AutoRAS - An Automated HEC-RAS based Short-Range Flood Forecast System at Building Level Resolution
Abstract
Accurate high resolution forecasts regarding flood depth and extent are critical for reducing human and infrastructure related losses caused by floods. The National Water Model (NWM) provides hourly discharge forecasts for every reach in the Continental United States (CONUS) with a lead time of 18 hours (short-range forecast). However, converting these discharge values into building or street level flood information across large spatial domains remains a challenge. This study aims to develop an automated building level flood warning system by simulating georeferenced HEC-RAS models with short-range NWM forecast discharges. The framework automatically reads NWM short-range streamflow forecasts for next 18 hours, searches and executes relevant HEC-RAS models, interpolates flood depth time series at Urban Flooding Open Knowledge Network (UFOKN) features and provide raw data outputs to the UFOKN. The flood forecasts are updated every hour as and when the NWM forecasts get updated. The proposed methodology is demonstrated for Indiana but can be deployed for large-scale applications anywhere in CONUS.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2022
- Bibcode:
- 2022AGUFM.H53E..05D