Matthew Barker
Physical Scientist for the Washington Water Science Center
Education and Certifications
BS Wildlife Ecology and Management, University of Nevada, Reno, 2016
MS Sustainable Forest Management – Geomatics, Oregon State University, 2021
PhD, Sustainable Forest Management – Geomatics, Oregon State University, 2024
Science and Products
A streamflow permanence classification model for forested streams that explicitly accounts for uncertainty and extrapolation A streamflow permanence classification model for forested streams that explicitly accounts for uncertainty and extrapolation
Accurate mapping of headwater streams and their flow status has important implications for understanding and managing water resources and land uses. However, accurate information is rare, especially in rugged, forested terrain. We developed a streamflow permanence classification model for forested lands in western Oregon using the latest light detection and ranging-derived hydrography...
Authors
Jonathan D. Burnett, Kristin Jaeger, Sherri Johnson, Steven M. Wondzell, Jason B. Dunham, Matthew Irwin Barker, Emily Heaston, Nathan Chelgren, Michael G. Wing, Brian Staab, Michael E. Brown
Non-USGS Publications**
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
NHM-Assist NHM-Assist
NHM-Assist is a collection of python workflows presented in Jupyter notebooks for evaluating, running and interpreting National Hydrologic Model (NHM) domains using pywatershed. NHM-Assist allows users to: evaluate hydrofabric element connections such as hydrologic response unit connections to streamflow segments, segment routing order, and gage placement accuracy; display NHM domain...
Science and Products
A streamflow permanence classification model for forested streams that explicitly accounts for uncertainty and extrapolation A streamflow permanence classification model for forested streams that explicitly accounts for uncertainty and extrapolation
Accurate mapping of headwater streams and their flow status has important implications for understanding and managing water resources and land uses. However, accurate information is rare, especially in rugged, forested terrain. We developed a streamflow permanence classification model for forested lands in western Oregon using the latest light detection and ranging-derived hydrography...
Authors
Jonathan D. Burnett, Kristin Jaeger, Sherri Johnson, Steven M. Wondzell, Jason B. Dunham, Matthew Irwin Barker, Emily Heaston, Nathan Chelgren, Michael G. Wing, Brian Staab, Michael E. Brown
Non-USGS Publications**
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
NHM-Assist NHM-Assist
NHM-Assist is a collection of python workflows presented in Jupyter notebooks for evaluating, running and interpreting National Hydrologic Model (NHM) domains using pywatershed. NHM-Assist allows users to: evaluate hydrofabric element connections such as hydrologic response unit connections to streamflow segments, segment routing order, and gage placement accuracy; display NHM domain...