Automated wave runup monitoring using coastal CCTV cameras for tsunami detection

Abstract

Abstract Coastal closed-circuit television (CCTV) cameras are ubiquitous yet rarely exploited quantitatively for tsunami detection. To address this gap and the scarcity of automated methods, we propose a technique that converts CCTV footage into a time-series of wave runup heights—instantaneous shoreline elevations corresponding to each incoming wave. The workflow has two main steps: (i) compute a luminance-variation (SIGMA) image in which the runup edge appears as a bright curve, and (ii) apply a color-based land–water mask to suppress dynamic noise on land. Preliminary tests under varied lighting, wave, and obstacle conditions confirmed the method’s stability. Application to footage from seven CCTV cameras during the 1 January 2024 Mw 7.5 Noto Peninsula tsunami revealed one of the tsunami’s dominant 300–500 s energy band and yielded root-mean-square errors of 0.094 m and 0.191 m at two sites after removing short-period (< 180 s) components—while processing ran faster than real time on a standard computer. In the cases studied, the extracted runup time-series demonstrated the potential to complement sparse offshore gauges for real-time tsunami detection and post-event analysis. Future work will target a broader range of recording conditions, refine signal separation, and validate the method on additional tsunami events with characteristics different from the Noto case.