Measurements of flood flow have been conducted intensively at major control sections in Japan for storing reliable hydrological data for use in a long-term river planning. However, such a measurement pays attention only to flow passing through one cross-section; thus, spatial flow features are not available, while river channel changes its feature at every flood event. In this research, we performed concurrent measurements of a snowmelt flood of the Uono River using an image analysis and radio-controlled acoustic Doppler current profiler (ADCP). In the image analysis with STIV (Space-time Image Velocimetry), three video cameras were used to cover a river reach of about 300m by changing their view angles at every location. On the other hand, the boat-mounted ADCP was remotely controlled to form a zigzag trajectory to cover the same reach. The accuracy and limitation of STIV was made clear through a comparison with ADCP data and a spatial distribution of correction factor from surface to depth-averaged velocity was found to have a weak correlation with a large-scale bed slope.

In recent years, the so-called unmanned air vehicles (UAV), remotely controlled airplanes or multicopters, have become available for various civil engineering purposes. In the field of river engineering, although they have been used to investigate the area of vegetation zone or other objectives, measurement of river flow has not been conducted by using an UAV, probably due to the difficulty of image stabilization. In this research, we developed a method to measure river surface velocity distributions by using videotaped images. The specific feature of the method is the introduction of a high-accurate and efficient image stabilization in order to apply the space-time image velocimetry (STIV) to airborne images. The developed method was applied to investigate snowmelt flood of the Uono River, with success of measuring twodimensional velocity distributions for a river reach of about four hundred meters. The obtained results were used to compare with those measured by ADCP or STIV using oblique images from a riverbank.

Measurements of flood flow have been conducted intensively at major control sections in Japan for storing reliable hydrological data to use for a long-term river planning. However, such a measurement pays attention only on a flow passing through one cross-section and thus spatial flow features are not available, while river channel changes its feature at every flood event. In this research, we performed concurrent measurements of a snowmelt flood of the Uono River by an image analysis and a radio-controlled ADCP. In the image analysis with STIV (Space-time Image Velocimetry), three video cameras were used to cover a river reach of about 500m by changing their view angles at every location. On the other hand, the boat-mounted ADCP was remotely controlled to form a zigzag trajectory to cover the same reach. The accuracy and limitation of STIV was made clear through a comparison with ADCP data and a spatial distribution of correction factor from surface to depth-averaged velocity was found to have a weak correlation with a large-scale bed slope.