Currently, Korea is undergoing significant local extreme rainfall, which contributes to more than 80% of flood disasters. Additionally, there is an increasing occurrence of such extreme rainfall in small stream basins, accounting for over 60% of flood disasters. Consequently, it becomes imperative to forecast runoff and water levels in advance to effectively mitigate flood disasters in small streams. The Flood Early Warning Framework (FEWF) presents one solution to reduce flood disasters by enabling the forecast of discharge and water levels during flood events. However, the application of FEWF in existing research is challenging due to the short flood travel time characteristic of small streams. This research proposes a methodology for constructing FEWF tailored to small streams using the nomograph and rating curve method. To evaluate the effectiveness of FEWF, a 6-year dataset from the Closed-circuit television-based Automatic Discharge Measurement Technique (CADMT) was utilized. The results indicate that FEWF successfully forecasts discharge and depth during flood events. By leveraging CADMT technology and real-time data, the development of precise and dependable FEWFs becomes possible. This advancement holds the potential to mitigate the consequences of extreme rainfall events and minimize flood-related casualties in small stream basins.

This study developed a disaster assessment system, which integrated flood inundation, risk analysis system, and a decision support system. The parameter representation of the model was selected through sensitivity analysis, used for automated parameter optimization of the model. The Bocheong watershed in South Korea was selected for this study. The results of the simulation were used for disaster assessments; estimated results were calculated basing from flood damages from historical flood disasters, GIS, population, and inundation results. Lastly, this study developed a user-support system to provide real-time meteorological and hydrological data to local government and disaster situation room in South Korea. From the results of the evaluation, the developed model in this study was proven to be more excellent than ModClark model. The application of this model was found superior for ungaged basin such as mountainous area and small creek basins.

Small streams have flood effects on both national and local streams located further downstream. Moreover, damages are increasing in these basins, making the development of adaptive prevention and response measures an urgent necessity. However, the challenge is that small streams remain non-measuring sites. Furthermore, there are about 22,800 small streams, which are too many for the local governments to measure during the flood season. Thus, in this study, a CCTV-based automatic discharge measurement technology was developed to support local governments in monitoring, and minimize the labor required. To evaluate the new technology, discharges were measured in Jungsunfil-chun of Ulju-gun, which is a test bed operated by the National Disaster Management Institute, and compared with the Aquatic Doppler Velocimetry (ADV) based discharges and the weir discharges. The results show that measurements using the new technology are in good agreement with the ADV based discharges. Furthermore, the new technology has the advantage of being able to capture peak flood discharges with short measurement times. Moreover, it is a sustainable measurement method to support flood control by verification of stream flow and situational influences, and provides stable measurements by using a non-contact measurement method. It is expected that the new technology may be used to increase the number of monitoring sites, and the hydraulic data sets collected from various small stream test beds can be used to enhance the design code for estimating flood discharges and the small stream flood warning system to reduce damage in small streams.

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.

Currently, Korea is experiencing localized extreme rainfall, which accounts for more than 80% of flood-related disasters, and is increasing in small river basins, where more than 60% of flood-related casualties occur. These events are caused by climate change and geological factors and their impact is becoming more severe. As a result, an effective measurement system is required to mitigate their impact, particularly in small stream basins that are especially vulnerable due to their steep slopes, small catchment areas, and lack of maintenance and management capacity. In addition, a Flood Early Warning Framework (FEWF) that forecasts discharge and depth during flood events is crucial for reducing casualties. Therefore, this research is focused on developing the FEWF using the nomograph and rating curve methods, which are established by the robust constrained nonlinear equation solver and are suitable for small streams. The FEWF is evaluated using real-time data observed over 7-years period from the Closed-circuit Television-based Automatic Discharge Measurement Technology (CADMT), and the results show that the FEWF is effective in forecasting discharge and depth during flood events. The use of CADMT technology for real-time data can develop an accurate and reliable FEWF, which can help mitigate the impacts of extreme rainfall events and reduce the number of flood-related casualties in small stream basins.

The Ministry of the Interior and Safety has developed a small stream flood warning system to reduce damages to small streams, which are estimated to be about 43% of total streams damages. This system, which was developed using a numerically-based nomograph to estimate discharge and depth, was based on rainfall estimates obtained by the McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation (MAPLE) because the small streams exist in unmeasured basins. Before implementing the small stream flood warning system, a study was performed to test its accuracy in estimating measured data obtained from a test basin during 2016 and 2017. Because the results of that study showed that the discharges and depths underestimated the measured data, this study was performed to establish a new nomograph using measured depth and discharge data in the test basin for two rainfall events in 2016. The evaluation results show that the new nomograph correctly represents the measured depth and discharge, and it can be used for enhancing the small stream flood warning system.