USGS library for S-PLUS for Windows -- Release 4.0

Lorenz, David L.; Ahearn, Elizabeth A.; Carter, Janet M.; Cohn, Timothy A.; Danchuk, Wendy J.; Frey, Jeffrey W.; Helsel, Dennis R.; Lee, Kathy E.; Leeth, David C.; Martin, Jeffrey D.; McGuire, Virginia L.; Neitzert, Kathleen M.; Robertson, Dale M.; Slack, James R.; Starn, J. Jeffrey; Vecchia, Aldo V.; Wilkison, Donald H.; Williamson, J

doi:10.3133/ofr20111130

Cited by 6 publications

(7 citation statements)

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“…A ranked multiple comparison test was performed using the USGS library functions in S-PLUS (Lorenz and others, 2011) to perform these tests (Helsel and Hirsch, 2002). The ranked test was used because the continuous variables were not necessarily normally distributed.…”

Section: Multiple Comparison Statisticsmentioning

confidence: 99%

Analysis of historic agricultural irrigation data from the Natural Resources Conservation Service monitoring and evaluation for Grand Valley, Lower Gunnison Basin, and McElmo Creek Basin, western Colorado, 1985 to 2003

Mayo¹

2015

Open-File Report

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Front cover: Top left, typical weather station measuring wind run, solar radiation, maximum-minimum temperatures, relative humidity, and precipitation; top right, pressure transducer to measure air pressure. Middle left, Datapod and housing box; middle right, Datapod, interface, and signal conditioner for a magnetic induction pipeline flow sensor. Bottom right, typical inflow installation with a stilling well and float potentiometer. For more information on the USGS-the Federal source for science about the Earth, its natural and living resources, natural hazards, and the environment, visit http://www.usgs.gov or call 1-888-ASK-USGS. Analysis of Historic Agricultural IrrigationFor an overview of USGS information products, including maps, imagery, and publications, visit http://www.usgs.gov/pubprodTo order this and other USGS information products, visit http://store.usgs.gov Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.Although this information product, for the most part, is in the public domain, it also may contain copyrighted materials as noted in the text. Permission to reproduce copyrighted items must be secured from the copyright owner.Suggested citation: Mayo, J.W., 2015, Analysis of historic agricultural irrigation data from the Natural Resources Conservation Service monitoring and evaluation for Grand Valley, Lower Gunnison Basin, and McElmo Creek Basin, western Colorado, 1985 to 2003: U.S. Geological Survey Open-File Report 2014-1261. ISSN 2331ISSN -1258 iii Acknowledgments While the USGS study found discrepancies in some of the results of the NRCS evaluation, the author of the USGS study respectfully recognizes the work performed by the NRCS staff to complete such a complex and long-running effort of field data collection and data analysis. The number of site-years evaluated over three salinity control units, with each site often requiring daily visits, would be very difficult to replicate today. Given the time frame that the evaluation was begun (early 1980s), electronic data collection instruments and office computer technologies were then in their infancy. The analysis software for the NRCS evaluation was hand coded in the Basic programming language and run on an early Tandy home computer. If errors in definitions in the analysis software occurred at the beginning of the evaluation, it would have been difficult to recognize those errors, and even more difficult to have the software modified later. The pioneering efforts by the staff of the NRCS evaluation to overcome many technical obstacles along the way led to the successful completion of a complex and worthwhile project. Overall, the results of the NRCS evaluation have been accurate and consistent and have provided real value to the salinity control activities in the Colorado River Basin.Thanks are extended to Frank Riggle, NRCS, former Assistant State Conservationist for Water Resources (retired), NRCS, Denver, Colo. The original project was envisioned by Frank, a...

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Section: Multiple Comparison Statisticsmentioning

confidence: 99%

Analysis of historic agricultural irrigation data from the Natural Resources Conservation Service monitoring and evaluation for Grand Valley, Lower Gunnison Basin, and McElmo Creek Basin, western Colorado, 1985 to 2003

Mayo¹

2015

Open-File Report

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“…The Edisto River has some of the highest recorded fish-tissue mercury concentrations in the United States (Scudder and others, 2009). To better understand why these high concentrations exist, the USGS collected hydrologic and water-quality data in the McTier Creek watershed including continuous streamflow at several streamflow-gaging stations and numerous discrete samples for 48 water-quality constituents over a 30-month period (Bradley and others, 2010;2011).…”

Section: Introductionmentioning

confidence: 99%

Data visualization, time-series analysis, and mass-balance modeling of hydrologic and water-quality data for the McTier Creek watershed, South Carolina, 2007-2009

Benedict¹,

Conrads²,

Feaster³

et al. 2012

Open-File Report

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The McTier Creek watershed is located in the headwaters of the Edisto River Basin, which is in the Coastal Plain region of South Carolina. The Edisto ecosystem has some of the highest recorded fish-tissue mercury concentrations in the United States. In an effort to advance the understanding of the fate and transport of mercury in stream ecosystems, the U.S. Geological Survey, as part of its National Water-Quality Assessment Program, initiated a field investigation of mercury in the McTier Creek watershed in 2006. The initial efforts of the investigation included the collection of extensive hydrologic and water-quality field data, along with the development of several hydrologic and water-quality models. This series of measured and modeled data forms the primary source of information for this investigation to assess the fate and transport of mercury within the McTier Creek watershed. The visualization of data is an important tool for understanding the trends and influencing variables of an ecosystem. One of the initial efforts for evaluating the hydrology and water quality in the McTier Creek watershed was the development of a digital spreadsheet for systematically visualizing and interrogating selected hydrologic, water-quality, and model data. This report briefly describes the development and application of the McTier Creek Data Viewer. The extensive database incorporated into the data viewer also provides a means for analysis and the development of analytical tools that may provide insights into the water quality within the McTier Creek watershed. One such application was the development of a simple water-quality load model that utilized a massbalance equation in conjunction with the topography-based hydrological model (TOPMODEL) developed to simulate flow in the McTier Creek watershed. Several variations of this simple load model were developed and are presented in the report.

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“…Censored and uncensored dependentvariable data can be included together in a censored regression analysis (Eash and Barnes, 2012). To develop the left-censored regression equation for this study, an AMLE procedure implemented in the USGS library version 4.0 (Lorenz and others, 2011) for Spotfire S+® statistical software (TIBCO Software Inc., 2008) was used. The final left-censored regression model was selected primarily on the basis of minimizing values of the SEE.…”

Section: Computing Daily Mean Streamflow At Ungaged Locations In Iowamentioning

confidence: 99%

“…Correlation between the independent variables and VIF (Marquardt, 1970;Helsel and Hirsch, 2002) was used to evaluate multicollinearity in the regression models. By using a regression diagnostics tool implemented in the USGS library version 4.0 (Lorenz and others, 2011) for Spotfire S+® statistical software (TIBCO Software Inc., 2008), multicollinearity problems were identified by checking each independent variable for VIF greater than 2.…”

Section: Computing Daily Mean Streamflow At Ungaged Locations In Iowamentioning

confidence: 99%

Computing daily mean streamflow at ungaged locations in Iowa by using the Flow Anywhere and Flow Duration Curve Transfer statistical methods

Linhart¹,

Nania²,

Sanders³

et al. 2012

Scientific Investigations Report

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USGS library for S-PLUS for Windows -- Release 4.0

Cited by 6 publications

References 0 publications

Analysis of historic agricultural irrigation data from the Natural Resources Conservation Service monitoring and evaluation for Grand Valley, Lower Gunnison Basin, and McElmo Creek Basin, western Colorado, 1985 to 2003

Analysis of historic agricultural irrigation data from the Natural Resources Conservation Service monitoring and evaluation for Grand Valley, Lower Gunnison Basin, and McElmo Creek Basin, western Colorado, 1985 to 2003

Data visualization, time-series analysis, and mass-balance modeling of hydrologic and water-quality data for the McTier Creek watershed, South Carolina, 2007-2009

Computing daily mean streamflow at ungaged locations in Iowa by using the Flow Anywhere and Flow Duration Curve Transfer statistical methods

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