본 연구에서는 표면영상유속계의 한계점으로 지적되어 온 야간이나 안개시 적용 문제를 해결하기 위해, 원적외선 카메라를 이용한 표면영상유 속계의 적용성을 검토하였다. 이를 위해 각 조건에 대한 원적외선 카메라의 측정 정확도 평가 실험을 진행하였다. 정확도 평가는 기존에 검증이 된 주간 조건의 일반카메라를 이용한 표면영상유속계 측정 결과에 대한 상대 오차를 산정하여 평가하였다. 결과적으로 원적외선 카메라를 이용한 표면영상유속계의 야간 측정 상대 오차는 최대 4.3%, 평균 1% 내외로 매우 낮게 나타나 정확도가 높음을 확인하였고, 안개 조건 또한 최대 5.2%, 평균 2% 내외로 매우 높은 정확도를 보였다. 이에 따라 일반 카메라로 수면 흐름을 가시화할 수 없던 비가시 환경에서 원적외선 카메라를 이용하는 경우 높은 정확도로 측정이 가능할 것으로 판단된다.

In this study, according to the reference setting based on the runoff video of 9:00 where the highest water level of 3.94 m has been recorded during the runoff of Cheon-mi Stream in Jeju Island by the attack of Typhoon no. 16 Sanba on September 17th, 2012, the error rate of long-distance and short-distance velocimetry and real-distance change rate by input error have been calculated and the input range value of reference point by stream has been suggested. In the reference setting process, if a long-distance reference point input error occurs, the real-distance change rate of 0.35 m in the x-axis direction and 1.35 m in y-axis direction is incurred by the subtle input error of 2~11 pixels, and if a short-distance reference point input error occurs, the real-distance change rate of 0.02 m in the x-axis direction and 0.81 m in y-axis direction is incurred by the subtle input error of 1~11 pixels. According to the long-distance reference point setting variable, the velocity error rate showed the range of fluctuation of at least 14.36% to at most 76.06%, and when calculating flux, it showed a great range of fluctuation of at least 20.48% to at most 78.81%.

This study is daytime and nighttime runoff image data caused by heavy rain on May 27, 2013 at Oedo Water Treatment Plant of Oedo-Stream, Jeju to compute runoff by applying Surface image velocimeter (SIV) and analyzing correlation according to current. At the same time, current was comparatively analyzed using ADCP observation data and fixed electromagnetic surface current meter (Kalesto) observed at the runoff site. As a result of comparison on resolutions of daytime and nighttime runoff images collected, correlation coefficient corresponding to the range of 0.6~0.7 was 6.8% higher for nighttime runoff image compared to daytime runoff image. On the contrary, correlation coefficient corresponding to the range of 0.9~1.0 was 17% lower. This result implies that nighttime runoff image has lower image quality than daytime runoff image. In the process of computing current using SIV, a rational filtering process for correlation coefficient is needed according to images obtained.

This study analyzed the velocimetry of runoff and measured the flood discharge by applying the SIV (Surface Image Velocimetrer) to the daytime and nighttime flow image data with special reference to Seong-eup Bridge at Cheonmi stream of Jeju during the flow by the severe rainstorm on May 27, 2013. A 1000W lighting apparatus with more than 150 lux was installed in order to collect proper nighttime flow image applied to the SIV. Its value was compared and analyzed with the velocity value of the fixed electromagnetic wave surface velocimetry (Kalesto) at the same point to check the accuracy and applicability of the measured velocity of flow. As a result, determination coefficient R2 values were 0.891 and 0.848 respectively in line with the velocity distribution of the daytime and nighttime image and the flow volume measured with Kalesto was approximately 18.2% larger than the value measured with the SIV.

Surface Image Velocimetry(SIV) is an instrument to measure water surface velocity by using image processing techniques. Since SIV is a non-contact type measurement method, it is very effective and useful to measure water surface velocity for steep mountainous streams, such as streams in Jeju island. In the present study, a surface imaging velocimetry system was used to calculate the flow rate for flood event due to a typhoon. At the same time, two types of electromagnetic surface velocimetries (electromagnetic surface current meter and Kalesto) were used to observe flow velocities and compare the accuracies of each instrument. The comparison showed that for velocity distributions root mean square error(RMSE) was 0.33 and R-squared was 0.72. For discharge measurements, root mean square error(RMSE) reached 6.04 and R-squared did 0.92. It means that surface image velocimetry could be used as an alternative method for electromagnetic surface velocimetries in measuring flood discharge.