Work

From Data Streams to Decisions: Multi-Source Hydrometeorological Integration Platforms for Interagency Risk-Management Capacity Building in Data-Limited Regions

Year: 2026

Type: book-chapter

Abstract: Recent advances in global hydrometeorological modelling and remote sensing have strengthened the monitoring and forecasting of extreme events, particularly where meteorological and hydrological observations are limited. In tropical regions such as Ecuador, steep topographic gradients, strong Pacific-Andes-Amazon contrasts, and pronounced interannual climate variability intensify exposure to floods, droughts, and other hydrometeorological hazards, highlighting the urgent need for integrated decision-support systems. In this regard, thanks to the NASA SERVIR-Amazonia initiative, open-source platforms have been developed to integrate hydrometeorological forecasts with satellite information and deliver actionable products across Ecuador, Brazil, Colombia, and Peru. This work presents the implementation of INAMHI GEOGLOWS in Ecuador, an open-source platform tailored to national needs and structured into five applications: Met Data Explorer, Hydroviewer, Historical Validation Tool, National Water Level Forecast, and Hydropower. The platform integrates near-real-time GOES monitoring, the Flash Flood Guidance System (FFGS), satellite-based precipitation products, numerical weather prediction models, and the GEOGLOWS River Forecast System to support operational monitoring, visualization, forecasting, and informed risk decision-making. Operational records confirm the platform’s effectiveness, with approximately 40 validated flood-warning cases across 38 river basins during 2024–2025. The platform has strengthened interinstitutional capacity, enhancing decision support and interagency coordination through a strategic deployment approach, sustained institutional engagement, and capacity-building that enable long-term operationalization. The platform architecture and deployment strategy are designed to be scalable and transferable to other data-limited regions.

Source: IntechOpen eBooks

DOI: 10.5772/intechopen.1015810