Last edited by Dulmaran
Tuesday, July 28, 2020 | History

3 edition of Regional regression equations for estimation of natural streamflow statistics in Colorado found in the catalog.

Regional regression equations for estimation of natural streamflow statistics in Colorado

Joseph P. Capesius

Regional regression equations for estimation of natural streamflow statistics in Colorado

by Joseph P. Capesius

  • 140 Want to read
  • 5 Currently reading

Published by U.S. Dept. of the Interior, U.S. Geological Survey in Reston, Va .
Written in English

    Subjects:
  • Stream measurements -- Colorado,
  • Streamflow -- Colorado,
  • Regression analysis

  • Edition Notes

    Statementby Joseph P. Capesius and Verlin C. Stephens.
    SeriesScientific investigations report -- 2009-5136, Scientific investigations report -- 2009-5136.
    ContributionsStephens, Verlin C., Geological Survey (U.S.), Colorado Water Conservation Board., Colorado. Dept. of Transportation.
    Classifications
    LC ClassificationsGB1225.C6 C36 2009
    The Physical Object
    Paginationiv, 46 p. :
    Number of Pages46
    ID Numbers
    Open LibraryOL24002128M
    ISBN 109781411325623
    LC Control Number2009039729
    OCLC/WorldCa449283905

      A complete discussion of this method is provided in HDS-2 (McCuen et al. ). National Streamflow Statistics Program As a result of the widespread use of various regression equations the USGS compiled all statewide and metropolitan area regression equations into a computer program titled the National Streamflow Statistics (NSS) program. Also presented are equations and=20 techniques by which the magnitude and frequency of floods can be = estimated for=20 any ungaged site on naturally flowing (unregulated) streams. The data = and=20 results are presented on figures = 1 to=20 10 and in tables 1 to 5 at the end of the report.=

    means it’s official. Federal government websites often end Before sharing sensitive information, make sure you're on a federal government site. Geological Survey (U.S.): Analysis of the streamflow-gaging station network in Ohio for effectiveness in providing regional streamflow information / (Columbus, Ohio: U.S. Dept. of the Interior, U.S. Geological Survey ; Denver, CO: Branch of Information Services [distributor], ), also by David E. Straub and Ohio. Division of Water (page.

    EPA/B /96 Edition ACCESS EPA Office of Information Resources Management U.S. Environmental Protection Agency M Street, SW Washington, DC For sale by the U.S. Government Printing Office ' • • Superintendent of Documents, Mail Stop: SSOP, Washington, DC ISBN ;.   A regularized joint inverse procedure is presented and used to estimate the magnitude of extreme rainfall events in ungauged coastal river basins of El Salvador: Paz, Jiboa, Grande de San Miguel, and Goascoran. Since streamflow measurements reflect temporal and spatial rainfall information, peak-flow discharge is hypothesized to represent a similarity measure suitable for regionalization. To.


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Regional regression equations for estimation of natural streamflow statistics in Colorado by Joseph P. Capesius Download PDF EPUB FB2

WSP (), Methods for Estimating Magnitude and Frequency of Floods in the Southwestern United States. WRIREstimation of Natural Streamflow Characteristics in Western Colorado.

SIRRegional Regression Equations to Estimate Flow-Duration Statistics at Ungaged Stream Sites in Connecticut. Description of study area --Previous studies --Regional regression equations for estimation of natural streamflow statistics in Colorado --Definition of hydrologic regions of Colorado --Selection of stations --Selection of stations for peak-streamflow statistics --Selection of stations for other streamflow statistics --Computation of streamflow.

The State/Regional Info tab provides (1) a description of the streamflow statistics that can be estimated by use of regression equations for the state that the user has selected, (2) citations for the reports that include the equations, (3) notes and cautions that are specific to using StreamStats for that state, (4) a link to information about.

Regional Regression Models of Annual Streamflow for the United States Article in Journal of Irrigation and Drainage Engineering (3) May with Reads How we measure 'reads'. Regional Regression Equations for Estimation of Natural Streamflow Statistics in Colorado by Joseph P.

Capesius, Verlin C. Stephens Unknown, 46 Pages, Published ISBN / ISBN / Pages: The U.S. Geological Survey (USGS), in cooperation with the Colorado Department of Transportation, developed regional-regression equations for estimating the,4- 2- 1-,percent annual exceedance-probability discharge (AEPD) for natural streamflow in eastern Colorado.

One example of this is the U.S. Geological Survey's National Streamflow Statistics Program, which has developed regional regression relationships for the prediction of a wide range of streamflow.

In addition, the USGS enhances and maintains the National Streamflow Statistics Program, the StreamStats flow statistics application and delivery tool, and WaterAlert, a tool for automatic notification of threshold exceedance for stream stage, streamflow, and other water‐ Updates to the Regional Regression Equations in Western Colorado in.

Simple-regression (drainage-area-only) equations for estimating bankfull characteristics of Ohio streams are presented in table 7. For the reader's convenience, the regional intercept term is combined with the equation constant and separate equations are presented for each region.

The multiple-linear-regression approach (illustrated by the example in figure 2) is commonly used by hydrologists to define regional variations of streamflow as a function of basin characteristics. This method was applied extensively in and in a nationwide U.S.

Geological Survey (USGS) program to provide a means for estimating. Considerable research has been done on the design of monitoring networks in the earth sciences. Perhaps most common are networks designed to use observations at discrete points in space and time to estimate the characteristics of a continuous field or flux (Bastin et al., ; Bras and Rodriguez-Iturbe, ; Pardo-Igúzquiza, ; Rodriguez-Iturbe and Megia, ; Sampson and Guttorp, ).

average of the – ‘Stress Test” observed natural streamflow is shown as a black square. The box-whiskers plots show the distribution of the year average values at (–); the outer boxes show the 10 th and 90 th thpercentiles; the inner boxes show 50 th, and 75 th. Colorado River Basin Climate and Hydrology.

State of the Science. April Editors and Lead Authors. Jeff Lukas, University of Colorado Boulder (CU Boulder), Cooperative Ins. Extensive research has been conducted on flow statistics to represent alterations to natural streamflow regimes.

Many different hydrologic indices have been developed to characterize flow alteration (Richter et al.,Olden and Poff,Gao et al.,Poff et al.,Poff and Zimmerman, ).The selection of a few simple statistics in the past has progressed, given new Cited by: WRI Regional equations for estimation of peak-streamflow frequency for natural Basins in Texas, by W.H.

Asquith and R.M. Slade, Jr. WRI Changes in Flow in the Beaver–North Canadian River Basin Upstream From Canton Lake, Western Oklahoma, by K.L. Wahl and R.L. Tortorelli. This study aims to address hydrological processes and impacts of an atmospheric river (AR) event that occurred during 15–18 February in the Russian River basin in California.

The National Water Model (NWM), a fully distributed hydrologic model, was used to evaluate the hydrological processes including soil moisture flux, overland flow, and by: 2.

The accuracy of low-flow estimation by means of regional regression models is often complicated by censored data (e.g. Kroll and Stedinger, ) and in general may range from ‘very poor’ to ‘very good’ depending on the quality and amount of streamflow data used to construct regression model, accuracy of estimation of independent Cited by:   Streamflow predictions, updated to include the regional drainage‐size‐dependent process uncertainties, provided an estimate of the latent “true” streamflow, which compensated for local prediction biases in the nonstate‐space hierarchical model at the calibration sites (e.g., compare the patterns in Figure 6a to those in Figure 2a).Author: Richard B.

Alexander, Gregory E. Schwarz, Elizabeth W. Boyer. Although this calibration method offers appealing benefits, limitations also exist. First, the use of streamflow characteristics is usually associated with a loss of information in lieu of the streamflow time series, which may have a negative impact on parameter estimation (Fenicia et al., ; Shafii & Tolson, ).

The “adequacy” of Cited by: 1. The data were available from to because hydrological observations in the two stations have been stopped since With a Global Water flow probe FP (Global Water, Inc., Gold River, Colorado, ), the streamflow was also measured in a field experiment during summer and to verify the simulation by: 7.

Description of Water‐Quality and Streamflow Data, and Data Screening. The dependent variable in SPARROW models is long‐term mean annual constituent load normalized to a base year (Preston et al., ).The base year for the regional nutrient SPARROW models described here iswhich was selected so that calculated loads would coincide with the most recently available geospatial datasets Cited by: This study incorporates antecedent (preceding) soil moisture into forecasting streamflow volumes within the North Platte River Basin, Colorado/Wyoming (USA).

The incorporation of antecedent soil moisture accounts for infiltration and can improve streamflow predictions. Current Natural Resource Conservation Service (NRCS) forecasting methods are replicated, and a comparison is drawn between Author: Abdoul Oubeidillah, Glenn Tootle, Thomas Piechota.ln(Streamflow) altered natural Fig.

2. An example of the estimation of natural and altered Flow Duration Curves (FDCs) for a sample basin. The delta between the points estimating the FDCs, shown at one exceedence probability by the two headed arrow, is used to .