Join the Global Flood Partnership Spring Webinar Series! This event will feature three exciting presentations from distinguished experts in the field, focusing on Earth Observation data.

• When: February 12th, 2026, 3:00–4:30 p.m. CET

We have three exciting presentations from experts in the field:

• Haiyan Liu (Southern Marine Science and Enginering Guangdong Laboratory (Zhuhai), China.)

  Title: From flood forecasting to effective early action: evidence from multi-hazard early warning systems

  Abstract: Flood forecasting has advanced rapidly in recent years, yet a key challenge remains: how forecast information can be translated into timely early warnings that trigger effective anticipatory action and, in turn, enhance disaster resilience. We will focus on the forecast–warning–action chain and present empirical evidence on how integrated multi-hazard early warning systems (MHEWS) shape human responses and recovery during extreme events.
  Using location-based human mobility data aggregated from over 1.1 billion mobile devices across Chinese cities, we quantify daily intracity mobility responses to 21,126 early warning signals issued during 19 tropical cyclones between 2021 and 2023. These warnings represent the operational translation of hazard forecasts into public alerts across multiple hazards and administrative levels.
  We find that, compared with single-hazard or single-level warnings, combined multi-level and multi-hazard warnings substantially strengthen anticipatory action. Additional warning types further accelerate post-event recovery. While absolute benefits are larger in coastal and wealthier cities, relative resilience gains are strongest in inland and socioeconomically disadvantaged areas. The findings highlight that advances in flood forecasting must be coupled with coordinated multi-hazard warning strategies to translate predictive skill into locally actionable and equitable resilience outcomes.
  This work has recently been published in Global Environmental Change (https://doi.org/10.1016/j.gloenvcha.2025.103111).

  Bio: Dr. Haiyan Liu is a Senior Researcher at the Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), China, and a Visiting Fellow at WorldPop, University of Southampton. Her research examines how extreme weather events and adaptation measures shape urban resilience, with a focus on evidence-based risk reduction strategies. She combines human mobility data, GeoAI, and causal inference to inform climate adaptation and disaster risk management, and actively engages in interdisciplinary research and policy-relevant review work. 

• Eylon Shamir (Hydrologic Research Center San Diego)

  Title: 20-Years of Global Flash Flood Guidance: Lessons Learned and the Way Forward.

  Abstract: The Flash Flood Guidance System (FFGS) is an operational platform designed to support national meteorological and hydrological services and disaster management agencies in issuing timely, location-specific advance warnings for flash floods. To address the global need for flash-flood early warning, a MoU was established among the WMO, USAID’s Office of Foreign Disaster Assistance, NOAA, and the Hydrologic Research Center (HRC) to implement FFGS worldwide. By the end of 2026, FFGS is expected to be operational in more than 80 countries across 16 regional centers, serving a population of over three billion people.
  Over the past two decades, FFGS has evolved in response to the practical needs of operational forecasters and disaster managers. Its development has encompassed advances in hydrological and meteorological sciences, impact-based forecasting and warning, uncertainty communication, integration of new observational and forecast datasets, and the expansion of system capabilities to address related hazards such as landslides, urban flooding, drought, and water-resources management. This presentation reviews the system’s progression from interdisciplinary research to sustained operational deployment across diverse hydroclimatic and institutional environments, highlighting key lessons learned and outlining a vision for future enhancements to global flash-flood early-warning capabilities.

  Bio: Dr. Eylon Shamir is the Chief Scientist of the Hydrologic Research Center (HRC) and has been a principal scientific and technical leader of the Flash Flood Guidance System (FFGS) program for more than two decades, supporting its implementation in over 80 countries worldwide.

  HRC is a non-profit research corporation based in San Diego, California, with a mission to advance the science and practice of operational hydrology and hydrometeorology through the development and deployment of decision-support and early-warning systems that address real-world water-resources and natural-hazards challenges. HRC has provided the core technical framework, training, and sustained technical support that have enabled FFGS to evolve into a globally recognized early-warning program.

• Jorge Luis Sánchez Lozano / Juseth Chancay (Water Resources Engineer, Aquaveo LLC)

  Title: Global Water Level Forecast System: Integrating EO Data for Hydrological Hazard Monitoring

  Abstract: The Global Water Level Forecast System (GWLFS) is an open-source web platform that integrates Earth Observation data with ensemble hydrological forecasts to support real-time flood risk monitoring worldwide. The system combines satellite-derived water level observations from the Hydroweb project (over 20,000 virtual stations) with GEOGLOWS ECMWF streamflow simulations, applying a Discharge-to-Water Level Transformation (DWLT) method to generate a retrospective water level simulation and a 15-day 52-ensemble water level forecast. Using monthly duration curves, DWLT statistically links simulated discharge to satellite altimetry, enabling the estimation of synthetic water level time series and high-flow thresholds based on Gumbel-distributed return periods. Transformed outputs are visualized through an interactive web application built on the Tethys platform, offering dynamic color-coded warnings, forecast animations, historical comparisons, and performance metrics. The system architecture leverages high-performance tools such as Polars and a microservices backend to enable scalability and rapid processing across more than 25,000 monitoring stations. The validation using the KGE metric demonstrates the model's reliability across diverse hydroclimatic regions.