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USGS2023

Supervised versus unsupervised approaches to classification of accelerometry data

Sophisticated animal-borne sensor systems are increasingly providing novel insight into how animals behave and move. Despite their widespread use in ecology, the diversity and expanding quality and quantity of data they produce have created a need for robust analytical methods for biological interpretation. Machine learning tools are often used to meet this need. However, their relative effectiveness is not well known and, in the case of unsupervised tools, given that they do not use validation data, their accuracy can be difficult to assess. We evaluated the effectiveness of supervised ( n = 6), semi-supervised ( n = 1), and unsupervised ( n = 2) approaches to analyzing accelerometry data collected from critically endangered California condors ( Gymnogyps californianus ). Unsupervised K-means and EM (expectation–maximization) clustering approaches performed poorly, with adequate classification accuracies of <0.8 but very low values for kappa statistics (range: −0.02 to 0.06). The semi-supervised nearest mean classifier was moderately effective at classification, with an overall classification accuracy of 0.61 but effective classification only of two of the four behavioral classes. Supervised random forest (RF) and k-nearest neighbor (kNN) machine learning models were most effective at classification across all behavior types, with overall accuracies >0.81. Kappa statistics were also highest for RF and kNN, in most cases substantially greater than for other modeling approaches. Unsupervised modeling, which is commonly used for the classification of a priori-defined behaviors in telemetry data, can provide useful information but likely is instead better suited to post hoc definition of generalized behavioral states. This work also shows the potential for substantial variation in classification accuracy among different machine learning approaches and among different metrics of accuracy. As such, when analyzing biotelemetry data, best practices appear to call for the evaluation of several machine learning techniques and several measures of accuracy for each dataset under consideration.

Ecology and Evolution↗

USGS2018

Combining nutrient, productivity, and landscape-based regressions improves predictions of lake nutrients and provides insight into nutrient coupling at macroscales

Empirical nutrient models that describe lake nutrient, productivity, and water clarity relationships among lakes play a prominent role in limnology. Landscape-based regressions are also used to understand macroscale variability of lake nutrients, clarity, and productivity (hereafter referred to as nutrient-productivity). Predictions from both models are used to inform eutrophication management globally. To date, these two classes of models are generally conducted separately, which ignores the known dependencies among nutrient-productivity variables. We present a statistical model that integrates nutrient-productivity and landscape-based regressions—where lake nutrients, productivity, and clarity variables are modeled jointly. We fitted a joint nutrient-productivity model to over 7000 lakes with three nutrients (total phosphorus, total nitrogen, nitrate concentrations), chlorophyll a concentrations, and Secchi disk depth as response variables and landscape features as predictor variables. Because lakes in different regions respond to landscape features differently, we focused our analysis on two subregions with different dominant land uses, the agricultural Midwest and the forested Northeast U.S. Predictive performance was enhanced by modeling nutrient-productivity variables jointly. We also found strong evidence that nutrient-productivity variables were coupled, and that only nitrate may be decoupled from other nutrient-productivity variables in the forested region. We speculate that these regional differences may be related to differences in the strength of biogeochemical cycles and stoichiometric controls between these regions. Jointly modeling nutrient-productivity variables in lakes effectively integrates the two dominant approaches for studying lakes nutrient-productivity relationships and provides novel insight into macroscale patterns of the coupling of nutrients, chlorophyll, and water clarity in lakes.

Limnology and Oceanography↗

USGS2023

Adjacent and downstream effects of forest harvest on the distribution and abundance of larval headwater stream amphibians in the Oregon Coast Range

Forest harvest is a primary landscape-scale management action affecting riparian forests. Although concerns about impacts of forest harvest on stream amphibians is generally limited to areas adjacent to harvest, there is a paucity of information regarding potential downstream effects of forest harvest on these species. We designed a before-after, control-impact (BACI) experiment to quantify potential impacts of clearcut logging that included 12-m buffers or smaller variable-width buffers on the distribution and abundance of headwater stream amphibians in adjacent and downstream areas. We sampled larval coastal tailed frogs ( Ascaphus truei ), coastal giant salamanders ( Dicamptodon tenebrosus ), and Columbia torrent salamanders ( Rhyacotriton kezeri ) across 3,915 sampling occasions that spanned 13 study reaches in 2008–2011 (pre-harvest) and 2013–2016 (post-harvest) as part of the Trask River Watershed Study in the Oregon Coast Range, U.S.A. We analyzed these data using occupancy models to estimate occupancy and (when possible) relative abundance, while accounting for various sources of imperfect detection. All species exhibited reduced occupancy adjacent to clearcuts with variable-width buffers (odds ratios [ORs] ranged = 0.24–0.48), and these negative impacts were not always diminished when increasing the buffer size to 12 m (ORs ranged = 0.20–3.56). Dicamptodon tenebrosus was the only species to have occupancy impacted in downstream areas, and this negative impact was related to clearcut logging with uniform 12-m buffers (OR = 0.60). This species was also the only species to have abundance negatively impacted by forest harvest in downstream areas (OR = 0.41 with uniform 12-m buffers, OR = 0.38 with variable-width buffers), albeit impacts to abundance were not evaluated for R. kezeri . Ascaphus truei abundance increased in areas downstream of clearcut logging with uniform 12-m buffers (OR = 2.92). Although we found the direction and magnitude of responses varied by species, our study confirms that clearcut logging can have negative impacts on amphibians that inhabit the adjacent stream areas. Perhaps more importantly, we also found that forest harvest can have negative effects on stream amphibians downstream of the harvested area and that increasing the buffer size to 12 m did not necessarily diminish these impacts in adjacent and downstream areas. Altogether, our study provides a nuanced picture of adjacent and downstream effects of forest harvest on three endemic headwater stream amphibians, and our findings demonstrate that forest management practices should consider downstream effects on aquatic taxa when assessing the impact of harvesting trees near headwater streams.

Oregon↗

USGS2018

Mapping forest change using stacked generalization: An ensemble approach

The ever-increasing volume and accessibility of remote sensing data has spawned many alternative approaches for mapping important environmental features and processes. For example, there are several viable but highly varied strategies for using time series of Landsat imagery to detect changes in forest cover. Performance among algorithms varies across complex natural systems, and it is reasonable to ask if aggregating the strengths of an ensemble of classifiers might result in increased overall accuracy. Relatively simple rules have been used in the past to aggregate classifications among remotely sensed maps (e.g. using majority predictions), and in other fields, empirical models have been used to create situationally specific algorithm weights. The latter process, called “stacked generalization” (or “stacking”), typically uses a parametric model for the fusion of algorithm outputs. We tested the performance of several leading forest disturbance detection algorithms against ensembles of the outputs of those same algorithms based upon stacking using both parametric and Random Forests-based fusion rules. Stacking using a Random Forests model cut omission and commission error rates in half in many cases in relation to individual change detection algorithms, and cut error rates by one quarter compared to more conventional parametric stacking. Stacking also offers two auxiliary benefits: alignment of outputs to the precise definitions built into a particular set of empirical calibration data; and, outputs which may be adjusted such that map class totals match independent estimates of change in each year. In general, ensemble predictions improve when new inputs are added that are both informative and uncorrelated with existing ensemble components. As increased use of cloud-based computing makes ensemble mapping methods more accessible, the most useful new algorithms may be those that specialize in providing spectral, temporal, or thematic information not already available through members of existing ensembles.

Remote Sensing of Environment↗

USGS2005

Comparison of constitutive flow resistance equations based on the Manning and Chezy equations applied to natural rivers

A set of conceptually derived in‐bank river discharge–estimating equations (models), based on the Manning and Chezy equations, are calibrated and validated using a database of 1037 discharge measurements in 103 rivers in the United States and New Zealand. The models are compared to a multiple regression model derived from the same data. The comparison demonstrates that in natural rivers, using an exponent on the slope variable of 0.33 rather than the traditional value of 0.5 reduces the variance associated with estimating flow resistance. Mean model uncertainty, assuming a constant value for the conductance coefficient, is less than 5% for a large number of estimates, and 67% of the estimates would be accurate within 50%. The models have potential application where site‐specific flow resistance information is not available and can be the basis for (1) a general approach to estimating discharge from remotely sensed hydraulic data, (2) comparison to slope‐area discharge estimates, and (3) large‐scale river modeling.

Water Resources Research↗

USGS2014

Pre‐Cambrian and Paleozoic vulcanism of interior Alaska

The history of vulcanism in Alaska is a topic of great universal interest, but one which has had no adequate treatment. For some years the writer has been accumulating comparative data on this subject, and it is hoped that this information may some time be sufficiently amplified and coordinated to justify a general description of the sequential igneous history of Alaska. The scope of such an undertaking, however, can well be appreciated from the statement that Alaska is nearly a fifth the size of the United States, and that geologic studies have shown that igneous rocks have originated in Alaska in every geologic period, excepting perhaps the Cambrian and the Silurian. Therefore, in the present paper, it has seemed best to present only a part of this interesting record, and perhaps in subsequent papers to expand the areal and geologic limits of discussion. ©1935. American Geophysical Union. All Rights Reserved.

Eos, Transactions, American Geophysical Union↗

USGS2026

Per- and polyfluoroalkyl substances (PFAS) and other contaminants of concern in tribal waters of Montana

We assessed potential exposures to a broad suite of contaminants (inorganic, organic and microbial) in culturally important surface waters from three watersheds in a northern plains Native American community (Apsáalooke [Crow Tribe of Montana]) in south-central Montana, United States, with water insecurity concerns. Inorganic (37), organic (435) and microbial (3) constituents were assessed in 12 surface water sites from the Pryor Creek ( n = 2), Bighorn River ( n = 2) and Little Bighorn River ( n = 8) valleys. Twenty-six organics, 33 inorganics and Escherichia coli were detected. Despite relatively low concentrations in surface waters within the Crow Reservation, mixture toxicity indicated prevalent chronic ecological effects and human-health secondary contact (recreation) effects at multiple sites. Further, to address Tribal concerns over the prevalence and corresponding risks of per- and polyfluoroalkyl substances (PFAS), we sampled water, sediment, biofilms and fish at a limited number of locations in the Little Bighorn River. Results indicated that PFAS were prevalent in fish tissues, including whole blood and filets, and to a lesser extent in biofilms, despite few detections in water and sediment samples. This is the first attempt to document environmental PFAS contamination within the reservation and the potential human-health concerns for the general population from consumption of recreational/subsistence fish. Overall, this effort provided preliminary information on the contaminant mixtures present and their potential health implications, which can support the protection of community health and culturally meaningful resources across the Crow Reservation.

Montana↗

USGS2022

Identifying monitoring information needs that support the management of fish in large rivers

Management actions intended to benefit fish in large rivers can directly or indirectly affect multiple ecosystem components. Without consideration of the effects of management on non-target ecosystem components, unintended consequences may limit management efficacy. Monitoring can help clarify the effects of management actions, including on non-target ecosystem components, but only if data are collected to characterize key ecosystem processes that could affect the outcome. Scientists from across the U.S. convened to develop a conceptual model that would help identify monitoring information needed to better understand how natural and anthropogenic factors affect large river fishes. We applied the conceptual model to case studies in four large U.S. rivers. The application of the conceptual model indicates the model is flexible and relevant to large rivers in different geographic settings and with different management challenges. By visualizing how natural and anthropogenic drivers directly or indirectly affect cascading ecosystem tiers, our model identified critical information gaps and uncertainties that, if resolved, could inform how to best meet management objectives. Despite large differences in the physical and ecological contexts of the river systems, the case studies also demonstrated substantial commonalities in the data needed to better understand how stressors affect fish in these systems. For example, in most systems information on river discharge and water temperature were needed and available. Conversely, information regarding trophic relationships and the habitat requirements of larval fishes were generally lacking. This result suggests that there is a need to better understand a set of common factors across large-river systems. We provide a stepwise procedure to facilitate the application of our conceptual model to other river systems and management goals.

Environmental Management↗

USGS2009

The SCEC/USGS dynamic earthquake rupture code verification exercise

Numerical simulations of earthquake rupture dynamics are now common, yet it has been difficult to test the validity of these simulations because there have been few field observations and no analytic solutions with which to compare the results. This paper describes the Southern California Earthquake Center/U.S. Geological Survey (SCEC/USGS) Dynamic Earthquake Rupture Code Verification Exercise, where codes that simulate spontaneous rupture dynamics in three dimensions are evaluated and the results produced by these codes are compared using Web-based tools. This is the first time that a broad and rigorous examination of numerous spontaneous rupture codes has been performed—a significant advance in this science. The automated process developed to attain this achievement provides for a future where testing of codes is easily accomplished. Scientists who use computer simulations to understand earthquakes utilize a range of techniques. Most of these assume that earthquakes are caused by slip at depth on faults in the Earth, but hereafter the strategies vary. Among the methods used in earthquake mechanics studies are kinematic approaches and dynamic approaches. The kinematic approach uses a computer code that prescribes the spatial and temporal evolution of slip on the causative fault (or faults). These types of simulations are very helpful, especially since they can be used in seismic data inversions to relate the ground motions recorded in the field to slip on the fault(s) at depth. However, these kinematic solutions generally provide no insight into the physics driving the fault slip or information about why the involved fault(s) slipped that much (or that little). In other words, these kinematic solutions may lack information about the physical dynamics of earthquake rupture that will be most helpful in forecasting future events. To help address this issue, some researchers use computer codes to numerically simulate earthquakes and construct dynamic, spontaneous rupture (hereafter called “spontaneous rupture”) solutions. For these types of numerical simulations, rather than prescribing the slip function at each location on the fault(s), just the friction constitutive properties and initial stress conditions are prescribed. The subsequent stresses and fault slip spontaneously evolve over time as part of the elasto-dynamic solution. Therefore, spontaneous rupture computer simulations of earthquakes allow us to include everything that we know, or think that we know, about earthquake dynamics and to test these ideas against earthquake observations.

Seismological Research Letters↗

USGS2010

Factors influencing nesting success of king eiders on northern Alaska's Coastal Plain

King eider (Somateria spectabilis) populations have declined markedly in recent decades for unknown reasons. Nest survival is one component of recruitment, and a female's chance of reproductive success increases with her ability to choose an appropriate nesting strategy. We estimated variation in daily nest survival of king eiders at 2 sites, Teshekpuk and Kuparuk, Alaska, USA, 2002-2005. We evaluated both a priori and exploratory competing models of nest survival that considered importance of nest concealment, seclusion, and incubation constancy as strategies to avoid 2 primary egg predators, avian (Larus spp., Stercorarius spp., and Corvus corax) and fox (Alopex lagopus). We used generalized nonlinear techniques to examine factors affecting nest survival rates and information-theoretic approaches to select among competing models. Estimated nest survival, accounting for a nest visitation effect, varied considerably across sites and years (0.21-0.57); however, given our small sample size, much of this variation maybe attributable to sampling variation (??process = 0.007, 95% CI: 0.003-0.070). Nest survival was higher at Kuparuk than Teshekpuk in all years; however, due to the correlative nature of our data, we cannot determine the underlying causes with any certainty. We found mixed support for the concealed breeding strategy, females derived no benefit from nesting in areas with more willow (Salix spp.; measure of concealment) except that the observer effect diminished as willow cover increased. We suggest these patterns are due to conflicting predation pressures. Nest survival was not higher on islands (measure of seclusion) or with increased incubation constancy but was higher post-fox removal, indicating that predator control on breeding grounds could be a viable management option. Nest survival was negatively affected by our nest visitations, most likely by exposing the nest to avian scavengers. We recommend precautions be taken to limit the effects of nest visits in future studies and to consider them as a possible negative bias in estimated nest survival. Future models of the impacts of development within the breeding grounds of king eider should consider the influence of humans in the vicinity of nests.

Journal of Wildlife Management↗

USGS2012

U.S. Geological Survey community for data integration: data upload, registry, and access tool

As a leading science and information agency and in fulfillment of its mission to provide reliable scientific information to describe and understand the Earth, the U.S. Geological Survey (USGS) ensures that all scientific data are effectively hosted, adequately described, and appropriately accessible to scientists, collaborators, and the general public. To succeed in this task, the USGS established the Community for Data Integration (CDI) to address data and information management issues affecting the proficiency of earth science research. Through the CDI, the USGS is providing data and metadata management tools, cyber infrastructure, collaboration tools, and training in support of scientists and technology specialists throughout the project life cycle. One of the significant tools recently created to contribute to this mission is the Uploader tool. This tool allows scientists with limited data management resources to address many of the key aspects of the data life cycle: the ability to protect, preserve, publish and share data. By implementing this application inside ScienceBase, scientists also can take advantage of other collaboration capabilities provided by the ScienceBase platform.

Fact Sheet↗

USGS2020

Effects of urbanization on water quality in the Edwards aquifer, San Antonio and Bexar County, Texas

Overview Continuous water-quality monitoring data and chemical analysis of surface-water and groundwater samples collected during 2017–19 in the recharge zone of the Edwards aquifer were used to develop a better understanding of the surface-water/groundwater connection in and around Bexar County in south-central Texas. This fact sheet is provided to inform water-resource managers, city planners, the scientific community, and the general public about the effects of urbanization on water quality in the Edwards aquifer recharge zone.

Texas↗

USGS2008

Preliminary Geologic Map of the North-Central Part of the Alamosa 30' x 60' Quadrangle, Alamosa, Conejos and Costilla Counties, Colorado

This geologic map presents new polygon (geologic map unit contacts) and line (terrace and lacustrine spit/barrier bar) vector data for a map comprised of four 7.5' quadrangles in the north-central part of the Alamosa, Colorado, 30' x 60' quadrangle. The quadrangles include Baldy, Blanca, Blanca SE, and Lasauses. The map database, compiled at 1:50,000 scale from new 1:24,000-scale mapping, provides geologic coverage of an area of current hydrogeologic, tectonic, and stratigraphic interest. The mapped area is located primarily in Costilla County, but contains portions of Alamosa and Conejos Counties, and includes the town of Blanca in its northeastern part. The map area is mainly underlain by surficial geologic materials (fluvial and lacustrine deposits, and eolian sand), but Tertiary volcanic and volcaniclastic rocks crop out in the San Luis Hills, which are in the central and southern parts of the mapped area. The surficial geology of this area has never been mapped at any scale greater than 1:250,000 (broad reconnaissance), so this new map provides important data for ground-water assessments, engineering geology, and the Quaternary geologic history of the San Luis Basin. Newly discovered shoreline deposits are of particular interest (sands and gravels) that are associated with the high-water stand of Lake Alamosa, a Pliocene to middle Pleistocene lake that occupied the San Luis basin prior to its overflow and cutting of a river gorge through the San Luis Hills. After the lake drained, the Rio Grande system included Colorado drainages for the first time since the Miocene (>5.3 Ma). In addition, Servilleta Basalt, which forms the Basaltic Hills on the east margin of the map area, is dated at 3.79+or-0.17 Ma, consistent with its general age range of 3.67-4.84 Ma. This map provides new geologic information for better understanding ground-water flow paths in and adjacent to the Rio Grande system. The map abuts U.S. Geological Survey Open File Report 2005-1392 (a map of the northwestern part of the Alamosa 30' x 60' quadrangle map) to the west and U.S. Geological Survey Scientific Investigations Map 2965 (Fort Garland 7.5' quadrangle) to the east.

Open-File Report↗

USGS2008

Regional Geochemical Results from Analyses of Stream-Water, Stream-Sediment, Soil, Soil-Water, Bedrock, and Vegetation Samples, Tangle Lakes District, Alaska

We report chemical analyses of stream-water, stream-sediment, soil, soil-water, bedrock, and vegetation samples collected from the headwaters of the Delta River (Tangle Lakes District, Mount Hayes 1:250,000-scale quadrangle) in east-central Alaska for the period June 20-25, 2006. Additionally, we present mineralogic analyses of stream sediment, concentrated by panning. The study area includes the southwestward extent of the Bureau of Land Management (BLM) Delta River Mining District (Bittenbender and others, 2007), including parts of the Delta River Archeological District, and encompasses an area of about 500 km2(approximately bordered by the Denali Highway to the south, near Round Tangle Lake, northward to the foothills of the Alaska Range (fig. 1). The primary focus of this study was the chemical characterization of native materials, especially surface-water and sediment samples, of first-order streams from the headwaters of the Delta River. The impetus for this work was the need, expressed by the Alaska Department of Natural Resources (ADNR), for an inventory of geochemical and hydrogeochemical baseline information about the Delta River Mining District. This information is needed because of a major upturn in exploration, drilling, and general mineral-resources assessments in the region since the late 1990s. Currently, the study area, called the 'MAN Project' area is being explored by Pure Nickel, Inc. (http://www.purenickel.com/s/MAN_Alaska.asp), and includes both Cu-Au-Ag and Ni-Cu-PGE (Pt-Pd-Au-Ag) mining claims. Geochemical data on surface-water, stream-sediment, soil, soil-water, grayleaf willow (Salix glauca L.), and limited bedrock samples are provided along with the analytical methodologies used and panned-concentrate mineralogy. We are releasing the data at this time with only minimal interpretation.

Open-File Report↗

USGS2008

Geologic map of Mount Mazama and Crater Lake Caldera, Oregon, including the database for the geologic map of Mount Mazama and Crater Lake Caldera, Oregon

Crater Lake partly fills one of the most spectacular calderas of the world, an 8-by-10-km basin more than 1 km deep formed by collapse of the volcano known as Mount Mazama (fig. 1) during a rapid series of explosive eruptions about 7,700 years ago. Having a maximum depth of 594 m, Crater Lake is the deepest lake in the United States. Crater Lake National Park, dedicated in 1902, encompasses 645 km2 of pristine forested and alpine terrain, including the lake itself, virtually all of Mount Mazama, and most of the area of the geologic map. The geology of the area was first described in detail by Diller and Patton (1902) and later by Williams (1942), whose vivid account led to international recognition of Crater Lake as the classic collapse caldera. Because of excellent preservation and access, Mount Mazama, Crater Lake caldera, and the deposits formed by the climactic eruption constitute a natural laboratory for study of volcanic and magmatic processes. For example, the climactic ejecta are renowned among volcanologists as evidence for systematic compositional zonation within a subterranean magma chamber. Mount Mazama's climactic eruption also is important as the source of the widespread Mazama ash, a useful Holocene stratigraphic marker throughout the Pacific Northwest, adjacent Canada, and offshore. A detailed bathymetric survey of the floor of Crater Lake in 2000 (Bacon and others, 2002) provides a unique record of postcaldera eruptions, the interplay between volcanism and filling of the lake, and sediment transport within this closed basin. Knowledge of the geology and eruptive history of the Mount Mazama edifice, greatly enhanced by the caldera wall exposures, gives exceptional insight into how large volcanoes of magmatic arcs grow and evolve. Lastly, the many smaller volcanoes of the High Cascades beyond the limits of Mount Mazama are a source of information on the flux of mantle-derived magma through the region. General principles of magmatic and eruptive processes revealed by the present study have been incorporated not only in scientific investigations elsewhere, but in the practical evaluation of hazards (Bacon and others, 1997b) and geothermal resources (Bacon and Nathenson, 1996) in the Crater Lake region. In addition to papers in scientific journals, field trip guides, and the hazard and geothermal reports, the major product of this long-term study of Mount Mazama is the geologic map. The map is unusual because it portrays bedrock (outcrop), surficial, and lake floor geology. Caldera wall geology is depicted in detail on the accompanying geologic panoramas.

Oregon↗

USGS2005

Augmenting two-dimensional hydrodynamic simulations with measured velocity data to identify flow paths as a function of depth on Upper St. Clair River in the Great Lakes basin

Upper St. Clair River, which receives outflow from Lake Huron, is characterized by flow velocities that exceed 7 feet per second and significant channel curvature that creates complex flow patterns downstream from the Blue Water Bridge in the Port Huron, Michigan, and Sarnia, Ontario, area. Discrepancies were detected between depth-averaged velocities previously simulated by a two-dimensional (2D) hydrodynamic model and surface velocities determined from drifting buoy deployments. A detailed ADCP (acoustic Doppler current profiler) survey was done on Upper St. Clair River during July 1–3, 2003, to help resolve these discrepancies. As part of this study, a refined finite-element mesh of the hydrodynamic model used to identify source areas to public water intakes was developed for Upper St. Clair River. In addition, a numerical procedure was used to account for radial accelerations, which cause secondary flow patterns near channel bends. The refined model was recalibrated to better reproduce local velocities measured in the ADCP survey. ADCP data also were used to help resolve the remaining discrepancies between simulated and measured velocities and to describe variations in velocity with depth. Velocity data from ADCP surveys have significant local variability, and statistical processing is needed to compute reliable point estimates. In this study, velocity innovations were computed for seven depth layers posited within the river as the differences between measured and simulated velocities. For each layer, the spatial correlation of velocity innovations was characterized by use of variogram analysis. Results were used with kriging to compute expected innovations within each layer at applicable model nodes. Expected innovations were added to simulated velocities to form integrated velocities, which were used with reverse particle tracking to identify the expected flow path near a sewage outfall as a function of flow depth. Expected particle paths generated by use of the integrated velocities showed that surface velocities in the upper layers tended to originate nearer the Canadian shoreline than velocities near the channel bottom in the lower layers. Therefore, flow paths to U.S. public water intakes located on the river bottom are more likely to be in the United States than withdrawals near the water surface. Integrated velocities in the upper layers are generally consistent with the surface velocities indicated by drifting-buoy deployments. Information in the 2D hydrodynamic model and the ADCP measurements was insufficient to describe the vertical flow component. This limitation resulted in the inability to account for vertical movements on expected flow paths through Upper St. Clair River. A three dimensional hydrodynamic model would be needed to account for these effects.

Scientific Investigations Report↗

USGS2014

Methods for estimating annual exceedance-probability discharges and largest recorded floods for unregulated streams in rural Missouri

Regression analysis techniques were used to develop a set of equations for rural ungaged stream sites for estimating discharges with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities, which are equivalent to annual flood-frequency recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. Basin and climatic characteristics were computed using geographic information software and digital geospatial data. A total of 35 characteristics were computed for use in preliminary statewide and regional regression analyses. Annual exceedance-probability discharge estimates were computed for 278 streamgages by using the expected moments algorithm to fit a log-Pearson Type III distribution to the logarithms of annual peak discharges for each streamgage using annual peak-discharge data from water year 1844 to 2012. Low-outlier and historic information were incorporated into the annual exceedance-probability analyses, and a generalized multiple Grubbs-Beck test was used to detect potentially influential low floods. Annual peak flows less than a minimum recordable discharge at a streamgage were incorporated into the at-site station analyses. An updated regional skew coefficient was determined for the State of Missouri using Bayesian weighted least-squares/generalized least squares regression analyses. At-site skew estimates for 108 long-term streamgages with 30 or more years of record and the 35 basin characteristics defined for this study were used to estimate the regional variability in skew. However, a constant generalized-skew value of -0.30 and a mean square error of 0.14 were determined in this study. Previous flood studies indicated that the distinct physical features of the three physiographic provinces have a pronounced effect on the magnitude of flood peaks. Trends in the magnitudes of the residuals from preliminary statewide regression analyses from previous studies confirmed that regional analyses in this study were similar and related to three primary physiographic provinces. The final regional regression analyses resulted in three sets of equations. For Regions 1 and 2, the basin characteristics of drainage area and basin shape factor were statistically significant. For Region 3, because of the small amount of data from streamgages, only drainage area was statistically significant. Average standard errors of prediction ranged from 28.7 to 38.4 percent for flood region 1, 24.1 to 43.5 percent for flood region 2, and 25.8 to 30.5 percent for region 3. The regional regression equations are only applicable to stream sites in Missouri with flows not significantly affected by regulation, channelization, backwater, diversion, or urbanization. Basins with about 5 percent or less impervious area were considered to be rural. Applicability of the equations are limited to the basin characteristic values that range from 0.11 to 8,212.38 square miles (mi 2 ) and basin shape from 2.25 to 26.59 for Region 1, 0.17 to 4,008.92 mi 2 and basin shape 2.04 to 26.89 for Region 2, and 2.12 to 2,177.58 mi 2 for Region 3. Annual peak data from streamgages were used to qualitatively assess the largest floods recorded at streamgages in Missouri since the 1915 water year. Based on existing streamgage data, the 1983 flood event was the largest flood event on record since 1915. The next five largest flood events, in descending order, took place in 1993, 1973, 2008, 1994 and 1915. Since 1915, five of six of the largest floods on record occurred from 1973 to 2012.

Missouri↗

USGS2017

Geologic field trip guide to Mount Mazama and Crater Lake Caldera, Oregon

Crater Lake partly fills one of the most spectacular calderas of the world—an 8 by 10 kilometer (km) basin more than 1 km deep formed by collapse of the Mount Mazama volcano during a rapid series of explosive eruptions ~7,700 years ago. Having a maximum depth of 594 meters (m), Crater Lake is the deepest lake in the United States. Crater Lake National Park, dedicated in 1902, encompasses 645 square kilometers (km 2 ) of pristine forested and alpine terrain, including the lake itself, and virtually all of Mount Mazama. The geology of the area was first described in detail by Diller and Patton (1902) and later by Williams (1942), whose vivid account led to international recognition of Crater Lake as the classic collapse caldera. Because of excellent preservation and access, Mount Mazama, Crater Lake caldera, and the deposits formed by the climactic eruption constitute a natural laboratory for study of volcanic and magmatic processes. For example, the climactic ejecta are renowned among volcanologists as evidence for systematic compositional zonation within a subterranean magma chamber. Mount Mazama’s climactic eruption also is important as the source of the widespread Mazama ash, a useful Holocene stratigraphic marker throughout the Pacific Northwest United States, adjacent Canada, and offshore. A detailed bathymetric survey of the floor of Crater Lake in 2000 (Bacon and others, 2002) provides a unique record of postcaldera eruptions, the interplay between volcanism and filling of the lake, and sediment transport within this closed basin. Knowledge of the geology and eruptive history of the Mount Mazama edifice, enhanced by the caldera wall exposures, gives exceptional insight into how large volcanoes of magmatic arcs grow and evolve. In addition, many smaller volcanoes of the High Cascades beyond the limits of Mount Mazama provide information on the flux of mantle-derived magma through the region. General principles of magmatic and eruptive processes revealed by geologic research at Crater Lake have been incorporated not only in scientific investigations elsewhere, but also in the practical evaluation of local hazards (Bacon and others, 1997b) and geothermal resources (Bacon and Nathenson, 1996). The 1:24,000-scale geologic map of Mount Mazama and Crater Lake caldera (Bacon, 2008) is unusual because it portrays bedrock (outcrop), surficial, and lake floor geology. Caldera wall geology is depicted in detail on the accompanying geologic panoramas, and bedrock geology is shown in a 1:50,000-scale geologic map. This field guide supersedes earlier geology guides of Crater Lake (Bacon, 1987, 1989).

Oregon↗