with quantitative analysis, additional associations and park specials noted during photointerpretation, and non-vegetated land cover, such as infrastructure, land use, and geological land cover. The base map classes consist of 5,007 polygons in the project area. A field-based accuracy assessment of the base map classes showed overall accuracy to be 43.5%. Seven map classes comprise 89.1% of the park vegetated land cover. The group map classes represent aggregations of the base map classes, approximating the group level of the National Vegetation Classification Standard, version 2 (Federal Geographic Data Committee 2007), and reflecting physiognomy and floristics. Terrestrial ecological systems, as described by NatureServe (Comer et al. 2003), were used as the fi rst approximation of the group level. The project team identified 14 group map classes for this project. The overall accuracy of the group map classes was determined using the same accuracy assessment data as for the base map classes. The overall accuracy of the group representation of vegetation was 80.3%. In consultation with park staff , the team developed management map classes, consisting of park-defined groupings of base map classes intended to represent a balance between maintaining required accuracy and providing a focus on vegetation of particular interest or import to park managers. The 23 management map classes had an overall accuracy of 73.3%. While the main products of this project are the vegetation classification and the vegetation map database, a number of ancillary digital geographic information system and database products were also produced that can be used independently or to augment the main products. These products include shapefiles of the locations of field-collected data and relational databases of field-collected data.

Mesa Verde National Park↗
USGS2018

Quantitative evaluation of vitrinite reflectance and atomic O/C in coal using Raman spectroscopy and multivariate analysis

Vitrinite reflectance (VRo) is a standard petrographic method for assessing thermal maturity (rank) of coal. The vitrinite reflectance technique, however, requires significant petrographic experience, can be time-consuming, and may be biased by analyst subjectivity. Correlations between coal rank and Raman spectral properties are a promising alternative that can supplant some of the limitations inherent in the VRo protocol. The traditional peak-fitting methodologies for quantifying metrics from Raman spectra, however, also suffer from analyst subjectivity that can affect correlations between analyte and spectral properties. This research combines high-throughput Raman spectroscopy with multivariate analysis (MVA) to create calibration models for the prediction of coal rank though VRo and atomic O/C ratio. MVA techniques eliminate the ambiguous subjectivity prevalent in peak-fitting methods by evaluating the full Raman spectrum, then identifying the integral vibrational modes for constructing accurate models. Partial least squares (PLS) regression models were developed using Raman spectra and VRo values (0.23–5.23%) for 68 geographically diverse coal samples. The calibration set was validated using one-half of the samples to rigorously assess the model’s predictive accuracy. The root mean standard error of prediction was 0.19 for the VRo model and 0.014 for the atomic O/C model. Both models exhibited linear correlations, with coefficients of determination ( R 2 ) for the validation set of 0.99 (VRo) and 0.93 (atomic O/C), despite the geographic and rank diversity of the samples. This study demonstrates the applicability and power of using PLS models for the prediction of both the VRo and atomic O/C ratio from Raman spectra. The quantitative MVA protocol contained herein provides a Raman alternative to the VRo industry benchmark for coal rank that is not subject to the limitations and subjectivity of peak-fitting methods.

Fuel↗
USGS2020

Biogeography and phylogeny of masting: Do global patterns fit functional hypotheses?

1) Interannual variability of seed crops (CVp) has profound consequences for plant populations and food webs, where high CVp is termed ‘masting’. Here we ask: is global variation in CVp better predicted by plant or habitat differences consistent with adaptive economies of scale, in which flower and seed benefits increase disproportionately during mast years; or to passive mechanisms, in which seed production responds to variation in resource availability associated with climate variability? 2) To address this question, we compiled a dataset for phylogenetic comparative analysis of long-term fruit/seed production for plants comprising 920 time-series spanning 311 plant species. 3) Factors associated with both adaptive benefits of CVp (wind pollination and seed dispersal) and climatic variability (variability of summer precipitation) were among the best predictors of global variation in CVp. We observed a hump-shaped relationship between CVp and latitude and intermediate phylogenetic and geographic signals in CVp. 4) CVp is patterned non-randomly across the globe and over the plant tree of life, where high CVp is associated with species benefiting from economies of scale of seed or flower production and with species that experience variable rainfall over summer months when seeds usually mature.

New Phytologist↗
USGS2002

Occurrence and status of volatile organic compounds in ground water from rural, untreated, self-supplied domestic wells in the United States, 1986-99

Samples of untreated ground water from 1,926 rural, self-supplied domestic wells were analyzed for volatile organic compounds (VOCs) during 1986-99. This information was used to characterize the occurrence and status of VOCs in domestic well water. The samples were either collected as part of the U.S. Geological Survey?s National Water-Quality Assessment (NAWQA) Program occurrence-assessment studies or were compiled by NAWQA from existing ambient ground-water or source-water-quality monitoring programs conducted by local, State, and other Federal agencies. Water samples were collected at the wellhead prior to treatment or storage. In most samples, 55 target VOCs were analyzed, and occurrence and status information generally was computed at an assessment level of 0.2 mg/L (microgram per liter). At least one VOC was detected in 12 percent of samples (232 samples) at an assessment level of 0.2 mg/L. This detection frequency is relatively low compared to the 26 percent detection frequency of at least one VOC in public sup-ply wells sampled by NAWQA, and the difference may be due, in part, to the higher pumping rates, pumping stress factors, and larger contributing areas of public supply wells. Samples with detections of at least one VOC were collected from wells located in 31 of 39 States. Solvents were the most frequently detected VOC group with detections in 4.6 percent of samples (89 samples) at an assessment level of 0.2 mg/L. The geographic distribution of detections of some VOC groups, such as fumigants and oxygenates, relates to the use pattern of com-pounds in that group. With the exception of com-pounds used in organic synthesis, detection frequencies of VOCs by group are proportional to the average half-life of compounds in the group. When the organic synthesis group is excluded from the analysis, a good correlation exists between the detection frequency of VOCs by group and average half-life of compounds in the group. Individually, VOCs were not commonly detected at an assessment level of 0.2 mg/L, with the seven most frequently detected VOCs found in only 1 to 5 percent of samples. Mixtures (two or more compounds) were a common mode of occurrence for VOCs when no assessment level was applied, and mixtures occurred in one-half of all samples that contained at least one VOC. Only 1.4 percent of samples (27 samples) had one or more VOC concentrations that exceeded a federally established drinking-water standard or health criterion. Only 0.1 percent of samples (2 samples) had one or more VOC concentrations that exceeded a taste/odor threshold. Potential point sources of VOCs near domestic wells are numerous. Leaks from under-ground storage tanks and aboveground storage tanks that hold gasoline, diesel fuel, or heating oil have the potential to be major point sources of contaminants to domestic wells. Shock chlorination may be a source of trichloromethane and other trihalomethanes in some domestic wells. Septic systems are believed to be an important source of contaminants to domestic wells, but extensive research on this subject does not exist. VOCs frequently are ingredients in household products such as cleansers and insecticides, and some VOCs have been found in septic systems.

Water-Resources Investigations Report↗
USGS2009

Mapping and monitoring Mt. Graham Red Squirrel habitat with GIS and thematic mapper imagery

To estimate the Mt. Graham red squirrel (MGRS) population, personnel visit a proportion of middens each year to determine their occupancy (Snow in this vol.). The method results in very tight confidence intervals (high precision), but the accuracy of the population estimate is dependent upon knowing where all the middens are located. I hypothesized that there might be areas outside the survey boundary that contained Mt. Graham red squirrel middens, but the ruggedness of the Pinaleno Mountains made mountain-wide surveys difficult. Therefore, I started exploring development of a spatially explicit (geographic information system [GIS]-based) habitat model in 1998 that could identify MGRS habitat remotely with satellite imagery and a GIS. A GIS-based model would also allow us to assess changes in MGRS habitat between two time periods because Landsat passes over the same location every 16 days, imaging the earth in 185 km swaths (Aronoff 1989). Specifically, the objectives of this analysis were to (1) develop a pattern recognition model for MGRS habitat, (2) map potential (predicted/modeled) MGRS habitat, (3) identify changes in potential MGRS habitat between 1993 and 2003, and (4) evaluate the current location of the MGRS survey boundary.

Arizona↗
USGS2018

Development of an aerial population survey method for elk (Cervus elaphus) in Rocky Mountain National Park, Colorado

Executive Summary Since the early 1990s, substantial effort and funding have been expended to conduct research to guide development of a 20-year Elk and Vegetation Management Plan for Rocky Mountain National Park (RMNP) in Colorado. One goal of the plan is to maintain the elk ( Cervus elaphus ) population size at the lower end of the natural range of variation. To implement management actions called for in the plan, accurate and reliable population estimates are needed, as well as a better understanding of the spatial and temporal distribution of elk. The previous aerial survey protocol and population estimation model used by the park had not been updated since the model’s initial calibration more than 15 years ago and the model was developed with an insufficient number (n=44) of observations. Thus we initiated research to reevaluate, update, and improve elk population estimation protocols for RMNP. We considered several alternative survey and analysis methods, and concluded that a hybrid population-estimation model using a simultaneous double-observer technique with sighting covariates was the most appropriate and effective aerial survey methodology for this population and the environmental conditions in RMNP. Instructional protocols for conducting these surveys in the future, along with datasheets, are provided in this report’s appendixes. To develop an improved method for aerial elk surveys, we used elk radio-collar location data from our study and other studies, and applied geographic information system analyses to define the survey area and develop effective, repeatable survey transect lines. We used telemetry data from radio-collared elk to inform our understanding of the temporal and spatial scale of elk movements across the park boundary, elk use of tree cover during potential survey hours, and elk use of different elevations within their range. Determining where elk were during surveys helped to fine-tune a survey design that improved spatial cover-age and decreased costs where possible, while standardizing the method to make it repeatable from year to year. We conducted aerial helicopter surveys to test our methodology in an adaptive, iterative process during three winters: 2007–2008, 2008–2009, and 2009–2010. We gained new information on each survey and used results to refine subsequent surveys. Our results confirm that elk movements were highly dynamic with respect to park boundary crossings; an average of six round trips from the park to Estes Park, Colorado, and back per month were taken by global positioning system-collared bull elk. We observed a strong diurnal temporal pattern of bull elk use of trees; elk were found in dense tree cover from 15:00−22:00 but not as often during morning and early afternoon hours when surveys were conducted. We used information on elk use of different altitudes to refine and establish a more efficient survey area. During the time of our study, a concurrent study in the park deployed 120 very high frequency radio collars on elk cows. We used those collar locations during our flights to increase sample size and to evaluate the level of precision we would gain by using “known fates analysis” (in which elk were known to be in the survey area, out of the survey area, or deceased based on radio-collar locations collected simultaneously during aerial surveys). Using radio-collar locations reduced bias by 1.1–8.8 percent and increased precision (that is, reduced the width of confidence intervals). This report provides final population estimates analyzed with and without radio-collar data to demonstrate what is gained by using marked individuals.

Colorado↗
USGS2017

An open source high-performance solution to extract surface water drainage networks from diverse terrain conditions

This paper describes a workflow for automating the extraction of elevation-derived stream lines using open source tools with parallel computing support and testing the effectiveness of procedures in various terrain conditions within the conterminous United States. Drainage networks are extracted from the US Geological Survey 1/3 arc-second 3D Elevation Program elevation data having a nominal cell size of 10 m. This research demonstrates the utility of open source tools with parallel computing support for extracting connected drainage network patterns and handling depressions in 30 subbasins distributed across humid, dry, and transitional climate regions and in terrain conditions exhibiting a range of slopes. Special attention is given to low-slope terrain, where network connectivity is preserved by generating synthetic stream channels through lake and waterbody polygons. Conflation analysis compares the extracted streams with a 1:24,000-scale National Hydrography Dataset flowline network and shows that similarities are greatest for second- and higher-order tributaries.

Cartography and Geographic Information Science↗
USGS2003

Using multiple logistic regression and GIS technology to predict landslide hazard in northeast Kansas, USA

Landslides in the hilly terrain along the Kansas and Missouri rivers in northeastern Kansas have caused millions of dollars in property damage during the last decade. To address this problem, a statistical method called multiple logistic regression has been used to create a landslide-hazard map for Atchison, Kansas, and surrounding areas. Data included digitized geology, slopes, and landslides, manipulated using ArcView GIS. Logistic regression relates predictor variables to the occurrence or nonoccurrence of landslides within geographic cells and uses the relationship to produce a map showing the probability of future landslides, given local slopes and geologic units. Results indicated that slope is the most important variable for estimating landslide hazard in the study area. Geologic units consisting mostly of shale, siltstone, and sandstone were most susceptible to landslides. Soil type and aspect ratio were considered but excluded from the final analysis because these variables did not significantly add to the predictive power of the logistic regression. Soil types were highly correlated with the geologic units, and no significant relationships existed between landslides and slope aspect. ?? 2003 Elsevier Science B.V. All rights reserved.

Engineering Geology↗
USGS2019

Global phylodynamic analysis of avian paramyxovirus-1 provides evidence of inter-host transmission and intercontinental spatial diffusion

Background Avian avulavirus (commonly known as avian paramyxovirus-1 or APMV-1) can cause disease of varying severity in both domestic and wild birds. Understanding how viruses move among hosts and geography would be useful for informing prevention and control efforts. A Bayesian statistical framework was employed to estimate the evolutionary history of 1602 complete fusion gene APMV-1 sequences collected from 1970 to 2016 in order to infer viral transmission between avian host orders and diffusion among geographic regions. Ancestral states were estimated with a non-reversible continuous-time Markov chain model, allowing transition rates between discrete states to be calculated. The evolutionary analyses were stratified by APMV-1 classes I ( n = 198) and II ( n = 1404), and only those sequences collected between 2006 and 2016 were allowed to contribute host and location information to the viral migration networks. Results While the current data was unable to assess impact of host domestication status on APMV-1 diffusion, these analyses supported the sharing of APMV-1 among divergent host taxa. The highest supported transition rate for both classes existed from domestic chickens to Anseriformes (class I:6.18 transitions/year, 95% highest posterior density (HPD) 0.31–20.02, Bayes factor (BF) = 367.2; class II:2.88 transitions/year, 95%HPD 1.9–4.06, BF = 34,582.9). Further, among class II viruses, domestic chickens also acted as a source for Columbiformes (BF = 34,582.9), other Galliformes (BF = 34,582.9), and Psittaciformes (BF = 34,582.9). Columbiformes was also a highly supported source to Anseriformes (BF = 322.0) and domestic chickens (BF = 402.6). Additionally, our results provide support for the diffusion of viruses among continents and regions, but no interhemispheric viral exchange between 2006 and 2016. Among class II viruses, the highest transition rates were estimated from South Asia to the Middle East (1.21 transitions/year; 95%HPD 0.36–2.45; BF = 67,107.8), from Europe to East Asia (1.17 transitions/year; 95%HPD 0.12–2.61; BF = 436.2) and from Europe to Africa (1.06 transitions/year, 95%HPD 0.07–2.51; BF = 169.3). Conclusions While migration appears to occur infrequently, geographic movement may be important in determining viral diversification and population structure. In contrast, inter-order transmission of APMV-1 may occur readily, but most events are transient with few lineages persisting in novel hosts.

BMC Evolutionary Biology↗
USGS2012

A spatial cluster analysis of tractor overturns in Kentucky from 1960 to 2002

Background: Agricultural tractor overturns without rollover protective structures are the leading cause of farm fatalities in the United States. To our knowledge, no studies have incorporated the spatial scan statistic in identifying high-risk areas for tractor overturns. The aim of this study was to determine whether tractor overturns cluster in certain parts of Kentucky and identify factors associated with tractor overturns. Methods: A spatial statistical analysis using Kulldorff's spatial scan statistic was performed to identify county clusters at greatest risk for tractor overturns. A regression analysis was then performed to identify factors associated with tractor overturns. Results: The spatial analysis revealed a cluster of higher than expected tractor overturns in four counties in northern Kentucky (RR = 2.55) and 10 counties in eastern Kentucky (RR = 1.97). Higher rates of tractor overturns were associated with steeper average percent slope of pasture land by county (p = 0.0002) and a greater percent of total tractors with less than 40 horsepower by county (p<0.0001). Conclusions: This study reveals that geographic hotspots of tractor overturns exist in Kentucky and identifies factors associated with overturns. This study provides policymakers a guide to targeted county-level interventions (e.g., roll-over protective structures promotion interventions) with the intention of reducing tractor overturns in the highest risk counties in Kentucky.

Kentucky↗
USGS2014

Evaluation of alternative groundwater-management strategies for the Bureau of Reclamation Klamath Project, Oregon and California

The water resources of the upper Klamath Basin, in southern Oregon and northern California, are managed to achieve various complex and interconnected purposes. Since 2001, irrigators in the Bureau of Reclamation Klamath Irrigation Project (Project) have been required to limit surface-water diversions to protect habitat for endangered freshwater and anadromous fishes. The reductions in irrigation diversions have led to an increased demand for groundwater by Project irrigators, particularly in drought years. The potential effects of sustained pumping on groundwater and surface-water resources have caused concern among Federal and state agencies, Indian tribes, wildlife groups, and groundwater users. To aid in the development of a viable groundwater-management strategy for the Project, the U.S. Geological Survey, in collaboration with the Klamath Water and Power Agency and the Oregon Water Resources Department, developed a groundwater-management model that links groundwater simulation with techniques of constrained optimization. The overall goal of the groundwater-management model is to determine the patterns of groundwater pumping that, to the extent possible, meet the supplemental groundwater demands of the Project. To ensure that groundwater development does not adversely affect groundwater and surface-water resources, the groundwater-management model includes constraints to (1) limit the effects of groundwater withdrawal on groundwater discharge to streams and lakes that support critical habitat for fish listed under the Endangered Species Act, (2) ensure that drawdowns do not exceed limits allowed by Oregon water law, and (3) ensure that groundwater withdrawal does not adversely affect agricultural drain flows that supply a substantial portion of water for irrigators and wildlife refuges in downslope areas of the Project. Groundwater-management alternatives were tested and designed within the framework of the Klamath Basin Restoration Agreement (currently [2013] awaiting authorizing Federal legislation), which would establish a permanent limit on the amount of surface water that can be diverted annually to the Project. Groundwater-management scenarios were evaluated for the period 1970•2004; supplemental groundwater demand by the Project was estimated as the part of irrigation demand that would not have been satisfied by the surface-water diversion allowed under the Klamath Basin Restoration Agreement. Over the 35-year management period, 22 years have supplemental groundwater demand, which ranges from a few thousand acre-feet (acre-ft) to about 100,000 acre-ft in the driest years. The results of the groundwater-management model indicate that supplemental groundwater pumping by the Project can be managed to avoid adverse effects to groundwater discharge that supports critical aquatic habitat. The existing configuration of wells in the Project would be able to meet groundwater-pumping goals in 14 of the 22 years with supplemental groundwater demand; however, substantial irrigation shortages can be expected during drought periods when the demand for supplemental groundwater is highest. The maximum irrigation-season withdrawal calculated by the groundwater-management model is about 60,000 acre-ft, the average withdrawal in drought years is about 54,000 acre-ft, and the amount of unmet groundwater demand reaches a maximum of about 45,000 acre-ft. A comparison of optimized groundwater withdrawals by geographic region shows that the highest annual withdrawals are associated with wells in the Tule Lake and Klamath Valley regions of the Project. The patterns of groundwater withdrawal also show that a substantial amount of the available pumping capacity is unused due to the restrictions imposed by drawdown constraints. Subsequent model applications were used to evaluate the sensitivity of optimization results to various factors. A sensitivity analysis quantified the changes in optimized groundwater withdrawals that result from changes in drawdown-constraint limits. The analysis showed the potential for substantial increases in withdrawals of groundwater with less restrictive drawdown limits at drawdown-control sites in the California part of the model. Systematic variation of the drains-constraint limit yielded a trade-off curve between optimized groundwater withdrawals and the allowable reduction in groundwater discharge to the Project drain system. Additional model applications were used to assess the value of increasing the pumping capacity of the network of wells serving the Project, and the relation between reduced off-Project groundwater pumping and increased pumping by Project irrigators.

California;Oregon↗
USGS1991

System requirements specification for the U.S. Geological Survey's National Water Information System II

The U.S. Geological Survey's Water Resources Division is designing and developing a new computer software system for processing and storing hydrologic data. This system, the National Water Information System (NWIS-II) will replace the current water-data and information systems: the National Water Data Storage and Retrieval System (WATSTORE), the National Water Data Exchange (NAWDEX), and the National Water-Use Information System, as well as the current National Water Information System (NWIS-I). The new system will be utilized across the Nation on the Distributed Information System (DIS-II), a network of 32-bit microcomputers on a wide-area network of desktop workstations and related hardware. The purpose of the NWIS-II System Requirements Specification is to integrate requirements described by eight User Groups representing the disciplines for Surface Water, Ground Water, Water Quality, Water Sediment, Water Use, Biology, Geographic Information, and National Water Data Exchange. The requirements specified in this document will serve as the framework for subsequent design and development activities throughout the life cycle of NWIS-II to ensure that the development products reflect the needs of the users. Specification details and associated data-base plans are contained in the description of the integrated functional requirements, the logical data model and the data dictionary, the plan for transferring data from the existing system to NWIS-II, and the descriptions of performance requirements and design constraints. The NWIS-II will be consistent across hydrologic disciplines and the other major Division software systems. The color-graphics desktop environment of NWIS-II will utilize multi-window and multi-tasking capabilities with multilevel of help for the users. Data will be distributed among nodes and be automatically accessible during input, editing, verification and analysis of data. Hydrologic data will be cataloged independent of the Environmental Protection Agency's storage and retrieval (STORET) codes. Character, digital, and graphical data will be entered into NWIS-II from digital and analog recorders, external files, or keyboard through standard and user-defined input forms. Data will be verified manually or automatically during input, retrieval, and editing of data. Numerous reference lists will be maintained so that entry of codes on forms will not be required. User-defined series of computer actions for standard programs will be supported for processing basic data and other frequently repeated processes. Data will be verified and exchanged through links to other DIS-II software, including a Geographic Information System, and selected external software. Quality assurance of data will include aging of data through change on status type and tracking access violations. Output of data will be to a variety of media in standard and user-defined formats. The data base will be preserved by operations such as backup, recovery, audit trails, archiving, and data histories. In addition, an index of water data from USGS and other agencies will be maintained.

Open-File Report↗
USGS2016

Forecasting tidal marsh elevation and habitat change through fusion of Earth observations and a process model

Reducing uncertainty in data inputs at relevant spatial scales can improve tidal marsh forecasting models, and their usefulness in coastal climate change adaptation decisions. The Marsh Equilibrium Model (MEM), a one-dimensional mechanistic elevation model, incorporates feedbacks of organic and inorganic inputs to project elevations under sea-level rise scenarios. We tested the feasibility of deriving two key MEM inputs—average annual suspended sediment concentration (SSC) and aboveground peak biomass—from remote sensing data in order to apply MEM across a broader geographic region. We analyzed the precision and representativeness (spatial distribution) of these remote sensing inputs to improve understanding of our study region, a brackish tidal marsh in San Francisco Bay, and to test the applicable spatial extent for coastal modeling. We compared biomass and SSC models derived from Landsat 8, DigitalGlobe WorldView-2, and hyperspectral airborne imagery. Landsat 8-derived inputs were evaluated in a MEM sensitivity analysis. Biomass models were comparable although peak biomass from Landsat 8 best matched field-measured values. The Portable Remote Imaging Spectrometer SSC model was most accurate, although a Landsat 8 time series provided annual average SSC estimates. Landsat 8-measured peak biomass values were randomly distributed, and annual average SSC (30 mg/L) was well represented in the main channels (IQR: 29–32 mg/L), illustrating the suitability of these inputs across the model domain. Trend response surface analysis identified significant diversion between field and remote sensing-based model runs at 60 yr due to model sensitivity at the marsh edge (80–140 cm NAVD88), although at 100 yr, elevation forecasts differed less than 10 cm across 97% of the marsh surface (150–200 cm NAVD88). Results demonstrate the utility of Landsat 8 for landscape-scale tidal marsh elevation projections due to its comparable performance with the other sensors, temporal frequency, and cost. Integration of remote sensing data with MEM should advance regional projections of marsh vegetation change by better parameterizing MEM inputs spatially. Improving information for coastal modeling will support planning for ecosystem services, including habitat, carbon storage, and flood protection.

California↗