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.

Surface Image Velocimetry (SIV) is a recently-developed discharge measurement instrument. It uses image processing techniques to measure the water surface velocity and estimate water discharge with given cross section. The present study aims to implement a FSIV (Fixed-type Surface Image Velocimetry) at Soojeon Bridge in the Dalcheon. The hardware system consists of two digital cameras, a computer, and a pressure-type water stage gauge. The images taken with the hardware system are sent to a server computer via a wireless internet, and analyzed with a image processing software (SIV software). The estimated discharges were compared with the observed discharges through Goesan dam spillway and index velocity method using ADVM. The computed results showed a good agreement with the observed one, except for the night time. The results compared with discharges through Goesan dam spillway reached around 5∼10% in the case of discharge over 30 m 3 /s, and the results compared with discharges through index velocity method using ADVM reached around 5% in the case of discharge over 200 m 3 /s. Considering the low cost of the system and the visual inspection of the site situation with the images, the SIV would be fairly good way to measure water discharge in real time.

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