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An Impact-Based Flood Forecasting System for Citizen Empowerment

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Listed:
  • Lagmay, Alfredo Mahar Francisco
  • Bagtasa, Gerry
  • Andal, Dinnah Feye
  • Andal, Fritz Dariel
  • Aldea, Janice
  • Bencito, Dianne Charmaine
  • Liporada, Kenneth
  • Delmendo, Patricia Anne

Abstract

This work addresses the critical issue of flooding, a significant natural hazard, consistently ranked highest in the 2023 World Risk Index. The annual onslaught of tropical cyclones and the associated abnormal rainfall threaten lives, and destroy crops and property, thereby causing great economic damage, demanding urgent and science-based decision-making. We introduce an impact-based flood forecasting system as a proactive anticipatory action (i.e., AA) measure, linking climate services and disaster risk management to mitigate extreme weather impacts. Developed by the University of the Philippines Resilience Institute, the National Operational Assessment of Hazards (NOAH) Center, and Gerry Bagtasa of the Institute of Environmental Science and Meteorology, this system advances disaster resilience efforts, leveraging science-based forecasts to prioritize vulnerable barangays (villages). Unlike traditional early warning systems, the proposed automated system predicts flooding one day in advance and assesses exposure levels based on population distribution. By utilizing global weather forecast models locally calibrated for Philippine conditions and 100-year rain return flood hazard maps for the Philippines, the system forecasts river inundated areas, enabling local government units (LGUs) and humanitarian organizations to prioritize preparations for communities and allocate resources during flooding events effectively. This system enhances the efficiency of disaster response planning, fostering a proactive and impactful strategy to address the recurring threat of flooding in the country. The system also underscores the role of open data in disaster resilience, exemplified by NOAH’s system to disseminating big data, which aligns with open governance principles. By encouraging transparency and stakeholder collaboration, data exchange is promoted, providing actionable information that fosters collaboration between the LGUs, humanitarian organizations, and other stakeholders. Cognizant of the importance of community engagement in disaster resilience, the newly developed impact-based flood forecasting system encourages community involvement by providing easily accessible information, which can be used to validate the forecasts based on local knowledge and experience. This research contributes to the urgent call for anticipatory action in the face of escalating extreme weather events globally.

Suggested Citation

  • Lagmay, Alfredo Mahar Francisco & Bagtasa, Gerry & Andal, Dinnah Feye & Andal, Fritz Dariel & Aldea, Janice & Bencito, Dianne Charmaine & Liporada, Kenneth & Delmendo, Patricia Anne, 2024. "An Impact-Based Flood Forecasting System for Citizen Empowerment," Asian Journal of Agriculture and Development, Southeast Asian Regional Center for Graduate Study and Research in Agriculture (SEARCA), vol. 21(AJAD 20th), October.
  • Handle: RePEc:ags:phajad:348355
    DOI: 10.22004/ag.econ.348355
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    References listed on IDEAS

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    1. Henry He Huang & Joseph Kerstein & Chong Wang & Feng (Harry) Wu, 2022. "Firm climate risk, risk management, and bank loan financing," Strategic Management Journal, Wiley Blackwell, vol. 43(13), pages 2849-2880, December.
    2. Michael K. Lindell & Ronald W. Perry, 2012. "The Protective Action Decision Model: Theoretical Modifications and Additional Evidence," Risk Analysis, John Wiley & Sons, vol. 32(4), pages 616-632, April.
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