Combining artificial and human intelligence to improve mountain flood prediction: Code
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| Resource type: | Composite Resource | |
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| Created: | Jan 09, 2018 at 8:46 p.m. | |
| Last updated: | May 14, 2018 at 12:04 a.m.
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| Citation: | See how to cite this resource |
| Sharing Status: | Public |
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Abstract
Testing ogh and pyDHSVM for the Sauk Watershed.
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Credits
Funding Agencies
This resource was created using funding from the following sources:
| Agency Name | Award Title | Award Number |
|---|---|---|
| University of Washington eScience Institute | Winter Incubator 2018 | |
| National Science Foundation | PREEVENTS TRACK 2: Integrated Modeling of Hydro-Geomorphic Hazards: Floods, Landslides and Sediment | 1663859 |
| Sauk Suiattle Indian Tribe | ||
| Bureau of Indian Affairs |
Contributors
People or Organizations that contributed technically, materially, financially, or provided general support for the creation of the resource's content but are not considered authors.
| Name | Organization | Address | Phone | Author Identifiers |
|---|---|---|---|---|
| Amanda Lehr | University of Washington |
How to Cite
| Shivraj, P., C. Bandaragoda (2018). Combining artificial and human intelligence to improve mountain flood prediction: Code, HydroShare, http://www.hydroshare.org/resource/7c3416535ab24d4f93b0b94741bb9572 |
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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