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Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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At least 559 records · Page 31Linked to original sources
USGS1997

A strategy for monitoring glaciers

Glaciers are important features in the hydrologic cycle and affect the volume, variability, and water quality of runoff. Assessing and predicting the effect of glaciers on water resources require a monitoring program to provide basic data for this understanding. The monitoring program of the U.S. Geological Survey employs a nested approach whereby an intensively studied glacier is surrounded by less intensively studied glaciers and those monitored solely by remote sensing. Ideally, each glacierized region of the United States would have such a network of glaciers. The intensively studied glacier provides a detailed understanding of the physical processes and their temporal changes that control the mass exchange of the glaciers in that region. The less intensively studied glaciers are used to assess the variability of such processes within the region.

Alaska↗
USGS1996

Reactive solute transport in streams: 2. Simulation of a pH modification experiment

We present an application of an equilibrium-based solute transport model to a p H-modification experiment conducted on the Snake River, an acidic, metal-rich stream located in the Rocky Mountains of Colorado. During the experiment, instream p H decreased from 4.2 to 3.2, causing a marked increase in dissolved iron concentrations. Model application requires specification of several parameters that are estimated using tracer techniques, mass balance calculations, and geochemical data. Two basic questions are addressed through model application: (1) What are the processes responsible for the observed increase in dissolved iron concentrations? (2) Can the identified processes be represented within the equilibrium-based transport model? Simulation results indicate that the increase in iron was due to the dissolution of hydrous iron oxides and the photoreduction of ferric iron. Dissolution from the streambed is represented by considering a trace compartment consisting of freshly precipitated hydrous iron oxide and an abundant compartment consisting of aged precipitates that are less soluble. Spatial variability in the solubility of hydrous iron oxide is attributed to heterogeneity in the streambed sediments, temperature effects, and/or variability in the effects of photoreduction. Solubility products estimated via simulation fall within a narrow range ( pK sp from 40.2 to 40.8) relative to the 6 order of magnitude variation reported for laboratory experiments ( pK sp from 37.3 to 43.3). Results also support the use of an equilibrium-based transport model as the predominate features of the iron and p H profiles are reproduced. The model provides a valuable tool for quantifying the nature and extent of p H-dependent processes within the context of hydrologic transport.

Water Resources Research↗
USGS1980

Physical and chemical properties of the Potomac River and environs, April-May 1978

Basic data on the physical and chemical properties measured over the period 24 April through 4 May 1978 on the tidally influenced Potomac River and estuary are presented herein. One 28-hour time series, 45 vertical profiles, and approximately 170 surface observations were made of the distributions of salinity, temperature, light transmission, chlorophyll-a fluorescence, dissolved oxygen, partial pressure of CO2, orthophosphate, nitrate+nitrite, nitrite, ammonia, and silicate. Additional analyses were performed on discrete samples collected for particulate organic carbon, alkalinity, pH, suspended particulate matter, total phosphate, total nitrogen, total dissolved phosphate, and total dissolved nitrogen.

Maryland, Virginia, West Virginia↗
USGS1994

Hydrologic data for northern Bucks County, Pennsylvania

Hydrologic and water-quality data were collected in northern Bucks County, Pa., as part of a study conducted by the U.S. Geological Survey, in cooperation with Bridgeton, Buckingham, Nockamixon, Plumstead, Solebury, Springfield, Tinicum, and Wrightstown Townships and New Hope Borough. Hydrologic data on ground water and surface water were collected to provide basic information on the quality and quantity of water resources in northern Bucks County. Ground-water data include descriptions of 1,357 wells and water levels for 28 observation wells measured during 1990-93. Ground-water-quality analyses for 117 wells include physical properties and concentrations of major ions, nutrients, selected metals and other trace constituents, radon, and volatile organic compounds. Surface-water data include chemical analyses of water samples collected at sites on Beaver Creek, Crooks Creek, Geddes Run, Little Tinicum Creek, Paunnacussing Creek, Pidcock Creek, Rapp Creek, Smithtown Creek, and Tinicum Creek.

Open-File Report↗
USGS2014

Bathymetric maps and water-quality profiles of Table Rock and North Saluda Reservoirs, Greenville County, South Carolina

Lakes and reservoirs are the water-supply source for many communities. As such, water-resource managers that oversee these water supplies require monitoring of the quantity and quality of the resource. Monitoring information can be used to assess the basic conditions within the reservoir and to establish a reliable estimate of storage capacity. In April and May 2013, a global navigation satellite system receiver and fathometer were used to collect bathymetric data, and an autonomous underwater vehicle was used to collect water-quality and bathymetric data at Table Rock Reservoir and North Saluda Reservoir in Greenville County, South Carolina. These bathymetric data were used to create a bathymetric contour map and stage-area and stage-volume relation tables for each reservoir. Additionally, statistical summaries of the water-quality data were used to provide a general description of water-quality conditions in the reservoirs.

South Carolina↗
USGS2014

Status of study of the frequency and magnitude of floods by the Mississippi Valley Committee of the Public Works Administration in collaboration with the United States Geological Survey

Active work under the recently authorized project relating to floods and their frequencies began in March, and such progress as may be reported at this time is largely that of organization and preliminary planning. One of the outstanding and impressive features of the organization is the provision for cooperative effort, whereby the mature judgment and possibly diverse viewpoints of various committees and consultants may be utilized to the fullest advantage. This arrangement should provide the necessary safeguard against adoption of immature individual views or favorite methods of analysis, to the exclusion of others of equal or greater merit. On the other hand, it is conceivable that too much of the limited time might be consumed in preliminary discussions of basic principles, methods of analysis, and formulas dealing with either magnitude or frequency of floods, if unanimity of opinion among several professional groups must precede the main work under the project authorized. In effect, such a procedure would require a practical and workable solution before the basic data had become available. To avoid such delays, a definite line of procedure has beer, proposed for consideration.

Eos, Transactions, American Geophysical Union↗
USGS2019

USGS near-real-time products-and their use-for the 2018 Anchorage earthquake

In the minutes to hours after a major earthquake, such as the recent 2018 M w "> M w 7.1 Anchorage event, the U.S. Geological Survey (USGS) produces a suite of interconnected earthquake products that provides diverse information ranging from basic earthquake source parameters to loss estimates. The 2018 Anchorage earthquake is the first major domestic earthquake to occur since several new USGS products have been developed, thus providing an opportunity to discuss the newly expanded USGS earthquake product suite, its timeliness, performance, and reception. Overall, the products were relatively timely, accurate, well received, and widely used, including by the media, who used information and visualizations from many products to frame their early reporting. One downside of the codependence of multiple products is that reasonable updates to upstream products (e.g., magnitude and source characterization) can result in significant changes to downstream products; this was the case for the Anchorage earthquake. However, the coverage of strong‐motion stations and felt reports was so dense that the ShakeMap and downstream products were relatively insensitive to changes in magnitude or fault‐plane orientation once the ground‐motion data were available. Shaking and loss indicators initially fluctuated in the first hour or two after the earthquake, but they stabilized quickly. To understand how the products are being used and how effectively they are being communicated, we analyze the media coverage of USGS earthquake products. Most references to USGS products occurred within the first 48 hr after the event. The lack of coverage after 48 hr could indicate that longer‐term products addressing what actions the USGS is taking or what early reconnaissance has revealed might be useful for those people wanting additional information about the earthquake.

Alaska↗
USGS1999

Turbidite pathways in Cascadia Basin and Tufts abyssal plain, Part A, Astoria Channel, Blanco Valley, and Gorda Basin

This open-file report was prepared in support of the USGS Earthquake Hazards of Cascadia Project. The primary objective of this phase of the project is to determine recurrence intervals of turbidites in Cascadia basin-floor channel systems and evaluate implications of this event record for the paleoseismic history of the Cascadia subduction zone. The purpose of this study is to determine whether the canyon/channel systems themselves are blocked or deformed in such a way that the downstream turbidite stratigraphy might be biased. To accomplish this investigation approximately 7500 kilometers of pre-existing 3.5 KHz seismic data were evaluated to determine the direction and extent of the Astoria Channel/pathway system, which originates at the base of the Astoria Fan. Additionally, distribution and thickness of turbidite sediment sequences were determined along each identified pathway. Bathymetery and distance were used to determine gradients along the main pathway axis and for each of the secondary pathways that feed into it. Channel pathways were identified on the basis of channel phyisiography, where visible at the seafloor, subbottom channel configuration, and acoustic packets of sediments that might represent turbidite deposits. A principal result of this study is that the Astoria Channel/pathway extends continuously from the base of the Astoria Fan southward along the base of the continental slope through the Blanco Valley, then heads southwestward through the Gorda Basin and into the region of the Escanaba Trough. Additionally it was determined that the Astoria Channel is filled and basically buried for it's full length south of 44 degrees latitude. The 44 North Slump, as defined by Goldfinger (1999, see Map 3 ref.), may have been instrumental in blocking the pathway and thus contributed to the filling of the channel/pathway. Sheets 1 and 2 show the Astoria and secondary turbidite pathways highlighted in blue. Ship survey tracklines are shown for the area studied; they are time and date coded, and color keyed to each ship ID data base listed at the bottom of each sheet. The first letter in the cruise ID is an abbreviation letter for the ship name, the following numbers represent the consecutive cruise number of that year, followed by the year number. The letters at the end of the ID represent the survey area, ie. NC- northern California, NP- north Pacific. Locations of selected sample seismic sections illustrated on sheets 3-5 also are shown. Scales for each of the sheets are the same as for sheets 3-5, which allows for overlaying of track data onto the interpretations shown on Maps A-C. Sheets 3 (MAP A), 4 (MAP B), and 5 (MAP C) show channel pathway location, bathymetric depth based on the USGS COW data base (Ca/Or/Wa), pathway morphology, and thickness of turbidite sediment fill at various locations. The interpreted turbidite sediments are color highlighted on the selected seismic sections to differentiate them from the typical deep sea sediments below and to the side of the turbidite pathways. Thickness of sediment fill, in meters, is shown along major pathways in white circular highlights. The data and interpretations rest on a background of USGS GLORIA side scan sonar imagery (1984) to illustrate the relationship of pathway position to sub sea features. Channel distance points are plotted along channel centerlines at 20,000 m intervals. These points begin at the start of each interpreted channel pathway. A bathymetric depth was assigned to each distance point. These data points were then used to construct channel gradient curves for the Astoria, Eel, Bear Valley, and Mendocino channel pathways. These gradients are plotted on sheet 6 of this report and illustrate the similarities and differences between each of the pathways. Sheet 7 shows various views of the Mendocino/Mattole Canyon heads as an example of useful derivative information of the Seabeam bathymetric data. These views illustrate that the Mendocino pathway probably was directed from it's canyon mouth, to the northwest at an earlier time, but was diverted to the west along the base of the Mendocino Ridge by a major fault event in the recent past. Offset of the southwest channel wall is readily evident in views B and D. This apparent disruption complicates the turbidite history of the Mendocino pathway.

California;Oregon↗
USGS2022

A practical guide to understanding and validating complex models using data simulations

Biologists routinely fit novel and complex statistical models to push the limits of our understanding. Examples include, but are not limited to, flexible Bayesian approaches (e.g. BUGS, stan), frequentist and likelihood-based approaches (e.g. packages lme4 ) and machine learning methods. These software and programs afford the user greater control and flexibility in tailoring complex hierarchical models. However, this level of control and flexibility places a higher degree of responsibility on the user to evaluate the robustness of their statistical inference. To determine how often biologists are running model diagnostics on hierarchical models, we reviewed 50 recently published papers in 2021 in the journal Nature Ecology & Evolution , and we found that the majority of published papers did not report any validation of their hierarchical models, making it difficult for the reader to assess the robustness of their inference. This lack of reporting likely stems from a lack of standardized guidance for best practices and standard methods. Here, we provide a guide to understanding and validating complex models using data simulations. To determine how often biologists use data simulation techniques, we also reviewed 50 recently published papers in 2021 in the journal Methods Ecology & Evolution . We found that 78% of the papers that proposed a new estimation technique, package or model used simulations or generated data in some capacity (18 of 23 papers); but very few of those papers (5 of 23 papers) included either a demonstration that the code could recover realistic estimates for a dataset with known parameters or a demonstration of the statistical properties of the approach. To distil the variety of simulations techniques and their uses, we provide a taxonomy of simulation studies based on the intended inference. We also encourage authors to include a basic validation study whenever novel statistical models are used, which in general, is easy to implement. Simulating data helps a researcher gain a deeper understanding of the models and their assumptions and establish the reliability of their estimation approaches. Wider adoption of data simulations by biologists can improve statistical inference, reliability and open science practices.

Methods in Ecology and Evolution↗
USGS2010

CoalVal-A coal resource valuation program

CoalVal is a menu-driven Windows program that produces cost-of-mining analyses of mine-modeled coal resources. Geological modeling of the coal beds and some degree of mine planning, from basic prefeasibility to advanced, must already have been performed before this program can be used. United States Geological Survey mine planning is done from a very basic, prefeasibility standpoint, but the accuracy of CoalVal's output is a reflection of the accuracy of the data entered, both for mine costs and mine planning. The mining cost analysis is done by using mine cost models designed for the commonly employed, surface and underground mining methods utilized in the United States. CoalVal requires a Microsoft Windows? 98 or Windows? XP operating system and a minimum of 1 gigabyte of random access memory to perform operations. It will not operate on Microsoft Vista?, Windows? 7, or Macintosh? operating systems. The program will summarize the evaluation of an unlimited number of coal seams, haulage zones, tax entities, or other area delineations for a given coal property, coalfield, or basin. When the reader opens the CoalVal publication from the USGS website, options are provided to download the CoalVal publication manual and the CoalVal Program. The CoalVal report is divided into five specific areas relevant to the development and use of the CoalVal program: 1. Introduction to CoalVal Assumptions and Concepts. 2. Mine Model Assumption Details (appendix A). 3. CoalVal Project Tutorial (appendix B). 4. Program Description (appendix C). 5. Mine Model and Discounted Cash Flow Formulas (appendix D). The tutorial explains how to enter coal resource and quality data by mining method; program default values for production, operating, and cost variables; and ones own operating and cost variables into the program. Generated summary reports list the volume of resource in short tons available for mining, recoverable short tons by mining method; the seam or property being mined; operating cost per ton; and discounted cash flow cost per ton to mine and process the resources. Costs are calculated as loaded in a unit train, free-on-board the tipple, at a rate of return prescribed by the evaluator. The recoverable resources (in short tons) may be grouped by incremental cost over any range chosen by the user. For example, in the Gillette coalfield evaluation, the discounted cash flow mining cost (at an 8 percent rate of return) and its associated tonnage may be grouped by any applicable increment (for example, $0.10 per ton, $0.20 per ton, and so on) and using any dollar per ton range that is desired (for example, from $4.00 per ton to $15.00 per ton). This grouping ability allows the user to separate the coal reserves from the nonreserve resources and to construct cost curves to determine the effects of coal market fluctuations on the availability of coal for fuel whether for the generation of electricity or for coal-to-liquids processes. Coking coals are not addressed in this report.

Open-File Report↗
USGS1974

Gravel resources, urbanization, and future land use, Front Range Urban Corridor, Colorado

An assessment of gravel needs in Front Range Urban Corridor markets to 2000 A.D., based on forecast population increases and urbanization, indicates that adequate resources to meet anticipated needs are potentially available, if future land use does not preclude their extraction. Because of urban encroachment onto gravel-bearing lands, this basic construction material is in short supply nationally and in the Front Range Urban Corridor. Longer hauls, increased prices, and use of alternatives, especially crushed rock aggregate, have resulted. An analysis of possible sequential land uses following gravel mining indicates that a desirable use is for 'real estate' ponds and small lakes. A method for computing gravel reserves, based on planimeter measurement of area of resource-bearing lands and statistical analysis of reliability of thickness and size distribution data, was developed to compute reserves in individual markets. A discussion of the qualitative 'usability' of these reserves is then made for the individual markets.

Colorado↗
USGS1997

Activities of the United States Geological Survey in Pennsylvania

Since the late 1800's, when the U.S. Geological Survey first established a presence in Pennsylvania, the focus of our work has changed from general hydrologic and geologic appraisals to issue-oriented investigations; from predominantly data collection to a balanced program of data collection, interpretation, and research; and from traditional, hand-drawn mapping to digitally produced coverages with specialized themes. Yet our basic mission has not changed. It is as relevant to the resource issues of today as it was when our geologists first arrived in western Pennsylvania in 1884. Continuing in this proud heritage and tradition, the U.S. Geological Survey is moving confidently toward the next century, evolving organizationally and technologically to better meet the needs of our many constituencies. One major organizational change is the recent accession of employees from the former National Biological Service, who now form the Survey's fourth program division, the Biological Resources Division. These employees join forces with colleagues in our other three divisions: Water Resources, Geologic, and National Mapping. More than any other change in decades, the addition of this biological expertise creates new and exciting opportunities for scientific research and public service. This report provides an overview of recent activities in Pennsylvania conducted by the four program divisions and is intended to inform those interested in U.S. Geological Survey products and services. Additional information is available on our home page (at http://wwwpah2o.er.usgs.gov/). Together with numerous Federal, State, and local agencies and organizations who are our customers and partners, we at the U.S. Geological Survey look forward to providing continued scientific contributions and public service to Pennsylvania and the Nation.

Pennsylvania↗
USGS1973

CRIB; the mineral resources data bank of the U.S. Geological Survey

The recently established Computerized Resources Information Bank (CRIB) of the U.S. Geological Survey is expected to play an increasingly important role in the study of United States' mineral resources. CRIB provides a rapid means for organizing and summarizing information on mineral resources and for displaying the results. CRIB consists of a set of variable-length records containing the basic information needed to characterize one or more mineral commodities, a mineral deposit, or several related deposits. The information consists of text, numeric data, and codes. Some topics covered are: name, location, commodity information, geology, production, reserves, potential resources, and references. The data are processed by the GIPSY program, which performs all the processing tasks needed to build, operate, and maintain the CRIB file. The sophisticated retrieval program allows the user to make highly selective searches of the files for words, parts of words, phrases, numeric data, word ranges, numeric ranges, and others, and to interrelate variables by logic statements to any degree of refinement desired. Three print options are available, or the retrieved data can be passed to another program for further processing.

Circular↗
USGS2018

The National Elevation Dataset

The National Elevation Dataset (NED) is a primary elevation data product that has been produced and distributed by the U.S. Geological Survey (USGS). Since its inception, the USGS has compiled and published topographic information in many forms, and the NED is a significant development in this long line of products that describe the land surface. The NED provides seamless raster elevation data of the conterminous United States (CONUS), Alaska, Hawaii, U.S. island territories, Mexico, and Canada. The NED is derived from diverse source datasets that are processed to a specification with consistent resolutions, coordinate system, elevation units, and horizontal and vertical datums. The NED was developed as the logical result of the maturation of the long-standing USGS elevation program, which for many years concentrated on production of quadrangle-based digital elevation models (DEM). The NED contributes to the elevation layer of The National Map, and it provides basic elevation information for earth science studies and mapping applications in the U.S. and most of North America. For over 15 years (1999–2014), the NED served as the flagship elevation product of the USGS. In 2015, the 3D Elevation Program (3DEP) was initiated. When the 3DEP initiative became operational, the name “National Elevation Dataset” (and the abbreviation “NED”) were retired as the USGS elevation activities and data were rebranded under the 3DEP banner. However, elevation data produced and distributed as part of the NED are still widely used (and distributed by other entities), so there is a continuing need for detailed documentation, including how it was produced, its accuracy, and how it is used. This chapter directly addresses that need for detailed information about the NED. The most recent detailed description of the NED appeared in the 2nd edition of the DEM Users Manual (2007), and because NED production continued through 2014, the details reported herein provide valuable information for data accessed by the user community from 2007 through 2014. The NED has been widely used in operational applications and research studies and is extensively cited in reports on those activities, so it is important for the user community to have access to information about the NED to better judge how its qualities and characteristics might affect results derived from its use as the elevation data source. Additionally, the NED seamless layers serve as one of the input data sources for the current 3DEP elevation production system, so, as with any input data source, an understanding of the data characteristics is critical.

Book chapter↗
USGS2019

2019 Joint Agency Commercial Imagery Evaluation—Land remote sensing satellite compendium

The Joint Agency Commercial Imagery Evaluation (JACIE) is a collaboration between five Federal agencies that are major users and producers of satellite land remote sensing data. In recent years, the JACIE group has observed ever-increasing numbers of remote sensing satellites being launched. This rapidly growing wave of new systems creates a need for a single reference for land remote sensing satellites that provides basic system specifications and linkage to any JACIE assessment that may have been completed on existing systems. This volume has been assembled by the Requirements, Capabilities, and Analysis for Earth Observation Project under the U.S. Geological Survey National Land Imaging Program as a contribution to the JACIE community. This is the first edition of the JACIE compendium, which is planned to be updated and released annually.

Circular↗
USGS2020

2020 Joint Agency Commercial Imagery Evaluation—Remote sensing satellite compendium

The Joint Agency Commercial Imagery Evaluation (JACIE) is a collaboration between five Federal agencies that are major users and producers of satellite land remote sensing data. In recent years, the JACIE group has observed ever-increasing numbers of remote sensing satellites being launched. This rapidly growing wave of new systems creates a need for a single reference for land remote sensing satellites that provides basic system specifications and linkage to any JACIE assessment that may have been completed on existing systems. This volume has been assembled by the Requirements, Capabilities, and Analysis for Earth Observation Project under the U.S. Geological Survey National Land Imaging Program as a contribution to the JACIE community. This is the second edition of the JACIE compendium, which is planned to be updated and released annually.

Circular↗
USGS2001

Coastal vulnerability to sea-level rise: a preliminary database for the U.S. Atlantic, Pacific, and Gulf of Mexico coasts

The prediction of coastal evolution is not straightforward. There is no standard methodology, and even the kind of data required to make such predictions are the subject of much scientific debate. Since a viable, quantitative predictive model for coastal evolution is not available. The relative susceptibility of the Nation's coastline to sea-level rise is quantified here at a regional to national scale using basic information on coastal geomorphology, rate of sea-level rise, past shoreline evolution and other factors. This approach combines the coastal system's susceptibility to change with its natural ability to adapt to changing environmental and conditions, and yields a relative measure of the system's natural vulnerability to the effects of sea-level rise. This information has immediate application to many of the decisions our society will be making regarding coastal development in both the short- and long-term.

Data Series↗
USGS2024

Introduction and methods of analysis for peak streamflow trends and their relation to changes in climate in Illinois, Iowa, Michigan, Minnesota, Missouri, Montana, North Dakota, South Dakota, and Wisconsin

Flood-frequency analysis, also called peak-flow frequency or flood-flow frequency analysis, is essential to water resources management applications including critical structure design and floodplain mapping. Federal guidelines for doing flood-frequency analyses are presented in a U.S. Geological Survey Techniques and Methods Report known as Bulletin 17C. A basic assumption within Bulletin 17C is that for drainage basins without major hydrologic alterations, statistical properties of the distribution of annual peak streamflows (peak flows) are stationary; that is, the mean, variance, and skew are constant. The stationarity assumption has been widely accepted within the flood-frequency community; however, a better understanding of long-term climatic persistence and concerns about potential climate change and land-use change has caused a reexamination of the stationarity assumption. Flood-frequency analyses that do not incorporate observed trends and abrupt changes may result in a poor representation of the true flood risk. Bulletin 17C does not offer guidance for incorporating nonstationarities when estimating floods, and it describes a need for studies that incorporate changing climate or basin characteristics. In response to this need and a history of concern regarding nonstationarity peak flows in the region, this study was done by the U.S. Geological Survey, in cooperation with the Departments of Transportation of Illinois, Iowa, Michigan, Minnesota, Missouri, South Dakota, and Wisconsin; the Montana Department of Natural Resources and Conservation; and the North Dakota Department of Water Resources, to assess potential nonstationarity in peak flows in the north-central United States. This chapter summarizes the methods used to detect hydroclimatic changes in peak-flow data in the study region. A wide range of analyses and statistical approaches are applied to document the primary mechanisms controlling floods and characterize temporal changes in hydroclimatic variables and peak flow. Four periods were selected for analysis of peak flow, daily streamflow, and climate data. The periods are (1) a 100-year period, 1921–2020; (2) a 75-year period, 1946–2020; (3) a 50-year period, 1971–2020; and (4) a 30-year period, 1991–2020. The climate data consist of monthly time series estimates of temperature, precipitation, potential evapotranspiration, actual evapotranspiration, snowfall, soil moisture storage, snow water equivalent, and runoff on a 3.1-mile by 3.1-mile grid for the conterminous United States. Statistical and graphical analyses were used to investigate potential changes in hydrology and climate. The starting point for these analyses was the initial data analysis of peak flow described in Bulletin 17C, which includes plotting the peak flow and checking for autocorrelation, monotonic trends, and changes points. Analyses were added to examine additional features in the data. To examine potential causal drivers of changes, the climate data were analyzed graphically and statistically. Results are provided in a U.S. Geological Survey data release. The study limitations are documented for users of the results.

Iowa, Illinois, Michigan, Missouri, Minnesota, Mon↗