An Operational Flash Flood Early Warning System for the Kingdom of SaudiArabia

Extreme rainfall events can trigger flash floods that pose serious risks to communities, infrastructure, and critical services, particularly in arid and rapidly urbanizing environments. In the Kingdom of Saudi Arabia, short hydrological response times, strong spatial variability of precipitation, complex topography, and limited observational data significantly challenge flood early warning capabilities, which affect emergency management at the national scale. Addressing these challenges requires integrated and scalable hydro-meteorological forecasting systems capable of operating across large spatial domains while resolving convective weather events and associated localized flood impacts in urban/suburban areas.
This study presents a nationwide, operational flash flood early warning system developed for the Kingdom of Saudi Arabia. The system is designed to provide consistent coverage across the country while capturing fine-scale weather, hydrological and hydrodynamic processes relevant to flash flooding in arid environments. It operates over 137 hydrological domains, representing more than 6,000 outlets, delivering 2D flood simulations at a spatial resolution of 30 m nationwide, with enhanced resolution of up to 2.5 m in selected urban areas.
The forecasting framework is structured as an end-to-end modeling chain that links atmospheric forcing, hydrological response, hydraulic flood propagation, and infrastructure impacts. High-resolution numerical weather predictions generated by the Weather Research and Forecasting (WRF) model are combined with real-time radar and rain gauge observations to produce hourly ensemble weather and precipitation forecasts and hindcasts. These meteorological inputs drive a distributed hydrological model (CREST), which simulates runoff generation across arid catchments using spatially explicit information on topography, land cover, soil properties, and drainage networks. A reservoir management module is fully integrated within the modeling chain, allowing the system to account for reservoir storage dynamics, controlled releases, and spillway operations, and to assess the influence of dam infrastructure on downstream flood evolution.
Hydrological outputs are used as boundary conditions to a two-dimensional hydrodynamic model, which simulates floodplain dynamics, water depths, and inundation extents.
All model components are coupled within a WebGIS-based operational platform that displays deterministic and ensemble weather and hydrologic forecasts, probabilistic flood warnings, and real-time nowcasting products. Flood hazard information is delivered through interactive maps, warning levels, and time series, to support decision- making by civil protection authorities and emergency managers at national and local scales.
The functionality and operational performance of the system are demonstrated through its application on a recent extreme rainfall and flash flood events that affected the entire region of Saudi Arabia in the period of December 9-16, 2025. The system successfully captured the timing, spatial extent, and severity of flooding across multiple domains, providing useful lead times and high-resolution inundation maps. This case study highlights the robustness, scalability, and operational value of the framework, demonstrating its potential to enhance flood preparedness through early warning, and risk management across the Kingdom of Saudi Arabia under increasing hydro- meteorological extremes.