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| Type: | Resource | |
| Storage: | The size of this resource is 237.6 KB | |
| Created: | Jan 02, 2018 at 9:33 p.m. (UTC) | |
| Last updated: | Mar 01, 2018 at 10:12 p.m. (UTC) (Metadata update) | |
| Published date: | Mar 01, 2018 at 10:12 p.m. (UTC) | |
| DOI: | 10.4211/hs.5db7884111fb4662a13f64707c0c6890 | |
| Citation: | See how to cite this resource | |
| Content types: | Single File Content |
| Sharing Status: | Published |
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| Views: | 3805 |
| Downloads: | 204 |
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Abstract
Script and accompanying notebook written in Python 2.7 for combining flood report data (output) and environmental data (input) into a format suitable for a data-driven model. These data used as target values for street data-driven flood prediction severity modeling for Norfolk, VA 2010-2016. This modeling is described in this Journal of Hydrology paper: https://doi.org/10.1016/j.jhydrol.2018.01.044.
Subject Keywords
Coverage
Spatial
Temporal
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| The content of this resource references | https://doi.org/10.1016/j.jhydrol.2018.01.044 |
| Title | Owners | Sharing Status | My Permission |
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| Data-driven street flood severity modeling in Norfolk, Virginia USA 2010-2016 | Jeff Sadler · Jonathan Goodall | Public & Shareable | Open Access |
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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