Floods are among the most deadly and costly disasters worldwide and are only increasing in severity due to climate change. To make matters worse, a large percentage of the world’s population lack the tools needed to detect and respond to floods, leaving them vulnerable to the full force of flood impacts. To help protect these communities, NASA’s Earth Applied Sciences Disasters program area has partnered with several leading scientific institutions to release a significant breakthrough in flood prediction technology to help save lives and aid early response to rising flood impacts worldwide.
“This new technology covers the face of the globe, enabling us to observe flood risk and anticipate the likelihood of floods in ways never before possible,” said Dr. Shanna N. McClain, Disasters Program Manager for NASA’s Earth Science Applied Sciences Program. “The technology we have developed will be transformative, enabling early action by communities around the globe—especially small island communities and developing states that lack the necessary early warning information to protect themselves and their loved ones during flood events.”
This “Model of Models” (MoM) tool combines data from open-source hydrological models with Earth observing satellite data to generate global flood risk severity updates several times per day. This is the first time that comprehensive global flood early warnings have been available at the sub-watershed level.
“The ‘Model of Models’ approach makes use of already existing technologies and combines them in unique ways that give us a powerful understanding of flood risk,” said NASA’s Margaret Glasscoe, Research Associate at the University of Alabama in Huntsville, who leads the project team.
Early warning to protect the vulnerable
Roughly half of the world’s countries lack adequate hazard early warning systems, according to a recent study by the United Nations Office for Disaster Risk Reduction (UNDRR) and the World Meteorological Organization (WMO). “
Until now, comprehensive global flood early warnings have not been possible. Either due to limitations in hydrologic monitoring networks, forecast models, or expertise to operate and widely disseminate their results, especially in small and vulnerable countries. MoM will be a game changer,” said Chris Chiesa, Deputy Executive Director of Pacific Disaster Center, a key partner in the project.
For the new technology to be put into use, it must reach the hands of local populations and decision-makers who need it most—that is where the Pacific Disaster Center (PDC) comes in. PDC is a University of Hawai’i applied science and research center specializing in disaster risk reduction science and technology that supports organizations worldwide in creating a safer world.
Pakistan Red Crescent Society provides aid to communities following catastrophic flooding in 2022 which caused more than 1,700 deaths and displaced more than 7.9 million people.
“Effective early warning information is proven to save lives. Flood early warning has so far been expensive and requiring hyper local investment, knowledge and maintenance. I am looking forward to helping PDC and NASA make this powerful tool available to all communities to complement the efforts of national disaster management organizations and meteorological agencies to help early warnings reach the last mile,” said Omar Abou-Samra, Director of the International Federation of Red Cross and Red Crescent Societies (IFRC)’s Global Disaster Preparedness Center. The IFRC currently integrates all of PDC’s DisasterAWARE early warning and risk information into its Go Platform which provides its 192 national societies and more than 15 million volunteers with critical emergency needs information and the tools they need to provide adequate response.
NASA’s Dr. McClain congratulated the entire Disasters flood team—acollective of cross-sectoral experts who dedicated the past three years to developing an algorithm to reduce the impact of global floods under the NASA ROSES A.37 project “Advancing Access to Global Flood Modeling and Alerting using the PDC DisasterAWARE® Platform and Remote Sensing Technologies”. Development continued under the Global Initiative for Flood Forecasting and Alerting (GIFFT) project, which enhanced MoM by incorporating features such as triggers for synthetic aperture radar (SAR) analysis, and exposure analysis through ImageCat’s Global Economic Dsruption Index (GEDI).
NASA partnered with PDC to integrate MoM into their global multi-hazard alerting platform DisasterAWARE. When MoM detects a high likelihood of flooding in a region, DisasterAWARE sends a flood early warning notification to impacted communities, letting them quickly take the steps necessary to save lives and livelihoods. Local authorities may use this information to activate emergency response plans, order evacuations, or deploy response teams and humanitarian relief. PDC was recently recognized in 2022 by the United Nations for its efforts to build resilience through a multi-hazard approach—receiving the 2022 U.N. Sasakawa Award for Disaster Risk Reduction.
“Our decades-long track record of innovating technologies for multi-hazard early warning, risk analysis, and impact estimation makes PDC an optimal partner for receiving NASA’s new daily global flood model updates,” said PDC’s Executive Director Ray Shirkhodai.
PDC’s DisasterAWARE platform serves tens of thousands of disaster management and humanitarian assistance professionals worldwide and reaches millions more through PDC’s free public app Disaster Alert. The business community is also able to access this new flood hazard information for supply chain and continuity of operations planning through DisasterAWARE Enterprise. Through MoM and DisasterAWARE, community leaders and disaster response teams can accurately gauge flood severity through various data layers that include multi-hazard risk, exposure, vulnerability, coping capacity and national profile assessments.
Sources:
Pacific Disaster Center
https://www.pdc.org/nasa-pdc-new-global-flood-early-warning-technology/ .
Provided by the IKCEST Disaster Risk Reduction Knowledge Service System
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