Articles | Volume 22, issue 4
Nat. Hazards Earth Syst. Sci., 22, 1371–1393, 2022
https://doi.org/10.5194/nhess-22-1371-2022
Nat. Hazards Earth Syst. Sci., 22, 1371–1393, 2022
https://doi.org/10.5194/nhess-22-1371-2022
Research article
19 Apr 2022
Research article | 19 Apr 2022

A performance-based approach to quantify atmospheric river flood risk

Corinne Bowers et al.

Data sets

The National Map (TNM) Download v2.0 USGS https://apps.nationalmap.gov/downloader/

National Flood Hazard Layer FEMA https://www.fema.gov/flood-maps/national-flood-hazard-layer

Russian River - 32' to 52' Flood Stages - Map County of Sonoma https://sonomacounty.maps.arcgis.com/home/item.html?id=9d8d63558c6b4124b000e6476a0a020d

Buildings County of Sonoma https://sonomacounty.maps.arcgis.com/home/item.html?id=0f5982c3582d4de0b811e68d7f0bff8f

Parcels Public Shapefile County of Sonoma https://sonomacounty.maps.arcgis.com/home/item.html?id=2202c1cd6708441f987ca5552f2d9659

Rapid Evaluation Safety Assessment (RESA) Map: 2019 Winter Storms and Flooding County of Sonoma https://permitsonoma.org/divisions/engineeringandconstruction/building/resa2019flooding

OpenFEMA Data Sets FEMA https://www.fema.gov/about/openfema/data-sets

Model code and software

Performance-based Atmospheric River Analysis (PARRA) Framework: Supplemental Code Release (v1.0.2) C. Bowers https://doi.org/10.5281/zenodo.6354880

tigris: Load Census TIGER/Line Shapefiles K. Walker https://cran.r-project.org/package=tigris

rnoaa: NOAA Weather Data from R S. Chamberlain https://cran.r-project.org/package=rnoaa

dataRetrieval: R packages for discovering and retrieving water data available from U.S. federal hydrologic web services L. A. De Cicco, D. Lorenz, R. M. Hirsch, W. Watkins, and M. Johnson https://doi.org/10.5066/P9X4L3GE

censusapi: Retrieve Data from the Census APIs H. Recht https://cran.r-project.org/package=censusapi

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Short summary
Atmospheric rivers (ARs) cause significant flooding on the US west coast. We present a new Performance-based Atmospheric River Risk Analysis (PARRA) framework that connects models of atmospheric forcings, hydrologic impacts, and economic consequences to better estimate losses from AR-induced river flooding. We apply the PARRA framework to a case study in Sonoma County, CA, USA, and show that the framework can quantify the potential benefit of flood mitigation actions such as home elevation.
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