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USGS1988

Borehole geophysics applied to ground-water investigations

The purpose of this manual is to provide hydrologists, geologists, and others who have the necessary training with the basic information needed to apply the most useful borehole-geophysical-logging techniques to the solution of problems in ground-water hydrology. Geophysical logs can provide information on the construction of wells and on the character of the rocks and fluids penetrated by those wells, in addition to changes in the character of these factors with time. The response of well logs is caused by: petrophysical factors; the quality; temperature, and pressure of interstitial fluids; and ground-water flow. Qualitative and quantitative analysis of the analog records and computer analysis of digitized logs are used to derive geohydrologic information. This information can then be extrapolated vertically within a well and laterally to other wells using logs. The physical principles by which the mechanical and electronic components of a logging system measure properties of rocks, fluids and wells, and the principles of measurement need to be understood to correctly interpret geophysical logs. Planning the logging operation involves selecting the equipment and the logs most likely to provide the needed information. Information on well construction and geohydrology are needed to guide this selection. Quality control of logs is an important responsibility of both the equipment operator and log analyst and requires both calibration and well-site standardization of equipment. Logging techniques that are widely used in ground-water hydrology or that have significant potential for application to this field include: spontaneous potential, resistance, resistivity, gamma, gamma spectrometry, gamma-gamma, neutron, acoustic velocity, acoustic televiewer, caliper, and fluid temperature, conductivity, and flow. The following topics are discussed for each of these techniques: principles and instrumentation, calibration and standardization, volume of investigation, extraneous effects, and interpretation and applications.

Open-File Report↗
USGS1988

Selected annotated bibliographies for adaptive filtering of digital image data

Digital spatial filtering is an important tool both for enhancing the information content of satellite image data and for implementing cosmetic effects which make the imagery more interpretable and appealing to the eye. Spatial filtering is a context-dependent operation that alters the gray level of a pixel by computing a weighted average formed from the gray level values of other pixels in the immediate vicinity. Traditional spatial filtering involves passing a particular filter or set of filters over an entire image. This assumes that the filter parameter values are appropriate for the entire image, which in turn is based on the assumption that the statistics of the image are constant over the image. However, the statistics of an image may vary widely over the image, requiring an adaptive or "smart" filter whose parameters change as a function of the local statistical properties of the image. Then a pixel would be averaged only with more typical members of the same population. This annotated bibliography cites some of the work done in the area of adaptive filtering. The methods usually fall into two categories, (a) those that segment the image into subregions, each assumed to have stationary statistics, and use a different filter on each subregion, and (b) those that use a two-dimensional "sliding window" to continuously estimate the filter either the spatial or frequency domain, or may utilize both domains. They may be used to deal with images degraded by space variant noise, to suppress undesirable local radiometric statistics while enforcing desirable (user-defined) statistics, to treat problems where space-variant point spread functions are involved, to segment images into regions of constant value for classification, or to "tune" images in order to remove (nonstationary) variations in illumination, noise, contrast, shadows, or haze. Since adpative filtering, like nonadaptive filtering, is used in image processing to accomplish various goals, this bibliography is organized in subsections based on application areas. Contrast enhancement, edge enhancement, noise suppression, and smoothing are typically performed in order imaging process, (for example, degradations due to the optics and electronics of the sensor, or to blurring caused by the intervening atmosphere, uniform motion, or defocused optics). Some of the papers listed may apply to more than one of the above categories; when this happens the paper is listed under the category for which the paper's emphasis is greatest. A list of survey articles is also supplied. These articles are general discussions on adaptive filters and reviews of work done. Finally, a short list of miscellaneous articles are listed which were felt to be sufficiently important to be included, but do not fit into any of the above categories. This bibliography, listing items published from 1970 through 1987, is extensive, but by no means complete. It is intended as a guide for scientists and image analysts, listing references for background information as well as areas of significant development in adaptive filtering.

Open-File Report↗
USGS1994

Methods of analysis by the U.S. Geological Survey National Water Quality Laboratory-Extraction of nitroaromatic compounds from water by polystyrene divinylbenzene cartridge and determination by high-performance liquid chromatography

Organic explosives are determined in samples of ground water and surface water with emphasis on identifying and quantifying trinitrotoluene (TNT) metabolites. Water samples are filtered to remove suspended particulate material and passed through a polystyrene divinylbenzene-packed cartridge by a vacuum-extraction system. The target analytes subsequently are eluted with acetonitrile. A high-performance liquid chromatograph (HPLC) equipped with a photodiode-array detector is used for sample analysis. Analytes are separated on an octadecylsilane column using a methanol, water, and acetonitrile gradient elution. The compounds 2,4- and 2,6-dinitrotoluene are separated through an independent, isocratic elution. Method detection limits, on the basis of a 1-liter sample size, range from 0.11 to 0.32 microgram per liter. Recoveries averaged from 71 to 101 percent for 13 analytes in one set of HPLC-grade water fortified at about 1 microgram per liter. The method is limited to use by analysts experienced in handling explosive materials. (USGS)

Open-File Report↗
USGS1998

Methods of analysis by the U.S. Geological Survey National Water Quality Laboratory-Determination of 86 volatile organic compounds in water by gas chromatography/mass spectrometry, including detections less than reporting limits

This report presents precision and accuracy data for volatile organic compounds (VOCs) in the nanogram-per-liter range, including aromatic hydrocarbons, reformulated fuel components, and halogenated hydrocarbons using purge and trap capillary-column gas chromatography/mass spectrometry. One-hundred-four VOCs were initially tested. Of these, 86 are suitable for determination by this method. Selected data are provided for the 18 VOCs that were not included. This method also allows for the reporting of semiquantitative results for tentatively identified VOCs not included in the list of method compounds. Method detection limits, method performance data, preservation study results, and blank results are presented. The authors describe a procedure for reporting low-concentration detections at less than the reporting limit. The nondetection value (NDV) is introduced as a statistically defined reporting limit designed to limit false positives and false negatives to less than 1 percent. Nondetections of method compounds are reported as ?less than NDV.? Positive detections measured at less than NDV are reported as estimated concentrations to alert the data user to decreased confidence in accurate quantitation. Instructions are provided for analysts to report data at less than the reporting limits. This method can support the use of either method reporting limits that censor detections at lower concentrations or the use of NDVs as reporting limits. The data-reporting strategy for providing analytical results at less than the reporting limit is a result of the increased need to identify the presence or absence of environmental contaminants in water samples at increasingly lower concentrations. Long-term method detection limits (LTMDLs) for 86 selected compounds range from 0.013 to 2.452 micrograms per liter (?g/L) and differ from standard method detection limits (MDLs) in that the LTMDLs include the long-term variance of multiple instruments, multiple operators, and multiple calibrations over a longer time. For these reasons, LTMDLs are expected to be slightly higher than standard MDLs. Recoveries for all of the VOCs tested ranged from 36 (tert-butyl formate) to 155 percent (pentachlorobenzene). The majority of the compounds ranged from 85 to 115 percent recovery and had less than 5 percent relative standard deviation for concentrations spiked between 1 to 500 ?g/L in volatile blank-, surface-, and ground-water samples. Recoveries of 60 set spikes at low concentrations ranged from 70 to 114 percent (1,2,3- trimethylbenzene and acetone). Recovery data were collected over 6 months with multiple instruments, operators, and calibrations. In this method, volatile organic compounds are extracted from a water sample by actively purging with helium. The VOCs are collected onto a sorbent trap, thermally desorbed, separated by a Megabore gas chromatographic capillary column, and finally determined by a full-scan quadrupole mass spectrometer. Compound identification is confirmed by the gas chromatographic retention time and by the resultant mass spectrum, typically identified by three unique ions. An unknown compound detected in a sample can be tentatively identified by comparing the unknown mass spectrum to reference spectra in the mass-spectra computer-data system library compiled by the National Institute of Standards and Technology.

Open-File Report↗
USGS2000

National Geochemical Database, U.S. Geological Survey RASS (Rock Analysis Storage System) geochemical data for Alaska

This dataset contains geochemical data for Alaska produced by the analytical laboratories of the Geologic Division of the U.S. Geological Survey (USGS). These data represent analyses of stream-sediment, heavy-mineral-concentrate (derived from stream sediment), soil, and organic material samples. Most of the data comes from mineral resource investigations conducted in the Alaska Mineral Resource Assessment Program (AMRAP). However, some of the data were produced in support of other USGS programs. The data were originally entered into the in-house Rock Analysis Storage System (RASS) database. The RASS database, which contains over 580,000 data records, was used by the Geologic Division from the early 1970's through the late 1980's to archive geochemical data. Much of the data have been previously published in paper copy USGS Open-File Reports by the submitter or the analyst but some of the data have never been published. Over the years, USGS scientists recognized several problems with the database. The two primary issues were location coordinates (either incorrect or lacking) and sample media (not precisely identified). This dataset represents a re-processing of the original RASS data to make the data accessible in digital format and more user friendly. This re-processing consisted of checking the information on sample media and location against the original sample submittal forms, the original analytical reports, and published reports. As necessary, fields were added to the original data to more fully describe the sample preparation methods used and sample medium analyzed. The actual analytical data were not checked in great detail, but obvious errors were corrected.

Alaska↗
USGS2010

Seismic precursors to volcanic explosions during the 2006 eruption of Augustine Volcano: Chapter 2 in The 2006 eruption of Augustine Volcano, Alaska

The 2006 eruption of Augustine Volcano, Alaska, generated more than 3,500 earthquakes in a month-long time frame bracketing the most explosive period of activity. We examine two quantitative tools that, in retrospective analysis, were excellent indicators of imminent eruption. The first tool, referred to as the frequency index ( FI ), is based on a simple ratio of high- and low-frequency energy in an earthquake seismogram. It is a metric that allows us to quantify the differences between the canonical high-frequency, hybrid, and low-frequency volcanic earthquakes. FI values greater than -0.4 indicate earthquakes classically referred to as high-frequency or volcano-tectonic events. FI values less than -1.3 correspond to events usually referred to as low-frequency earthquakes. Because the FI is based on a ratio and not a spectral peak, hybrid earthquakes are successfully assigned FI values intermediate to these two classes. In this eruption, we find a remarkable correlation between events with FI less than -1.8 and explosive eruptions. The second tool we examine is based on repeating seismic waveforms identified through waveform cross-correlation. Although the vast majority of earthquakes during this eruption have unique waveforms, subsets of events exhibiting a high degree of similarity occur and are closely tied to explosive eruption events. Of the 13 large explosion events, seven were preceded by clusters of highly similar earthquakes. We apply the FI and correlation tools together to identify changes in high- and low-frequency earthquake occurrences and examine their relations to the precursory, explosive, and continuous phases of the eruption. We find that earthquakes that have low FI values and earthquakes exhibiting high degrees of similarity occur almost exclusively within hours of explosive eruptions and postulate that they occur as a result of the final ascent of magma in the volcanic edifice. Because neither of these methods requires analyst-reviewed earthquake locations, we believe that they have considerable potential as automated real-time volcano monitoring tools.

Alaska↗
USGS2006

Statewide analysis of the drainage-area ratio method for 34 streamflow percentile ranges in Texas

The drainage-area ratio method commonly is used to estimate streamflow for sites where no streamflow data are available using data from one or more nearby streamflow-gaging stations. The method is intuitive and straightforward to implement and is in widespread use by analysts and managers of surface-water resources. The method equates the ratio of streamflow at two stream locations to the ratio of the respective drainage areas. In practice, unity often is assumed as the exponent on the drainage-area ratio, and unity also is assumed as a multiplicative bias correction. These two assumptions are evaluated in this investigation through statewide analysis of daily mean streamflow in Texas. The investigation was made by the U.S. Geological Survey in cooperation with the Texas Commission on Environmental Quality. More than 7.8 million values of daily mean streamflow for 712 U.S. Geological Survey streamflow-gaging stations in Texas were analyzed. To account for the influence of streamflow probability on the drainage-area ratio method, 34 percentile ranges were considered. The 34 ranges are the 4 quartiles (0-25, 25-50, 50-75, and 75-100 percent), the 5 intervals of the lower tail of the streamflow distribution (0-1, 1-2, 2-3, 3-4, and 4-5 percent), the 20 quintiles of the 4 quartiles (0-5, 5-10, 10-15, 15-20, 20-25, 25-30, 30-35, 35-40, 40-45, 45-50, 50-55, 55-60, 60-65, 65-70, 70-75, 75-80, 80-85, 85-90, 90-95, and 95-100 percent), and the 5 intervals of the upper tail of the streamflow distribution (95-96, 96-97, 97-98, 98-99 and 99-100 percent). For each of the 253,116 (712X711/2) unique pairings of stations and for each of the 34 percentile ranges, the concurrent daily mean streamflow values available for the two stations provided for station-pair application of the drainage-area ratio method. For each station pair, specific statistical summarization (median, mean, and standard deviation) of both the exponent and bias-correction components of the drainage-area ratio method were computed. Statewide statistics (median, mean, and standard deviation) of the station-pair specific statistics subsequently were computed and are tabulated herein. A separate analysis considered conditioning station pairs to those stations within 100 miles of each other and with the absolute value of the logarithm (base-10) of the ratio of the drainage areas greater than or equal to 0.25. Statewide statistics of the conditional station-pair specific statistics were computed and are tabulated. The conditional analysis is preferable because of the anticipation that small separation distances reflect similar hydrologic conditions and the observation of large variation in exponent estimates for similar-sized drainage areas. The conditional analysis determined that the exponent is about 0.89 for streamflow percentiles from 0 to about 50 percent, is about 0.92 for percentiles from about 50 to about 65 percent, and is about 0.93 for percentiles from about 65 to about 85 percent. The exponent decreases rapidly to about 0.70 for percentiles nearing 100 percent. The computation of the bias-correction factor is sensitive to the range analysis interval (range of streamflow percentile); however, evidence suggests that in practice the drainage-area method can be considered unbiased. Finally, for general application, suggested values of the exponent are tabulated for 54 percentiles of daily mean streamflow in Texas; when these values are used, the bias correction is unity.

Scientific Investigations Report↗
USGS2011

Design and evaluation of a field study on the contamination of selected volatile organic compounds and wastewater-indicator compounds in blanks and groundwater samples

The Field Contamination Study (FCS) was designed to determine the field processes that tend to result in clean field blanks and to identify potential sources of contamination to blanks collected in the field from selected volatile organic compounds (VOCs) and wastewater-indicator compounds (WICs). The VOCs and WICs analyzed in the FCS were detected in blanks collected by the U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) Program during 1996–2008 and 2002–08, respectively. To minimize the number of variables, the study required ordering of supplies just before sampling, storage of supplies and equipment in clean areas, and use of adequate amounts of purge-and-trap volatile-grade methanol and volatile pesticide-grade blank water (VPBW) to clean sampling equipment and to collect field blanks. Blanks and groundwater samples were collected during 2008–09 at 16 sites, which were a mix of water-supply and monitoring wells, located in 9 States. Five different sample types were collected for the FCS at each site: (1) a source-solution blank collected at the USGS National Water Quality Laboratory (NWQL) using laboratory-purged VPBW, (2) source-solution blanks collected in the field using laboratory-purged VPBW, (3) source-solution blanks collected in the field using field-purged VPBW, (4) a field blank collected using field-purged VPBW, and (5) a groundwater sample collected from a well. The source-solution blank and field-blank analyses were used to identify, quantify, and document extrinsic contamination and to help determine the sources and causes of data-quality problems that can affect groundwater samples. Concentrations of compounds detected in FCS analyses were quantified and results were stored in the USGS National Water Information System database after meeting rigorous identification and quantification criteria. The study also utilized information provided by laboratory analysts about evidence indicating the presence of selected compounds, using less rigorous identification criteria than is required for reporting data to the National Water Information System database. For the FCS, these data are considered adequate to indicate "evidence of presence," and were used only for diagnostic purposes. Evidence of VOCs and WICs at low concentrations near or less than the long-term method detection level can indicate a contamination problem that could affect future datasets if method detection levels were ever to be lowered.

Scientific Investigations Report↗
USGS2012

Interlaboratory comparison of three microbial source tracking quantitative polymerase chain reaction (qPCR) assays from fecal-source and environmental samples

During summer and early fall 2010, 15 river samples and 6 fecal-source samples were collected in West Virginia. These samples were analyzed by three laboratories for three microbial source tracking (MST) markers: AllBac, a general fecal indicator; BacHum, a human-associated fecal indicator; and BoBac, a ruminant-associated fecal indicator. MST markers were analyzed by means of the quantitative polymerase chain reaction (qPCR) method. The aim was to assess interlaboratory precision when the three laboratories used the same MST marker and shared deoxyribonucleic acid (DNA) extracts of the samples, but different equipment, reagents, and analyst experience levels. The term assay refers to both the markers and the procedure differences listed above. Interlaboratory precision was best for all three MST assays when using the geometric mean absolute relative percent difference (ARPD) and Friedman's statistical test as a measure of interlaboratory precision. Adjustment factors (one for each MST assay) were calculated using results from fecal-source samples analyzed by all three laboratories and applied retrospectively to sample concentrations to account for differences in qPCR results among labs using different standards and procedures. Following the application of adjustment factors to qPCR results, ARPDs were lower; however, statistically significant differences between labs were still observed for the BacHum and BoBac assays. This was a small study and two of the MST assays had 52 percent of samples with concentrations at or below the limit of accurate quantification; hence, more testing could be done to determine if the adjustment factors would work better if the majority of sample concentrations were above the quantification limit.

West Virginia↗
USGS2013

Analytical properties of some commercially available nitrate reductase enzymes evaluated as replacements for cadmium in automated, semiautomated, and manual colorimetric methods for determination of nitrate plus nitrite in water

A multiyear research effort at the U.S. Geological Survey (USGS) National Water Quality Laboratory (NWQL) evaluated several commercially available nitrate reductase (NaR) enzymes as replacements for toxic cadmium in longstanding automated colorimetric air-segmented continuous-flow analyzer (CFA) methods for determining nitrate plus nitrite (NO x ) in water. This research culminated in USGS approved standard- and low-level enzymatic reduction, colorimetric automated discrete analyzer NO x methods that have been in routine operation at the NWQL since October 2011. The enzyme used in these methods (AtNaR2) is a product of recombinant expression of NaR from Arabidopsis thaliana (L.) Heynh. (mouseear cress) in the yeast Pichia pastoris. Because the scope of the validation report for these new automated discrete analyzer methods, published as U.S. Geological Survey Techniques and Methods 5–B8, was limited to performance benchmarks and operational details, extensive foundational research with different enzymes—primarily YNaR1, a product of recombinant expression of NaR from Pichia angusta in the yeast Pichia pastoris—remained unpublished until now. This report documents research and development at the NWQL that was foundational to development and validation of the discrete analyzer methods. It includes: (1) details of instrumentation used to acquire kinetics data for several NaR enzymes in the presence and absence of known or suspected inhibitors in relation to reaction temperature and reaction pH; and (2) validation results—method detection limits, precision and bias estimates, spike recoveries, and interference studies—for standard- and low-level automated colorimetric CFA-YNaR1 reduction NO x methods in relation to corresponding USGS approved CFA cadmium-reduction (CdR) NO x methods. The cornerstone of this validation is paired sample statistical and graphical analysis of NOx concentrations from more than 3,800 geographically and seasonally diverse surface-water and groundwater samples that were analyzed in parallel by CFA-CdR and CFA enzyme-reduction methods. Finally, (3) demonstration of a semiautomated batch procedure in which 2-milliliter analyzer cups or disposable spectrophotometer cuvettes serve as reaction vessels for enzymatic reduction of nitrate to nitrite prior to analytical determinations. After the reduction step, analyzer cups are loaded onto CFA, flow injection, or discrete analyzers for simple, rapid, automatic nitrite determinations. In the case of manual determinations, analysts dispense colorimetric reagents into cuvettes containing post-reduction samples, allow time for color to develop, insert cuvettes individually into a spectrophotometer, and record percent transmittance or absorbance in relation to a reagent blank. Data presented here demonstrate equivalent analytical performance of enzymatic reduction NO x methods in these various formats to that of benchmark CFA-CdR NO x methods.

Scientific Investigations Report↗
USGS2018

Stream-channel and watershed delineations and basin-characteristic measurements using lidar elevation data for small drainage basins within the Des Moines Lobe landform region in Iowa

Basin-characteristic measurements related to stream length, stream slope, stream density, and stream order have been identified as significant variables for estimation of flood, flow-duration, and low-flow discharges in Iowa. The placement of channel initiation points, however, has always been a matter of individual interpretation, leading to differences in stream definitions between analysts. This study investigated five different methods to define stream initiation using 3-meter light detection and ranging (lidar) digital elevation models (DEMs) data for 17 streamgages with drainage areas less than 50 square miles within the Des Moines Lobe landform region in north-central Iowa. Each DEM was hydrologically enforced and the five stream initiation methods were used to define channel initiation points and the downstream flow paths. The five different methods to define stream initiation were tested side-by-side for three watershed delineations: (1) the total drainage-area delineation, (2) an effective drainage-area delineation of basins based on a 2-percent annual exceedance probability (AEP) 12-hour rainfall, and (3) an effective drainage-area delineation based on a 20-percent AEP 12-hour rainfall. Generalized least squares regression analysis was used to develop a set of equations for sites in the Des Moines Lobe landform region for estimating discharges for ungaged stream sites with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent AEPs. A total of 17 streamgages were included in the development of the regression equations. In addition, geographic information system software was used to measure 58 selected basin-characteristics for each streamgage. Results of the regression analyses of the 15 lidar datasets indicate that the datasets that produce regional regression equations (RREs) with the best overall predictive accuracy are the National Hydrographic Dataset, Iowa Department of Natural Resources, and profile curvature of 0.5 stream initiation methods combined with the 20-percent AEP 12-hour rainfall watershed delineation method. These RREs have a mean average standard error of prediction (SEP) for 4-, 2-, and 1-percent AEP discharges of 53.9 percent and a mean SEP for all eight AEPs of 55.5 percent. Compared to the RREs developed in this study using the basin characteristics from the U.S. Geological Survey StreamStats application, the lidar basin characteristics provide better overall predictive accuracy.

Iowa↗
USGS2018

Evaluation of whole-water churn splitters for suspended-sediment sample collection and analysis

The U.S. Geological Survey (USGS) collects a wide range of whole-water samples to test for the many physical and chemical constituents that represent stream conditions at the time of sampling to assess the quality of the Nation’s waters. During sampling efforts, in which a suspended-sediment concentration is one result among a broader suite of constituents, a sample is sometimes composited into a churn splitter and then subdivided for analysis. Five churn splitters—comprising three sizes and two different materials—used by the USGS were tested for single-withdrawal accuracy from one-half of full capacity and for multiple-withdrawal accuracy at varied volumes of fullness to see if churn splitters introduce bias during the collection of sediment samples. Both tests were similar to previously conducted tests for consistency, but the tests conducted in this report also attempted to answer questions that arose during previous evaluations of churn splitters. The purpose of this report is to inform sediment analysts about the capabilities and limitations of all available churn-splitter sizes and materials used by the USGS for the analysis of suspended sediment. The results indicate that suspended-sediment samples and constituents absorbed into suspended sediment may have substantial bias errors when withdrawn from churn splitters. Results were affected by the settling velocity of sediment particles relative to the resuspension velocities induced by the churning, the effects of prior withdrawals of the water-sediment mixture, and the remaining volume in a churn splitter after samples were withdrawn.

Scientific Investigations Report↗
USGS2020

Ungulate migrations of the western United States, Volume 1

Across the western United States, many ungulate herds must migrate seasonally to access resources and avoid harsh winter conditions. Because these migration paths cover vast landscapes (in other words migration distances up to 150 miles [241 kilometers]), they are increasingly threatened by roads, fencing, subdivisions, and other development. Over the last decade, many new tracking studies have been conducted on migratory herds, and analytical methods have been developed that allow for population-level corridors and stopovers to be mapped and prioritized. In 2018, the U.S. Geological Survey assembled a Corridor Mapping Team to provide technical assistance to western states working to map bison, elk, moose, mule deer, and pronghorn migrations using existing Global Positioning System data. Led by the Wyoming Cooperative Fish and Wildlife Research Unit, the team consists of federal scientists, university researchers, and biologists and analysts from participating state agencies. In its first year, the team has worked to develop standardized analytical and computational methods and a workflow applicable to datasets typically collected by state agencies. In 2019, the team completed analyses necessary to map corridors, stopovers, routes and winter ranges in Arizona, Idaho, Nevada, Utah, and Wyoming. A total of 26 corridors, 16 migration routes, 25 stopovers, and 9 winter ranges were mapped across these states and are included in this report. This report and associated data release provide the means for the habitats required for migration to be taken into account by state and federal transportation officials, land and wildlife managers, planners, and other conservationists working to maintain big-game migration in the western states.

Scientific Investigations Report↗
USGS2020

Quality of data from the U.S. Geological Survey National Water Quality Network for water years 2013–17

Water samples from 122 sites in the U.S. Geological Survey National Water Quality Network were collected in 2013–17 to document ambient water-quality conditions in surface water of the United States and to determine status and trends of loads and concentrations for nutrients, contaminants, and sediment to estuaries and streams. Quality-control (QC) samples collected in the field with environmental samples were combined with QC samples from laboratory processing to provide information and documentation about the quality of the environmental data. Quality assurance for inorganic and organic compounds assessed in the National Water Quality Network includes collection of field blanks to determine contamination bias and field replicates to determine variability bias. No contamination bias was found for 6 of the 13 nutrient compounds analyzed, and some potential contamination bias for some years was found for the other 7 nutrient compounds. Contamination bias was not found for carbon compounds or ultraviolet-absorbance measurements and was not assessed for sediment. All major ions and trace elements except potassium and lithium showed moderate contamination bias for at least 1 water year; generally, this bias was not at environmentally relevant concentrations. All compounds in the nutrient, carbon, and sediment group and in the major ions and trace elements group had low variability both in detection frequency and in concentration. Exceptions to this low variability were total particulate inorganic carbon and sediment for 2015, both of which are particulate substances with intrinsically high sampling variability. The risk of contamination bias for pesticides in National Water Quality Network samples was low, as indicated by very few detections in field blanks. Sixteen pesticide compounds showed potential contamination bias based on unexpected detections in third-party blind spikes (false-positive results for compounds that are not included in the spike mixture of a sample, where the identity as a QC sample is unknown to the analyst), and 47 different compounds (out of 225 pesticide compounds) showed potential contamination bias from laboratory blanks. However, when timing and relative magnitudes of detections in blank samples, environmental samples, and benchmark concentrations are considered, most of this potential contamination is not relevant to interpretation of published pesticide results. Overall variability in detection frequency for pesticides from field replicates was low or moderate. Also based on field replicates, 55 pesticides had overall high variability in concentrations for at least 1 water year, although these assessments likely overestimate high variability. At least 1 QC issue was found for 87 pesticides; however, most of the QC issues had no or little effect on the interpretation of environmental results because the U.S. Geological Survey National Water Quality Laboratory addressed the QC issue before publishing the environmental results, environmental results were almost entirely nondetections, concentrations of environmental results were higher than potential contamination bias, or benchmark concentrations were orders of magnitude higher than all environmental results. Eight compounds affected by two QC issues had a benchmark less than 100 nanograms per liter and warranted careful consideration of timing and magnitude of QC results in relation to surface-water results before interpretive use.

Scientific Investigations Report↗
USGS2022

Ungulate migrations of the western United States, volume 2

Migration is widespread across taxonomic groups and increasingly recognized as fundamental to maintaining abundant wildlife populations and communities. Many ungulate herds migrate across the western United States to access food and avoid harsh environmental conditions. With the advent of global positioning system (GPS) collars, researchers can describe and map the year-round movements of ungulates at both large and small spatial scales. The migrations can traverse landscapes that are a mix of different jurisdictional ownership and management. Today, the landscapes migrating herds traverse are increasingly threatened by fencing, high-traffic roads, oil and gas development, and other types of permanent development. Through the use of GPS collars, a model of science-based conservation emerged in which migration corridors, stopovers, and winter ranges can be mapped in detail, thereby allowing threats and conservation opportunities to be identified and remedied. In 2018, the U.S. Geological Survey (USGS) assembled a Corridor Mapping Team (CMT) to work collaboratively with western states to map migrations of Odocoileus hemionus (mule deer), Cervus canadensis (elk), and Antilocapra americana (pronghorn). Led by the USGS Wyoming Cooperative Fish and Wildlife Research Unit, the team consists of Federal scientists, university researchers, and biologists and analysts from participating State and Tribal agencies. The first set of maps described a total of 42 migrations across 5 western states and was published in 2020 as the first volume of this report series. This second volume describes an additional 65 migrations mapped within 9 western states and select Tribal lands. As the western United States continues to grow, this report series and the associated map files released by the USGS will allow for migration maps to be used for conservation planning by a wide array of State and Federal stakeholders to reduce barriers to migration caused by fences, roads, and other development.

western United States↗
USGS2012

Analyzing legacy U.S. Geological Survey geochemical databases using GIS: applications for a national mineral resource assessment

This report emphasizes geographic information system analysis and the display of data stored in the legacy U.S. Geological Survey National Geochemical Database for use in mineral resource investigations. Geochemical analyses of soils, stream sediments, and rocks that are archived in the National Geochemical Database provide an extensive data source for investigating geochemical anomalies. A study area in the Egan Range of east-central Nevada was used to develop a geographic information system analysis methodology for two different geochemical datasets involving detailed (Bureau of Land Management Wilderness) and reconnaissance-scale (National Uranium Resource Evaluation) investigations. ArcGIS was used to analyze and thematically map geochemical information at point locations. Watershed-boundary datasets served as a geographic reference to relate potentially anomalous sample sites with hydrologic unit codes at varying scales. The National Hydrography Dataset was analyzed with Hydrography Event Management and ArcGIS Utility Network Analyst tools to delineate potential sediment-sample provenance along a stream network. These tools can be used to track potential upstream-sediment-contributing areas to a sample site. This methodology identifies geochemically anomalous sample sites, watersheds, and streams that could help focus mineral resource investigations in the field.

Egan Range↗
USGS2025

Long Term Resource Monitoring procedures—Aquatic vegetation monitoring

This standard operating procedure (SOP) manual describes the collection of standardized, long-term data for aquatic vegetation communities in selected study pools of the Upper Mississippi River System in the United States. The primary intent of the data collection is to assess the status and trends that aid in understanding the unique river ecosystem and to guide large-scale ecological restoration of the river and its biological communities, like aquatic plants and their dependent wildlife. This SOP is an update to the version published in 2000 and reflects modifications to sample sizes and additions of new data collection procedures. All long-term monitoring programs and their SOPs must be adapted to changing conditions and be improved through learning, and this SOP clarifies procedures and adds new elements since the initial SOP was written more than 25 years ago. The SOP is intended for multiple audiences, including vegetation specialists through the Upper Mississippi River Restoration Program, data analysts using the publicly available data generated through this SOP, and natural resource managers and restoration practitioners who need data and science to guide some decisions. This SOP may be transferable and adaptable to other ecosystems when the aquatic plant community is the focus.

Illinois, Iowa, Minnesota, Missouri, Wisconsin↗
USGS2018

SWToolbox: A surface-water tool-box for statistical analysis of streamflow time series

This report is a user guide for the low-flow analysis methods provided with version 1.0 of the Surface Water Toolbox (SWToolbox) computer program. The software combines functionality from two software programs—U.S. Geological Survey (USGS) SWSTAT and U.S. Environmental Protection Agency (EPA) DFLOW. Both of these programs have been used primarily for computation of critical low-flow statistics. The main analysis methods are the computation of hydrologic frequency statistics such as the 7-day minimum flow that occurs on average only once every 10 years (7Q10), computation of design flows including biologically based flows, and computation of flow-duration curves and duration hydrographs. Other annual, monthly, and seasonal statistics can also be computed. The interface facilitates retrieval of streamflow discharge data from the USGS National Water Information System and outputs text reports for a record of the analysis. Tools for graphing data and screening tests are available to assist the analyst in conducting the analysis.

Techniques and Methods↗