BIL: Integrating Social and Meteorological Data to Assess the Dynamics of Flood Hazards and Impacts: An Interdisciplinary Approach to Leveraging AI, Risk Communication, and Data Sciences

Details

• Personal Author:
  Amy McGovern ; Ann Bostrom ; Julie Demuth ; David John Gagne ; Gabrielle Wong-Parodi ; John Williams
• Corporate Authors:
  AI2ES/University of Oklahoma ; University of Washington ; National Center for Atmospheric Research ; Stanford University ; The Weather Company/IBM
• NOAA Program & Office:
  OAR (Oceanic and Atmospheric Research) ; WPO (Weather Program Office)
• Description:
  This project aims to provide insights into how physical and social science data can be integrated to better understand risk perceptions, response, and impacts to inland flooding hazards. Additionally, this project aims to expand their previously developed longitudinal survey methodology to collect real-time data on people's risk perceptions, response, and impacts to inland flooding events.
• Content Notes:
  Award amount: $1,034,942
• DOI:
  https://doi.org/10.25923/na23oar4050503i
• ISSN:
  0000 0005 0384 6885
• Identifier:
  https://doi.org/10.13039/100018606
• Format:
  htm
• Publisher:
  National Oceanic and Atmospheric Administration ; OAR (Oceanic and Atmospheric Research) ; WPO (Weather Program Office)
• Document Type:
  Grant
• Funding:
  Grant no. NA23OAR4050503I
• Is Part Of:
  Cooperative Agreement ; Bipartisan Infrastructure Law (BIL)
• Type:
  Noncompetitive RFA
• File Type:
  [HTML]
• Collection(s):
  Office of Oceanic and Atmospheric Research (OAR)
• Main Document Checksum:
  urn:sha-512:cf83e1357eefb8bdf1542850d66d8007d620e4050b5715dc83f4a921d36ce9ce47d0d13c5d85f2b0ff8318d2877eec2f63b931bd47417a81a538327af927da3e