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|Created:||Jan 02, 2018 at 9:47 p.m.|
|Last updated:|| Mar 01, 2018 at 10:13 p.m.
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|Content types:||Single File Content|
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Script and accompanying ipython notebook written in Python 2.7 for aggregating sub-daily environmental data (rainfall, tide, wind, groundwater) to a daily timescale. The input data are from Norfolk, Virginia. Several different methods of aggregation are used including averages and maximums. The processed/aggregated data are combined with street flood report data to be used in data-driven, predictive modeling. The script in this resource was used in the analysis described in this Journal of Hydrology paper: https://doi.org/10.1016/j.jhydrol.2018.01.044.
|The content of this resource references||https://doi.org/10.1016/j.jhydrol.2018.01.044|
|Title||Owners||Sharing Status||My Permission|
|Data-driven street flood severity modeling in Norfolk, Virginia USA 2010-2016||Jeff Sadler · Jonathan Goodall||Public & Shareable||Open Access|
This resource was created using funding from the following sources:
|Agency Name||Award Title||Award Number|
|Mid-Atlantic Transportation Sustainability Center|
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This resource is shared under the Creative Commons Attribution CC BY.http://creativecommons.org/licenses/by/4.0/