The Flood Forecasting and Warning Community of Practice is a collaborative space for professionals working on flood forecasting, warning, and early action, aimed at improving flood early warning systems and ensuring that timely, actionable information reaches those at risk.
Flooding is one of the most devastating natural hazards, affecting millions of people and causing significant economic losses each year. To minimize floods' impacts and enhance communities resilience, effective flood forecasting and warning systems are critical.
The World Meteorological Organization (WMO), together with the Global Water Partnership (GWP), officially launched the Community of Practice (CoP) on 13 October 2025. The initiative aims to connect National Meteorological and Hydrological Services (NMHSs), technical professionals, researchers, and disaster-risk practitioners to accelerate the development and uptake of flood forecasting and early warning systems, ultimately saving lives and protecting livelihoods. The CoP serves as a space for sharing best practices, innovative tools, and methodologies for flood forecasting and warning. It also allows members to stay up-to-date with upcoming events and opportunities, as well as to showcase case studies and lessons learned from different regions.
The event counted over 300 participants from 60 countries, reflecting broad global engagement from both operational and academic communities. It underscored WMO's commitment to the Early Warnings for All (EW4All) initiative and introduced two WMO success stories:
- The Water at the Heart of Climate Action (WHCA) and CREWS projects, illustrating how multi-country and basin-wide approaches are improving climate resilience in Africa; and
- Flood Forecasting Framework (FFF), a modular and open-source approach designed to strengthen interoperability, scalability, and sustainability of flood forecasting services worldwide.
Four national case studies demonstrated the real-world urgency of improving early flood warning:
- Pakistan, highlighting operational lessons from recent monsoon floods;
- Niger, showing improved flood management through regional coordination along the Niger River;
- China, emphasizing the role of data automation and capacity development through WMO Regional Training Centres; and
- South Africa, sharing experience in implementing impact-based forecasting and community response.
Discussions explored how countries can integrate flood early warning into multi-hazard systems, use AI and machine learning for data fusion and real-time detection, and strengthen coordination between hydrology, meteorology, and disaster-management agencies.
The event included high-level talks on national and regional flood forecasting with representatives of national meteorological services from a wide range of countries and opened the floor for a direct exchange with the forecasting community. Discussions also focused on how new Members can access regional support and forecasting platforms, as well as WMO's guidance to build capacities against hydrometeorological hazards.
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