Gridded flood depth estimates from satellite-derived inundations

Bryant, Seth; McGrath, Heather; Boudreault, Mathieu

doi:https://doi.org/10.5194/nhess-22-1437-2022

Articles | Volume 22, issue 4

https://doi.org/10.5194/nhess-22-1437-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/nhess-22-1437-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 22, issue 4

Research article

|

21 Apr 2022

Research article |

| 21 Apr 2022

Gridded flood depth estimates from satellite-derived inundations

Seth Bryant, Heather McGrath, and Mathieu Boudreault

Supplement

https://doi.org/10.5194/nhess-22-1437-2022-supplement

Data sets

Flood Risk Areas and Historical Floods GeoNB http://www.snb.ca/geonb1/e/DC/floodraahf.asp

National Hydro Network Data Production Catalogue Government of Canada https://ftp.maps.canada.ca/pub/nrcan_rncan/vector/geobase_nhn_rhn/doc/GeoBase_nhn_en_Catalogue_1_2.pdf

Floods in Canada -- Archive Natural Resources Canada https://open.canada.ca/data/en/dataset/74144824-206e-4cea-9fb9-72925a128189

High Resolution Digital Elevation Model Mosaic (HRDEM Mosaic) Natural Resources Canada https://open.canada.ca/data/en/dataset/0fe65119-e96e-4a57-8bfe-9d9245fba06b

Model code and software

cefect/RICorDE_pub S. Bryant https://github.com/cefect/RICorDE_pub

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Short summary

The advent of new satellite technologies improves our ability to study floods. While the depth of water at flooded buildings is generally the most important variable for flood researchers, extracting this accurately from satellite data is challenging. The software tool presented here accomplishes this, and tests show the tool is more accurate than competing tools. This achievement unlocks more detailed studies of past floods and improves our ability to plan for and mitigate disasters.