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At least 199 records · Page 11Linked to original sources
USGS2024

Special topic—Boreholes

Introduction Installation of instrument packages in deep (several hundred to several thousand meters) boreholes near volcanoes is relatively expensive (a few million to tens of millions of U.S. dollars), but can provide a low-noise, high-quality source of geophysical (seismic, strain, tilt, and pore pressure), physical (temperature and water level), and geochemical data. Observations from instruments at depth have the potential to provide insights into processes associated with magma intrusion, unrest, and eruption that would not otherwise be possible (Lowenstern and others, 2017; Eichelberger, 2020). Examples of instrumented boreholes in volcanic areas include the 3-kilometer (km)-deep Long Valley Exploratory Well (LVEW) in California (for example, Priest and others, 1998; Prejean and Ellsworth, 2001; Fischer and others, 2003; Roeloffs and others, 2003; Sorey and others, 2003), the 1,262 meter-deep NSF Well (commonly referred to as the “Keller Well”) within the summit caldera of Kīlauea, Hawaiʻi (Keller and others, 1979; Myren and others, 2006), and the Caribbean Andesite Lava Island-volcano Precision Seismo-geodetic Observatory (CALIPSO) project at Soufrière Hills, Montserrat, which includes a series of four 200-meter (m)-deep holes (for example, Mattioli and others, 2004; Voight and others, 2006). The Plate Boundary Observatory (PBO) of the National Science Foundation’s Earthscope project placed seismometers, tiltmeters, strainmeters, and pore-pressure sensors at depths of 100 to 250 m in more than 100 boreholes scattered in western North America, including at Mount St. Helens, Washington, and Yellowstone Caldera, Wyoming. The total cost for an instrumented PBO borehole ranged from $250,000 to $270,000 U.S. dollars (USD) and a few thousand USD are required annually for maintenance (David Mencin, UNAVCO, written commun., October 2020).

Scientific Investigations Report↗
USGS1996

Changes in high-flow frequency and channel geometry of the Neosho River downstream from John Redmond Dam, southeastern Kansas

The streamflow regimen of the Neosho River downstream from John Redmond Dam in southeastern Kansas has changed significantly since the dam's completion in 1964. The controlled releases from the dam have decreased the magnitudes of peak discharges and increased the magnitudes of low discharges. The trends in river stage for selected discharges also have changed at two of the streamflow-gaging stations--those closest to the dam. There is a significant downward trend in the stages associated with the median annual peak discharges, but no significant trend in the stages associated with the annual mean discharges, which indicates that the river channel is increasing in width but not depth or that the hflow velocity has increased at the streamflow-gaging stations. Because there were not significant trends present in precipitation, mean annual discharge, or annual peak discharge, the changes are attributed to John Redmond Dam.

Water-Resources Investigations Report↗
USGS2026

Estimating the magnitude and frequency of floods at ungaged locations on urban streams in Tennessee and parts of Alabama, Georgia, Mississippi, North Carolina, and South Carolina, using data through the 2022 water year

In 2024, the U.S. Geological Survey, in cooperation with the Tennessee Department of Transportation, updated the methods for predicting the magnitude and frequency of floods at ungaged locations on streams in urban areas in Tennessee. The study area included 136 streamgages in urban areas in Tennessee, Mississippi, Alabama, Georgia, South Carolina, and North Carolina that had at least 10 percent developed imperviousness in their basins as indicated by data from the 2011 National Land Cover Database. Regression equations were developed to predict streamflows corresponding to the 50-​, 20-​, 10-​, 4-​, 2-​, 1-​, 0.5-​, and 0.2-​percent annual exceedance probabilities (AEPs) and were incorporated into the StreamStats application. In generalized least-​squares regression, the base-​10 logarithm of drainage area, the percentages of the streamgage basins in developed land use, and the percentages of the streamgage basins in the Piedmont and Ridge and Valley Level 3 ecoregions were statistically significant in explaining the variability in annual peak streamflows in the study area. Drainage areas ranged from 0.164 to 93.4 square miles, the percentage of the streamgage basins in developed land use ranged from 26 to 100 percent, and the percentage of the streamgage basins in Piedmont and Ridge and Valley Level 3 ecoregions ranged from 0 to 100 percent. Pseudo R-​squared values for the regression equations ranged from 0.86, or 86 percent, for the 50-​ and 20-​percent AEPs (2-​ and 5-​year floods) to 0.71, or 71 percent, for the 0.2-​percent AEP (500-​year flood). The average variance of prediction (in log base-​10 units) ranged from 0.023 for the 20-​ and 10-​percent AEPs to 0.05 for the 0.2-​percent AEP. The average variance of prediction can be reported as a percentage of the predicted value, known as the standard error of prediction, which ranged from 35.8 percent for the 20-​percent AEP (5-​year flood) to 55.4 percent for the 0.2-​percent AEP (500-​year flood). Methods are presented for estimating annual peak streamflows for gaged locations, ungaged locations on gaged streams, and locations on ungaged streams.

Alabama, Georgia, Mississippi, North Carolina, Sou↗
USGS2009

Abundance and distribution of benthic macroinvertebrates in offshore soft sediments in Western Lake Huron, 2001-2007

Invasive species have had major impacts on the Great Lakes. This is especially true of exotic dreissenid mussels which are associated with decreased abundance of native macroinvertebrates and changes in food availability for fish. Beginning in 2001, we added a benthic macroinvertebrate survey to the USGS-Great Lakes Science Center's annual fall prey fish assessment of Lake Huron to monitor abundance of macrobenthos. Mean abundance of Diporeia, the most abundant benthic taxon in Lake Huron reported by previous investigators, declined greatly between 2001 and 2007. Diporeia was virtually absent at 27-m sites by 2001, decreased and was lost completely from 46-m depths by 2006, but remained present at reduced densities at 73-m sites. Dreissenids in our samples were almost entirely quagga mussels Dreissena bugensis. Zebra mussels Dreissena polymorpha were virtually absent from our samples, suggesting that they were confined to nearshore areas shallower than we sampled. Loss of Diporeia at individual sites was associated with arrival of quagga mussels, even when mussel densities were low. Quagga mussel density peaked during 2002, then decreased thereafter. During the study quagga mussels became established at most 46-m sites, but remained rare at 73-m sites. Length frequency distributions suggest that initial widespread recruitment may have occurred during 2001-2002. Like other Great Lakes, Lake Huron quagga mussels were associated with decreased abundance of native taxa, but negative effects occurred even though dreissenid densities were much lower. Dreissenid effects may extend well into deep oligotrophic habitats of Lake Huron.

Journal of Great Lakes Research↗
USGS2001

Low-flow characteristics of streams in Ohio through water year 1997

This report presents selected low-flow and flow-duration characteristics for 386 sites throughout Ohio. These sites include 195 long-term continuous- record stations with streamflow data through water year 1997 (October 1 to September 30) and for 191 low-flow partial-record stations with measurements into water year 1999. The characteristics presented for the long-term continuous-record stations are minimum daily streamflow; average daily streamflow; harmonic mean flow; 1-, 7-, 30-, and 90-day minimum average low flow with 2-, 5-, 10-, 20-, and 50-year recurrence intervals; and 98-, 95-, 90-, 85-, 80-, 75-, 70-, 60-, 50-, 40-, 30-, 20-, and 10-percent daily duration flows. The characteristics presented for the low-flow partial-record stations are minimum observed streamflow; estimated 1-, 7-, 30-, and 90-day minimum average low flow with 2-, 10-, and 20-year recurrence intervals; and estimated 98-, 95-, 90-, 85- and 80-percent daily duration flows. The low-flow frequency and duration analyses were done for three seasonal periods (warm weather, May 1 to November 30; winter, December 1 to February 28/29; and autumn, September 1 to November 30), plus the annual period based on the climatic year (April 1 to March 31).

Ohio↗
USGS2009

Estimation of Streamflow Characteristics for Charles M. Russell National Wildlife Refuge, Northeastern Montana

Charles M. Russell National Wildlife Refuge (CMR) encompasses about 1.1 million acres (including Fort Peck Reservoir on the Missouri River) in northeastern Montana. To ensure that sufficient streamflow remains in the tributary streams to maintain the riparian corridors, the U.S. Fish and Wildlife Service is negotiating water-rights issues with the Reserved Water Rights Compact Commission of Montana. The U.S. Geological Survey, in cooperation with the U.S. Fish and Wildlife Service, conducted a study to gage, for a short period, selected streams that cross CMR, and analyze data to estimate long-term streamflow characteristics for CMR. The long-term streamflow characteristics of primary interest include the monthly and annual 90-, 80-, 50-, and 20-percent exceedance streamflows and mean streamflows (Q.90, Q.80, Q.50, Q.20, and QM, respectively), and the 1.5-, 2-, and 2.33- year peak flows (PK1.5, PK2, and PK2.33, respectively). The Regional Adjustment Relationship (RAR) was investigated for estimating the monthly and annual Q.90, Q.80, Q.50, Q.20, and QM, and the PK1.5, PK2, and PK2.33 for the short-term CMR gaging stations (hereinafter referred to as CMR stations). The RAR was determined to provide acceptable results for estimating the long-term Q.90, Q.80, Q.50, Q.20, and QM on a monthly basis for the months of March through June, and also on an annual basis. For the months of September through January, the RAR regression equations did not provide acceptable results for any long-term streamflow characteristic. For the month of February, the RAR regression equations provided acceptable results for the long-term Q.50 and QM, but poor results for the long-term Q.90, Q.80, and Q.20. For the months of July and August, the RAR provided acceptable results for the long-term Q.50, Q.20, and QM, but poor results for the long-term Q.90 and Q.80. Estimation coefficients were developed for estimating the long-term streamflow characteristics for which the RAR did not provide acceptable results. The RAR also was determined to provide acceptable results for estimating the PK1.5., PK2, and PK2.33 for the three CMR stations that lacked suitable peak-flow records. Methods for estimating streamflow characteristics at ungaged sites also were derived. Regression analyses that relate individual streamflow characteristics to various basin and climatic characteristics for gaging stations were performed to develop regression equations to estimate streamflow characteristics at ungaged sites. Final equations for the annual Q.50, Q.20, and QM are reported. Acceptable equations also were developed for estimating QM for the months of February, March, April, June, and July, and Q.50, Q.20, and QM on an annual basis. However, equations for QM for the months of February, March, April, June, and July were determined to be less consistent and reliable than the use of estimation coefficients applied to the regression equation results for the annual QM. Acceptable regression equations also were developed for the PK1.5, PK2, and PK2.33.

Scientific Investigations Report↗
USGS2021

A reassessment of Chao2 estimates for population monitoring of grizzly bears in the Greater Yellowstone Ecosystem

The Yellowstone Ecosystem Subcommittee (YES) asked the Interagency Grizzly Bear Study Team (IGBST) to re-assess a technique used in annual population estimation and trend monitoring of grizzly bears in the Greater Yellowstone Ecosystem (GYE). This technique is referred to as the Chao2 approach and estimates the number of females with cubs-of-the-year (hereafter, females with cubs) and, in association with other demographic data, is used by the IGBST to produce annual population estimates. Females with cubs are an easily recognizable population segment, and trends for this reproductive segment of the population are assumed to be representative of trend for the entire population. The overarching objective of the analyses presented in this report was to provide a more accurate representation of the GYE grizzly bear population using the current methodologies in place. Specifically, we addressed two limitations of the current Chao2 approach: 1) underestimation bias associated with a distance criterion used to differentiate annual sightings of females with cubs into unique individuals and 2) limitations of the model-averaging approach to effectively distinguish among potential future population trajectories (decline, stability, and growth). The first issue addressed in this report is the underestimation bias associated with the rule set that Knight et al. (1995) developed to differentiate sightings of females with cubs into unique individuals (i.e., unique family groups). The rule set was originally designed to be conservative by reducing the risk of identifying more females with cubs than actually existed, primarily through use of a distance criterion of 30 km to separate sightings of unique females. This approach resulted in an underestimation bias, and previous research demonstrated that this bias increases with increasing number of females with cubs. Using location data from radio-marked females with cubs, we evaluated alternative distance criteria by simulating scenarios with varying numbers of true females with cubs and sightings. Findings from these analyses demonstrate that bias in estimates of females with cubs can be substantially reduced by changing the 30-km distance criterion in the rule set to 16 km, which produced relatively unbiased estimates. Findings also indicate, however, the importance of adaptability with regard to the distance criteria because of the complex relationships and biases among the various parameters involved in estimation of unique females with cubs. The total number of annual sightings and the true number of females with cubs play particularly important roles. Whereas these analyses remind us that there is no perfect approach to estimating the number of females with cubs from sightings under various scenarios, they provide us with new tools to determine when and how to adapt the monitoring program. The second issue we were tasked to investigate was the potential for improvement of the technique referred to as model-averaging, which serves to smooth relatively high variation in annual estimates. This technique was chosen by YES as the basis for monitoring the Yellowstone grizzly bear population, as described in the 2016 Conservation Strategy. This choice was made in part because the technique has been well documented and population estimates derived from counts of females with cubs are conservative. Using simulations of population trends, we demonstrate why the model-averaging technique currently used cannot distinguish between plausible future trend scenarios. As a suitable alternative to model averaging, we propose the use of generalized additive models (GAMs). Using a suite of simulated trend dynamics relevant to management, we demonstrate GAM performance for tracking trends in females with cubs within the context of the annual monitoring program. We demonstrate the ability to not only document directional changes in population trend but also patterns of stabilization or resiliency after such changes. Furthermore, the proposed monitoring framework provides objective measures useful for early detection of directional changes in trend. The new framework is flexible, allowing retrospective analysis of Chao2-based estimates and future applications to time series of other population metrics, such as vital rates. The aforementioned updates provide us with new tools to determine when and how to adapt the monitoring program. Within the context of current monitoring protocols and effort, and considering the full suite of simulations presented in this report and previous studies, the IGBST plans to incorporate the following changes to the population monitoring protocol: 1) modify the distance criterion, starting with 16 km under current sampling conditions and 2) revise the population monitoring framework using GAMs as the basis for smoothing of annual estimates and detecting trends and changes in trend. Implementation of the 16-km distance criterion combined with use of GAM techniques would affect some of the population metrics (e.g., annual population size and uncertainty, population trend, mortality rates) used to inform management responses. A primary consideration is that the 16-km distance criterion results in total population estimates derived from the Chao2 estimates that are greater than those we have reported in the past. This increase is due to a change in the implementation of the technique and more accurately represents the number of females with cubs in the GYE grizzly bear population. Additionally, interpretation of retrospective trend patterns may change due to the combination of a different distance criterion and enhanced trend monitoring based on the GAM approach we present here. Implementation will require relatively minor changes in the monitoring protocols described in Appendices B and C of the 2016 Conservation Strategy. Finally, we note that the IGBST has ongoing investigations into the merits of an Integrated Population Model (IPM), for which annual Chao2-based estimates are important input data. The IGBST plans to continue those investigations using the 16-km distance criterion to derive Chao2 estimates.

Idaho, Montana, Wyoming↗
USGS2016

Magnitude, frequency, and trends of floods at gaged and ungaged sites in Washington, based on data through water year 2014

An investigation into the magnitude and frequency of floods in Washington State computed the annual exceedance probability (AEP) statistics for 648 U.S. Geological Survey unregulated streamgages in and near the borders of Washington using the recorded annual peak flows through water year 2014. This is an updated report from a previous report published in 1998 that used annual peak flows through the water year 1996. New in this report, a regional skew coefficient was developed for the Pacific Northwest region that includes areas in Oregon, Washington, Idaho and western Montana within the Columbia River drainage basin south of the United States-Canada border, the coastal areas of Oregon and western Washington, and watersheds draining into Puget Sound, Washington. The skew coefficient is an important term in the Log Pearson Type III equation used to define the distribution of the log-transformed annual peaks. The Expected Moments Algorithm was used to fit historical and censored peak-flow data to the log Pearson Type III distribution. A Multiple Grubb-Beck test was employed to censor low outliers of annual peak flows to improve on the frequency distribution. This investigation also includes a section on observed trends in annual peak flows that showed significant trends ( p -value < 0.05) in 21 of 83 long-term sites, but with small magnitude Kendall tau values suggesting a limited monotonic trend in the time series of annual peaks. Most of the sites with a significant trend in western Washington were positive and all the sites with significant trends (three sites) in eastern Washington were negative. Multivariate regression analysis with measured basin characteristics and the AEP statistics at long-term, unregulated, and un-urbanized (defined as drainage basins with less than 5 percent impervious land cover for this investigation) streamgages within Washington and some in Idaho and Oregon that are near the Washington border was used to develop equations to estimate AEP statistics at ungaged basins. Washington was divided into four regions to improve the accuracy of the regression equations; a set of equations for eight selected AEPs and for each region were constructed. Selected AEP statistics included the annual peak flows that equaled or exceeded 50, 20, 10, 4, 2, 1, 0.5 and 0.2 percent of the time equivalent to peak flows for peaks with a 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence intervals, respectively. Annual precipitation and drainage area were the significant basin characteristics in the regression equations for all four regression regions in Washington and forest cover was significant for the two regression regions in eastern Washington. Average standard error of prediction for the regional regression equations ranged from 70.19 to 125.72 percent for Regression Regions 1 and 2 on the eastern side of the Cascade Mountains and from 43.22 to 58.04 percent for Regression Regions 3 and 4 on the western side of the Cascade Mountains. The pseudo coefficient of determination (where a value of 100 signifies a perfect regression model) ranged from 68.39 to 90.68 for Regression Regions 1 and 2, and 92.35 to 95.44 for Regions 3 and 4. The calculated AEP statistics for the streamgages and the regional regression equations are expected to be incorporated into StreamStats after the publication of this report. StreamStats is the interactive Web-based map tool created by the U.S. Geological Survey to allow the user to choose a streamgage and obtain published statistics or choose ungaged locations where the program automatically applies the regional regression equations and computes the estimates of the AEP statistics.

Washington↗
USGS1982

Precipitation data for burial grounds 5 and 6, Oak Ridge National Laboratory, Tennessee, 1976-1980

As part of a hydrogeologic investigation, precipitation data were collected at two stations, one each in Burial Grounds 5 and 6 at the Oak Ridge National Laboratory, Tennessee. Daily, monthly, and annual values are reported herein for the period from January 1976 through December 1980. During this period, annual values ranged from about 25 percent above to about 25 percent below the calculated mean of 51.96 inches at Burial Ground 5 and 49.60 inches at Burial Ground 6.

Tennessee↗
USGS2015

Community for Data Integration 2013 Annual Report

The U.S. Geological Survey (USGS) conducts earth science to help address complex issues affecting society and the environment. In 2006, the USGS held the first Scientific Information Management Workshop to bring together staff from across the organization to discuss the data and information management issues affecting the integration and delivery of earth science research and investigate the use of &ldquo;communities of practice&rdquo; as mechanisms to share expertise about these issues. Out of this effort emerged the Council for Data Integration, which was conceived as an official organizational function that would help guide data integration activities and formalize communities of practice into working groups. However by 2009, it became apparent that many members of the council had an interest in developing data integration solutions and sharing expertise in a less formal grassroots perspective, thus transforming the &ldquo;Council&rdquo; into a &ldquo;Community&rdquo; for Data Integration (CDI). Today, the CDI represents a dynamic community of practice focused on advancing science data and information management and integration capabilities across the USGS and the CDI community. The CDI fosters an environment for collaboration and sharing by bringing together expertise from external partners and representatives across USGS who are involved in research, data management, and information technology. Membership is voluntary and open to USGS employees and other individuals and organizations willing to contribute to the community (if interested, contact cdi@usgs.gov). The purpose of the CDI is to advance understanding of Earth systems through enhanced use of data and information including associated tools and techniques provide a forum for people doing work with data integration to come together to share ideas as well as learn new skills and techniques, and grow overall USGS capabilities with data and information by increasing visibility of the work of many people throughout the USGS and the CDI community. To achieve these goals, the CDI operates within four applied areas: monthly forums, annual workshop/webinar series, working groups, and projects. The monthly forums, also known as the Opportunity/Challenge of the Month, provide an open dialogue to share and learn about data integration efforts or to present problems that invite the Community to offer solutions, advice, and support. Since 2010, the CDI has also sponsored annual workshops/webinar series to encourage the exchange of ideas, sharing of activities, presentations of current projects, and networking among members. Stemming from common interests, the working groups are focused on efforts to address data management and technical 2 challenges, including the development of standards and tools, improving interoperability and information infrastructure, and data preservation within USGS and its partners. The growing support for the activities of the working groups led to the CDI&rsquo;s first formal request for proposals (RFP) process in 2013 to fund projects that produced tangible products. Today the CDI continues to hold an annual RFP that create data management tools and practices, collaboration tools, and training in support of data integration and delivery.

Open-File Report↗
USGS2015

Community for Data Integration 2014 annual report

The U.S. Geological Survey (USGS) researches Earth science to help address complex issues affecting society and the environment. In 2006, the USGS held the first Scientific Information Management Workshop to bring together staff from across the organization to discuss the data and information management issues affecting the integration and delivery of Earth science research and investigate the use of &ldquo;communities of practice&rdquo; as mechanisms to share expertise about these issues. Out of this effort emerged the Council for Data Integration, which was conceived as an official organizational function that would help guide data integration activities and formalize communities of practice into working groups; however, by 2009 it became evident that many members of the Council for Data Integration had an interest in developing data integration solutions and sharing expertise in a less formal, grassroots manner, which transformed the Council into a Community for Data Integration (CDI). As of 2014, the CDI represents a dynamic community of practice focused on advancing science data and information management and integration capabilities across the USGS and the CDI community. The CDI fosters an environment for collaboration and sharing by bringing together expertise from external partners and representatives across the USGS who are involved in research, data management, and information technology. Membership is voluntary and open to USGS employees and other individuals and organizations willing to contribute to the community (if interested, contact cdi@usgs.gov). The purpose of the CDI is to do the following: &bull; advance understanding of Earth systems through enhanced use of data and information including associated tools and techniques, &bull; provide a forum for people doing work with data integration to come together to share ideas and learn new skills and techniques, and &bull; grow overall USGS capabilities with data and information by increasing visibility of the work of many people throughout the USGS and the CDI community. To achieve these goals, the CDI operates within four applied areas: monthly forums, annual workshop/webinar series, working groups, and projects. The monthly forums, also known as the Opportunity/Challenge of the Month, provide an open dialogue to share and learn about data integration efforts or to present problems that invite the community to offer solutions, advice, and support. Since 2010, the CDI has also sponsored annual workshops/webinar series to encourage the exchange of ideas, sharing of activities, presentations of current projects, and networking among members. Stemming from common interests, the working groups are focused on efforts to address data management and technical challenges including the development of standards and tools, improving interoperability and information infrastructure, and data preservation within USGS and its partners. The growing support for the activities of the working groups led to the CDI&rsquo;s first formal request for proposals (RFP) process in 2013 to fund projects that produced tangible products. As of 2014, the CDI continues to hold an annual RFP that creates data management tools and practices, collaboration tools, and training in support of data integration and delivery.

Open-File Report↗
USGS2009

Water Levels and Selected Water-Quality Conditions in the Sparta-Memphis Aquifer (Middle Claiborne Aquifer) in Arkansas, Spring-Summer 2007

The U.S. Geological Survey in cooperation with the Arkansas Natural Resources Commission and the Arkansas Geological Survey has monitored water levels in the Sparta Sand of Claiborne Group and Memphis Sand of Claiborne Group (herein referred to as the Sparta Sand and the Memphis Sand, respectively), since the 1920s. Groundwater withdrawals have increased while water levels have declined since monitoring was initiated. Herein, aquifers in the Sparta Sand and Memphis Sand will be referred to as the Sparta-Memphis aquifer throughout Arkansas. During the spring of 2007, 309 water levels were measured in wells completed in the Sparta-Memphis aquifer. During the summer of 2007, 129 water-quality samples were collected and measured for temperature and specific conductance and 102 were collected and analyzed for chloride from wells completed in the Sparta-Memphis aquifer. Water-level measurements collected in wells screened in the Sparta-Memphis aquifer were used to produce a regional potentiometric-surface map. The regional direction of groundwater flow in the Sparta-Memphis aquifer is generally to the south-southeast in the northern half of Arkansas and to the east and south in the southern half of Arkansas, away from the outcrop area except where affected by large ground-water withdrawals. The highest water-level altitude measured in the Sparta-Memphis aquifer was 326 feet above National Geodetic Vertical Datum of 1929, located in Grant County in the outcrop at the western boundary of the study area; the lowest water-level altitude was 161 feet below National Geodetic Vertical Datum of 1929 in Union County near the southern boundary of the study area. Eight cones of depression (generally represented by closed contours) are located in the following counties: Bradley, Drew, and Ashley; Calhoun; Cleveland; Columbia; Crittenden; Arkansas, Jefferson, and Lincoln; Cross and Poinsett; and Union. Two large depressions are shown on the 2007 potentiometric-surface map, centered in Jefferson and Union Counties, as a result of large withdrawals for industrial and public supplies. The depression centered in Jefferson County deepened and expanded in recent years into Arkansas and Prairie Counties as a result of large withdrawals for irrigation and public supply. The area enclosed within the 40-foot contour has expanded on the 2007 potentiometric-surface map when compared with the 2005 potentiometric-surface map. In 2003, the depression in Union County was elongated east and west and beginning to coalesce with the depression in Columbia County. The deepest measurement during 2007 in the center of the depression in Union County has risen 38 feet since 2003. The area enclosed by the deepest contour, 160 feet below National Geodetic Vertical Datum of 1929, on the 2007 potentiometric-surface map is less than 10 percent of the area on the 2005 potentiometric-surface map. A broad depression in western Poinsett and Cross Counties was first shown in the 1995 potentiometric-surface map caused by withdrawals for irrigation extending north to the Poinsett-Craighead County line, and south into Cross County. A water-level difference map was constructed using the difference between water-level measurements made during 2003 and 2007 from 283 wells. The difference in water level between 2003 and 2007 ranged from -49.8 to 60.0 feet. Areas with a general rise in water levels are shown in northern Arkansas, Columbia, southern Jefferson, and most of Union Counties. In the area around west-central Union County, water levels rose as much as 60.0 feet with water levels in 15 wells rising 20 feet or more, which is an average annual rise of 5 feet or more. Water levels generally declined throughout most of the rest of Arkansas. Hydrographs from 157 wells were constructed with a minimum of 25 years of water-level measurements. During the period 1983-2007, the county mean annual water level rose in Calhoun, Columbia, Hot Spring, and Lafayette Counties. Mean an

Scientific Investigations Report↗
USGS2014

Trends in annual, seasonal, and monthly streamflow characteristics at 227 streamgages in the Missouri River watershed, water years 1960-2011

The Missouri River and its tributaries are an important resource that serve multiple uses including agriculture, energy, recreation, and municipal water supply. Understanding historical streamflow characteristics provides relevant guidance to adaptive management of these water resources. Streamflow records in the Missouri River watershed were examined for trends in time series of annual, seasonal, and monthly streamflow. A total of 227 streamgages having continuous observational records for water years 1960–2011 were examined. Kendall’s tau nonparametric test was used to determine statistical significance of trends in annual, seasonal, and monthly streamflow. A trend was considered statistically significant for a probability value less than or equal to 0.10 that the Kendall’s tau value equals zero. Significant trends in annual streamflow were indicated for 101 out of a total of 227 streamgages. The Missouri River watershed was divided into six watershed regions and trends within regions were examined. The western and the southern parts of the Missouri River watershed had downward trends in annual streamflow (56 streamgages), whereas the eastern part of the watershed had upward trends in streamflow (45 streamgages). Seasonal and monthly streamflow trends reflected prevailing annual streamflow trends within each watershed region.

Missouri River Watershed↗
USGS2019

Hydrologic and hydraulic analyses of selected streams in Richland County, Ohio

Hydrologic and hydraulic analyses were done for selected reaches of Clear Fork Mohican River and Cedar Fork in Richland County, Ohio. To update and expand a portion of the Federal Emergency Management Agency detailed Flood Insurance Study, the U.S. Geological Survey (USGS) and the Muskingum Watershed Conservancy District initiated a cooperative study. The study comprised an 18.6-mile reach of the Clear Fork Mohican River and a 5.9-mile reach of Cedar Fork. Historical streamflow data from the streamgage Clear Fork Mohican River at Bellville, Ohio (USGS station number 03131982) and regional regression equations were used to estimate instantaneous peak streamflows for floods with 10-, 4-, 2-, 1-, and 0.2-percent and 1-percent plus annual exceedance probabilities. The 1-percent plus flood elevation is defined by the Federal Emergency Management Agency as a flood elevation derived by using streamflows that include the average predictive error for the regression equation streamflow calculation for the Flood Risk project. This error is then added to the 1-percent annual exceedance probability flood streamflow to calculate the new 1-percent plus streamflow. The annual exceedance probability streamflows were then used in a Hydrologic Engineering Center-River Analysis System step-backwater model to determine water-surface elevation profiles and flood-inundation boundaries for the 10-, 4-, 2-, 1-, and 0.2-percent and 1-percent plus annual exceedance probability floods and a regulatory floodway along a selected reach of each stream. The Clear Fork Mohican River model was calibrated to 16 flood events by using the current stage-streamflow relation at the streamgage Clear Fork Mohican River at Bellville, Ohio (USGS station number 03131982) and a submersible pressure transducer. Flood-inundation boundaries for the 1- and 0.2-percent annual exceedance probability floods and a regulatory floodway were mapped for each stream.

Ohio↗
USGS2019

An evaluation of methods for computing annual water-quality loads

The U.S. Geological Survey publishes information on the mass, or load, of water-quality constituents transported through rivers and streams sampled as part of the operation of the National Water Quality Network (NWQN). This study evaluates methods for computing annual water-quality loads, specifically with respect to procedures currently (2019) used at sites in the NWQN. Near-daily datasets of chloride, total nitrogen, nitrate plus nitrite, total phosphorus, and suspended sediment were subset to determine the accuracy of various load-estimation methods, including linear interpolation, ratio estimators, and linear and weighted-regression methods. Water-quality loads are computed under different sampling strategies and at multiple sampling sites to provide a more complete evaluation of load-estimation methods. Estimation methods were less accurate when computing loads at annual rather than decadal time steps. Depending on the water-quality constituent, annual loads were within comparable accuracy thresholds 21 to 64 percent of the time relative to decadal loads. The accuracy of annual load estimates varied among water-quality constituents, sampling strategies, sampling sites, and estimation methods. Methods were most accurate when estimating chloride and decreased in accuracy when estimating total nitrogen, nitrate plus nitrite, total phosphorus, and suspended-sediment loads. Estimation methods were most likely to compute accurate annual loads when samples were collected frequently (26 samples per year) and when sampling strategies targeted high-flow conditions. For a given water-quality constituent, estimation accuracy differed substantially among sampling sites; estimates were more likely to be accurate at large rivers with less variability in concentration and (or) discharge conditions and were less likely to be accurate at smaller stream sites with more variable streamflow and (or) water-quality concentrations. The Weighted Regressions on Time, Discharge, and Season method with Kalman filtering (WRTDS_K) generally produced the most accurate annual load estimates among sampling sites and water-quality constituents. Although WRTDS_K was the most accurate generally, every estimation method evaluated had the potential to produce accurate (and inaccurate) load estimates depending on the site, constituent, and water year. Linear interpolation and ratio estimators that used samples exclusively from the year being estimated were among the best performing methods for total nitrogen and nitrate plus nitrite loads but were among the least accurate when estimating annual total phosphorus and suspended-sediment loads. Ratio estimation that considered samples from previous years and stratified based on streamflow conditions produced among the most accurate total phosphorus estimates but was among the least accurate for other constituents. Regression-based methods that assumed linear or quadratic relations among the logarithm of water-quality concentrations and streamflow conditions were among the least accurate methods generally, whereas regression-based methods that considered cubic relations among the logarithm of concentration and streamflow and the Weighted Regressions on Time, Discharge, and Season (WRTDS) method were typically more accurate. Methods that adjusted daily estimates computed from regression or weighted-regression methods based on departures from sampled values, such as WRTDS_K and the composite method, improved estimate accuracy for most sites and constituents, but especially for chloride, total nitrogen, nitrate plus nitrite, and suspended-sediment estimates. Investigation of the underlying causes of estimation method bias indicated that sites and years with more variability in concentration and loading conditions, higher slopes in the relation of the logarithm of concentration and discharge, and sampling plans that underrepresented high-flow conditions generally led to less accurate load estimates. Finally, because all methods indicated the capacity to produce biased load estimates, additional work is needed to identify the capacity of new technologies, such as continuous water-quality sensors, to improve the accuracy of annual or shorter term load estimates. Based on findings in this report, the NWQN will continue to publish water-quality loads using LOADEST-based methods that consider multiple transformations of streamflow, as well as season, time, and variables indicative of historical streamflow conditions to maintain consistent methods for stakeholders. However, the NWQN also plans to begin publishing annual load estimates using the WRTDS_K method in 2020 because this method was determined to be the most accurate for a given site, constituent, and water year.

Scientific Investigations Report↗
USGS1996

Evaluating evapotranspiration for six sites in Benton, Spokane, and Yakima counties, Washington, May 1990 to September 1992

This report evaluates evapotranspiration for six sites in Benton, Spokane, and Yakima Counties, Washington. Three sites were located on the Arid Lands Ecology Reserve in Benton County: one at a full-canopy grassland in Snively Basin (Snively Basin site), one at a sparse-canopy grassland adjacent to two weighing lysimeters (grass lysimeter site), and one at a sagebrush grassland adjacent to two weighing lysimeters (sage lysimeter site). Two sites were located on the Turnbull National Wildlife Refuge in Spokane County: one at a full-canopy grassland in a meadow (Turnbull meadow site), the other a full-canopy grassland near a marsh (Turnbull marsh site). The last site was located in a sagebrush grassland in the Black Rock Valley in Yakima County (Black Rock Valley site). The periods of study at the six sites varied, ranging from 5 months at the Black Rock Valley site to more than 2 years at the Snively Basin, grass lysimeter, and sage lysimeter sites. The periods of study were May 1990 to September 1992 for the Snively Basin, grass lysimeter, and sage lysimeter sites; May 1991 to September 1992 for the Turnbull meadow site; May 1991 to April 1992 for the Turnbull marsh site; and March to September 1992 for the Black Rock Valley site. Evapotranspiration and energy-budget fluxes were estimated for the Snively Basin site, the Turnbull meadow site, and the Black Rock Valley site using the Bowen-ratio and Penman-Monteith methods. Daily evapotranspiration for the Snively Basin site was also estimated using a deep-percolation model for the Columbia Basin. The Bowen-ratio method and weighing lysimeters were used at the grass and sage lysimeter sites. The Penman-Monteith method was used at the Turnbull marsh site. Daily evapotranspiration at the sites ranged from under 0.2 millimeter during very dry or cold periods to over 4\x11millimeters after heavy rainfall or during periods of peak transpiration. At all sites, peak evapotranspiration occurred in spring, coinciding with plant growth, and the lowest evapotranspiration occurred in late summer and winter, coinciding with plant dormancy and extremely hot or cold temperatures. Water budgets for the Snively Basin, grass lysimeter, and sage lysimeter sites were based on estimates of precipitation, evapotranspiration, and surface runoff. Surface runoff was estimated at zero for all sites. For the Snively Basin site, 1991 and 1992 water budgets using Penman-Monteith evapotranspiration estimates agreed within 1 percent of the annual budgets computed using deep-percolation model estimates; daily estimates of evapotranspiration by the two methods varied considerably, however. For the Snively Basin site, 100 percent of the precipitation became ET in 1991, and in 1992, about 91 percent of the precipitation became evapotranspiration. Water budgets based on weighing lysimeter data at the grass and sage lysimeter sites agreed within 1 percent of each other for 1991 and within 5 percent of each other for 1992. For 1991, 10 percent of the precipitation became ET at both lysimeter sites. For 1992, 94 to 98 percent of the precipitation became ET at the grass lysimeter site while 98 to 9 percent of the precipitation became ET at the sage lysimeter site. Though there were uncertainties in the methods used, recharge estimates for the Snively Basin and grass and sage lysimeter sites were of the same order of magnitude. The Penman-Monteith method (which incorporated Bowen-ratio measurements), deep- percolation model, and weighing lysimeters indicated that no recharge to subsurface systems (soil profile, unsaturated zone, and ground water) occurred in 1991 and that, in 1992, recharge to subsurface systems was probably less than 10 percent of the annual precipitation at the Snively Basin and grass and sage lysimeter sites.

Washington↗