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Estimating current and future streamflow characteristics at ungaged sites, central and eastern Montana, with application to evaluating effects of climate change on fish populations

Scientific Investigations Report 2017-5002

Prepared in cooperation with the Plains and Prairie Potholes Landscape Conservation Cooperative and the Bureau of Land Management
By:
and
DOI:10.3133/sir20175002

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Abstract

A common statistical procedure for estimating streamflow statistics at ungaged locations is to develop a relational model between streamflow and drainage basin characteristics at gaged locations using least squares regression analysis; however, least squares regression methods are parametric and make constraining assumptions about the data distribution. The random forest regression method provides an alternative nonparametric method for estimating streamflow characteristics at ungaged sites and requires that the data meet fewer statistical conditions than least squares regression methods.

Random forest regression analysis was used to develop predictive models for 89 streamflow characteristics using Precipitation-Runoff Modeling System simulated streamflow data and drainage basin characteristics at 179 sites in central and eastern Montana. The predictive models were developed from streamflow data simulated for current (baseline, water years 1982–99) conditions and three future periods (water years 2021–38, 2046–63, and 2071–88) under three different climate-change scenarios. These predictive models were then used to predict streamflow characteristics for baseline conditions and three future periods at 1,707 fish sampling sites in central and eastern Montana. The average root mean square error for all predictive models was about 50 percent. When streamflow predictions at 23 fish sampling sites were compared to nearby locations with simulated data, the mean relative percent difference was about 43 percent. When predictions were compared to streamflow data recorded at 21 U.S. Geological Survey streamflow-gaging stations outside of the calibration basins, the average mean absolute percent error was about 73 percent.

Suggested Citation

Sando, Roy, and Chase, K.J., 2017, Estimating current and future streamflow characteristics at ungaged sites, central and eastern Montana, with application to evaluating effects of climate change on fish populations: U.S. Geological Survey Scientific Investigations Report 2017–5002, 23 p., https://doi.org/10.3133/sir20175002.

ISSN: 2328-0328 (online)

Study Area

Table of Contents

  • Abstract
  • Introduction
  • Data Analysis Methods
  • Results from the Random Forest Regression Models
  • Quality Assurance and Accuracy Assessment
  • Limitations of the Random Forest Regression Analyses
  • Summary
  • References Cited
  • Appendix 1. Supplemental Information Relating to the Statistical Analysis

Additional publication details

Publication type:
Report
Publication Subtype:
USGS Numbered Series
Title:
Estimating current and future streamflow characteristics at ungaged sites, central and eastern Montana, with application to evaluating effects of climate change on fish populations
Series title:
Scientific Investigations Report
Series number:
2017-5002
DOI:
10.3133/sir20175002
Year Published:
2017
Language:
English
Publisher:
U.S. Geological Survey
Publisher location:
Reston, VA
Contributing office(s):
WY-MT Water Science Center
Description:
Report: vi, 26 p.; Appendixes 1-1 to 1-18
Country:
United States
State:
Montana
Online Only (Y/N):
Y
Additional Online Files (Y/N):
Y