thumbnail

Estimates of Long-Term Mean Daily Streamflow and Annual Nutrient and Suspended-Sediment Loads Considered for Use in Regional SPARROW Models of the Conterminous United States, 2012 Base Year

Scientific Investigations Report 2019-5069
By: , , , , , , , , and 
https://doi.org/10.3133/sir20195069

Links

  • Document: Report (3.32 MB pdf)
  • Data Releases:
    • USGS data release - Water-Quality and Streamflow Datasets Used for Estimating Long-Term Mean Daily Streamflow and Annual Loads to be Considered for Use in Regional Streamflow, Nutrient and Sediment SPARROW Models, United States, 1999-2014
    • USGS data release - Water-quality and streamflow datasets used for estimating long-term mean daily streamflow and annual loads to be considered for use in regional streamflow, nutrient and sediment SPARROW models, United States, 1999-2014
  • Download citation as: RIS | Dublin Core

Abstract

Streamflow, nutrient, and sediment concentration data needed to estimate long-term mean daily streamflow and annual constituent loads were compiled from Federal, State, Tribal, and regional agencies, universities, and nongovernmental organizations. The streamflow and loads are used to develop Spatially Referenced Regressions on Watershed Attributes (SPARROW) models. SPARROW models help describe the distribution, sources, and transport of streamflow, nutrients, and sediment in streams throughout five regions of the conterminous United States. After the data were screened, approximately 5,200 streamflow, 3,000 sediment, and 3,300 nutrient sites, sampled by 137 agencies and organizations were identified as having suitable data for calculating the long-term mean daily streamflow and annual nutrient and sediment loads required for SPARROW model estimation. These sites are representative of a wide range in terms of watershed size, contaminant source types, and land-use and other important watershed characteristics. The methods used to estimate long-term mean annual loads include the Beale ratio estimator and Fluxmaster regression method with Kalman smoothing.

Suggested Citation

Saad, D.A., Schwarz, G.E., Argue, D.M., Anning, D.W., Ator, S.W., Hoos, A.B., Preston, S.D., Robertson, D.M., and Wise, D.R., 2019, Estimates of long-term mean daily streamflow and annual nutrient and suspended-sediment loads considered for use in regional SPARROW models of the conterminous United States, 2012 base year: U.S. Geological Survey Scientific Investigations Report 2019–5069, 51 p., https://doi.org/10.3133/sir20195069.

ISSN: 2328-0328 (online)

Study Area

Table of Contents

  • Foreword
  • Abstract
  • Introduction
  • Streamflow and Water-Quality Data Used to Estimate Long-Term Mean Daily Streamflow and Annual Loads
  • Methods for Estimating Long-Term Mean Daily Streamflows and Annual Loads
  • Final Streamflow and Load Estimates Considered for Use in the 2012 Regional SPARROW Models
  • Streamflow and Constituent Yields for Sites Considered for Use in the 2012 Regional SPARROW Models
  • Summary
  • References Cited
  • Appendix 1. Sampling Agencies Associated with Water-Quality Data Used To Compute Mean Annual Load Estimates Considered for Use in 2012 Regional SPARROW Models
  • Appendix 2. A Kalman-Smoothing Estimate of Water-Quality Loads Based on Simulated Maximum Likelihood Estimation for Censored Data: The Fluxmaster-K Algorithm
  • Appendix 3. Derivation of Regularity Conditions Used to Evaluate the Covariance Matrix and Asymptotic Efficiency of the Estimates Produced by the Fluxmaster-K Algorithm
Publication type Report
Publication Subtype USGS Numbered Series
Title Estimates of long-term mean daily streamflow and annual nutrient and suspended-sediment loads considered for use in regional SPARROW models of the Conterminous United States, 2012 base year
Series title Scientific Investigations Report
Series number 2019-5069
DOI 10.3133/sir20195069
Year Published 2019
Language English
Publisher U.S. Geological Survey
Publisher location Reston, VA
Contributing office(s) Wisconsin Water Science Center, WMA - Integrated Modeling and Prediction Division, Upper Midwest Water Science Center
Description Report: vii, 51 p.; Data Release
Country United States
Other Geospatial Conterminous United States
Online Only (Y/N) Y
Additional Online Files (Y/N) N
Google Analytic Metrics Metrics page
Additional publication details