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As the frequency of local extreme rainfall increases due to climate change, frequent flood damage is occurring in small stream watersheds. Casualties in these small-streams can only be significantly reduced through non-structural measures, such as the development of flood early warning systems. Howeve owever, the development and evaluation of flood early warning systems have been limited due to a lack of measurement data in small streams. Recently, the National Disaster Management Institute operated five test beds for small streams across the country. A dditionally, the Ministry of Interior and Safety, along with local governments, established a smart measurement and management system for approximately 10% of all small streams, totaling 2,200, by 2027, making it possible to secure measurement data in small streams. Considering onsidering the flow characteristics of small streams, an optimization system is developed using the rainfall-discharge nomograph and rating curve rather than a numerical-based method that requires considerable calculation time. To evaluate the developed system, the discharge and depth data measured at the time of a flood accident on August 16, 2021, are compared on a one-to-one basis with the prediction results. The prediction results show that the measured discharge and depth distribution of the five small streams over time were accurately reproduced. Based on these results, the developed rainfall-discharge nomograph and rating curve are expected to serve as effective tools to support flood early warning systems.
Cheong et al. (Wed,) studied this question.