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USGS2024

Water-quality comparisons in the Greater Mooses Tooth unit of the National Petroleum Reserve in Alaska, 2010 and 2023

The United States has long held oil reserves in the National Petroleum Reserve in Alaska (NPR–A), but oil production did not begin until 2015. The waters of the NPR–A are generally considered “pristine,” but water quality has not been characterized temporally or spatially in a rigorous manner. In 2010 and 2023, the U.S. Geological Survey, in cooperation with the Bureau of Land Management, collected water-quality samples from four small, beaded streams in the NPR–A, three of which currently (2024) have oil and gas infrastructure within their drainage. Samples collected preconstruction and postconstruction were analyzed and compared to determine concentration changes in nutrients, major ions, trace elements, and volatile organic compounds to evaluate the effectiveness of required operating procedures designed to minimize potential effects to water quality from oil and gas activities. The four small streams in the Greater Mooses Tooth unit of the NPR–A had similar water-quality characteristics in the 2010 and 2023 samples. Most analytes were measured at low concentrations or below the reporting level for both samples. For analytes that were detected, variability between the two samples was generally low and mostly showed lower concentrations in the 2023 samples, possibly partially because of recent rainfall that led to streamflow being much higher at the time of the 2023 sample. Trichloromethane was present in the sample at one site in both years and at a second site in the 2023 sample. All three detections of trichloromethane were within the expected natural background range for the area. The few increases in analyte concentrations in the watersheds with oil and gas facilities were all within the range of predevelopment concentrations or background concentrations for the area.

Alaska↗
USGS2026

Colocating artificial intelligence data centers with energy infrastructure on Federal public lands—A science synthesis and spatial analysis to inform decision making

Executive Summary Artificial intelligence (AI) is rapidly transforming industries and economies, creating an urgent need to strategically plan for the energy and infrastructure required to support increasing AI use. U.S. Federal agencies and bureaus have been directed to explore ways to accelerate permitting, development, and deployment of energy resources and AI technologies, including encouraging the colocation of energy infrastructure and data centers. To inform these initiatives, this report synthesizes relevant scientific information and presents a spatial analysis of existing energy infrastructure and data centers on or near U.S. Federal public lands managed by the Bureau of Land Management (BLM). The purpose of this science synthesis and spatial analysis is to provide the BLM with foundational information for considering potential colocation of data centers with energy infrastructure on Federal public lands to support evidence-based decisions. Additionally, this report provides insight into current (2025) and potential future energy demands by providing projections of a range of potential future environmental conditions relevant to maintaining industry-recommended cooling temperature standards necessary for efficient data center operations. As a part of this effort, a rapid response literature review was conducted of the best available science on the topic of data center development and energy infrastructure in July–August 2025, supplemented by additional resources recommended by U.S. Federal agency and bureau subject matter experts (hereafter experts; including the U.S. Department of Energy National Laboratory of the Rockies) and peer reviewers. To better understand current conditions relevant to AI data center development, a spatial analysis was conducted across Alaska and 11 States in the Western United States, Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, Washington, and Wyoming, all of which contain extensive BLM-managed surface lands (hereafter referred to as “BLM lands”) that could be considered for the colocation of energy infrastructure and AI data centers. This effort identified BLM lands within 10 miles of existing transmission lines, consistent with methods used in previous BLM programmatic environmental impact statements. This report describes the types of data centers operating within the United States, which vary in ownership, size, technology, and proximity to end users. This report then outlines the primary considerations of data center development, including reliable energy supply, natural resources (such as water availability to support cooling requirements), and relevant policy and regulatory considerations. Energy supply considerations are pivotal for data center operation. Between 2014 and 2018, data centers in the United States accounted for nearly 2 percent of the Nation’s total electricity consumption, and data center energy consumption is projected to increase from 2 to 6.7–12 percent of total U.S. electricity use by 2028. These energy requirements necessitate careful consideration of energy supply when considering potentially suitable locations for data center development. Experts anticipate that an increase in renewable energy generation will likely support most potential future power demand needs, including for data centers, followed by increases in natural gas, nuclear, and geothermal energy production. Additional capacity in the form of battery storage will likely not generate electricity, but may improve the reliability and flexibility of supply, helping to ensure that growing data center loads can be met. However, the U.S. Department of Energy estimates that the United States will need, on average, 57 percent more energy transmission infrastructure by 2035 to account for the growing power demand introduced by development such as data centers. Cooling server equipment in data centers requires large amounts of electricity and water, and this demand can be exacerbated by hot and humid conditions. Energy efficient water-based cooling technologies may reduce electricity consumption onsite but require more water consumption. This additional water demand has the potential to increase water stress and competition with other users. As such, developing data centers will likely need a thorough assessment of current and potential future water availability, as well as consideration of how water demand may change across other sectors. Data center development involves policy and regulatory considerations, as projects must undergo environmental review and authorization processes that can take 18–24 months. Coordinating these environmental reviews and authorizations with other energy development projects, such as building new transmission lines, may cause additional delays. Recent efforts by the U.S. Department of Energy and U.S. Department of the Interior aim to expedite environmental reviews and authorizations and improve coordination across agencies. The spatial analysis identified 771 existing AI data centers and more than 3,300 power plants. The spatial analysis found that 6 percent of AI data centers and 22 percent of power plants in the Western United States were on or within 1 mile of BLM lands, and California had the largest number of facilities. Most existing AI data centers were near high-voltage transmission lines and close to power plants, supporting efficient energy delivery. More than 90,000,000 acres of BLM lands were within 10 miles of existing high-voltage transmission lines, representing 38 percent of BLM lands in the study area. Available transmission infrastructure and the overlap with BLM lands varied by State, and Alaska had limited overlap compared to the rest of the Western United States. To operate most efficiently, data center temperatures must be at or below 80.6 degrees Fahrenheit. This analysis of future temperature and precipitation projections indicated increasing cooling demands for data centers, particularly in Arizona, California, and Nevada, where rising temperatures are expected to increase energy and operational costs while potentially stressing current regional electrical grid infrastructure. This report highlights relevant energy supply, natural resources, and regulatory considerations for data center development on BLM lands. This report does not provide a comprehensive ecological, regulatory, land suitability, or permitting analysis. The factors described here are contextual considerations only and are not intended to identify, rank, quantify, or recommend optimal areas for data center colocation. This spatial analysis focused solely on energy considerations relevant to data centers and did not consider water availability, critical habitats, BLM National Conservation Lands, areas of cultural or historical significance, and other sensitive resources. These topics are recognized as critical but were not within the scope of this science synthesis and spatial analysis.

Scientific Investigations Report↗
USGS2002

Statistical methods in water resources

Preface This book began as class notes for a course we teach on applied statistical methods to hydrologists of the Water Resources Division, U. S. Geological Survey (USGS). It reflects our attempts to teach statistical methods which are appropriate for analysis of water resources data. As interest in this course has grown outside of the USGS, incentive grew to develop the material into a textbook. The topics covered are those we feel are of greatest usefulness to the practicing water resources scientist. Yet all topics can be directly applied to many other types of environmental data. This book is not a stand-alone text on statistics, or a text on statistical hydrology. For example, in addition to this material we use a textbook on introductory statistics in the USGS training course. As a consequence, discussions of topics such as probability theory required in a general statistics textbook will not be found here. Derivations of most equations are not presented. Important tables included in all general statistics texts, such as quantiles of the normal distribution, are not found here. Neither are details of how statistical distributions should be fitted to flood data -- these are adequately covered in numerous books on statistical hydrology. We have instead chosen to emphasize topics not always found in introductory statistics textbooks, and often not adequately covered in statistical textbooks for scientists and engineers. Tables included here, for example, are those found more often in books on nonparametric statistics than in books likely to have been used in college courses for engineers. This book points the environmental and water resources scientist to robust and nonparametric statistics, and to exploratory data analysis. We believe that the characteristics of environmental (and perhaps most other 'real') data drive analysis methods towards use of robust and nonparametric methods. Exercises are included at the end of chapters. In our course, students compute each type of analysis (t-test, regression, etc.) the first time by hand. We choose the smaller, simpler examples for hand computation. In this way the mechanics of the process are fully understood, and computer software is seen as less mysterious. We wish to acknowledge and thank several other scientists at the U. S. Geological Survey for contributing ideas to this book. In particular, we thank those who have served as the other instructors at the USGS training course. Ed Gilroy has critiqued and improved much of the material found in this book. Tim Cohn has contributed in several areas, particularly to the sections on bias correction in regression, and methods for data below the reporting limit. Richard Alexander has added to the trend analysis chapter, and Charles Crawford has contributed ideas for regression and ANOVA. Their work has undoubtedly made its way into this book without adequate recognition. Professor Ken Potter (University of Wisconsin) and Dr. Gary Tasker (USGS) reviewed the manuscript, spending long hours with no reward except the knowledge that they have improved the work of others. For that we are very grateful. We also thank Madeline Sabin, who carefully typed original drafts of the class notes on which the book is based. As always, the responsibility for all errors and slanted thinking are ours alone.

Techniques of Water-Resources Investigations↗
USGS1978

Technique for estimating the magnitude and frequency of floods in St. Louis County, Missouri

Equations and nomographs in.this report can be used to estimate peak flood-discharges having recurrence intervals up to 100 years in rural and urban areas of St. Louis County, Mo. The basin characteristics significant at the 5-percent probability level were drainage area and percentage imperviousness. Drainage area can be measured from maps, while percentage of imperviousness can either be measured from aerial photographs or estimated from land-use projections. These equations are based upon the analysis of hydrologic data collected at 30 continuous-recording gaging stations with drainage areas ranging from 0.8 to 39.0 square miles, and with impervious areas ranging from 1 to 32 percent.

Missouri↗
USGS1984

Ground-water level data and preliminary potentiometric-surface maps, Yucca Mountain and vicinity, Nye County, Nevada

The report contains a table of ground-water level data and two preliminary potentiometric-surface maps for the Yucca Mountain area. The water-level surface shown on the maps generally represents water-table (unconfined) conditions. The water table in the Yucca Mountain area occurs in ash-flow and air-fall tuffs of tertiary age. West of the crest of Yucca Mountain, water-level altitudes are about 775 meters above sea level. Along the eastern edge and southern end of Yucca Mountain, the potentiometic surface generally is nearly flat, is about 728 to 730 meters above sea level, and has a southeastward slope. (USGS)

Water-Resources Investigations Report↗
USGS1992

Aquifer-test results, direction of ground-water flow, and 1984-90 annual ground-water pumpage for irrigation, lower Big Lost River Valley, Idaho

The study area (see index map of Idaho), part of the Big Lost River drainage basin, is at the northern side of the eastern Snake River Plain. The lower Big Lost River Valley extends from the confluence of Antelope Creek and the Big Lost River to about 4 mi south of Arco and encompasses about 145 mi 2 (see map showing water-level contours). The study area is about 18 mi long and, at its narrowest, 4 mi wide. Arco, Butte City, and Moore, with populations of 1,016, 59, and 190, respectively, in 1990, are the only incorporated towns. The entire study area, except the extreme northwestern part, is in Butte City. The study area boundary is where alluvium and colluvium pinch out and abut against the White Knob Mountains (chiefly undifferentiated sedimentary rock with lesser amounts of volcanic rock) on the west and the Lost River Range (chiefly sedimentary rock) on the east. Gravel and sand in the valley fill compose the main aquifer. The southern boundary is approximately where Big Lost River valley fill intercalates with or abuts against basalt of the Snake River Group. Spring ground-water levels and flow in the Big Lost River depend primarily on temperature and the amount and timing of precipitation within the entire drainage basin. Periods of abundant water supply and water shortages are, therefore, related to the amount of annual precipitation. Surface reservoir capacity in the valley (Mackay Reservoir, about 20 mi northwest of Moore) is only 20 percent of the average annual flow of the Big Lost River (Crosthwaite and others, 1970, p. 3). Stored surface water is generally unavailable for carryover from years of abundant water supply to help relieve drought conditions in subsequent years. Many farmers have drilled irrigation wells to supplement surface-water supplies and to increase irrigated acreage. Average annual flow of the Big Lost River below Mackay Reservoir near Mackay (gaging station 13127000, not shown) in water years 1905, 1913-14, and 1920-90 was about 224,600 acre-ft; average annual flow of the Big Lost River near Arco (gaging station 13132500; see map showing water-level contours) in water years 1947-61, 1967-80, and 1983-90 was about 79,000 acre-ft (Harenberg and others, 1991, p. 254-255). Moore Canal and East Side Ditch divert water from the Big Lost River at the Moore Diversion, 3 mi north of Moore (see map showing water-level contours) and supply water for irrigation near the margins of the valley. When water supply is average or greater, water in the Big Lost River flows through the study area and onto the Snake River Plain, where it evaporates or infiltrates into the Snake River Plain aquifer. When water supply is below average, water in the Big Lost River commonly does not reach Arco; rather, it is diverted for irrigation in the interior of the valley, evaporates, or infiltrates to the valley-fill aquifer. This report describes the results of a study by the U.S. Geological Survey, in cooperation with the Idaho Department of Water Resources, to collect hydrologic data needed to help address water-supply problems in the Big Lost River Valley. Work involved (1) field inventory of 81 wells, including 46 irrigation wells; (2) measurement of water levels in 154 wells in March 1991; (3) estimation of annual ground-water pumpage for irrigation from 1984 through 1990; and (4) analysis of results of an aquifer test conducted southwest of Moore. All data obtained during this study may be inspected at the U.S. Geological Survey, Idaho District office, Boise.

Idaho↗
USGS1999

Geohydrology of monitoring wells drilled in Oasis Valley near Beatty, Nye County, Nevada, 1997

Twelve monitoring wells were installed in 1997 at seven sites in and near Oasis Valley, Nevada. The wells, ranging in depth from 65 to 642 feet, were installed to measure water levels and to collect water-quality samples. Well-construction data and geologic and geophysical logs are presented in this report. Seven geologic units were identified and described from samples collected during the drilling: (1) Ammonia Tanks Tuff; (2) Tuff of Cutoff Road; (3) tuffs, not formally named but informally referred to in this report as the 'tuff of Oasis Valley'; (4) lavas informally named the 'rhyolitic lavas of Colson Pond'; (5) Tertiary colluvial and alluvial gravelly deposits; (6) Tertiary and Quaternary colluvium; and (7) Quaternary alluvium. Water levels in the wells were measured in October 1997 and February 1998 and ranged from about 18 to 350 feet below land surface. Transmissive zones in one of the boreholes penetrating volcanic rock were identified using flowmeter data. Zones with the highest transmissivity are at depths of about 205 feet in the 'rhyolitic lavas of Colson Pond' and 340 feet within the 'tuff of Oasis Valley.'

Nevada↗
USGS1980

Streamflow characteristics of the Yellowstone River Basin, Montana, through 1976

Statistical summaries of streamflow data for selected stream-gaging and crest-stage gage sites are presented in this report to aid in appraising the hydrology of the Yellowstone River basin, Montana. Streamflow records presented for 45 gaging stations and 45 crest-stage gages for the period of record. Streamflow record collection in the Yellowstone River basin began in 1889. For each gaging station selected for this report, a brief description is given for station location, drainage area , period of record, revisions of previously published records, type and history of gages, regulation and diversions, and extremes of discharge. These data are followed by tables of monthly and annual flow statistics, high-flow and low-flow frequency data, flood-frequency data, flow-duration information, and for natural-flow sites selected basin characteristics. For each crest-stage gage, the brief description consists of location, drainage area, period of record, and type and history of gage. This information is followed by tables of flood-frequency data and selected basin characteristics.

Montana↗
USGS1982

Water quality of the three major tributaries to the Chesapeake Bay, the Susquehanna, Potomac, and James Rivers, January 1979 - April 1981

Water-quality constituent loads at the Fall Line stations of the Susquehanna, Potomac, and James Rivers, the three major tributaries to the Chesapeake Bay, can be estimated with reasonable accuracy by regression techniques, especially for wet periods of 1 year or more. Net transport of all nutrient species and most other constituents, especially those found in greatest concentrations associated with suspended material, is dominated by a few spring and storm-related high-flow events. Atrazine and 2,4-D are the two herbicides most consistently detected at the Fall Line of the Susquehanna and Potomac Rivers. Concentrations of total residual chlorine and low-molecular-weight, halogenated hydrocarbons at selected sites in estuaries to the upper Bay are generally at or below detection limits. When compared to the two other major tributaries, the James River has the lowest discharge-weighted-sulfate concentrations, presumably because of the lack of coal mining activity in this basin. This river also has lower total nitrogen concentrations. Ammonia concentrations and loads are decreasing at all three Fall Line stations, as is orthophosphate in the Susquehanna and Potomac Rivers. Slight increases in total nitrogen and nitrite plus nitrate concentrations in the Susquehanna River from 1969 to 1980 may warrant continued monitoring. Analyses of data for this report confirm the previous suggestion that when water discharge of the Susquehanna River at Conowingo, Maryland, is below about 400,000 cubic feet per second, sediment, with sorbed nutrients and other constituents, is deposited behind the three hydroelectric dams on this river between Harrisburg, Pennsylvania, and its mouth. Discharges above 400,000 cubic feet per second resuspend these sediments and transport constituent loads to the Bay well in excess of loads transported by the Susquehanna River at Harrisburg. In addition to precipitation quantity and intensity, antecedent conditions and season of the year play a major role in the transport of sediments and their associated chemical constituents at all three stations.

James River, Potomac River, Susquehanna River↗
USGS1985

Analysis of water-level fluctuations of the U.S. Highway 90 retention pond, Madison, Florida

A closed basin stormwater retention pond, located 1 mile west of Madison, Florida, has a maximum storage capacity of 134.1 acre-feet at the overtopping altitude of 100.2 feet. The maximum observed altitude (July 1982 to March 1984) was 99.52 feet (126.7 acre-feet) on March 28, 1984. This report provides a technique for simulating net monthly change-in-altitude in response to rainfall and evaporation. A regression equation was developed which relates net monthly change in altitude (dependent variable) to rainfall and evaporation (independent variables). Rainfall frequency curves were developed using a log-Pearson Type III distribution of the annual, January through April, June through August, and July monthly rainfall totals for the years 1908-72, 1974, 1976-82. The altitude of the retention pond increased almost 7 feet during the 4-month period January through April 1983. The rainfall total was 35.1 inches, and the recurrence interval exceeded the 100-year January-April rainfall.

Florida↗
USGS1967

Hydrologic and climatologic data, 1966, Salt Lake County, Utah

An investigation of the water resources of Salt Lake County, Utah, was undertaken by the Water Resources Division of the U.S. Geological Survey in July 1963. This investigation is a cooperative project financed equally by the State of Utah and the Federal Government in accordance with an agreement between the State Engineer and the Geological Survey. The Utah Water and Power Board, Utah Fish and Game Commission, Salt Lake County Water Conservancy District, Metropolitan Water District of Salt Lake City, Salt Lake County, Kennecott Copper Corporation, Utah Power and Light Company, Salt Lake City Chamber of Commerce, and the Central Utah Water Conservancy District contributed funds to the State Engineer's office toward support of the project. The investigation encompasses the collection and interpretation of a large variety of climatologic, hydrologic, and geologic data in and near Salt Lake County. Utah Basic-Data Releases 11 and 12 contain data collected through 1965. This release contains climatologic and surface-water data for the 1966 water year (October 1965 to September 1966) and groundwater data collected during the 1966 calendar year. Similar annual releases will contain data collected during the remainder of the investigation, and interpretive reports will be prepared as the investigation proceeds. Organizations that furnished data are acknowledged in station descriptions and footnotes to tables.

Utah↗
USGS2011

Groundwater conditions in Utah, spring of 2011

This is the forty-eighth in a series of annual reports that describe groundwater conditions in Utah. Reports in this series, published cooperatively by the U.S. Geological Survey and the Utah Department of Natural Resources, Division of Water Rights, and the Utah Department of Environmental Quality, Division of Water Quality, provide data to enable interested parties to maintain awareness of changing groundwater conditions. This report, like the others in the series, contains information on well construction, groundwater withdrawal from wells, water-level changes, precipitation, streamflow, and chemical quality of water. Information on well construction included in this report refers only to wells constructed for new appropriations of groundwater. Supplementary data are included in reports of this series only for those years or areas that are important to a discussion of changing groundwater conditions and for which applicable data are available. This report includes individual discussions of selected significant areas of groundwater development in the State for calendar year 2010. Most of the reported data were collected by the U.S. Geological Survey in cooperation with the Utah Department of Natural Resources, Division of Water Rights, and the Utah Department of Environmental Quality, Division of Water Quality. This report is also available online at http:// www.waterrights.utah.gov/techinfo/ and http://ut.water.usgs. gov/publications/GW2011.pdf. Groundwater conditions in Utah for calendar year 2009 are reported in Burden and others (2010) and available online at http://ut.water.usgs.gov/ publications/GW2010.pdf. Analytical results associated with water samples collected from each area of groundwater development were compared to State of Utah Maximum Contaminant Levels (MCLs) and secondary drinking-water standards of routinely measureable substances present in water supplies. The MCLs and secondary drinking-water standards can be accessed online at http://www.rules.utah.gov/publicat/code/r309/r309-200. htm#T5. The U.S. Environmental Protection Agency (EPA) drinking-water standards can be accessed at http://www.epa. gov/safewater/mcl.html#mcls. Maximum Contaminant Levels and secondary drinking-water standards were developed for public water systems and do not apply to the majority of wells sampled during this study.

Utah↗
USGS2010

Approaches to highly parameterized inversion: A guide to using PEST for model-parameter and predictive-uncertainty analysis

Analysis of the uncertainty associated with parameters used by a numerical model, and with predictions that depend on those parameters, is fundamental to the use of modeling in support of decisionmaking. Unfortunately, predictive uncertainty analysis with regard to models can be very computationally demanding, due in part to complex constraints on parameters that arise from expert knowledge of system properties on the one hand (knowledge constraints) and from the necessity for the model parameters to assume values that allow the model to reproduce historical system behavior on the other hand (calibration constraints). Enforcement of knowledge and calibration constraints on parameters used by a model does not eliminate the uncertainty in those parameters. In fact, in many cases, enforcement of calibration constraints simply reduces the uncertainties associated with a number of broad-scale combinations of model parameters that collectively describe spatially averaged system properties. The uncertainties associated with other combinations of parameters, especially those that pertain to small-scale parameter heterogeneity, may not be reduced through the calibration process. To the extent that a prediction depends on system-property detail, its postcalibration variability may be reduced very little, if at all, by applying calibration constraints; knowledge constraints remain the only limits on the variability of predictions that depend on such detail. Regrettably, in many common modeling applications, these constraints are weak. Though the PEST software suite was initially developed as a tool for model calibration, recent developments have focused on the evaluation of model-parameter and predictive uncertainty. As a complement to functionality that it provides for highly parameterized inversion (calibration) by means of formal mathematical regularization techniques, the PEST suite provides utilities for linear and nonlinear error-variance and uncertainty analysis in these highly parameterized modeling contexts. Availability of these utilities is particularly important because, in many cases, a significant proportion of the uncertainty associated with model parameters-and the predictions that depend on them-arises from differences between the complex properties of the real world and the simplified representation of those properties that is expressed by the calibrated model. This report is intended to guide intermediate to advanced modelers in the use of capabilities available with the PEST suite of programs for evaluating model predictive error and uncertainty. A brief theoretical background is presented on sources of parameter and predictive uncertainty and on the means for evaluating this uncertainty. Applications of PEST tools are then discussed for overdetermined and underdetermined problems, both linear and nonlinear. PEST tools for calculating contributions to model predictive uncertainty, as well as optimization of data acquisition for reducing parameter and predictive uncertainty, are presented. The appendixes list the relevant PEST variables, files, and utilities required for the analyses described in the document.

Michigan↗
USGS2012

Survey of hydrologic models and hydrologic data needs for tracking flow in the Rio Grande, north-central New Mexico, 2010

The six Middle Rio Grande Pueblos have prior and paramount rights to deliveries of water from the Rio Grande for their use. When the pueblos or the Bureau of Indian Affairs Designated Engineer identifies a need for additional flow on the Rio Grande, the Designated Engineer is tasked with deciding the timing and amount of releases of prior and paramount water from storage at El Vado Reservoir to meet the needs of the pueblos. Over the last three decades, numerous models have been developed by Federal, State, and local agencies in New Mexico to simulate, understand, and (or) manage flows in the Middle Rio Grande upstream from Elephant Butte Reservoir. In 2008, the Coalition of Six Middle Rio Grande Basin Pueblos entered into a cooperative agreement with the U.S. Geological Survey to conduct a comprehensive survey of these hydrologic models and their capacity to quantify and track various components of flow. The survey of hydrologic models provided in this report will help water-resource managers at the pueblos, as well as the Designated Engineer, make informed water-resource-management decisions that affect the prior and paramount water use. Analysis of 4 publicly available surface-water models and 13 publicly available groundwater models shows that, although elements from many models can be helpful in tracking flow in the Rio Grande, numerous data gaps and modeling needs indicate that accurate, consistent, and timely tracking of flow on the Rio Grande could be improved. Deficient or poorly constrained hydrologic variables are sources of uncertainty in hydrologic models that can be reduced with the acquisition of more refined data. Data gaps need to be filled to allow hydrologic models to be run on a real-time basis and thus ensure predictable water deliveries to meet needs for irrigation, domestic, stock, and other water uses. Timeliness of flow-data reporting is necessary to facilitate real-time model simulation, but even daily data are sometimes difficult to obtain because the data come from multiple sources. Each surface-water model produces results that could be helpful in quantifying the flow of the Rio Grande, specifically by helping to track water as it moves down the channel of the Rio Grande and by improving the understanding of river hydraulics for the specified reaches. The ability of each surface-water model to track flow on the Rio Grande varies according to the purpose for which each model was designed. The purpose of Upper Rio Grande Water Operations Model (URGWOM) - to simulate water storage and delivery operations in the Rio Grande - is more applicable to tracking flow on the Rio Grande than are any of the other surface-water models surveyed. Specifically, the strengths of URGWOM in relation to modeling flow are the details and attention given to the accounting of Rio Grande flow and San Juan-Chama flow at a daily time step. The most significant difficulty in using any of the surveyed surface-water models for the purpose of predicting the need for requested water releases is that none of the surface-water models surveyed consider water accounting on a real-time basis. Groundwater models that provide detailed simulations of shallow groundwater flow in the vicinity of the Rio Grande can provide large-scale estimates of flow between the Rio Grande and shallow aquifers, which can be an important component of the Rio Grande water budget as a whole. The groundwater models surveyed for this report cannot, however, be expected to provide simulations of flow at time scales of less than the simulated time step (1 month to 1 year in most cases). Of those of the currently used groundwater models, the purpose of model 13 - to simulate the shallow riparian groundwater environment - is the most appropriate for examining local-scale surface-water/groundwater interactions. The basin-scale models, however, are also important in understanding the large-scale water balances between the aquifers and the surface water. In the case of the Upper and Middle Rio Grande Valley, models 6, 10, and 12 are the most accurate and current groundwater models available.

Colorado;New Mexico↗
USGS2012

Estimation of baseline daily mean streamflows for ungaged locations on Pennsylvania streams, water years 1960-2008

Water-resource managers use daily mean streamflows to generate streamflow statistics and analyze streamflow conditions. An in-depth evaluation of flow regimes to promote instream ecological health often requires streamflow information obtainable only from a time series hydrograph. Historically, it has been difficult to estimate daily mean streamflow for an ungaged location. The U.S. Geological Survey (USGS), in cooperation with the Pennsylvania Department of Environmental Protection, Susquehanna River Basin Commission, and The Nature Conservancy, has developed the Ba seline S treamflow E stimator (BaSE) to estimate baseline streamflow at a daily time scale for ungaged streams in Pennsylvania using data collected during water years 1960–2008. Baseline streamflow is minimally altered by regulation, diversion, or mining, and other anthropogenic activities. Daily mean streamflow is estimated in BaSE using a methodology that equates streamflow as a percentile from a flow duration curve for a particular day at an ungaged location with streamflow as a percentile from the flow duration curve for the same day at a reference streamgage that is considered to be hydrologically similar to the ungaged location. An appropriate reference streamgage is selected using map correlation, in which variogram models are developed that correlate streamflow at one streamgage with streamflows at all other streamgages. The percentiles from a flow duration curve for the ungaged location are converted to streamflow through the use of regression equations. Regression equations used to predict 17 flow-duration exceedance probabilities were developed for Pennsylvania using geographic information system-derived basin characteristics. The standard error of prediction for the regression equations ranged from 11 percent to 92 percent with the mean of 31 percent. The map correlation method for estimating streamflow was tested at locations within two pilot basins, the Upper Delaware River Basin and the Lower Susquehanna River Basin, before being applied statewide. Reference streamgages within the pilot basins were used as ungaged locations for analyzing the map correlation method. Correlation using Spearman’s rho and centroid distance performed as well as, or better than, the method using the closest streamgage as a reference streamgage. Map correlation using the correlation metrics identified in the pilot basins was applied to 156 streamgages in and near Pennsylvania. BaSE uses the map correlation method and flow-duration exceedance probability regression equations to estimate baseline daily mean streamflow for an ungaged location. The output from BaSE is a Microsoft Excel® report file that summarizes the reference streamgage and ungaged location information, including basin characteristics, percent difference in basin characteristics between the two locations, any warning associated with the basin characteristics, mean and median streamflow for the ungaged location, and a daily hydrograph of streamflow for water years 1960–2008 for the ungaged location. The daily mean streamflow for the ungaged location can be exported as a text file to be used as input into other statistical software packages. BaSE estimates daily mean streamflow for baseline conditions only, and any alterations to streamflow from regulation, large water use, or substantial mining are not reflected in the estimated streamflow.

Pennsylvania↗
USGS2001

Methods of analysis by the U. S. Geological Survey National Water Quality Laboratory-Determination of organic plus inorganic mercury in filtered and unfiltered natural water with cold vapor; atomic fluorescence spectrometry

An analytical method using cold vapor-atomic fluorescence spectrometry was developed by the U.S. Geological Survey in 2001 for the determination of organic plus inorganic mercury in filtered and unfiltered natural water. This method was developed to eliminate the use of acid dichromate preservative and to provide capability to measure ambient mercury concentrations in natural water. Dissolved mercury includes all oxidizable mercury species present in natural water that has been filtered through a 0.45- micrometer pore size capsule filter. Wholewater recoverable mercury includes dissolved mercury species and mercury species adsorbed to particulate matter in unfiltered natural water. Mercury species can include elemental mercury, mercury (II), mercury (II) complexes, various alkyl- and phenylmercury compounds, and other forms of mercury. In this method, samples are collected and processed according to standard U.S. Geological Survey protocols. Samples are preserved onsite with 6N hydrochloric acid in a ratio of 1 to 100 in a borosilicateglass bottle with fluoropolymer-lined cap. Mercury species are oxidized to mercury (II) by using bromine monochloride; excess oxidation reagent is neutralized with hydroxylamine hydrochloride. Elemental mercury produced after adding stannous chloride is purged from the solution with ultrapure argon gas into a cell in which the mercury concentration is measured by atomic fluorescence emission at 253.7 nanometers. The analytical response is linear up to 125 nanograms per liter (ng/L) of mercury, and the short-term method detection limit is about 5 ng/L. The analytical variability at 50 ng/L is about 10 percent. This report describes the method and compares the use of hydrochloric acid to acid dichromate as a field preservative. Ambient mercury concentrations in hydrochloric acidpreserved samples stored in borosilicate-glass bottles with fluoropolymer-lined caps are shown to be stable for at least 30 days. Mercury concentrations are stable for at least 5 months after bromine monochloride is added to the sample bottles in the laboratory. The long-term average percent recoveries at 20, 45, and 75 ng/L in reagent water, filtered and unfiltered ground water, and filtered and unfiltered surface water range from 89 to 108, 96 to 103, and 94 to 98 percent, respectively.

Water-Resources Investigations Report↗
USGS1979

Pesticide residues in agricultural drains, southeastern desert area, California

A study is being made to determine the occurrence and distribution of pesticides in the agricultural drains for approximately 3/4 million irrigated acres in the southeastern desert area of California. This report describes the results of the first year of sampling and analyzing (1) water in the drains , (2) bed material in the drains, (3) water from field tile-drainage lines, and (4) irrigation tailwater and water in the drains directly exposed to drift from aerial application of pesticides. Residues of almost all the pesticides selected for monitoring were found in water in the drains. Examination of the data to determine the probable source of pesticides indicated generally slight concentrations from bed material in the drains, usually no detectable concentrations from field tile-drainage lines, and apparently large concentrations from irrigation tailwater and drift from aerial application. (Woodard-USGS)

Water-Resources Investigations Report↗
USGS1983

Ground water in carbonate rocks and regolith in the Fairview area, Tennessee

Fourteen test wells drilled in the Fairview area, Tennessee, produce from 3 to 100 gallons per minute and have an average yield of 32 gallons per minute, measured while blowing water from the wells with compressed air. In comparison, the average yield of supply wells reported by drillers is 13 gallons per minute. Specific capacities for three of the test wells ranged from 0.3 to 0.6 gallons per minute per foot of drawdown after 8 hours of pumping at 20 to 47 gallons per minute. Two test wells had specific capacities of 1.1 and 0.4 gallons per foot of drawdown after 72 hours of pumping at 55 and 43 gallons per minute. The mineral content of ground water increases greatly below a gypsum horizon approximately 100 feet below the top of the Fort Payne Formation. Ground water above the gypsum horizon, however, meets the standards for finished drinking water. (USGS)

Water-Resources Investigations Report↗