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
Ensemble methods for history matching and uncertainty quantification with a watershed model Ensemble methods for history matching and uncertainty quantification with a watershed model
History matching of large hydrologic models is challenging due to data sparsity and non-unique process combinations (and associated parameters) that can produce similar model predictions. We develop an ensemble-based history matching (and uncertainty quantification) approach using an iterative ensemble smoother (iES) method for three cutouts of the National Hydrologic Model (NHM) and...
Authors
Michael N. Fienen, Andrew J. Long, Katherine H. Markovich, Adel E. Haj, Matthew Irwin Barker
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 L. Jaeger, Sherri L Johnson, Steven M. Wondzell, Jason B. Dunham, Matthew Irwin Barker, Emily Dawn 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.
Airborne Thermal Infrared and True-color Imagery and Longitudinal Profiles of Stream Temperatures, McKenzie River Basin, Oregon, September 1999 Airborne Thermal Infrared and True-color Imagery and Longitudinal Profiles of Stream Temperatures, McKenzie River Basin, Oregon, September 1999
This dataset includes high-resolution thermal infrared (TIR) and true-color images collected from crewed aircraft and a point shapefile and corresponding comma-delimited tabular data representing the longitudinal spatial patterns of water surface temperature in the surveyed streams in the McKenzie River basin, Oregon. The USDA Forest Service, McKenzie River Ranger District contracted...
Airborne Thermal Infrared and True-color Imagery and Longitudinal Profiles of Stream Temperatures, Santiam River Basin, Oregon, August 2000 Airborne Thermal Infrared and True-color Imagery and Longitudinal Profiles of Stream Temperatures, Santiam River Basin, Oregon, August 2000
This dataset includes high-resolution thermal infrared (TIR) and true-color images collected from crewed aircraft and a point shapefile and corresponding comma-delimited tabular data representing the longitudinal spatial patterns of surface water temperature in the surveyed streams in the Santiam River Basin, Oregon. The aerial surveys were contracted through Watershed Sciences, LLC by...
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
Ensemble methods for history matching and uncertainty quantification with a watershed model Ensemble methods for history matching and uncertainty quantification with a watershed model
History matching of large hydrologic models is challenging due to data sparsity and non-unique process combinations (and associated parameters) that can produce similar model predictions. We develop an ensemble-based history matching (and uncertainty quantification) approach using an iterative ensemble smoother (iES) method for three cutouts of the National Hydrologic Model (NHM) and...
Authors
Michael N. Fienen, Andrew J. Long, Katherine H. Markovich, Adel E. Haj, Matthew Irwin Barker
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 L. Jaeger, Sherri L Johnson, Steven M. Wondzell, Jason B. Dunham, Matthew Irwin Barker, Emily Dawn 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.
Airborne Thermal Infrared and True-color Imagery and Longitudinal Profiles of Stream Temperatures, McKenzie River Basin, Oregon, September 1999 Airborne Thermal Infrared and True-color Imagery and Longitudinal Profiles of Stream Temperatures, McKenzie River Basin, Oregon, September 1999
This dataset includes high-resolution thermal infrared (TIR) and true-color images collected from crewed aircraft and a point shapefile and corresponding comma-delimited tabular data representing the longitudinal spatial patterns of water surface temperature in the surveyed streams in the McKenzie River basin, Oregon. The USDA Forest Service, McKenzie River Ranger District contracted...
Airborne Thermal Infrared and True-color Imagery and Longitudinal Profiles of Stream Temperatures, Santiam River Basin, Oregon, August 2000 Airborne Thermal Infrared and True-color Imagery and Longitudinal Profiles of Stream Temperatures, Santiam River Basin, Oregon, August 2000
This dataset includes high-resolution thermal infrared (TIR) and true-color images collected from crewed aircraft and a point shapefile and corresponding comma-delimited tabular data representing the longitudinal spatial patterns of surface water temperature in the surveyed streams in the Santiam River Basin, Oregon. The aerial surveys were contracted through Watershed Sciences, LLC by...
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...