Optimizing Hydrometric Network Design for National Flood Forecasting and Warning Services (NFFWS)

Effective flood forecasting and warning systems depend on robust hydrometric networks tailored to meet the functional, geographical, and operational demands of real-time monitoring. This study outlines the ideal requirements for hydrometric data collection and transmission systems to support the National Flood Forecasting and Warning Service (NFFWS). Key considerations include spatial and temporal coverage, gauge placement in flood-prone areas, and sufficient resolution to align with hydrological models.

Recommendations emphasize the need for durable, reliable infrastructure designed for extreme conditions, adherence to international standards, and regular maintenance protocols. Priority gauges—those critical for public safety, hydrological model calibration, and flood risk management—should be safeguarded, with enhancements in accuracy, redundancy, and telemetry for real-time data transmission. Network resilience is bolstered by backup power, dual communication systems, and fault alerts.

Another critical component for flood forecasting is the sub-daily rainfall network. High-resolution, high-quality rainfall data at sub-daily intervals are essential for capturing short-duration, intense rainfall events that can lead to flash flooding. The design of a sub-daily rainfall network should prioritize strategic placement of gauges in areas with high rainfall variability and known flood risk areas. Real-time data collection and transmission are paramount to ensure timely updates for flood forecasting models. Integration of automated quality control processes can further enhance the reliability of sub-daily rainfall data.

We propose systematic reviews of network performance, integration of historical and real-time data archives, and automated quality control to improve data reliability. Advanced metadata management and API-based data dissemination enhance usability for stakeholders. These standards ensure hydrometric networks remain integral to flood forecasting, minimizing flood risks and improving public safety. The findings provide a blueprint for developing resilient, effective hydrometric networks that address the evolving needs of flood forecasting and warning services.