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USGS2008

Summary of annual mean and annual harmonic mean statistics of daily mean streamflow for 620 U.S. Geological Survey streamflow-gaging stations in Texas through water year 2007

Analysts and managers of surface-water resources have interest in annual mean and annual harmonic mean statistics of daily mean streamflow for U.S. Geological Survey (USGS) streamflow-gaging stations in Texas. The mean streamflow represents streamflow volume, whereas the harmonic mean streamflow represents an appropriate statistic for assessing constituent concentrations that might adversely affect human health. In 2008, the USGS, in cooperation with the Texas Commission on Environmental Quality, conducted a large-scale documentation of mean and harmonic mean streamflow for 620 active and inactive, continuous-record, streamflow-gaging stations using period of record data through water year 2007. About 99 stations within the Texas USGS streamflow-gaging network are part of the larger national Hydroclimatic Data Network and are identified. The graphical depictions of annual mean and annual harmonic mean statistics in this report provide a historical perspective of streamflow at each station. Each figure consists of three time-series plots, two flow-duration curves, and a statistical summary of the mean annual and annual harmonic mean streamflow statistics for available data for each station.The first time-series plot depicts daily mean streamflow for the period 1900-2007. Flow-duration curves follow and are a graphical depiction of streamflow variability. Next, the remaining two time-series plots depict annual mean and annual harmonic mean streamflow and are augmented with horizontal lines that depict mean and harmonic mean for the period of record. Monotonic trends for the annual mean streamflow and annual harmonic mean streamflow also are identified using Kendall's tau, and the slope of the trend is depicted using the nonparametric (linear) Theil-Sen line, which is only drawn for p-values less than .10 of tau. The history of annual mean and annual harmonic mean streamflow of one or more streamflow-gaging stations could be used in a watershed, river basin, or other regional context by analysts and managers of surface-water resources to guide scientific, regulatory, or other inquiries of streamflow conditions in Texas.

Data Series↗
USGS2016

Assessing the socioeconomic impact and value of open geospatial information

The production and accessibility of geospatial information including Earth observation is changing greatly both technically and in terms of human participation. Advances in technology have changed the way that geospatial data are produced and accessed, resulting in more efficient processes and greater accessibility than ever before. Improved technology has also created opportunities for increased participation in the gathering and interpretation of data through crowdsourcing and citizen science efforts. Increased accessibility has resulted in greater participation in the use of data as prices for Government-produced data have fallen and barriers to access have been reduced. The increase in participation in the production and in the use of data, defined as data democracy for this workshop, are having great impacts on economics and more generally on society. There is also a strong drive by governments around the world, as shown by the G8 Declaration in June 2013, to make public sector information and scientific data more widely accessible. These are respectively termed “open data” and “open research data.” This report summarizes discussion at the Workshop on Assessing the Impact and Value of Open Geospatial Information held at George Washington University in Washington, D.C. in October 2014. Workshop participants examined the consequences of expanding data democracy with a focus on its socioeconomic impacts. Evaluations were presented of state-of-the-art methods to assess these socioeconomic impacts, which included position papers and remarks by discussants. The workshop included discussions about the following topics: (1) increased and expanded information sources; (2) societal impacts, including approaches to economics assessments; (3) constraints to open access, including the demands for return on investment, specifications of intellectual property rights, and privacy issues; and (4) learning from the experiences of other data-rich domains, such as environmental management, internet businesses, health, and transportation. The workshop was a working meeting with strong participant engagement, leading to recommendations for action. The meeting included five topic-driven sessions and keynote presentations. Precirculated position papers for each panel session facilitated preparation and remarks by discussants. After the position papers are updated following the discussants’ remarks, it is planned to submit them for publication. The workshop included 68 participants coming from international organizations, the U.S. public and private sectors, nongovernmental organizations, and academia. Participants included policy makers and analysts, financial analysts, economists, information scientists, geospatial practitioners, and other discipline experts.

Open-File Report↗
USGS2024

Determination of antimycin–a in a liquid formulation by high performance liquid chromatography–mass spectrometry

Pesticide formulations containing the active ingredient antimycin–a (ANT–A) have been used by fisheries and aquaculture managers for several decades to remove nuisance fish species. Analytical methods for measuring ANT–A during pesticide treatments have been done using high performance liquid chromatography (HPLC) paired with multiple detection methods (for example, electrochemical, ultraviolet, fluorescence, mass spectrometry). However, instruments and analytical chemistry methods can advance over time because of the need to develop timely, reliable, cost effective, and reproducible methods. Subsequently, ANT–A analytical chemistry methods and sample processing techniques also have improved over the past several decades. In the present study, we describe a liquid chromatography–mass spectrometry method and its verification across three analysts. Each analyst group created a single calibration curve and verified ANT–A in a liquid formulation using the averaged total response of all major ANT–A homologs (A1, A3, A3, A4). The advantage of this technique is that it creates a more resilient ANT–A quantification method amendable to batch-batch differences in major homologs. The method demonstrated how ANT–A can be effectively measured with high accuracy (98–99 percent), precision (2.7–16.2 percent), and specificity within a pesticide liquid formulation using a method applicable for Federal registration requirements.

Open-File Report↗
USGS1976

The weathering of sulfide ores in Shasta County, California, and its relationship to pollution associated with acid mine drainage

The West Shasta Copper-Zinc District of Shasta County, California is presently acting as a source of acid mine drainage which is entering the Shasta Lake and the Keswick Reservoirs (Nordstrom et al., 1976). The purpose of the present investigation was to study in the field the weathering of these sulfide ores and their associated wastes to elucidate the processes involved in the formation of acid mine drainage. An understanding of these processes is essential to the design of abatement projects for the district. The area investigated is illustrated in Figure 1. The detailed geology of the mining district has been summarized by Kinkel et al. (1956), whose work served as the geologic framework for this investigation. The process of sulfide weathering was examined in two distinct environments, i.e. in-situ and in waste piles associated with mining operations. A suite of 59 solid samples and associated waters were collected from various examples of the two environments. The mineral samples were studied by X-ray diffraction, reflected light microscopy, and by selective chemical analysis. The waters were studied through field measurement of pH, eH, conductivity, detailed chemical analysis by atomic absorption (D. Kirk Nordstrom, analyst), and emission spectrographic analysis of evaporates (Chris Heropoulos, analyst).

California↗
USGS1998

Summary of the U.S. Geological Survey National Field Quality Assurance Program from 1979 through 1997

Since the inception of the U.S. Geological Survey National Field Quality Assurance Program, over 85,000 proficiency samples have been analyzed by water-quality analysts. This includes more than 10,000 alkalinity samples, more than 15,000 pH samples, and more than 16,000 specific conductance samples, which were analyzed from 1990 through 1997, and a total of more than 43,000 proficiency samples analyzed from 1979 through 1989. The analyte values were evaluated to determine the fourth-spread, a measure of the width of the middle half of the data, and the F-pseudosigma, a robust replacement for the standard deviation, for each of the different measurement ranges. The result of the statistical evaluation showed that the vast majority of reference sample measurements made by water-quality analysts were within acceptable ranges. From 1990 to 1997, the measurement of pH had the highest level of acceptable results, 98.4 percent, followed by specific conductance with 95.2 percent acceptable results, and alkalinity with 88.6 percent acceptable results. The statistical summary of pH indicates the calculated fourth-spread values for the entire tested range is +0.06 pH units. For specific conductance, the magnitude of the fourth-spread increases as the magnitude of the specific conductance ranges increases. The average relative fourth-spread percent for all reported specific conductance values is +1.8 percent. From 1990 through 1997, the evaluation of the results for alkalinity measurement for the average fourth-spread was determined to be + 3.3 milligrams per liter as calcium carbonate.

Open-File Report↗
USGS2014

Land-cover mapping of Red Rock Canyon National Conservation Area and Coyote Springs, Piute-Eldorado Valley, and Mormon Mesa Areas of Critical Environmental Concern, Clark County, Nevada

DigitalGlobe’s QuickBird satellite high-resolution multispectral imagery was classified by using Visual Learning Systems’ Feature Analyst feature extraction software to produce land-cover data sets for the Red Rock Canyon National Conservation Area and the Coyote Springs, Piute-Eldorado Valley, and Mormon Mesa Areas of Critical Environmental Concern in Clark County, Nevada. Over 1,000 vegetation field samples were collected at the stand level. The field samples were classified to the National Vegetation Classification Standard, Version 2 hierarchy at the alliance level and above. Feature extraction models were developed for vegetation on the basis of the spectral and spatial characteristics of selected field samples by using the Feature Analyst hierarchical learning process. Individual model results were merged to create one data set for the Red Rock Canyon National Conservation Area and one for each of the Areas of Critical Environmental Concern. Field sample points and photographs were used to validate and update the data set after model results were merged. Non-vegetation data layers, such as roads and disturbed areas, were delineated from the imagery and added to the final data sets. The resulting land-cover data sets are significantly more detailed than previously were available, both in resolution and in vegetation classes.

Nevada↗
USGS2017

Application of decline curve analysis to estimate recovery factors for carbon dioxide enhanced oil recovery

Introduction In the decline curve analysis (DCA) method of estimating recoverable hydrocarbon volumes, the analyst uses historical production data from a well, lease, group of wells (or pattern), or reservoir and plots production rates against time or cumu­lative production for the analysis. The DCA of an individual well is founded on the same basis as the fluid-flow principles that are used for pressure-transient analysis of a single well in a reservoir domain and therefore can provide scientifically reasonable and accurate results. However, when used for a group of wells, a lease, or a reservoir, the DCA becomes more of an empirical method. Plots from the DCA reflect the reservoir response to the oil withdrawal (or production) under the prevailing operating and reservoir conditions, and they continue to be good tools for estimating recoverable hydrocarbon volumes and future production rates. For predicting the total recov­erable hydrocarbon volume, the DCA results can help the analyst to evaluate the reservoir performance under any of the three phases of reservoir productive life—primary, secondary (waterflood), or tertiary (enhanced oil recovery) phases—so long as the historical production data are sufficient to establish decline trends at the end of the three phases.

Scientific Investigations Report↗
USGS2006

User's manual for the Graphical Constituent Loading Analysis System (GCLAS)

This manual describes the Graphical Constituent Loading Analysis System (GCLAS), an interactive cross-platform program for computing the mass (load) and average concentration of a constituent that is transported in stream water over a period of time. GCLAS computes loads as a function of an equal-interval streamflow time series and an equal- or unequal-interval time series of constituent concentrations. The constituent-concentration time series may be composed of measured concentrations or a combination of measured and estimated concentrations. GCLAS is not intended for use in situations where concentration data (or an appropriate surrogate) are collected infrequently or where an appreciable amount of the concentration values are censored. It is assumed that the constituent-concentration time series used by GCLAS adequately represents the true time-varying concentration. Commonly, measured constituent concentrations are collected at a frequency that is less than ideal (from a load-computation standpoint), so estimated concentrations must be inserted in the time series to better approximate the expected chemograph. GCLAS provides tools to facilitate estimation and entry of instantaneous concentrations for that purpose. Water-quality samples collected for load computation frequently are collected in a single vertical or at single point in a stream cross section. Several factors, some of which may vary as a function of time and (or) streamflow, can affect whether the sample concentrations are representative of the mean concentration in the cross section. GCLAS provides tools to aid the analyst in assessing whether concentrations in samples collected in a single vertical or at single point in a stream cross section exhibit systematic bias with respect to the mean concentrations. In cases where bias is evident, the analyst can construct coefficient relations in GCLAS to reduce or eliminate the observed bias. GCLAS can export load and concentration data in formats suitable for entry into the U.S. Geological Survey's National Water Information System. GCLAS can also import and export data in formats that are compatible with various commonly used spreadsheet and statistics programs.

Techniques and Methods↗
USGS2021

Comparison of simple averaging and latent class modeling to estimate the area of land cover in the presence of reference data variability

Estimates of the area or percent area of the land cover classes within a study region are often based on the reference land cover class labels assigned by analysts interpreting satellite imagery and other ancillary spatial data. Different analysts interpreting the same spatial unit will not always agree on the land cover class label that should be assigned. Two approaches for accommodating interpreter variability when estimating the area are simple averaging (SA) and latent class modeling (LCM). This study compares agreement between area estimates obtained from SA and LCM using reference data obtained by seven trained, professional interpreters who independently interpreted an annual time series of land cover reference class labels for 300 sampled Landsat pixels. We also compare the variability of the LCM and SA area estimates over different numbers of interpreters and different subsets of interpreters within each interpreter group size, and examine area estimates of three land cover classes (forest, developed, and wetland) and three change types (forest gain, forest loss, and developed gain). Differences between the area estimates obtained from SA and LCM are most pronounced for the estimates of wetland and the three change types. The percent area estimates of these rare classes were usually greater for LCM compared to SA, with the differences between LCM and SA increasing as the number of interpreters providing the reference data increased. The LCM area estimates generally had larger standard deviations and greater ranges over different subsets of interpreters, indicating greater sensitivity to the selection of the individual interpreters who carried out the reference class labeling.

Washington↗
USGS1987

GEOLOGICAL APPLICATIONS OF WELL LOGS: AN INTRODUCTORY BIBLIOGRAPHY AND SURVEY OF THE WELL LOGGING LITERATURE THROUGH SEPTEMBER 1986 ARRANGED BY SUBJECT.

This report includes over 1,350 individual citations as well as a first-author index. The purpose of this bibliography is twofold, 1) to provide a basic, first-stop resource on well logging which the non-specialist, i. e. , geoscientist, can consult and, 2) to provide a reference on geologic applications for the non-geoscientist, i. e. , log analyst or petroleum engineer, as well as for the geoscientist.

Log Analyst↗
USGS1992

Acoustic waveform logging: Advances in theory and application

Full-waveform acoustic logging has made significant advances in both theory and application in recent years, and these advances have greatly increased the capability of log analysts to measure the physical properties of formations. Advances in theory provide the analytical tools required to understand the properties of measured seismic waves, and to relate those properties to such quantities as shear and compressional velocity and attenuation, and primary and fracture porosity and permeability of potential reservoir rocks. The theory demonstrates that all parts of recorded waveforms are related to various modes of propagation, even in the case of dipole and quadrupole source logging. However, the theory also indicates that these mode properties can be used to design velocity and attenuation picking schemes, and shows how source frequency spectra can be selected to optimize results in specific applications. Synthetic microseismogram computations are an effective tool in waveform interpretation theory; they demonstrate how shear arrival picks and mode attenuation can be used to compute shear velocity and intrinsic attenuation, and formation permeability for monopole, dipole and quadrupole sources. Array processing of multi-receiver data offers the opportunity to apply even more sophisticated analysis techniques. Synthetic microseismogram data is used to illustrate the application of the maximum-likelihood method, semblance cross-correlation, and Prony's method analysis techniques to determine seismic velocities and attenuations. The interpretation of acoustic waveform logs is illustrated by reviews of various practical applications, including synthetic seismogram generation, lithology determination, estimation of geomechanical properties in situ, permeability estimation, and design of hydraulic fracture operations.

Log Analyst↗
USGS2002

Grid-cell-based crop water accounting for the famine early warning system

Rainfall monitoring is a regular activity of food security analysts for sub-Saharan Africa due to the potentially disastrous impact of drought. Crop water accounting schemes are used to track rainfall timing and amounts relative to phenological requirements, to infer water limitation impacts on yield. Unfortunately, many rain gauge reports are available only after significant delays, and the gauge locations leave large gaps in coverage. As an alternative, a grid-cell-based formulation for the water requirement satisfaction index (WRSI) was tested for maize in Southern Africa. Grids of input variables were obtained from remote sensing estimates of rainfall, meteorological models, and digital soil maps. The spatial WRSI was computed for the 1996–97 and 1997–98 growing seasons. Maize yields were estimated by regression and compared with a limited number of reports from the field for the 1996–97 season in Zimbabwe. Agreement at a useful level ( r = 0·80) was observed. This is comparable to results from traditional analysis with station data. The findings demonstrate the complementary role that remote sensing, modelling, and geospatial analysis can play in an era when field data collection in sub-Saharan Africa is suffering an unfortunate decline.

Hydrological Processes↗
USGS1998

Considerations in As analysis and speciation

This article summarizes recent experiences in arsenic (As) quantification, preservation, and speciation developed during AWWA Research Foundation (AWWARF) and Water Industry Technical Action Fund (WITAF) projects. The goal of this article is to alert analysts and decision-makers to potential problems in As analysis and speciation, because there appear to be several unresolved problems with routine analytical approaches. In true split drinking water samples As was quantified by three accepted analytical methods in three laboratories. The techniques used were graphite furnace atomic absorption spectrometry (GFAAS), inductively coupled plasma mass spectrometry (ICP-MS), and hydride generation inductively coupled plasma-emission spectrometry (HG-ICP-AES). Experimental findings are organized into sections on As analysis, particulate As in water supplies, and examination of As speciation methods.

Journal of the American Water Works Association↗
USGS2013

Demographics of reintroduced populations: estimation, modeling, and decision analysis

Reintroduction can be necessary for recovering populations of threatened species. However, the success of reintroduction efforts has been poorer than many biologists and managers would hope. To increase the benefits gained from reintroduction, management decision making should be couched within formal decision-analytic frameworks. Decision analysis is a structured process for informing decision making that recognizes that all decisions have a set of components—objectives, alternative management actions, predictive models, and optimization methods—that can be decomposed, analyzed, and recomposed to facilitate optimal, transparent decisions. Because the outcome of interest in reintroduction efforts is typically population viability or related metrics, models used in decision analysis efforts for reintroductions will need to include population models. In this special section of the Journal of Wildlife Management, we highlight examples of the construction and use of models for informing management decisions in reintroduced populations. In this introductory contribution, we review concepts in decision analysis, population modeling for analysis of decisions in reintroduction settings, and future directions. Increased use of formal decision analysis, including adaptive management, has great potential to inform reintroduction efforts. Adopting these practices will require close collaboration among managers, decision analysts, population modelers, and field biologists.

Journal of Wildlife Management↗
USGS2014

Increased flexibility for modeling telemetry and nest-survival data using the multistate framework

Although telemetry is one of the most common tools used in the study of wildlife, advances in the analysis of telemetry data have lagged compared to progress in the development of telemetry devices. We demonstrate how standard known-fate telemetry and related nest-survival data analysis models are special cases of the more general multistate framework. We present a short theoretical development, and 2 case examples regarding the American black duck and the mallard. We also present a more complex lynx data analysis. Although not necessary in all situations, the multistate framework provides additional flexibility to analyze telemetry data, which may help analysts and biologists better deal with the vagaries of real-world data collection.

Journal of Wildlife Management↗
USGS2018

Seeking excellence: An evaluation of 235 international laboratories conducting water isotope analyses by isotope-ratio and laser-absorption spectrometry

Rationale Water stable isotope ratios ( δ 2 H and δ 18 O values) are widely used tracers in environmental studies; hence, accurate and precise assays are required for providing sound scientific information. We tested the analytical performance of 235 international laboratories conducting water isotope analyses using dual-inlet and continuous-flow isotope ratio mass spectrometers and laser spectrometers through a water isotope inter-comparison test. Methods Eight test water samples were distributed by the IAEA to international stable isotope laboratories. These consisted of a core set of five samples spanning the common δ -range of natural waters, and three optional samples (highly depleted, enriched, and saline). The fifth core sample contained unrevealed trace methanol to assess analyst vigilance to the impact of organic contamination on water isotopic measurements made by all instrument technologies. Results For the core and optional samples ~73 % of laboratories gave acceptable results within 0.2 ‰ and 1.5 ‰ of the reference values for δ 18 O and δ 2 H, respectively; ~27 % produced unacceptable results. Top performance for δ 18 O values was dominated by dual-inlet IRMS laboratories; top performance for δ 2 H values was led by laser spectrometer laboratories. Continuous-flow instruments yielded comparatively intermediate results. Trace methanol contamination of water resulted in extreme outlier δ -values for laser instruments, but also affected reactor-based continuous-flow IRMS systems; however, dual-inlet IRMS δ -values were unaffected. Conclusions Analysis of the laboratory results and their metadata suggested inaccurate or imprecise performance stemmed mainly from skill- and knowledge-based errors including: calculation mistakes, inappropriate or compromised laboratory calibration standards, poorly performing instrumentation, lack of vigilance to contamination, or inattention to unreasonable isotopic outcomes. To counteract common errors, we recommend that laboratories include 1–2 'known' control standards in all autoruns; laser laboratories should screen each autorun for spectral contamination; and all laboratories should evaluate whether derived d- excess values are realistic when both isotope ratios are measured. Combined, these data evaluation strategies should immediately inform the laboratory about fundamental mistakes or compromised samples.

Rapid Communications in Mass Spectrometry↗
USGS1994

The space-time structure of oil and gas field growth in a complex depositional system

Shortly after the discovery of an oil and gas field, an initial estimate is usually made of the ultimate recovery of the field. With the passage of time, this initial estimate is almost always revised upward. The phenomenon of the growth of the expected ultimate recovery of a field, which is known as "field growth," is important to resource assessment analysts for several reasons. First, field growth is the source of a large part of future additions to the inventory of proved reserves of crude oil and natural gas in most petroliferous areas of the world. Second, field growth introduces a large negative bias in the forecast of the future rates of discovery of oil and gas fields made by discovery process models. In this study, the growth in estimated ultimate recovery of oil and gas in fields made up of sandstone reservoirs formed in a complex depositional environment (Frio strand plain exploration play) is examined. The results presented here show how the growth of oil and gas fields is tied directly to the architectural element of the shoreline processes and tectonics that caused the deposition of the individual sand bodies hosting the producible hydrocarbon. ?? 1994 Oxford University Press.

Nonrenewable Resources↗
USGS2018

Statistical detection of flow regime changes in horizontal hydraulically fractured Bakken oil wells

The application of horizontal and hydraulically fractured wells for producing oil from low permeability formations has changed the face of the North American oil industry. One feature of the production profile of many such wells is a transition from transient linear oil flow to boundary-dominated flow. The identification of the time of this transition is important for the calibration of models that forecast the well’s future production and the expected ultimate recovery. It is preferable that such models generally use data from the boundary-dominated flow regime for parameter calibration. Accurate well production forecasts are needed for operational decisions, long-term planning, commercial transactions, regulatory proceedings, and asset valuation. Petroleum engineers frequently make the call on the transition point based on subjective visual interpretations of log–log plots for individual wells. This is time-consuming and is generally not repeatable by other analysts. This note evaluates statistical approaches that can serve as alternatives to the subjective visual interpretations. Specifically, the predictive performance of production models calibrated with boundary-dominated data based on transition dates calculated with constrained nonlinear least squares and Bayesian regressions was very close to that obtained using the visual method, suggesting that statistical approaches may indeed be constructed to replace less objective visual approaches without loss of accuracy.

Natural Resources Research↗