High-tech “decision support systems” (DSS) could in the future help government agencies and emergency responders — such as those currently dealing with the aftermath of Hurricane Sandy in the US — better predict where rivers are most likely to flood.
Such systems could also be used to prevent flooding caused by climate change and other human activities, according to researchers with the European RamWass (for “Risk Assessment Model of the Water-Sediment-Soil”) project.
The RamWass system has so far been tested for the Elbe River in Germany, the Po River in Italy and the Doñana marshes in Spain. It combines satellite, sensor and on-the-ground data with computer simulation and artificial intelligence tools to come up with up-to-the-minute 3D models and maps showing water speeds, flows, elevations, risks and flood times.
“The quasi-real-time approach is also needed, because emergency responders are often dealing with outdated information, especially when river characteristics change during, and because of, the flood,” said Ilan Kelman, a researcher at the Center for International Climate and Environmental Research in Oslo, Norway, which was not involved in the project.
Now being tested in Central America and Argentina, the system’s risk management capabilities could also be extended to future-focused emergency planning.
“In the long term, this kind of research/tools can help governments and funding agencies to test ‘what-if’ failure scenarios for flood protection that could lead to effective mitigation actions to protect people, private property and public infrastructure during the occurrence of extreme events,” said Pablo Tassi, a research engineer with the French power company EDF, which was also not involved in the project.