Hi, I'm an error. x

Combining artificial and human intelligence to improve mountain flood prediction: Code


Authors:
Owners:
Resource type: Composite Resource
Storage: The size of this resource is 13.2 MB
Created: Jan 09, 2018 at 8:46 p.m.
Last updated: May 14, 2018 at 12:04 a.m.
Citation: See how to cite this resource
Sharing Status: Public
Views: 361
Downloads: 27
+1 Votes: Be the first one to  +1 this.  (You need to be logged in to rate this.)
Comments: No comments (yet)

Abstract

Testing ogh and pyDHSVM for the Sauk Watershed.

Subject Keywords

  • No subject keywords have been added.
  • ${ k }

Duplicate. Keyword not added.

Error: ${ error }
Deleting all keywords will set the resource sharing status to private.

Content

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 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/
CC-BY

Comments

There are currently no comments

New Comment

required