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This resource does not have an owner who is an active HydroShare user. Contact CUAHSI (help@cuahsi.org) for information on this resource. |
| Type: | Resource | |
| Storage: | The size of this resource is 295.9 MB | |
| Created: | Oct 14, 2025 at 7:06 p.m. (UTC) | |
| Last updated: | Aug 17, 2026 at 6:39 p.m. (UTC) (Metadata update) | |
| Published date: | Aug 17, 2026 at 6:39 p.m. (UTC) | |
| DOI: | 10.4211/hs.4ba6663de66a42be81422d39ae349b66 | |
| Citation: | See how to cite this resource | |
| Content types: | CSV Content |
| Sharing Status: | Published |
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| Views: | 1049 |
| Downloads: | 107 |
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Abstract
This resource contains data and code for Seybold et al. (2026, Geophysical Research Letters).
Data:
This dataset includes the HUC12 IDs of 82,312 HUC12s across the contiguous United States and an assigned "headwater type"/cluster ID derived from k-means clustering of this publicly available USGS dataset: https://www.sciencebase.gov/catalog/item/67fffc34d4be020983ea0055.
Code:
Step 1 is the geospatial analysis and extraction of watershed attributes for 82,213 headwater watersheds across the continental United States. This information can also be found in the following USGS data release: https://www.usgs.gov/data/headwater-and-downstream-attributes-select-huc12-units-across-conterminous-united-states-conus
Step 2 takes the extracted data from Step 1 and performs a k-means clustering of headwater watershed attributes. The final results of this clustering (linking HUC12 IDs and cluster assignments) is published as a standalone HydroShare resource and can be found here: Seybold, E. (2025). Headwater HUC12 IDs and associated Clusters, HydroShare, http://www.hydroshare.org/resource/4ba6663de66a42be81422d39ae349b66.
Step 3 takes the transformed headwater and downstream attributes generated in Step 1 (and used in Step 2) to train a random forest classification model that predicts headwater vs. downstream class membership.
Subject Keywords
Coverage
Spatial
Content
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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