Kwonkyu Yu

Real-time Discharge Measurement of the River Using Fixed-type Surface Image Velocimetry

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 m3/s, and the results compared with discharges through index velocity method using ADVM reached around 5% in the case of discharge over 200 . 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.

A Test of a Far Infrared Camera for Development of New Surface Image Velocimeter for Day and Night Measurement

In flow velocity measurement of natural rivers, taking images with proper image quality is the fundamental and the most important step. Since flood peaks generally occur in night time, it is very difficult to capture proper images in that time. The present study aims to test a far infra-red camera as a adequate alternative to resolve the various problems in measuring flood discharges. The far infra-red cameras are able to capture images in night time without help of any extra illuminations. Futhermore they are not affected by fog nor smoke, hence they can be adapted for a fixed-type surface image velocimeters. For comparison, a commercial camcorder and a near infra-red cameras were used together. The test images were taken at a day time and a night time, and the image acquisition work were performed at an artificial flow channel of the Andong River Experiment Station. The analyzed results showed that the far infra-red camera would be a good instrument for surface image velocimeters, since they were able to capture regardless light condition. There are, however, a few minor problems in their accuracy of the analyzed results. About their accuracy a more study would be required.

Estimatation of Mean Velocity from Surface Velocity

LSIV은 표면유속을 측정하는 영상기반 유속측정법중의 하나이다. 이 방법은 기존 측정기법에 비해 측정이 용이할 뿐만 아니라 경제적이기 때문에 유량측정 등의 실제 하천의 유속 측정에 활용하려는 연구들이 시도되고 있다. 그러나 이 기법은 표면유속을 측정하기 때문에 유량 산정을 위해서는 측정된 표면유속을 평균유속으로 환산할 수 있는 방법이 필요하다. 본 연구에서는 하상 및 흐름조건에 대한 다양한 수리실험을 통해 개수로 난류 흐름에 대한 연직유속분포의 특성을 파악하였다. 수리실험결과 수표면 영역의 유속감소를 확인하였으며, 이러한 유속감소는 조도보다는 Froude 수의 영향이 더 큰 것으로 나타났다. 실험 결과를 이용하여 표면유속으로부터 평균유속을 추정하는 두 가지 방법을 제시하였다. 제안된 방법들은 표면유속 보정량을 이용하여 후류법칙의 유속분포를 보정하는 방법과 평균유속과 표면유속의 비를 이용한 방법이다. 제시된 방법들은 실제 하천의 유속 측정 자료들을 이용하여 검증하였다 검증결과 이 방법들은

Measurement of Two-Dimensional Velocity Distribution of Spatio-Temporal Image Velocimeter using Cross-Correlation Analysis

6\%

Analysis of Loop-Rating Curve in a Gravel and Rock-bed Mountain Stream

이내의 오차를 보이는 것으로 나타났다. 【LSIV (Large Scale Image Velcocimetry) Is one of the image-based velocity measurement techniques. Since it measures surface velocities, it gives simple and inexpensive way to measure velocity, compared to other methods. Because of these advantages, there have been many studies to apply LSIV to the river discharge measurement in the field. Measuring the discharge by using LSIV requires a method which converts a surface velocity to a mean velocity In the present study, experiments and analysis of vortical velocity profile of open-channel flow in various conditions were performed to develop methods which estimate a mean velocity from a surface velocity. The result of this experiment reveals that velocity-dip phenomena occur at free-surface layer in open channel flow and Froude number affects more than bed roughness does. Two methods for estimating the mean velocity were proposed. One is to correct the wake laws profiles by using the difference of surface velocity from the mean velocity, and the other is to use the ratio of mean and surface velocities. The result of applying these methods in an experiment shows that they are quite accurate having an error of approximately

A Surface Image Velocimetry Algorithm for Analyzing Swaying Images

6\%

Development of a real-time surface image velocimeter using an android smartphone

only.】

Error Analysis of Image Velocimetry According to the Variation of the Interrogation Area

Surface image velocimetry was introduced as an efficient and sage alternative to conventional river flow measurement methods during floods. The conventional surface image velocimetry uses a pair of images to estimate velocity fields using cross-correlation analysis. This method is appropriate to analyzing images taken with a short time interval. It, however, has some drawbacks; it takes a while to analyze images for the verage velocity of long time intervals and is prone to include errors or uncertainties due to flow characteristics and/or image taking conditions. Methods using spatio-temporal images, called STIV, were developed to overcome the drawbacks of conventional surface image velocimetry. The grayscale-gradient tensor method, one of various STIVs, has shown to be effectively reducing the analysis time and is fairly insusceptible to any measurement noise. It, unfortunately, can only be applied to the main flow direction. This means that it can not measure any two-dimensional flow field, e.g. flow in the vicinity of river structures and flow around river bends. The present study aimed to develop a new method of analyzing spatio-temporal images in two-dimension using cross-correlation analysis. Unlike the conventional STIV, the developed method can be used to measure two-dimensional flow substantially. The method also has very high spatial resolution and reduces the analysis time. A verification test using artificial images with lid-driven cavity flow showed that the maximum error of the method is less than 10 % and the average error is less than 5 %. This means that the developed scheme seems to be fairly accurate, even for two-dimensional flow.

A Comparison and Analysis of the Levee Height Determination Methods in Korea and the USA

It is well-known that loop effect of the stage-discharge relationship is formulated based on many field observations especially for the sand rivers. Theoretical understandings of the loop effect for the sand rivers have been widely provided, based on the facts that it is driven by the flood wave propagation and bed form changes over the given flood period. However, very few theoretical studies or field observations associated with loop-rating curves in the gravel or rock-bed mountain streams have been attempted so far, due particularly to the difficulties in the accurate discharge measurement during the flood in such field conditions. The present paper aims to report a unique loop-rating curve measured at a gravel and rock-bed mountain stream based on the flood discharge observation acquired during the typhoon, Muifa that passed nearby Jeju Island in summer of 2011. As velocity instrumentation, a non-intrusive Surface Velocity Doppler Radar to be suitable for the flood discharge measurement was utilized, and discharges were consecutively measured for every hour. Interestingly, the authors found that the hysteresis of the loop-rating curve was adverse compared to the typical trend of the sand bed streams, which means that the discharge of the rising limb is smaller than the falling limb at the same stage. We carefully speculate that the adverse trend of the loop-rating curve in the gravel bed was caused by the bed resistance change that works differently from the sand bed case.

Coordinate Transform Method of Surface Image Velocimetry with a Calibrated Camera

Surface Image Velocimetry (SIV) is an instrument to measure water surface velocity by using image processing techniques. To improve its measuring accuracy, it is essential to get high quality images with low skewness. A truck-mounted SIV system would be a good way to get images, since its crane gives high altitude to the images. However, the images taken with a truck-mounted SIV would be swayed due to the movement of crane and the camera by winds. In that case, to analyze the images, it is necessary to compensate the side sway in the images. The present study is to develop an algorithm to analyze the swayed images by combining common image processing techniques and coordinate transform techniques. The system follows the traces of some selected fixed points and calculates the displacements of the video camera. By subtracting the average velocity of the fixed points from that of grid points, the velocity fields of the flow can be corrected. To evaluate the system`s performance, two image sets were used, one image set without side sway and another set with side sway. The comparison of their results showed very close with the error of around 6 %.