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Generalized Additive Model Estimation of No-Flow Fractions and L-Moments to Support Flow-Duration Curve Quantile Estimation Using Selected Probability Distributions for Bay and Estuary Restoration in the Gulf States

Scientific Investigations Report 2022-5051
Prepared in cooperation with the Gulf Coast Ecosystem Restoration Council
By: , , and 
https://doi.org/10.3133/sir20225051

Links

  • Document: Report (25.2 MB pdf) , XML
  • Dataset: USGS National Water Information System database —USGS water data for the Nation
  • Data Releases:
    • USGS data release - Estimated quantiles of decadal flow-duration curves using selected probability distributions fit to no-flow fractions and L-moments predicted for streamgages and for pour points of level-12 hydrologic unit codes in the southeastern United States, 1950–2010
    • USGS data release - Summary of decadal no-flow fractions and decadal L-moments of nonzero streamflow flow-duration curves for National Hydrography Dataset, version 2 catchments in the southeastern United States, 1950–2010
    • USGS data release - Estimated daily mean streamflows for HUC12 pour points in the southeastern United States, 1950–2009
  • Software Release: USGS software release —RESTORE/fdclmrpplo—Source code for estimation of L-moments and percent no-flow conditions for decadal flow-duration curves and estimation at level-12 hydro­logic unit codes
  • Download citation as: RIS | Dublin Core

Abstract

Censored and uncensored generalized additive models (GAMs) were developed using streamflow data from 941 U.S. Geological Survey streamflow-gaging stations (streamgages) to predict decadal statistics of daily streamflow for streams draining to the Gulf of Mexico. The modeled decadal statistics comprise no-flow fractions and L-moments of logarithms of nonzero streamflow for six decades (1950–2009). These statistics represent metrics of decadal flow-duration curves (dFDCs) derived from about 10 million daily mean streamflows. The L-moments comprise the mean, coefficient of L-variation, and the third through fifth L-moment ratios. The GAMs were fit to the statistics from 941 streamgages and 2,750 streamgage-decades by using watershed properties such as basin area and slope, decadal precipitation and temperature, and decadal values of flood storage and urban development percentages. The GAMs then estimated decadal statistics for 9,220 prediction locations (stream reaches) coincident with outlets of level-12 hydrologic unit codes. Both entire dataset (whole model) and leave-one-watershed-out model results are reported. No-flow fractions are censored data, and Tobit extensions to GAMs were used to model ephemeral streamflow conditions. Conversely, uncensored GAMs were used for estimation of the L-moments. The GAMs are shown, by coverage probabilities, to construct reliable 95-percent prediction limits. An example shows how no-flow fractions and L-moments may be used to approximate dFDCs by using selected probability distributions (mathematical formulas) including the asymmetric exponential power, generalized normal, and kappa distributions.

Suggested Citation

Crowley-Ornelas, E.R., Asquith, W.H., and Worland, S.C., 2023, Generalized additive model estimation of no-flow fractions and L-moments to support flow-duration curve quantile estimation using selected probability distributions for bay and estuary restoration in the Gulf States: U.S. Geological Survey Scientific Investigations Report 2022–5051, 35 p., https://doi.org/​10.3133/​sir20225051.

ISSN: 2328-0328 (online)

Study Area

Table of Contents

  • Acknowledgments
  • Abstract
  • Introduction
  • Data Sources and Statistical Methods
  • Summary of Generalized Additive Model Computations for No-Flow Fractions and L-Moments
  • Results of Generalized Additive Models for No-Flow Fractions and L-Moments
  • Flow-Duration Curve Quantile Estimation Using Selected Probability Distributions
  • Summary
  • References Cited
  • Glossary
Publication type Report
Publication Subtype USGS Numbered Series
Title Generalized additive model estimation of no-flow fractions and L-moments to support flow-duration curve quantile estimation using selected probability distributions for bay and estuary restoration in the Gulf States
Series title Scientific Investigations Report
Series number 2022-5051
DOI 10.3133/sir20225051
Year Published 2023
Language English
Publisher U.S. Geological Survey
Publisher location Reston, VA
Contributing office(s) Tennessee Water Science Center, Texas Water Science Center, Lower Mississippi-Gulf Water Science Center
Description Report: viii, 35 p.; 3 Data Releases; Dataset; Software Release
Country United States
State Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Mississippi, Missouri, Oklahoma, Tennessee, Texas
Online Only (Y/N) Y
Google Analytic Metrics Metrics page
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