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Synthesis of Habitat Availability and Carrying Capacity Research to Support Water Management Decisions and Enhance Conditions for Pacific Salmon in the Willamette River, Oregon

Open-File Report 2021-1114
Prepared in cooperation with the U.S. Army Corps of Engineers
By: , , , , , and 
https://doi.org/10.3133/ofr20211114

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Abstract

Flow management is complex in the Willamette River Basin where the U.S. Army Corps of Engineers owns and operates a system of 13 dams and reservoirs (hereinafter Willamette Project), which are spread throughout three large tributaries including the Middle Fork Willamette, McKenzie, and Santiam Rivers. The primary purpose of the Willamette Project is flood-risk management, which provides critical protection to the Willamette Valley, but flow managers must also consider factors such as power generation, water-quality improvement, irrigation, recreation, and protection for aquatic species such as U.S. Endangered Species Act-listed Chinook salmon (Oncorhynchus tshawytscha) and steelhead (O. mykiss). Flow-management decision-making in the basin can benefit from models that allow for flow-scenario comparisons and a wide range of modeling methods are available. For this study, we examined existing datasets and modeling efforts in the basin and provided an overview of available options. Most previous studies used Physical Habitat Simulation System, habitat data were collected from a series of transects within modeled reaches, and habitat suitability indices were obtained from the literature, or using expert opinion. These studies provide information for specific reaches of the Willamette River Basin, which limits their ability to provide broad-scale predictive capability. Recent efforts to develop a two-dimensional hydraulic model in the mainstem Willamette River, and in specific reaches of primary tributaries downstream from Project dams, have bolstered modeling capabilities in the basin. This work has developed spatially continuous water depth and velocity data in more than 250 kilometers (km) of river downstream from Project dams and has predictive capability throughout the year at flows up to normal peak levels. Additionally, other methods are described for estimating habitat availability, which include habitat suitability criteria, logistic regression, occupancy and abundance modeling, and energetic based approaches. There are strengths and weaknesses to each approach and selection of the preferred approach in the Willamette River Basin will depend on the desired metrics of interest and the risk tolerance of managers and stakeholders in the basin.

Suggested Citation

Kock, T.J., Perry, R.W., Hansen, G.S., White, J., Stratton Garvin, L., and Wallick, J.R., 2021, Synthesis of habitat availability and carrying capacity research to support water management decisions and enhance conditions for Pacific salmon in the Willamette River, Oregon: U.S. Geological Survey Open-File Report 2021–1114, 24 p., https://doi.org/10.3133/ofr20211114.

ISSN: 2331-1258 (online)

Study Area

Table of Contents

  • Acknowledgments
  • Abstract
  • Introduction
  • Objective 1—Review Existing Willamette River Datasets and Identify Key Data Gaps
  • Objective 2—Summarize Methods to Estimate Habitat Availability
  • Objective 3—Identify Optimal Methods for Estimating Carrying Capacity and its Influence on Density-Dependent Processes in the Willamette River and its Major Tributaries
  • Summary
  • References Cited
Publication type Report
Publication Subtype USGS Numbered Series
Title Synthesis of habitat availability and carrying capacity research to support water management decisions and enhance conditions for Pacific salmon in the Willamette River, Oregon
Series title Open-File Report
Series number 2021-1114
DOI 10.3133/ofr20211114
Year Published 2021
Language English
Publisher U.S. Geological Survey
Publisher location Reston, VA
Contributing office(s) Oregon Water Science Center, Western Fisheries Research Center
Description vii, 24 p.
Country United States
State Oregon
Other Geospatial Willamette River
Online Only (Y/N) Y
Google Analytic Metrics Metrics page
Additional publication details