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Development of Flash Flood Forecasting System for Small and Medium‐Sized Rivers
ABSTRACT Owing to the increased frequency of short‐duration extreme rainfall events caused by climate change, peak flood flows are expected to increase substantially in small and medium‐sized rivers (SMRs) with a short time of concentration for a catchment (Tc). Accurate flood forecasts and corresponding evacuation are effective in reducing the number of casualties caused by flash floods in SMRs. Currently, flood forecasting using observed rainfall in SMRs has a short lead time, which often delays the issuance of evacuation orders by local governments. Moreover, the large number of SMRs necessitates a system that can be widely used by local governments for disaster response tasks, such as issuing evacuation orders. Therefore, we developed a system that can accurately predict when river water levels will reach the Flood Risk Level (FRL). This forecasting approach uses the rainfall–runoff–inundation (RRI) model and the H–Q equation. The parameters in the RRI model were optimized using the Shuffled Complex Evolution algorithm developed at the University of Arizona (SCE‐UA) to reduce the required time and effort. The system uses real‐time water level observation data to sequentially modify the basin state quantities in the RRI model using the particle filter method to improve the water level forecast accuracy. The system was implemented in 200 rivers in Japan with diverse rainfall and geological characteristics and was tested during the flood season. Accuracy verification was conducted when the forecasted water levels were operated within a range of ± 50 cm. The results showed that 75% of the flood events could be forecasted more than 2 h before reaching the FRLs. Furthermore, 89% of the flood events could be predicted with a lead time (LT; time that water levels reach the FRL—time of first forecast) of 2 h or more or a lead time equal to the Tc or more. These findings show that this system has the potential to enhance and strengthen flood warning and evacuation systems.
Development of Flash Flood Forecasting System for Small and Medium‐Sized Rivers
ABSTRACT Owing to the increased frequency of short‐duration extreme rainfall events caused by climate change, peak flood flows are expected to increase substantially in small and medium‐sized rivers (SMRs) with a short time of concentration for a catchment (Tc). Accurate flood forecasts and corresponding evacuation are effective in reducing the number of casualties caused by flash floods in SMRs. Currently, flood forecasting using observed rainfall in SMRs has a short lead time, which often delays the issuance of evacuation orders by local governments. Moreover, the large number of SMRs necessitates a system that can be widely used by local governments for disaster response tasks, such as issuing evacuation orders. Therefore, we developed a system that can accurately predict when river water levels will reach the Flood Risk Level (FRL). This forecasting approach uses the rainfall–runoff–inundation (RRI) model and the H–Q equation. The parameters in the RRI model were optimized using the Shuffled Complex Evolution algorithm developed at the University of Arizona (SCE‐UA) to reduce the required time and effort. The system uses real‐time water level observation data to sequentially modify the basin state quantities in the RRI model using the particle filter method to improve the water level forecast accuracy. The system was implemented in 200 rivers in Japan with diverse rainfall and geological characteristics and was tested during the flood season. Accuracy verification was conducted when the forecasted water levels were operated within a range of ± 50 cm. The results showed that 75% of the flood events could be forecasted more than 2 h before reaching the FRLs. Furthermore, 89% of the flood events could be predicted with a lead time (LT; time that water levels reach the FRL—time of first forecast) of 2 h or more or a lead time equal to the Tc or more. These findings show that this system has the potential to enhance and strengthen flood warning and evacuation systems.
Development of Flash Flood Forecasting System for Small and Medium‐Sized Rivers
Koji Ikeuchi (author) / Daiki Kakinuma (author) / Yosuke Nakamura (author) / Shingo Numata (author) / Takafumi Mochizuki (author) / Keijiro Kubota (author) / Masaki Yasukawa (author) / Toshihiro Nemoto (author) / Toshio Koike (author)
2025
Article (Journal)
Electronic Resource
Unknown
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Development of Flash Flood Forecasting System for Small and Medium‐Sized Rivers
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