Headwater streams account for more than half of the streams in the United States by length. The substantial occurrence and susceptibility to change of headwater streams makes regular updating of related maps vital to the accuracy of associated analysis and display. Here we present work testing new methods of completely automated remote headwater stream identification using metrics derived from channel Digital Elevation Model (DEM) cross-sections. A jump in standard deviation of curvature (sK) is found to correlate with the presence of stream heads. Field and remotely validated stream and channel initiation points from 4 diverse study areas in North Carolina as well as a simulated surface are used to test the sK findings. The sK value within individual catchments equal to 0.5*Tukey's upper inner fence is found to be a reliable threshold for identifying the upslope extent of channels in varied landscapes.
Citation Information
| Publication Year | 2020 |
|---|---|
| Title | Channel cross-section analysis for automated stream head identification |
| DOI | 10.1016/j.envsoft.2020.104809 |
| Authors | Ethan J. Shavers, Larry Stanislawski |
| Publication Type | Article |
| Publication Subtype | Journal Article |
| Series Title | Environmental Modelling & Software |
| Index ID | 70225726 |
| Record Source | USGS Publications Warehouse |
| USGS Organization | Center for Geospatial Information Science (CEGIS) |
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Ethan Shavers, PhD
CEGIS Section Chief/ Supervisory Geographer
Larry Stanislawski
Research Cartographer
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Ethan Shavers, PhD
CEGIS Section Chief/ Supervisory GeographerEmailPhoneLarry Stanislawski
Research CartographerEmailPhone