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29 October 2012

Flood water in silico

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Scientists are now using high-tech solutions to provide real-time forecast of the dangers of river floods caused by climate change and human activities to help avoid disasters

Not all countries are equal in the face of floods. To provide support for the variety of scenarios encountered, the RAMWASS research project developed a tool for gauging and managing the dangers of floods in specific river zones. The system can also be used for preventing floods caused by climate change and human activities. It was tested for the Elbe river, Germany, the Po river in Italy and the Donana marshes in Spain. But it could be applied anywhere in the world.
To simulate and predict floods this so-called decision support system (DSS) relies on environmental data from satellites, sensors and information from the ground, computer simulation and artificial intelligence tools. “The outputs from the DSS are 3-D models of results and hydraulic maps with water speeds, flows and elevations and risk maps and flood times,” Javier Piazzese tells youris.com. He coordinated the project while at CIMNE (Centre Internacional de Mètodes Numèrics en Enginyeria), a research organisation in Barcelona, Spain.

“The results are shown using a geographical information system developed by CIMNE and available online.” Piazzese adds. Its up-to-the-minute specificity is attractive  “The quasi-real-time approach is also needed, because emergency responders are often dealing with outdated information, especially when river characteristics change during, and because of, the flood,”  comments Ilan Kelman, researcher at the Center for International Climate and Environmental Research in Oslo, Norway, who was not involved in the project.

This approach also presents the advantage of providing low cost flood risk management. “The use of numerical modelling tools can help governments and funding agencies to quantify, delimit and manage flood risk areas with a relatively low-cost,” youris.com heard from research engineer Pablo Tassi at Paris-based power company EDF (Eléctricité de France), who is not connected to the project.

This risk management can be extended to the future. “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.”

This tool could make a difference through advance planning.  It is being tested in Central America and in Argentina. There, it could benefit the Santa Fe region and other northern urban and rural areas prone to flooding. With such tools, “the impact of the catastrophic flood [that affected Santa Fe in April 2003] could have been identified much earlier, perhaps days, and potential areas evacuated to reduce flood losses and deaths,” says Piazzese, now manager of the Argentina-based Fundación CIMNE Latinoamérica (FCL), which is piloting the system in the country.

Yet, for Kelman the social component to floods is not to be underestimated for such tools to be effective. “The difference between the developing and developed locations is not so much in the usefulness of the technology, but in the social contexts.” He notes that the keys to reducing flood risk and flood vulnerability are very much in advanced planning and risk assessment, which need technology but are mainly social processes: “Advanced planning is needed for reducing vulnerability, to ensure that a flood does not become a flood disaster. Risk assessment must identify not only the expected flood characteristics (the hazard), but also the ongoing vulnerabilities that lead to the disaster.”

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