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Use of Boosted Regression Trees to Quantify Cumulative Instream Flow Resulting from Curtailment of Irrigation in the Sprague River Basin, Oregon

Scientific Investigations Report 2019-5130
Prepared in cooperation with the Bureau of Reclamation
(Interagency Agreement R16PG00120)
By:
https://doi.org/10.3133/sir20195130

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Abstract

A boosted regression trees (BRT) approach was used to estimate the amount by which streamflow is increased when irrigation is regulated (curtailed) upstream of a streamgage on the Sprague River in southern-central Oregon. The BRT approach differs from most other approaches that require baseline conditions for comparison, where those baseline conditions are determined from past observations by searching for hydrologically similar years when irrigation was not regulated. Such baseline conditions are always imperfect estimates of the true baseline conditions. The BRT approach instead estimates unique baseline conditions for any year in which irrigation is regulated by calculating the baseline condition based on measurements of precipitation and weather observations that determine evapotranspiration, and other measurements that are proxies for the effects of climate and regional groundwater pumping on water-table elevation, using a model that has been trained in years of no regulation. The amount by which streamflow is increased by regulation is then calculated by subtracting the estimated baseline conditions from the measured streamflow. The approach is challenged by the fact that the streamflow increase may be a small fraction of the total streamflow; nonetheless, during 2 years in which regulation was started early and was implemented consistently through the season, the increased flow made up about one third of the flow past the streamgage during the regulation period. An advantage of this approach is that with rigorous model testing with holdout data, the threshold for detecting streamflow increase and intervals around the estimates of increase at a desired level of confidence can be quantified. The model relies on datasets that are readily available and updated continuously and therefore can be used operationally to inform resource management.

Suggested Citation

Wood, T.M., 2019, Use of boosted regression trees to quantify cumulative instream flow resulting from curtailment of irrigation in the Sprague River basin, Oregon: U.S. Geological Survey Scientific Investigations Report 2019-5130, 25 p., https://doi.org/10.3133/sir20195130.

ISSN: 2328-0328 (online)

Study Area

Table of Contents

  • Abstract
  • Introduction
  • Use Of Boosted Regression Trees To Model Streamflow
  • Data Used To Develop Sprague River Discharge Boosted Regression Trees Model
  • Building And Evaluating The Sprague River Discharge Boosted Regression Trees Model
  • Using The Boosted Regression Trees Model To Quantify Cumulative Instream
  • Flow Resulting From Curtailment Of Irrigation
  • Conclusion
  • References Cited
Publication type Report
Publication Subtype USGS Numbered Series
Title Use of boosted regression trees to quantify cumulative instream flow resulting from curtailment of irrigation in the Sprague River basin, Oregon
Series title Scientific Investigations Report
Series number 2019-5130
DOI 10.3133/sir20195130
Year Published 2020
Language English
Publisher U.S. Geological Survey
Publisher location Reston, VA
Contributing office(s) Oregon Water Science Center
Description vi, 25 p.
Country United States
State Oregon
Other Geospatial Sprague River Basin
Online Only (Y/N) Y
Google Analytic Metrics Metrics page
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