Evaluation of Water Surface Velocity Distribution Using a Quasi-Static Stabilization Technique for Social Sensing

Given that flood disasters often occur in areas without sufficient instrumentation, conventional observation networks alone may be inadequate to capture the actual evolution of flood events. However, video content from diverse sources such as smartphones, dashboard cameras, surveillance cameras, and helicopters or drones used for rescue, reconnaissance, or reporting, are increasingly collected incidentally and are gaining attention as complementary sensing modalities. Quasi-viewpoint fixation is key to quantitative hydraulic measurements because such videos involve significant changes in their point of view over the course of a given clip. To this end, we developed a quasistatic stabilization technique for social sensing referred to as QS4. The results of a laboratory experiment show that QS4 reproduced velocity distributions comparable to those of a fixed camera for pan-dominant videos recorded with a moving camera. In the 2024 Tsukada River flood, QS4 yielded stable velocity fields despite high turbidity, driftwood, and partial occlusions. Following the blockage of a bridge, flows were detoured along buildings shifting from a channel to flow through farmland, where ~5 m/s flows caused building failures that could not be detected by fixed observations. QS4 offers a practical pathway for transforming incidental videos into quantitative hydraulic observations.