Quantification of continuous flood hazard using random forest classification and flood insurance claims at large spatial scales:  a pilot study in southeast Texas

Mobley, William; Sebastian, Antonia; Blessing, Russell; Highfield, Wesley E.; Stearns, Laura; Brody, Samuel D.

doi:https://doi.org/10.5194/nhess-21-807-2021

Articles | Volume 21, issue 2

https://doi.org/10.5194/nhess-21-807-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/nhess-21-807-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 21, issue 2

Research article

|

01 Mar 2021

Research article |

| 01 Mar 2021

Quantification of continuous flood hazard using random forest classification and flood insurance claims at large spatial scales: a pilot study in southeast Texas

William Mobley, Antonia Sebastian, Russell Blessing, Wesley E. Highfield, Laura Stearns, and Samuel D. Brody

Data sets

Flood Hazard Modeling Output William Mobley, Antonia Sebastian, Russell Blessing, Wesley E. Highfield, Laura Stearns, and Samuel D. Brody https://doi.org/10.18738/T8/FVJFSW

Independent drivers for the flood hazard model Center for Texas Beaches and Shores (CTBS) https://dataverse.tdl.org/dataverse/M3FR

Flood Hazard Modeling Output, V2 William Mobley https://doi.org/10.18738/T8/FVJFSW

Rasterio: geospatial raster I/O for Python programmers Sean Gillies, Adam J. Stewart, Alan D. Snow, et al.: https://github.com/mapbox/rasterio

Short summary

In southeast Texas, flood impacts are exacerbated by increases in impervious surfaces, human inaction, outdated FEMA-defined floodplains and modeling assumptions, and changing environmental conditions. The current flood maps are inadequate indicators of flood risk, especially in urban areas. This study proposes a novel method to model flood hazard and impact in urban areas. Specifically, we used novel flood risk modeling techniques to produce annualized flood hazard maps.