Abstract
Early warnings decision support systems are recognized as effective soft adaptation tools to prepare for the impacts of imminent flooding and minimize potential injuries and/or loss of life in flood-prone regions. This paper presents a case study of a pilot project that aimed to establish an impacts-based flood monitoring, early warnings, and decision support system for the Vaisigano River which flows through Apia, the capital of Samoa. This river is located in a characteristic short and steep catchment with rapid critical flood peak durations following periods of intense rainfall. The developed system integrates numerical weather prediction rainfall forecasts, real-time rainfall, river level and flow monitoring data, precomputed rainfall-runoff simulations, and flood inundation estimates of exposure levels and threat to human safety at buildings and on roads for different return period events. Information is ingested into a centralized real-time, web-based, flood decision support system portal that enables hydrometeorological officers to monitor, forecast and alert relevant emergency or humanitarian responders of imminent flooding with adequate lead time. This includes nowcasts and forecasts of estimated flood peak time, magnitude and likely impacts of inundation. The occurrence of three distinct extreme rainfall and flood events over the 2020/2021 tropical cyclone season provided a means to operationally test the system. In each case, the system proved adequate in alerting duty officers of imminent flooding in the Vaisigano catchment with up to 24 h warnings and response lead time. Gaps for improvement of system capabilities and performance are discussed, with recommendations for future work suggested.
Highlights
Flood-related events have been the most frequent natural hazard disaster type between 2000–2019, incurring the largest average annualized losses at a global scale compared with any other natural hazard [1,2,3,4]
We present a case study of a pilot impacts-based flood early warning decision support system developed for the Vaisigano River which flows through the Samoan capital of Apia
This paper aimed to describe a pilot flood decision support system (FDSS) for the Vaisigano River, Samoa, which is comprised of a suite of integrated rainfall/river observations and forecast tools that are linked with precomputed hazard exposure scenarios to enable real-time flood-impacts warnings forecasting for the Vaisigano catchment
Summary
Flood-related events have been the most frequent natural hazard disaster type between 2000–2019, incurring the largest average annualized losses at a global scale compared with any other natural hazard [1,2,3,4]. Soft adaptation approaches such as early warnings systems are considered effective tools that enhance the safety and resilience of people to the impacts of flood events (e.g., [5,6,7,8]). While much progress has been made in weather forecasting over the last few decades [12], challenges remain in forecasting flash floods which are influenced by a combination of geomorphic, hydrological, soil moisture capacity and antecedent trigger conditions [14,15,16]
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