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7a.005.UL_UVA - A Cyberinfrastructure System for Real-Time Flood Forecasting in Low-Relief Coastal Plain Basins

Project - Summary

In this project we developed a data and modeling-driven cyberinfrastructure for real-time flood forecasting in support of community resilience. Our project resulted in scalable and transformative methodologies that can be adopted for other regions beyond our study areas which include coastal Virginia and Louisiana. The project took advantage of recent advances in numerical modeling, hydroinformatics, cloud computing, and web-based visualization to translate real-time data and complex model simulations into useful information that can be directly used by public, local municipalities and emergency operation.

Project - Team

Team Member Role Email Phone Number Academic Site/IAB
Emad Habib PI (337) 482-6513 UL Lafayette
Khalid Elgazzar Co-PI Not available UL Lafayette
Mohamed Elsaadani Researcher Not available (337) 789-9828 UL Lafayette
Jon Goodall Co-PI (434) 243-5019 University of Virginia
Peter Beling Researcher (434) 982-2066 University of Virginia
Yawen Shen Researcher/Student Not available University of Virginia
Brian Miles Project Mentor Not available Not available CGI

Project - Novelty of Approach

  1. Development and application of data analytics and visualization techniques in a “real-time” mode taking advantage of model simulations and data feeds from a variety of sources including real time sensors.
  2. Application of innovative data analytics methods for processing and mining useful information from large-size datasets produced by the flood models
  3. Producing general methods tested in two geographic regions but applicable more broadly beyond these two regions

Project - Deliverables

1 Algorithms and workflows for coupling multi-resolution models to run in real-time on a scalable HPC infrastructure with elastic resource provisioning.
2 Algorithms for producing location-specific analytics based on smart sensors and model forecasts.
3 Innovative web-based visualization tools with a design relational database for storing, handling, and displaying real-time data streams from various complex forecast models.

Project - Benefits to IAB

The outcome of this project allows for the dissemination of critical information which can have a significant impact on the safety of the residents at the impacted basins. The use of complex physically based hydrologic and hydrodynamic models produces relatively more accurate results compared to the currently used forecasting systems. This project can also with developing decision support techniques and tools which eventually will help decision makers interpret large amounts of information from various sources.

Project - Presentation Video

Project - Documents

projects/year7/7a.005.ul_uva.txt · Last modified: 2021/06/02 14:32 by sally.johnson