Accurate predictions of maximum initial wave amplitude are essential for coastal impact assessment of tsunami waves generated by submarine landslides. Here, we analyse the existing predictive equations for the maximum initial amplitude (max) of submarine landslide-generated waves and study their performance in reproducing real-world landslide incidents. Existing equations include various landslide parameters such as specific gravity (γ s), initial submergence (d), slide length (B), width (w), thickness (T) and slope angle (θ). To determine how landslide parameters affect wave amplitude, we conduct a systematic sensitivity analysis. Results indicate that the slide volume (V = B × w × T) and d are among the most sensitive parameters. The data from the 1994 Skagway (observed max : 1.0-2.0 m) and 1998 Papua New Guinea (PNG) (observed max : 10-16 m) incidents provided valuable benchmarks for evaluating the performance of the existing equations. The predicted maximum initial amplitudes of 0.03-686.5 m and 3.7-6746.0 m were obtained for the 1994 and 1998 events, respectively, indicating a wide range for wave amplitudes. The predicted estimates for the smaller-sized event, i.e. the 1994 Skagway, appear to be more accurate than those made for the larger event, i.e. the 1998 PNG case. We develop a new predictive equation by fitting an equation to actual submarine landslide tsunamis: max = 50.67 V d 0.34 , where V is the slide volume (km 3), d is initial submergence depth (m), and max is in metres. Our new equation gives wave amplitudes of 1.6 m and 7.8 m for the 1994 and 1998 landslide tsunamis, respectively, which are fairly consistent with real observations.
The accurate prediction of landslide tsunami amplitudes has been a challenging task given large uncertainties associated with landslide parameters and often the lack of enough information of geological and rheological characteristics. In this context, physical modelling and empirical equations have been instrumental in developing landslide tsunami science and engineering. This study is focused on developing a new empirical equation for estimating the maximum initial landslide tsunami amplitude for solid-block submarine mass movements. We are motivated by the fact that the predictions made by existing equations were divided by a few orders of magnitude (10−1–104 m). Here, we restrict ourselves to three main landslide parameters while deriving the new predictive equation: initial submergence depth, landslide volume and slope angle. Both laboratory and field data are used to derive the new empirical equation. As existing laboratory data was not comprehensive, we conduct laboratory experiments to produce new data. By applying the genetic algorithm approach and considering non-dimensional parameters, we develop and examine 14 empirical equations for the non-dimensional form of the maximum initial tsunami amplitude. The normalized root mean square error (NRMSE) index between observations and calculations is used to choose the best equation. Our proposed empirical equation successfully reproduces both laboratory and field data. This equation can be used to provide a preliminary and rapid estimate of the potential hazards associated with submarine landslides using limited landslide parameters.
We report and analyze a case study of landslide-generated waves that occurred in the Apporo dam reservoir (Hokkaido, Japan) culminating from the rare incident of hazard combination from the September 2018 Typhoon Jebi and Hokkaido earthquake (Mw 6.6 on 5 September 2018). The typhoon and earthquake were concurrent and produced thousands of landslides in the area by the combined effects of soil saturation and ground acceleration. Here, we report the results of our field surveys of the landslides that occurred around the Apporo dam and generated damaging waves in the reservoir. We identified six landslides at a close distance to the dam body; the largest one has a length of 330 m, a maximum width of 140 m and a volume of 71,400 m3. We measured wave runup at a single point with height of 5.3 m for the landslide-generated wave in the reservoir and recorded the damage made to the revetments at the reservoir banks. By considering the locations of the landslides and their potential propagation paths, we speculate that possibly three of the six surveyed landslides contributed to the measured wave runup. The surveyed runup was reproduced by inputting landslide parameters into two independent empirical equations; however, other independent empirical relationships failed to reproduce the observed runup. Our field data from the Apporo dam can be used to improve the quality of predictions made by empirical equations and to encourage further research on this topic. In addition, our field data serves as a call for strengthening dams’ safety to landslide-generated waves in reservoirs.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.