Skip Links

USGS - science for a changing world

Scientific Investigations Report 2014–5231

In cooperation with the Department of the Interior WaterSMART Program

A Comparison of Methods to Predict Historical Daily Streamflow Time Series in the Southeastern United States

By William H. Farmer, Stacey A. Archfield, Thomas M. Over, Lauren E. Hay, Jacob H. LaFontaine, and Julie E. Kiang

Thumbnail of and link to report PDF (1.14 MB)Abstract

Effective and responsible management of water resources relies on a thorough understanding of the quantity and quality of available water. Streamgages cannot be installed at every location where streamflow information is needed. As part of its National Water Census, the U.S. Geological Survey is planning to provide streamflow predictions for ungaged locations. In order to predict streamflow at a useful spatial and temporal resolution throughout the Nation, efficient methods need to be selected. This report examines several methods used for streamflow prediction in ungaged basins to determine the best methods for regional and national implementation. A pilot area in the southeastern United States was selected to apply 19 different streamflow prediction methods and evaluate each method by a wide set of performance metrics. Through these comparisons, two methods emerged as the most generally accurate streamflow prediction methods: the nearest-neighbor implementations of nonlinear spatial interpolation using flow duration curves (NN-QPPQ) and standardizing logarithms of streamflow by monthly means and standard deviations (NN-SMS12L). It was nearly impossible to distinguish between these two methods in terms of performance. Furthermore, neither of these methods requires significantly more parameterization in order to be applied: NN-SMS12L requires 24 regional regressions—12 for monthly means and 12 for monthly standard deviations. NN-QPPQ, in the application described in this study, required 27 regressions of particular quantiles along the flow duration curve. Despite this finding, the results suggest that an optimal streamflow prediction method depends on the intended application. Some methods are stronger overall, while some methods may be better at predicting particular statistics. The methods of analysis presented here reflect a possible framework for continued analysis and comprehensive multiple comparisons of methods of prediction in ungaged basins (PUB). Additional metrics of comparison can easily be incorporated into this type of analysis. By considering such a multifaceted approach, the top-performing models can easily be identified and considered for further research. The top-performing models can then provide a basis for future applications and explorations by scientists, engineers, managers, and practitioners to suit their own needs.

First posted March 11, 2015

  • Tables 1-7 (PDF, 185 KB)
    Contains: Records for each streamgage used in the Southeast Model Comparsion, a listing of all names and abbreviations of prediction methods, root-mean-square error data, fitted coefficients and goodness-of-fit statistics, mean rank performance metric, and mean and standard deviation of average ranks for each method of prediction.

For additional information, contact:
Director, Office of Surface Water
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA, 20192
http://water.usgs.gov/osw/

Part or all of this report is presented in Portable Document Format (PDF). For best results viewing and printing PDF documents, it is recommended that you download the documents to your computer and open them with Adobe Reader. PDF documents opened from your browser may not display or print as intended. Download the latest version of Adobe Reader, free of charge. More information about viewing, downloading, and printing report files can be found here.


Suggested citation:

Farmer, W.H., Archfield, S.A., Over, T.M., Hay, L.E., LaFontaine, J.H., and Kiang, J.E., 2014, A comparison of methods to predict historical daily streamflow time series in the southeastern United States: U.S. Geological Survey Scientific Investigations Report 2014–5231, 34 p., http://dx.doi.org/10.3133/sir2014-5231.

ISSN 2328-0328 (online)



Contents

Abstract

Introduction

Study Area, Streamgage Selection, and Dataset Development

Methods to Predict Daily Streamflow

Methods of Analysis

Results and Discussion

Summary and Conclusions

Acknowledgments

References Cited


Accessibility FOIA Privacy Policies and Notices

USA.gov logo U.S. Department of the Interior | U.S. Geological Survey
URL: https://pubs.usgs.gov/sir/2014/5231/
Page Contact Information: Contact USGS
Page Last Modified: Wednesday, March 11, 2015, 11:43:15 AM