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At least 937 records · Page 52Linked to original sources
USGS1990

Guidelines for collection and field analysis of water-quality samples from streams in Texas

This manual provides standardized guidelines and quality-control procedures for the collection and preservation of water-quality samples and defines procedures for making field analyses of unstable constituents or properties. Descriptions and procedures are given for several methods of sampling for which a variety of samplers may be used. Sample-processing devices such as sample churns and filtration apparatus are discussed along with methods of cleaning. Analyses for unstable constituents or properties are by necessity performed in the field. This manual addresses analytical techniques and quality assurance for: (1) Water temperature; (2) specific conductance; (3) pH; (4) alkalinity; (5) dissolved oxygen; and (6) bacteria.

Texas↗
USGS2010

Occam's shadow: levels of analysis in evolutionary ecology - where to next?

Evolutionary ecology is the study of evolutionary processes, and the ecological conditions that influence them. A fundamental paradigm underlying the study of evolution is natural selection. Although there are a variety of operational definitions for natural selection in the literature, perhaps the most general one is that which characterizes selection as the process whereby heritable variation in fitness associated with variation in one or more phenotypic traits leads to intergenerational change in the frequency distribution of those traits. The past 20 years have witnessed a marked increase in the precision and reliability of our ability to estimate one or more components of fitness and characterize natural selection in wild populations, owing particularly to significant advances in methods for analysis of data from marked individuals. In this paper, we focus on several issues that we believe are important considerations for the application and development of these methods in the context of addressing questions in evolutionary ecology. First, our traditional approach to estimation often rests upon analysis of aggregates of individuals, which in the wild may reflect increasingly non-random (selected) samples with respect to the trait(s) of interest. In some cases, analysis at the aggregate level, rather than the individual level, may obscure important patterns. While there are a growing number of analytical tools available to estimate parameters at the individual level, and which can cope (to varying degrees) with progressive selection of the sample, the advent of new methods does not reduce the need to consider carefully the appropriate level of analysis in the first place. Estimation should be motivated a priori by strong theoretical analysis. Doing so provides clear guidance, in terms of both (i) assisting in the identification of realistic and meaningful models to include in the candidate model set, and (ii) providing the appropriate context under which the results are interpreted. Second, while it is true that selection (as defined) operates at the level of the individual, the selection gradient is often (if not generally) conditional on the abundance of the population. As such, it may be important to consider estimating transition rates conditional on both the parameter values of the other individuals in the population (or at least their distribution), and population abundance. This will undoubtedly pose a considerable challenge, for both single- and multi-strata applications. It will also require renewed consideration of the estimation of abundance, especially for open populations. Thirdly, selection typically operates on dynamic, individually varying traits. Such estimation may require characterizing fitness in terms of individual plasticity in one or more state variables, constituting analysis of the norms of reaction of individuals to variable environments. This can be quite complex, especially for traits that are under facultative control. Recent work has indicated that the pattern of selection on such traits is conditional on the relative rates of movement among and frequency of spatially heterogeneous habitats, suggesting analyses of evolution of life histories in open populations can be misleading in some cases.

Journal of Applied Statistics↗
USGS2021

Optimization of the Idaho National Laboratory water-quality aquifer monitoring network, southeastern Idaho

Long-term monitoring of water-quality data collected from wells at the Idaho National Laboratory (INL) has provided essential information for delineating the movement of radiochemical and chemical wastes in the eastern Snake River Plain aquifer, southeastern Idaho. Since 1949, the U.S. Geological Survey, in cooperation with the U.S. Department of Energy, has maintained as many as 200 wells in the INL water-quality monitoring network. A network design tool, distributed as an R package, was developed to evaluate and optimize groundwater monitoring in the existing network based on water-quality data collected at 153 sampling sites since January 1, 1989. The objective of the optimization design tool is to reduce well monitoring redundancy while retaining sufficient data to reliably characterize water-quality conditions in the aquifer. A spatial optimization was used to identify a set of wells whose removal leads to the smallest increase in the deviation between interpolated concentration maps using the existing and reduced monitoring networks while preserving significant long-term trends and seasonal components in the data. Additionally, a temporal optimization was used to identify reductions in sampling frequencies by minimizing the redundancy in sampling events. Spatial optimization uses an islands genetic algorithm to identify near-optimal network designs removing 10, 20, 30, 40, and 50 wells from the existing monitoring network. With this method, choosing a greater number of wells to remove results in greater cost savings and decreased accuracy of the average relative difference between interpolated maps of the reduced-dataset and the full-dataset. The genetic search algorithm identified reduced networks that best capture the spatial patterns of the average concentration plume while preserving long-term temporal trends at individual wells. Concentration data for 10 analyte types are integrated in a single optimization so that all datasets may be evaluated simultaneously. A constituent was selected for inclusion in the spatial optimization problem when the observations were sufficient to (1) establish a two-range variability model, (2) classify at least one concentration time series as a continuous record block, and (3) make a prediction using the quantile-kriging interpolation method. The selected constituents include sodium, chloride, sulfate, nitrate, carbon tetrachloride, 1,1-dichloroethylene, 1,1,1-trichloroethane, trichloroethylene, tritium, strontium-90, and plutonium-238. In temporal optimization, an iterative-thinning method was used to find an optimal sampling frequency for each analyte-well pair. Optimal frequencies indicate that for many of the wells, samples may be collected less frequently and still be able to characterize the concentration over time. The optimization results indicated that the sample-collection interval may be increased by an of average of 273 days owing to temporal redundancy.

Idaho↗
USGS2006

Semianalytical computation of path lines for finite-difference models

A semianalytical particle tracking method was developed for use with velocities generated from block centered finite-difference ground-water flow models. The method is based on the assumption that each directional velocity component varies linearly within a grid cell in its own coordinate directions. This assumption allows an analytical expression to be obtained describing the flow path within an individual grid cell. Given the initial position of a particle anywhere in a cell, the coordinates of any other point along its path line within the cell, and the time of travel between them, can be computed directly. For steady-state systems, the exit point for a particle entering a cell at any arbitrary location can be computed in a single step. By following the particle as it moves from cell to cell, this method can be used to trace the path of a particle through any multidimensional flow field generated from a block-centered finite-difference flow model.

Ground Water↗
USGS2018

A parasitism-mutualism-predation model consisting of crows, cuckoos and cats with stage-structure and maturation delays on crows and cuckoos

In this paper, a parasitism-mutualism-predation model is proposed to investigate the dynamics of multi-interactions among cuckoos, crows and cats with stage-structure and maturation time delays on cuckoos and crows. The crows permit the cuckoos to parasitize their nestlings (eggs) on the crow chicks (eggs). In return, the cuckoo nestlings produce a malodorous cloacal secretion to protect the crow chicks from predation by the cats, which is apparently beneficial to both the crow and cuckoo population. The multi-interactions, i.e., parasitism and mutualism between the cuckoos (nestlings) and crows (chicks), predation between the cats and crow chicks are modeled both by Holling-type II and Beddington-DeAngelis-type functional responses. The existence of positive equilibria of three subsystems of the model are discussed. The criteria for the global stability of the trivial equilibrium are established by the Krein-Rutman Theorem and other analysis methods. Moreover, the threshold dynamics for the coexistence and weak persistence of the model are obtained, and we show, both analytically and numerically, that the stabilities of the interior equilibria may change with the increasing maturation time delays. We find there exists an evident difference in the dynamical properties of the parasitism-mutualism-predation model based on whether or not we consider the effects of stage-structure and maturation time delays on cuckoos and crows. Inclusion of stage structure results in many varied dynamical complexities which are difficult to encompass without this inclusion.

Journal of Theoretical Biology↗
USGS2013

Gaussian process regression for sensor networks under localization uncertainty

In this paper, we formulate Gaussian process regression with observations under the localization uncertainty due to the resource-constrained sensor networks. In our formulation, effects of observations, measurement noise, localization uncertainty, and prior distributions are all correctly incorporated in the posterior predictive statistics. The analytically intractable posterior predictive statistics are proposed to be approximated by two techniques, viz., Monte Carlo sampling and Laplace's method. Such approximation techniques have been carefully tailored to our problems and their approximation error and complexity are analyzed. Simulation study demonstrates that the proposed approaches perform much better than approaches without considering the localization uncertainty properly. Finally, we have applied the proposed approaches on the experimentally collected real data from a dye concentration field over a section of a river and a temperature field of an outdoor swimming pool to provide proof of concept tests and evaluate the proposed schemes in real situations. In both simulation and experimental results, the proposed methods outperform the quick-and-dirty solutions often used in practice.

IEEE Transactions on Signal Processing↗
USGS2013

The environmental-data automated track annotation (Env-DATA) system: linking animal tracks with environmental data

The movement of animals is strongly influenced by external factors in their surrounding environment such as weather, habitat types, and human land use. With advances in positioning and sensor technologies, it is now possible to capture animal locations at high spatial and temporal granularities. Likewise, scientists have an increasing access to large volumes of environmental data. Environmental data are heterogeneous in source and format, and are usually obtained at different spatiotemporal scales than movement data. Indeed, there remain scientific and technical challenges in developing linkages between the growing collections of animal movement data and the large repositories of heterogeneous remote sensing observations, as well as in the developments of new statistical and computational methods for the analysis of movement in its environmental context. These challenges include retrieval, indexing, efficient storage, data integration, and analytical techniques.

Movement Ecology↗
USGS1987

Alleghanian deformation, metamorphism, and granite emplacement in the central Piedmont of the southern Appalachians

Evidence of late Paleozoic (Alleghanian) penetrative deformation, amphilbolite-facies, metamorphism, and syntectonic granite emplacement has been found in an area of the central Piedmont in the southern Appalachians. The High Shoals Granite batholith in the Kings Mountain belt of south-central North Carolina consists of coarse-grained, megacrystic biotite granite with a strong, nearly vertical, gneissoid, foliation, defined by parallel feldspar megacrysts and biotite. U-Ph isotopic data on zircons from the granite yield a concordant age of 317 Ma (Pennsylvanian). This pervasively deformed late Paleozoic granite in the central Piedmont is far west of those known in the Kiokee and Raleigh belts. Field relationships indicate that the High Shoals Granite was emplaced during the late stages of regional F2 folding, close in time to the thermal peak of amphibolite-facies metamorphism. Mineral assemblages typical of Barrovian metamorphism are found in zones of decreasing grade away from the High Shoals contact. These zones, delimited by a kyanite(out)-sillimanite (in) isograd which completely surrounds the batholith and by part of a regional chloritoid (out)-staurolite (in) isograd west and southwest of it, conform to the shape of the batholith and cut across F2 folds. Furthermore, hornblendes from epidoteamphibolite facies to upper amphibolite facies metamorphic rocks in the Kings Mountain belt of North Carolina and South Carolina yield 40Ar/39Ar plateau ages of 318 to 323 Ma. These dates are analytically the same as the crystallization age of High Shoals Granite as established of zireon using the U-Ph method and demonstrate the synchroneity of intrusion of the High Shoals with the dominant regional metamorphism in this part of the Kings Mountain belt.

Southern Appalachians↗
USGS2005

Quality of nutrient data from streams and ground water sampled during water years 1992-2001

Proper interpretation of water-quality data requires consideration of the effects that bias and variability might have on measured constituent concentrations. In this report, methods are described to estimate the bias due to contamination of samples in the field or laboratory and the variability due to sample collection, processing, shipment, and analysis. Contamination can adversely affect interpretation of measured concentrations in comparison to standards or criteria. Variability can affect interpretation of small differences between individual measurements or mean concentrations. Contamination and variability are determined for nutrient data from quality-control samples (field blanks and replicates) collected as part of the National Water-Quality Assessment (NAWQA) Program during water years 1992-2001. Statistical methods are used to estimate the likelihood of contamination and variability in all samples. Results are presented for five nutrient analytes from stream samples and four nutrient analytes from ground-water samples. Ammonia contamination can add at least 0.04 milligram per liter in up to 5 percent of all samples. This could account for more than 22 percent of measured concentrations at the low range of aquatic-life criteria (0.18 milligram per liter). Orthophosphate contamination, at least 0.019 milligram per liter in up to 5 percent of all samples, could account for more than 38 percent of measured concentrations at the limit to avoid eutrophication (0.05 milligram per liter). Nitrite-plus-nitrate and Kjeldahl nitrogen contamination is less than 0.4 milligram per liter in 99 percent of all samples; thus there is no significant effect on measured concentrations of environmental significance. Sampling variability has little or no effect on reported concentrations of ammonia, nitrite-plus-nitrate, orthophosphate, or total phosphorus sampled after 1998. The potential errors due to sampling variability are greater for the Kjeldahl nitrogen analytes and for total phosphorus sampled before 1999. The uncertainty in a mean of 10 concentrations caused by sampling variability is within a small range (1 to 7 percent) for all nutrients. These results can be applied to interpretation of environmental data collected during water years 1992-2001 in 52 NAWQA study units.

Scientific Investigations Report↗
USGS1968

Determination of discharge during pulsating flow

Pulsating flow in an open channel is a manifestation of unstable-flow conditions in which a series of translatory waves of perceptible magnitude develops and moves rapidly downstream. Pulsating flow is a matter of concern in the design and operation of steep-gradient channels. If it should occur at high stages in a channel designed for stable flow, the capacity of the channel may be inadequate at a discharge that is much smaller than that for which the channel was designed. If the overriding translatory wave carries an appreciable part of the total flow, conventional stream-gaging procedures cannot be used to determine the discharge; neither the conventional instrumentation nor conventional methodology is adequate. A method of determining the discharge during pulsating flow was tested in the Santa Anita Wash flood control channel in Arcadia, Calif., April 16, 1965. Observations of the dimensions and velocities of translatory waves were made during a period of controlled reservoir releases of about 100, 200, and 300 cfs (cubic feet per second). The method of computing discharge was based on (1) computation of the discharge in the overriding waves and (2) computation of the discharge in the shallow-depth, or overrun, part of the flow. Satisfactory results were obtained by this method. However, the procedure used-separating the flow into two components and then treating the shallow-depth component as though it were steady--has no theoretical basis. It is simply an expedient for use until laboratory investigation can provide a satisfactory analytical solution to the problem of computing discharge during pulsating flow. Sixteen months prior to the test in Santa Anita Wash, a robot camera had been designed .and programmed to obtain the data needed to compute discharge by the method described above. The photographic equipment had been installed in Haines Creek flood control channel in Los Angeles, Calif., but it had not been completely tested because of the infrequency of flow in that channel. Because the Santa Anita Wash tests afforded excellent data for analysis, further development of the photographic ,technique at Haines Creek was discontinued. Three methods for obtaining the data needed to compute discharge during pulsating flow are proposed. In two of the methods--the photographic method and the depth-recorder method--the dimensions and velocities of translatory waves are recorded, and discharge is then computed by the procedure developed in this report. The third method?the constant-rate-dye-dilution method--yields the discharge more directly. The discharge is computed from the dye-injection rate and the ratio of the concentration of dye in the injected solution to the concentration of dye in the water sampled at a site downstream. The three methods should be developed and tested in ,the Santa Anita Wash flood control channel under controlled conditions similar to those in the test of April 1965.

Water Supply Paper↗
USGS2014

Path durations for use in the stochastic‐method simulation of ground motions

The stochastic method of ground‐motion simulation assumes that the energy in a target spectrum is spread over a duration D T . D T is generally decomposed into the duration due to source effects (D S ) and to path effects (D P ). For the most commonly used source, seismological theory directly relates D S to the source corner frequency, accounting for the magnitude scaling of D T . In contrast, D P is related to propagation effects that are more difficult to represent by analytic equations based on the physics of the process. We are primarily motivated to revisit D T because the function currently employed by many implementations of the stochastic method for active tectonic regions underpredicts observed durations, leading to an overprediction of ground motions for a given target spectrum. Further, there is some inconsistency in the literature regarding which empirical duration corresponds to D T . Thus, we begin by clarifying the relationship between empirical durations and D T as used in the first author’s implementation of the stochastic method, and then we develop a new D P relationship. The new D P function gives significantly longer durations than in the previous D P function, but the relative contribution of D P to D T still diminishes with increasing magnitude. Thus, this correction is more important for small events or subfaults of larger events modeled with the stochastic finite‐fault method.

Bulletin of the Seismological Society of America↗
USGS1997

Evaluation of unconfined-aquifer parameters from pumping test data by nonlinear least squares

Nonlinear least squares (NLS) with automatic differentiation was used to estimate aquifer parameters from drawdown data obtained from published pumping tests conducted in homogeneous, water-table aquifers. The method is based on a technique that seeks to minimize the squares of residuals between observed and calculated drawdown subject to bounds that are placed on the parameter of interest. The analytical model developed by Neuman for flow to a partially penetrating well of infinitesimal diameter situated in an infinite, homogeneous and anisotropic aquifer was used to obtain calculated drawdown. NLS was first applied to synthetic drawdown data from a hypothetical but realistic aquifer to demonstrate that the relevant hydraulic parameters (storativity, specific yield, and horizontal and vertical hydraulic conductivity) can be evaluated accurately. Next the method was used to estimate the parameters at three field sites with widely varying hydraulic properties. NLS produced unbiased estimates of the aquifer parameters that are close to the estimates obtained with the same data using a visual curve-matching approach. Small differences in the estimates are a consequence of subjective interpretation introduced in the visual approach.

Journal of Hydrology↗
USGS2013

Effect of correlated observation error on parameters, predictions, and uncertainty

Correlations among observation errors are typically omitted when calculating observation weights for model calibration by inverse methods. We explore the effects of omitting these correlations on estimates of parameters, predictions, and uncertainties. First, we develop a new analytical expression for the difference in parameter variance estimated with and without error correlations for a simple one-parameter two-observation inverse model. Results indicate that omitting error correlations from both the weight matrix and the variance calculation can either increase or decrease the parameter variance, depending on the values of error correlation (ρ) and the ratio of dimensionless scaled sensitivities (r dss ). For small ρ, the difference in variance is always small, but for large ρ, the difference varies widely depending on the sign and magnitude of r dss . Next, we consider a groundwater reactive transport model of denitrification with four parameters and correlated geochemical observation errors that are computed by an error-propagation approach that is new for hydrogeologic studies. We compare parameter estimates, predictions, and uncertainties obtained with and without the error correlations. Omitting the correlations modestly to substantially changes parameter estimates, and causes both increases and decreases of parameter variances, consistent with the analytical expression. Differences in predictions for the models calibrated with and without error correlations can be greater than parameter differences when both are considered relative to their respective confidence intervals. These results indicate that including observation error correlations in weighting for nonlinear regression can have important effects on parameter estimates, predictions, and their respective uncertainties.

Water Resources Research↗
USGS2001

Confidence intervals for expected moments algorithm flood quantile estimates

Historical and paleoflood information can substantially improve flood frequency estimates if appropriate statistical procedures are properly applied. However, the Federal guidelines for flood frequency analysis, set forth in Bulletin 17B, rely on an inefficient “weighting” procedure that fails to take advantage of historical and paleoflood information. This has led researchers to propose several more efficient alternatives including the Expected Moments Algorithm (EMA), which is attractive because it retains Bulletin 17B's statistical structure (method of moments with the Log Pearson Type 3 distribution) and thus can be easily integrated into flood analyses employing the rest of the Bulletin 17B approach. The practical utility of EMA, however, has been limited because no closed‐form method has been available for quantifying the uncertainty of EMA‐based flood quantile estimates. This paper addresses that concern by providing analytical expressions for the asymptotic variance of EMA flood‐quantile estimators and confidence intervals for flood quantile estimates. Monte Carlo simulations demonstrate the properties of such confidence intervals for sites where a 25‐ to 100‐year streamgage record is augmented by 50 to 150 years of historical information. The experiments show that the confidence intervals, though not exact, should be acceptable for most purposes.

Water Resources Research↗
USGS2018

Crustal structure and quaternary acceleration of deformation rates in central Washington revealed by stream profile inversion, potential field geophysics, and structural geology of the Yakima folds

Post‐Miocene tectonic uplift along fault‐cored anticlines within central Washington produced the Yakima Fold Province, a region of active NNE‐SSW shortening in the Cascadian backarc. The relative timing and rate of deformation along individual structures is coarsely defined yet imperative for seismic hazard assessment. In this work, we use geomorphic and geophysical mapping, stream profile inversion, and balanced cross‐section methods to constrain fault geometries and slip rates in the Yakima Canyon region. We extract stream profiles from LiDAR data and analytically solve for the rate of relative rock uplift along several active fault‐cored anticlines. To constrain the fault geometries at depth and the long‐term magnitude of deformation, we constructed two line‐balanced cross sections across the folds with forward‐modeled magnetic and gravity anomaly data. Our stream profile results indicate an increase of incision rates in the Pleistocene, and we infer the increase is tectonically controlled. We estimate modern slip rates between 0.4 and 0.6 mm/year accommodated on reverse faults that core the Manastash Ridge, Umtanum Ridge, and Selah Butte anticlines and establish that these faults reactivate and invert older normal faults in basement rocks. Finally, we calculate the time required to accumulate sufficient strain energy for a large magnitude earthquake (M ≥ 7) along individual structures in the Yakima Fold Province. Results show that the Yakima folds likely accommodate large magnitude earthquakes and that it takes several hundred to several thousand years to accumulate sufficient strain energy for an M ≥ 7 earthquake.

Washington↗
USGS2016

Detecting failure of climate predictions

The practical consequences of climate change challenge society to formulate responses that are more suited to achieving long-term objectives, even if those responses have to be made in the face of uncertainty 1 , 2 . Such a decision-analytic focus uses the products of climate science as probabilistic predictions about the effects of management policies 3 . Here we present methods to detect when climate predictions are failing to capture the system dynamics. For a single model, we measure goodness of fit based on the empirical distribution function, and define failure when the distribution of observed values significantly diverges from the modelled distribution. For a set of models, the same statistic can be used to provide relative weights for the individual models, and we define failure when there is no linear weighting of the ensemble models that produces a satisfactory match to the observations. Early detection of failure of a set of predictions is important for improving model predictions and the decisions based on them. We show that these methods would have detected a range shift in northern pintail 20 years before it was actually discovered, and are increasingly giving more weight to those climate models that forecast a September ice-free Arctic by 2055.

Nature Climate Change↗
USGS1982

Analysis of barium and strontium in sediments by dc plasma emission spectrometry

The dc plasma arc is suited to analysis of barium and strontium in a wide range of sedimentary rock matrices, from sands, shales, and carbonates, to ferromanganese nodules. Samples containing 10 ppm to more than 3000 ppm barium and strontium were studied. Both alkali (3500 ppm lithium borate, from a preliminary fusion) and lanthanum salts (1%) in the final solution are needed to achieve freedom from systematic effects due to extreme variation in matrix. In the absence of La, neither Li, Na, K, nor Cs totally eliminated effects of Al and other constituents on emission. Silica addition to the fusion helps achieve proper flux viscosity to aid removal of fused beads from graphite crucibles. The effect of refractory-substance formers such as aluminum with calcium can be reduced or removed by selection of a portion of the arc for emission measurement. However, it was decided not to pursue this approach because of loss in analytical sensitivity and need for greater precision in optical adjustment. Analysis of standard rock samples showed generally satisfactory agreement with precision methods of analysis, and some new standard rock data are reported.

Applied Spectroscopy↗
USGS1998

Theoretical Evaluation of the Transient Response of Constant Head and Constant Flow-Rate Permeability Tests

A theoretical analysis is presented that compares the response characteristics of the constant head and the constant flowrate (flow pump) laboratory techniques for quantifying the hydraulic properties of geologic materials having permeabilities less than 10-10 m/s. Rigorous analytical solutions that describe the transient distributions of hydraulic gradient within a specimen are developed, and equations are derived for each method. Expressions simulating the inflow and outflow rates across the specimen boundaries during a constant-head permeability test are also presented. These solutions illustrate the advantages and disadvantages of each method, including insights into measurement accuracy and the validity of using Darcy's law under certain conditions. The resulting observations offer practical considerations in the selection of an appropriate laboratory test method for the reliable measurement of permeability in low-permeability geologic materials.

Geotechnical Testing Journal↗