Flood early warning system with data assimilation enables site-level forecasting of bridge impacts
Abstract Vehicle-related flood fatalities account for a majority of flooding deaths in the United States. As floods become more frequent and severe, emergency operators need accurate early warning systems to enact road closures and dispatch first responders. We present an operational flood forecasti...
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| Format: | Article |
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Nature Portfolio
2025-07-01
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| Series: | npj Natural Hazards |
| Online Access: | https://doi.org/10.1038/s44304-025-00116-0 |
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| author | Jeil Oh Matthew Bartos |
| author_facet | Jeil Oh Matthew Bartos |
| author_sort | Jeil Oh |
| collection | DOAJ |
| description | Abstract Vehicle-related flood fatalities account for a majority of flooding deaths in the United States. As floods become more frequent and severe, emergency operators need accurate early warning systems to enact road closures and dispatch first responders. We present an operational flood forecasting framework that connects large-scale hydrologic predictions with site-level transportation impacts. This system integrates NOAA’s National Water Model (NWM) with a new data assimilation framework based on Kalman Filtering to generate improved discharge and stage predictions at progressive 12-hour forecast horizons. These discharge and stage forecasts are joined with a large-scale bridge infrastructure database to generate site-level probabilistic flood warnings. Tested across two major river basins in Texas, our data assimilation and forecasting framework outperforms the NWM’s existing nudging method at predicting bridge flooding impacts over all lead times considered. By enabling accurate site-level bridge warnings, the proposed framework will enable more targeted management of transportation systems during floods. |
| format | Article |
| id | doaj-art-7e5f63c8c9174aadacd6dd500d73aa7f |
| institution | Kabale University |
| issn | 2948-2100 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Natural Hazards |
| spelling | doaj-art-7e5f63c8c9174aadacd6dd500d73aa7f2025-08-20T03:42:40ZengNature Portfolionpj Natural Hazards2948-21002025-07-012111310.1038/s44304-025-00116-0Flood early warning system with data assimilation enables site-level forecasting of bridge impactsJeil Oh0Matthew Bartos1Fariborz Maseeh Department of Civil, Architectural and Environmental Engineering, The University of Texas at AustinFariborz Maseeh Department of Civil, Architectural and Environmental Engineering, The University of Texas at AustinAbstract Vehicle-related flood fatalities account for a majority of flooding deaths in the United States. As floods become more frequent and severe, emergency operators need accurate early warning systems to enact road closures and dispatch first responders. We present an operational flood forecasting framework that connects large-scale hydrologic predictions with site-level transportation impacts. This system integrates NOAA’s National Water Model (NWM) with a new data assimilation framework based on Kalman Filtering to generate improved discharge and stage predictions at progressive 12-hour forecast horizons. These discharge and stage forecasts are joined with a large-scale bridge infrastructure database to generate site-level probabilistic flood warnings. Tested across two major river basins in Texas, our data assimilation and forecasting framework outperforms the NWM’s existing nudging method at predicting bridge flooding impacts over all lead times considered. By enabling accurate site-level bridge warnings, the proposed framework will enable more targeted management of transportation systems during floods.https://doi.org/10.1038/s44304-025-00116-0 |
| spellingShingle | Jeil Oh Matthew Bartos Flood early warning system with data assimilation enables site-level forecasting of bridge impacts npj Natural Hazards |
| title | Flood early warning system with data assimilation enables site-level forecasting of bridge impacts |
| title_full | Flood early warning system with data assimilation enables site-level forecasting of bridge impacts |
| title_fullStr | Flood early warning system with data assimilation enables site-level forecasting of bridge impacts |
| title_full_unstemmed | Flood early warning system with data assimilation enables site-level forecasting of bridge impacts |
| title_short | Flood early warning system with data assimilation enables site-level forecasting of bridge impacts |
| title_sort | flood early warning system with data assimilation enables site level forecasting of bridge impacts |
| url | https://doi.org/10.1038/s44304-025-00116-0 |
| work_keys_str_mv | AT jeiloh floodearlywarningsystemwithdataassimilationenablessitelevelforecastingofbridgeimpacts AT matthewbartos floodearlywarningsystemwithdataassimilationenablessitelevelforecastingofbridgeimpacts |