{"paper_id":"0afbfdca-552f-46f8-b79c-9aab1cbfa7f9","body_text":"Large-scale three-dimensional experimental investigation on potential high position landslide‑induced waves in Gushui Reservoir, China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Large-scale three-dimensional experimental investigation on potential high position landslide‑induced waves in Gushui Reservoir, China Shizhuang Chen, Weiya Xu, Yelin Feng, Long Yan, Yangyang Zhang, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3711802/v2 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Nov, 2024 Read the published version in Ocean Engineering → Version 2 posted You are reading this latest preprint version Show more versions Abstract The occurrence of landslides in reservoir areas and the potential secondary disasters near dams are characterized by their sudden and catastrophic nature, often limiting the availability of actual measurement data. To address this challenge, prototype physical model test always proves to be valuable method to replicate or reproduce such geological hazards. In this study, we focused on the Meilishi landslide in the Gushui reservoir area as a case study to analyze the potential threat of high position landslide-induced waves under gravity. Based on field investigations and relevant statistical geological data, a large-scale three-dimensional physical model was carried out that integrated the interactions of the landslide, the river, and the dam. With a scale of 1:150, the model had the dimensions of 57, 27, and 8 m. Water level and the maximum sliding velocity into the water were selected as independent variables, leading to a total of 18 experiments. An adaptive landslide motion simulation system based on velocity equivalence and a comprehensive measurement system with tracking technology based on hydrodynamics were independently developed. Those approaches allowed us to reveal the propagation characteristics and attenuation laws of high position landslide-induced waves in a curved channel under various complex conditions. The data showed that the maximum wave run-up height on dam was 17.97 m under the most dangerous working condition (H3C09). Importantly, this value did not exceed the maximum height of dam, indicating a certain level of safety margin for the dam. Combined with the data of different working conditions, the optimal window for landslide risk prevention and control warnings was within 550 s after the onset of landslide instability. The key parameters predicted by the tests, including head wave height, wave run-up height on the opposite bank, wave run-up height on dam, and the propagation times, provided a technical basis and valuable reference for dam engineering design and safety. These results make significant contributions to the prevention and control of similar surges hazard induced by high position landslides around the world. High position landslide‑induced waves Large-scale three-dimensional experiment Prototype physical model Gushui Reservoir Meilishi landslide Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 Figure 15 Introduction Landslide‑induced waves are important formative mode in hazard chain of wading landslides, which have always been practically hot research topics in fields of engineering geology, hydraulic engineering, disaster prevention and mitigation engineering (Panizzo et al. 2005b , Sassa 2023 , Shanmugam and Wang 2015 , Tang et al. 2019 ). Geological disasters such as large-scale landslides and collapses around river channels and reservoirs may block rivers and produce huge surges, which seriously threaten the safety of waterways, residents, and engineering projects along the reservoir area, and even dams and hydropower stations (Ataie-Ashtiani and Nik-Khah 2008 , Davidson and McCartney 1975 , De Carvalho and Antunes do Carmo 2007 , Van Asch et al. 2007 ). The best well-known example is the Vajont landslide in Italy on October 9, 1963. The massive surges caused by nearly 270 million m 3 of rock debris poured into the reservoir, which obliterated five surrounding towns and killed about 2000 people. The devastating disaster and financial losses shocked the whole engineering and technology industry (Kilburn and Petley 2003 , Panizzo et al. 2005a ). In recent years, these hazards have been extremely prevalent all over the world. On July 20, 2009, the Huangtian landslide triggered by rainfall in the Xiaowan reservoir in Southwest China killed approximately 14 people (Huang C et al. 2023 , Xu et al. 2021 ). The impulse wave of more than 5 m induced by the Hongyanzi landslide in the Three Gorges Reservoir Area (TGRA) caused 2 deaths on June 24, 2015 (Xiao et al. 2018 , Zhou et al. 2016 ). A cascading rainfall-landslide-tsunami event occurred on 29 June 2022 in a lake in Southern Chile after 4 days of heavy rains. The landslide with a total volume of 1.05×10 4 m 3 that generated a tsunami with an initial tsunami amplitude of about 1 m. The event resulted in the collapse of a pedestrian bridge and overturning other mooring facilities in the lake and the coast (Aránguiz et al. 2023 ). The examples reiterated the catastrophic nature of landslide-induced waves. The variation of water level is a major trigger factor to induce new landslides and revive old landslides in reservoirs (Dai et al. 2022 , Fujita 1977 , Zhang et al. 2023 ). At the initial stage of reservoir impoundment, the slope exposed to air is softened by water immersion, which results in a significant reduction in its shear strength. For the rock landslide with poor permeability, the water buoyancy on the leading edge also aggravates the deformation and failure of the landslide. Meanwhile, large hydropower stations often have tens of meters of water level fluctuation zones during operation. When water level plummets, the dissipation of pore water lags the dissipation of external water, and the pore water pressure and hydrodynamic pressure formed are not conducive to anti-sliding stability of landslides. On the contrary, the rapid rise of water level will sharply raise the groundwater level in the landslide and reduce its slip resistance. The Baihetan Hydropower Station on the lower reaches of the Jinsha River is the second largest hydropower station in China after the Three Gorges Hydropower Station. In the process of reservoir impoundment, the Wangjiashan landslide, Tuandigou landslide and Wulipo landslide have deformed to different degrees (Chen et al. 2023 , Cheng et al. 2023 , Yi et al. 2023 ). Landslides induced by reservoir impoundment have gradually become a contentious issue in the Baihetan reservoir area (Li et al. 2022 , Yang et al. 2023 ). In addition, earthquake, rainfall, artificial disturbance, and other factors will further aggravate the possibility of geological disasters in reservoir area, especially landslide‑induced waves (Demirel and Aydin 2016 , Wang et al. 2020 , Yan et al. 2019 ). The whole process of landslide-generated waves can be divided into five stages: the instability of the landslide, their motion, the generation of waves, their propagation, and the effects of the waves on the affected body, which is an interaction with the gas, liquid and solid (Chen et al. 2023 a, Laurmaa et al. 2018 , Mao et al. 2020 , Tan and Chen 2017 ). Five methods can be adopted to investigate landslide dangers and the catastrophic effects of landslide-induced waves: field analytical investigations, empirical equations, numerical simulations, general physical model tests and prototype physical model tests (Chang and Wang 2011 , Fritz et al. 2009 , Yu et al. 2023 ). Due to the strong occurrence of landslide-induced waves and the rapid disappearance of residual water traces on both sides of the river, the actual measurement data are extremely rare, which leads to the limitation of case study and increases the research difficulty. Most of the general physical model tests mainly focus on the mechanism research of landslide-induced waves, which are simplified without fully considering the complex conditions. And the relationship between each stage of landslide-induced waves is artificially separated (Bregoli et al. 2017 , Fritz et al. 2004 , Heller and Spinneken 2015 , McFall and Fritz 2016 ). In sharp contrast, prototype physical model tests mainly are used to solve a single practical engineering problem. The whole process of landslide-induced waves can be visually reproduced or rehearsed to obtain mass of data under different constraints. These data are interrelated and can be systematically analyzed (Chen et al. 2023 b, Deng et al. 2019 , Xue et al. 2019 ). Prototype physical model tests are not a widely used method due to the huge cost, large-scale, and long construction time required. However, for such complex research objects, prototype physical model tests are still the best method mentioned above. Yin et al. ( 2012 ) took the channel of Baishuihe landslide in TGRA as prototype, established the river physical model in map scale 1:200, and thus developed landslide surge three-dimensional physical model experiment by adopting the experimental control system and measurement system. Han et al. ( 2022 ) studied the effects of sharply curved river bends on the wave transmission and run-up features of breaking waves in a 90° channel bend, and the derived run-up equations were applied to a field case in TGRA. Based on Gongjiafang landslide in TGRA and the Wangjiashan landslide in Baihetan reservoir area, Huang BL et al ( 2014 , 2023 ) set up the large scale three-dimensional physical model with a scale of 1:200 and 1:150, respectively. The law of wave interaction deeply explored, and the difference of attenuation rate between wave propagation and run-up process were described in detail. The above cases are aimed at the surge problem of typical partially submerged landslide, and there are few reports on high position landslide‑induced waves above the water. In this paper, large scale three-dimensional experiments of potential high position landslide‑induced waves were carried out based on the Meilishi (MLS) landslide in Gushui (GS) reservoir area, China. Water level and the maximum sliding velocity into water were selected as independent variables in the experiments. The laws of wave generation and propagation were analyzed under varied test conditions, and the times to reach the dam after the wave generation were predicted. Statistics and methods in this paper contribute to the understanding of high position landslide‑induced waves. Overview of the MLS landslide The GS hydropower station is a large-scale step hydropower project in the Lancang River and is located in Deqin County of the Diqing Tibetan Autonomous Prefecture, Yunnan Province (Fig. 1 ), which normal water level, dead water level, and construction water level are 2267m, 2230m, and 2128.65m, respectively. The retaining structure is a concrete faced rockfill dam with a maximum height of 240m. Extensive field survey and engineering investigations of this landslide have been performed by PowerChina Kunming Engineering Corporation Limited. Furthermore, three field investigations were conducted by the authors of this paper in June 2022, August 2022, and April 2023. The geotechnical properties, hydrogeological circumstances, and form features of the MLS landslide were adequately recognized based on these works. As shown in Figs. 1 and 2 , the MLS landslide is located about 4 ~ 5km upstream of the dam site, which is composed of four individual landslides with shape of isosceles trapezoid, named H 3 , H 4 , H 5 , and H 6 , with corresponding volumes of 1907×10 4 , 1428×10 4 , 200×10 4 , and 100×10 4 m 3 , respectively. This valley presents a topography with a steep below and gentle above surface. The distribution altitudes of H 3 and H 4 are relatively high, approximately between 2600 and 3250 m. The distance between H 3 and H 4 is 300m, with the mountain ridge as the boundary. They are formed by the toppling, breaking, and sliding of layered rock masses. The basalt is exposed at their front edges, acting as a large retaining wall. The Fig. 3 depicts the typical geological profile of H 3 , indicates that it is mainly composed of surface colluvium layer, loose accumulation layer, sliding weak zone, and bedrock. There is an obvious boundary between the colluvium layer and the accumulation layer, and the surface of bedrock is more fragmented. The sliding weak zone exposed in exploration adit PD2004 (Fig. 3 ) is at the bottom of the landslide, which shows yellow-brown clay mixed with gravel, and the gravel content is between 5 and 10%. The geomechanics of H 4 and H 3 are very similar. The altitudes of the landslide toe and head scarp of H 5 and H 6 are 2130 and 2400 m, respectively. Their main components were formed by H 4 accumulated in the valley after sliding. When the reservoir water level is raised to 2267 m, most of the relatively stable H 5 and H 6 landslides will be underwater, so they will not be used as controlling factors in subsequent studies. The local areas of H 3 and H 4 are still in the creep deformation stage now. From October 2014 to December 2020, the average deformation rate of H 3 was 0.77 mm per year, and the average deformation rate of H 4 was 6.86 mm per year (Guo et al. 2021 ). The stability assessment of H 3 and H 4 cannot meet the engineering design requirements, and which are characterized by large scale and high shear crack in narrow valley. Once the landslides become unstable, it is easy to cause chain hazard such as river blockage or surges, which will seriously threaten the safety of dam, waterways, and river coast in reservoir. Therefore, the problem of potential impulse waves induced by high position landslide needs to be paid serious attention. Methodologies used in the physical experiments Set up of the physical model The three-dimensional physical model was built at Water Flow Experiment Center of Hohai University, which is mainly consist of landslide scale model, river scale model, the dam scale model, hydraulic structures scale model, water flow circulation system, etc. According to the Froude similarity criterion, when the geometric scale was 1: 150, the time and velocity scale was 1: \\(\\surd 150\\) and the density scale and gravitational acceleration was 1:1. The scaled model had a length of 57 m and a width of 27 m and resembled an about 8 km stretch of the river from MLS landslide location to the dam site area. The average elevation of the bottom of the natural valley is approximately 2060 m, the maximum height of the river scaled model is 3.6 m, and the maximum height of the landslide scaled model is 8 m (Fig. 4 ). The landslide motion is simulated by an adaptive starting device based on velocity equivalence. The device includes a sliding box, jacks, high-pressure oil pumps, starting valves, etc. The elevations of both landslides shear exits are approximately 2600m. The terrain slope in the area below the landslide shear exit is steep, and the slope foot is generally 35 ~ 40°. The area is poured with concrete following the original topography. Two sliding boxes are provided above the shearing exit. Since the bottom surfaces of the landslides are all in the shape of a knife and only small areas of the front and rear edges are arc-shaped, the bottom surface of the sliding box can be simplified to a flat slope. The inclination angle of the sliding box is set to the average slope of the actual landslide. Different sliding velocities of landslide body can be obtained by changing the bottom surface material and adjusting the inclination angle of the sliding box with the high-pressure oil pumps and starting valves, which need to be kept within the preset level range. The starting valve is set on the front edge of the sliding box, which controls the downward reversal of the sliding door, allowing the initially stable sliding body to start in place. The river scale model is made of cement, sand, bricks, and steel bars using the fracture plate method, and each panel section is spaced approximately 0.5 m apart. The contour method is used in areas with complex terrain, and each contour line is spaced approximately 0.05 m apart. The water circulation system uses water pumps to pump water from underground reservoirs to achieve model water supply. There are water level probes inside the model to record the water level heights to meet the needs of different water depths in the test. There is also a crane in the upstream area to transport and lift the sliding body during repeated tests and speed up the test progress. In landslide‑induced waves physical tests, landslides are generally simplified into three modes, including rigid body, granular body, and deformation body. The sliding body is made of granular body in this test, and the granular materials are black pebbles. The granular particle density of black pebbles is about 1.5 ~ 1.6 g/cm 3 , and the maximum particle size is 6 ~ 8cm. The Fig. 5 is the particle size distribution curve of the landslide body, and regions ①, ②, ③ and ④ correspond to the proportions of 0.075 ~ 2mm, 2 ~ 10 mm, 10 ~ 20mm, 20 ~ 60mm particle size respectively. According to the actual particle size and scale of the landslide, the four-particle size black pebbles are proportioned according to 2.5: 2.5: 1: 1.5. Different from common landslide-induced wave experiments, this study only used the model similarity of the sliding velocity, not of the rheological behavior of the landslide (Ataie-Ashtiani and Shobeyri 2008 , Yavari-Ramshe and Ataie-Ashtiani 2019 ). A large amount of data prove that the sliding velocity is one of the most important factors controlling the characteristics of wave height (Fritz et al. 2004 , Noda 1970 , Scheidegger 1973 , Wang et al. 2012 ). Measurement system and technology A full elements measuring system and tracking technology based on hydrodynamics are independently developed, which includes the wave height testing system, the sliding velocity testing system, and the video collection system. The wave height testing system is obtained by outputting electrical signals to the computer from the DYS50-3000 digital wave height collector. The sampling frequency is 50 Hz, and the accuracy is 0.1 mm. The Fig. 6 shows that the scale model has a total of 22 wave height measurement points, 8 in the near field area, 11 along the river, and 3 near the dam area. The collector at the dam site location is assigned a station ID 0 + 000 m, and the station IDs of the other collectors are respectively 0–017 m, 0–241 m, 0–606 m, 0–977 m, 0–1293 m, 0–1655 m, 0–2065 m, 0–2573 m, 0–3107 m, 0–3637 m, 0–4161 m, 0–4726 m, 0–5300 m, and 0–5835 m. Contour scales are also drawn on both sides of the river, with a ruler accuracy of 0.01m, to facilitate the observation of climbing waves along the river coast (Fig. 5 ). The sliding velocity is measured using an attitude meter and a turntable contact speedometer, respectively. The attitude meter is fixed inside the sliding body, measures its acceleration, and obtains the velocity-time curve by integrating over time. The turntable contact speedometer is used as an auxiliary test equipment, and the error between its test results and the attitude meter is within 2% in the preliminary experiment. The video collection system mainly consists of high-definition cameras, drone photography and real-time collection devices. The 4 high- definition cameras are used to observe the process of landslides falling into water. The 11 high-definition cameras simultaneously recorded at a frequency of 50 fps, basically covering the entire range of the physical model flow field, which had 1600×2500 pixels. Drones are used to assist in capturing landslide or surge images at key locations. Design of the experimental program The experimental program is shown in Table 1 . Water level and maximum sliding velocity are two independent variables. Since H 3 and H 4 slide independently, 9 sets of tests were designed for each landslide. According to the results of landslide stability assessment and instability mode analysis, the potential instability volume of H 3 and H 4 are 1907×10 4 and 1428×10 4 m 3 . The equivalent instability volumes converted through similarity criterion are 5.65, and 4.23 m 3 , respectively. The Water levels are 0.46m, 1.13m, and 1.38m respectively, corresponding to the water level elevations of 2128.65m, 2230m, and 2267m. In order to delineate the impact of sliding velocity on wave height, different materials are used to adjust the friction coefficient of the sliding bottom surface under in same water level. The velocity refers to the maximum sliding velocity corresponding to the barycenter of the sliding body entering the water. Controlling the three-dimensional landslide sliding velocity is challenging, the experimental data are widely dispersed. Therefore, multiple parallel experiments were carried out to control the final data fluctuation within the range of ± 0.02 m/s. The data below are the prototype values unless otherwise specified. Table 1 Experimental design of the MLS landslide under different working conditions Working condition Landslide name Landslide volume (m 3 ) Water level (m) Maximum sliding velocity (m/s) Prototype Model Prototype Model Prototype Model H3C01 H 3 1907×10 4 5.65 2128.65 0.46 65.35 5.34 H3C02 71.12 5.81 H3C03 82.16 6.71 H3C04 2230 1.13 65.77 5.37 H3C05 74.59 6.09 H3C06 80.71 6.59 H3C07 2267 1.38 66.01 5.39 H3C08 70.91 5.79 H3C09 83.53 6.82 H4C10 H 4 1428×10 4 4.23 2128.65 0.46 69.61 5.68 H4C11 80.33 6.56 H4C12 89.29 7.29 H4C13 2230 1.13 72.27 5.90 H4C14 79.70 6.51 H4C15 91.00 7.43 H4C16 2267 1.38 70.55 5.76 H4C17 83.41 6.81 H4C18 91.61 7.48 Experimental analyses Process of landslide movement Taking the classic working condition H4C17 as an example, the experimental analysis was carried out. As shown in Fig. 7 , it took about 120 s for the landslide to slide completely into the water. The landslide moved in the form of a debris flow accompanied by white smoke produced by friction. Figure 8 showed the time series of the average acceleration and velocity of the landslide in H4C17. It is obvious that the entire process from the start of the landslide to the entry into the water is not uniform acceleration or deceleration. The acceleration of the sliding body fluctuates with time, which is caused by certain differences in the kinetic friction coefficients in each area of the sliding surface. Overall, the acceleration first increases and then gradually decreases with time. Air resistance exists but is basically negligible at this stage. The time series of the average velocity curve can be mainly divided into three stages: (1) Slow acceleration stage: The sliding velocity increases slowly and linearly with a lower slope from the beginning to the front edge of the sliding body in contact with water. (2) Acceleration stage: The gravitational potential energy of the sliding body is quickly converted into kinetic energy during this stage. Most of the sliding bodies slide out of the shear exit position and further accelerate on the sliding surface along the way. When the barycenter of the sliding body enters the water, the velocity reaches its maximum value. (3) Rapid deceleration stage: The landslide quickly decelerates and gradually stops moving under the combined action of scraping friction resistance and water resistance after entering the water. Some of the sliding bodies hit the bottom of the valley, and some of them accumulate on the lower bodies. The velocity curves show a dramatical decline, and the acceleration becomes negative. Ultimately, acceleration and velocity will fluctuate around zero due to inertia. Generation features of waves in near field The near field area is a small range of waves-affected area near the water entry point of the landslide body. An obvious arc-shaped wave crater is formed due to the impact of the landslide into the water at high speed (Fig. 7 ). The impulse waves propagate to the surroundings in the form of a ring wave and reaches the opposite bank 75 seconds later and then the waves are reflected. Because the river channel is narrow, the reflected wave and subsequent incoming waves meet quickly, creating more reflections and superpositions, and resulting water in oscillating back and forth in the river channel. Figure 9 shows time series of free surface elevation of wave height collectors along the sliding direction in H4C17. Different from underwater landslides and partially submerged landslides, subaerial landslides generally generate wave crests first and then troughs, and the wave crests are larger than the wave troughs. In the early stage, the wave height changed drastically, and the digital wave height collectors recorded a total of three waves in 150 s. Results of the experiments show that the general patterns of waves in all series are the same, but the amplitudes and periods vary. The first two waves have similar amplitudes, and the amplitude of the third wave begins to decrease significantly, and the period gradually becomes longer. The MLS landslide is a typical high-altitude landslide, and its high potential energy is converted into high kinetic energy, resulting in a large speed of the sliding body, so the Froude number is much larger than 1. The relative thickness of the landslide is calculated to be between 0.15 and 0.45. So impulse waves are classified as nonlinear transition waves of type B according to the near-field wave theory of Noda ( 1970 ). The first wave is generated when the sliding body enters the water, and the height of the first wave is obviously higher than other waves. Then the amplitude decreases rapidly, and the wave shape becomes dispersive. The wave curve shows an oscillating trend over time, and the wave amplitude does not decrease step by step, and the wave amplitude fluctuates up and down in some areas. With the continuous dissipation of energy, the wave gradually tends to fluctuate periodically, and the wave height changes gradually become stable and eventually approach zero. Propagation features of waves in far field Figure 10 and 11 reflect the surge process in the river channel, especially the interaction process over time and space. The ordinate in Fig. 10 represents the wave heights at different spatial locations. It is obvious that the first four independent impulse waves propagated to the downstream river channel, with a maximum wave crest of 26.85m and a period of about 20s in the gray area ①. With the passage of time and space, the wave trough gradually becomes smaller, and the waves slowly overlap. The shape of waves gradually changes from a single peak to a smooth shape, the amplitude steadily attenuates, and the period becomes longer. When it reaches the dam, the first four rows of solitary waves have formed a large peak wave. At the same time, the large peak wave is followed by some small amplitude waves. This is because the impulse waves will be reflected when they are transmitted to the solid wall of the riverbank. And more reflected waves produced by secondary interaction between the reflected wave and incoming wave. The yellow area ② in Fig. 10 is the wave propagation process after the interaction between impulse waves and reflected waves. The wave shape in this area is irregular, and the wave curves appear to be multi-peaked in each period. The wave period is extremely unstable, the frequency is accelerated, and larger wave crests can also be formed in the process. Figure 11 shows the distribution law of waves propagation and attenuation in the river channel. The wave height is affected by changes in the river topography and direction. It shows obvious topographic correlation and is difficult to quantify. The attenuation of the wave amplitude along the center of the river is obviously not a constant attenuation, but an undulating attenuation. The waves climb to a certain extent when it reaches the dam site. The whole process can be divided into a sharp attenuation stage and a gentle attenuation stage. The sharp attenuation stage shows an exponential decline pattern. The wave heights within 1km attenuate by more than 15m, accounting for 58% of the maximum wave height. The average wave attenuation within 100m is 1.5m. Beyond 1km, the wave heights attenuation rate slows down, with an average wave attenuation of about 1.15m per 1km. However, the wave heights still change significantly in the trenches and gullies areas. Effects of impulse wave on the dam area Figure 12 shows time series of wave run-up height on dam curve. Among them, the wave heights collected by digital wave height collectors #1, #2 and #3 are 11.75m, 11.88m and 12.15m respectively, corresponding to the left bank, middle and right bank of the dam. There is a large-angle terrain in front of the GS Hydropower Station. When the surge arrived here, it is strongly affected by the change of the river topography on the one hand, and the surge propagates unevenly on the left and right banks. Overall, wave run-up height on dam shows a trend that the right bank is larger than the middle and larger than the left bank. On the other hand, due to the uplift of the dam topography, the surge will climb upward along the dam surface. The data shows that the impulse wave curve is relatively smooth within 880s and propagates in the form of superimposed sine waves. The curve fluctuates unstably up and down after 880 s, which is due to the inability of the energy in the model system to dissipate in time and the water surface to oscillate. Three waves hit the dam, the first of which was the largest, followed by two smaller waves. For the first wave, the crest is slightly larger than the trough, and the fluctuation period is about 100s. The first wave can be used as an ideal waveform input to predict subsequent surge propagation. After 880s, the amplitude of impulse wave is small, the period is relatively chaotic, the crest line is not obvious, and it is difficult to identify the crest and trough directly. This also makes the surge in the formation and propagation process has a certain degree of concealment and confusion, which is not conducive to identification and emergency warning. Variation law of key parameters under different working conditions Figure 13 summarizes key parameters such as head wave height, wave run-up height on the opposite bank, wave run-up height on dam, and the propagation time under different test conditions. The head wave height, wave run-up height on the opposite bank, and wave run-up height on dam are positively correlated with sliding velocity. The smoother the sliding surface, the less work the landslide will do to overcome frictional resistance during the sliding process. The more kinetic energy is converted from gravitational potential energy, the greater sliding velocity will be. All the kinetic energy are transmitted to the water body after the sliding body enters the water, which will drive the water and create the head wave height, wave run-up height on the opposite bank, and wave run-up height on dam. For example, working conditions H3C07, H3C08 and H3C09 correspond to sliding velocities of 66.01, 70.91 and 83.53m/s respectively, and wave run-up heights on dam of 14.31, 16.11 and 17.97m respectively. The head wave height, wave run-up height on the opposite bank, and wave run-up height on dam are positively negatively correlated with water level. Different water depths and water volumes have different abilities to consume impact energy. The corresponding water levels of H3C02, H3C05 and H3C08 are 2128.65, 2230 and 2267m respectively, and waves run-up heights on dam are 19.13, 18.92 and 16.11m respectively. In addition, the topography and river curvature caused by different water levels are also different, which also has a great impact on the test results. The data show that the maximum wave run-up height on dam is 17.97 m under the most dangerous working condition (H3C09), which does not exceed the maximum height of dam, so the dam has a certain safety margin. Under different working conditions, the propagation times for the surge to reach the dam shows disorder, but it is basically within the range of 550s-750s. It can be considered that the 550s is the prime time for early warning after landslide occurrence. During this period, residents along the bank and vessels on waterway should be evacuated in a timely manner, and corresponding protective measures should be installed in the dam area. At the same time, it is also necessary to strengthen landslide deformation monitoring and real-time data feedback to lay the foundation for the early identification and early warning of disasters. Discussion To explore the impact of sliding body materials on wave height of high position landslide‑induced waves, and to demonstrate the accuracy and reliability of the test results, the deformation body are used as a sliding body material to carry out controlled tests (Fig. 14 ). These bodies have a certain deformation ability and are made of very soft bags filled with granular particle materials, which size is 0.8m×0.4m×0.15m. The Fig. 15 shows the statistical results of the key parameters of the test H4C17 using granular bodies and deformation bodies respectively. It is obviously found that the propagation and attenuation laws of wave height obtained by using granular particles and deformation bodies are similar under the same conditions of landslide volume, water level and sliding velocity, and the propagation time is also similar. There is a certain difference between the wave heights in near field and the wave heights in far field are similar. It is preliminarily believed that the sliding body shape affects waves characteristics much more in the near field than in the far field. As for the contribution of far-field wave height, the sliding body shape is much smaller than the sliding velocity factor and water level factor. When the volume and velocity of the sliding body are the same, the total energy carried by the sliding body during the sliding process is the same. The same water level conditions determine the same energy dissipation capabilities, so the far-field wave heights are close to each other. The individual deformation body carries large amounts of energy, which ability to disturb water is much greater than that of particles, so there is a difference in near-field wave heights between the two. Since the deformation bodies will be limited in their movement posture during the sliding process of high position landslide‑induced waves, the waves will be broken and discontinuous, which will cause the test results to be unstable and have a large degree of discreteness. Therefore, the granular bodies are finally selected for this test as the sliding body material. In addition, considering that during the actual sliding process of the landslide, the landslide body does not completely disintegrate into debris, some deformation bodies can be added to granular particles to simulate the sliding body in subsequent tests. Conclusion The following conclusions can be drawn with large-scale three-dimensional prototype physical model experimental investigation on potential impulse waves induced by MLS landslide: 1. Taking the MLS landslide in the GS reservoir area as the prototype, based on the similarity theory and using a scale of 1:150, the large-scale three-dimensional physical model was established that integrated the interactions of the landslide, the river, and the dam. Water level and the maximum sliding velocity into water were selected as independent variables, and a total of 18 experiments were carried out. The methodologies used in the physical experiments in this paper can be used to predict and study similar high position landslide‑induced waves problems. 2· The adaptive landslide motion simulation system based on velocity equivalence was independently developed to simulate process of landslide movement. The landslide moved in the form of a debris flow accompanied by white smoke produced by friction, which had typical high-position long-runout landslide dynamic characteristics. The landslide movement process can be divided into three stages: slow acceleration stage, acceleration stage and rapid deceleration stage. 3. The impulse waves propagated from the generating point to the surroundings in an arc shape, and they had nonlinear transition wave characteristics in the near field area. The data showed that a total of three larger waves were reflected on the opposite bank, and a total of four larger waves propagated downstream along the river. The superposition and reflection of these waves were all recorded by the full elements measuring system, clearly demonstrating the interaction process of waves during waves propagation. 4. The experimental data carefully depicted the difference in attenuation rates of waves propagation in the river channel. The whole process can be divided into a sharp attenuation stage and a gentle attenuation stage. The sharp attenuation stage showed an exponential decline pattern, and the attenuation rate was as high as about 58%. In the gentle attenuation stage, the wave height attenuation speed slowed down. The wave height was significantly affected by the changes in river topography and direction and was difficult to quantify. 5. The large-angle terrain change in front of the GS Hydropower Station caused uneven propagation of the surge on the left and right banks. Overall, wave run-up height on dam showed a trend that the right bank is larger than the middle and larger than the left bank. A total of three larger waves were recorded impacting the dam in the form of superimposed sine waves. The crest lines of subsequent waves were not obvious, making it difficult to directly identify the crests and troughs. This also showed that the formation and propagation process of surges had a certain degree of concealment and confusion. 6. The series of test data showed that the maximum wave run-up height on dam was 17.97 m under the most dangerous working condition, which did not exceed the maximum height of dam, so the dam had a certain safety margin. The golden time of landslide risk prevention and control warning was within 550 s after landslide instability. The key parameters predicted by the tests, such as the head wave height, wave run-up height on the opposite bank, wave run-up height on dam, and the propagation time provided a technical basis and a useful reference for the dam engineering design and safety. Declarations Acknowledgements PowerChina Kunming Engineering Corporation Limited is gratefully acknowledged for providing the study site and geological data. Funding This work was financially supported by the National Natural Science Foundation of China (51939004) and China Huaneng Group Corporation Limited (HNKJ22-H107). Data availability The data that support the findings of this study are available from the corresponding author upon reasonable request. Declaration of interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. References Aránguiz R, Caamaño D, Espinoza M, Gómez M, Maldonado F, Sepúlveda V, Rogel I, Oyarzun JC and Duhart P (2023) Analysis of the cascading rainfall–landslide–tsunami event of June 29th, 2022, Todos los Santos Lake, Chile. Landslides 20: 801-811. https://doi.org/10.1007/s10346-022-02015-1 Ataie-Ashtiani B, Nik-Khah A (2008) Impulsive waves caused by subaerial landslides. 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Cite Share Download PDF Status: Published Journal Publication published 06 Nov, 2024 Read the published version in Ocean Engineering → Version 2 posted You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {\"props\":{\"pageProps\":{\"initialData\":{\"identity\":\"rs-3711802\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":266733858,\"identity\":\"2bcfdf21-c7fb-4228-8c22-8ebe06e2c0ef\",\"order_by\":0,\"name\":\"Shizhuang 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3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":201961,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eThe typical geological profile of H\\u003csub\\u003e3\\u003c/sub\\u003e landslide. The inset shows the sliding weak zone exposed in exploration adit PD2003.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3835232/v1/0ea3d86069ff6bdfba8e40d4.png\"},{\"id\":49538726,\"identity\":\"aeb5a7c3-a5a5-42fe-a4fb-0d24b4131fd2\",\"added_by\":\"auto\",\"created_at\":\"2024-01-11 16:12:08\",\"extension\":\"png\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":239110,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eThe large-scale three-dimensional physical model of landslide, river, and dam interaction.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage4.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3835232/v1/96a4e4870971596f1167e62b.png\"},{\"id\":49538728,\"identity\":\"8ae9c791-08d0-420d-aab8-7553fcabe711\",\"added_by\":\"auto\",\"created_at\":\"2024-01-11 16:20:08\",\"extension\":\"png\",\"order_by\":5,\"title\":\"Figure 5\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":150354,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eThe particle size distribution curve of the landslide body. The inset shows the black pebbles used in experiments.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage5.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3835232/v1/a48ce1319944e96db4547754.png\"},{\"id\":49538730,\"identity\":\"069d49f0-f8e0-406a-ae29-b0794bc7b081\",\"added_by\":\"auto\",\"created_at\":\"2024-01-11 16:20:08\",\"extension\":\"png\",\"order_by\":6,\"title\":\"Figure 6\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":871631,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eLocations of digital wave height collectors.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage6.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3835232/v1/416cb624d618a8fbbc8bfc7e.png\"},{\"id\":49538732,\"identity\":\"a500d3d6-9a24-4c9e-9d29-c89ae332766c\",\"added_by\":\"auto\",\"created_at\":\"2024-01-11 16:12:08\",\"extension\":\"png\",\"order_by\":7,\"title\":\"Figure 7\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":375330,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eVisual documentation of high position landslides sliding into the water.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage7.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3835232/v1/01e52d7486ebebf4d2da00f9.png\"},{\"id\":49538734,\"identity\":\"0f6725ed-fe7d-477b-bc86-dc1cdecc2c4e\",\"added_by\":\"auto\",\"created_at\":\"2024-01-11 16:36:08\",\"extension\":\"png\",\"order_by\":8,\"title\":\"Figure 8\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":668635,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eTime series of the average acceleration and velocity of the sliding body in H4C17.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage8.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3835232/v1/09f346f8f1f8b2c04329e3b3.png\"},{\"id\":49538736,\"identity\":\"1599400d-511c-4bdb-9ef9-01cb12984cfa\",\"added_by\":\"auto\",\"created_at\":\"2024-01-11 16:12:08\",\"extension\":\"png\",\"order_by\":9,\"title\":\"Figure 9\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":219627,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eTime series of free surface elevation of wave height collectors along the sliding direction in H4C17.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage9.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3835232/v1/c4fcf57ba268ce986368e873.png\"},{\"id\":49538738,\"identity\":\"95be9334-671a-4225-8847-82354f59322f\",\"added_by\":\"auto\",\"created_at\":\"2024-01-11 16:12:08\",\"extension\":\"png\",\"order_by\":10,\"title\":\"Figure 10\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":1430129,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eWave height process lines of collectors in river channel in H4C17.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure10.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3835232/v1/dd2322b78260c4daf275f704.png\"},{\"id\":49538740,\"identity\":\"230566da-7d86-42ee-b2dd-c1644db69f50\",\"added_by\":\"auto\",\"created_at\":\"2024-01-11 16:12:08\",\"extension\":\"png\",\"order_by\":11,\"title\":\"Figure 11\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":88624,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eVariation curve of wave heights along the river channel in H4C17.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure11.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3835232/v1/e21b2c97f01b30b8e29bf9af.png\"},{\"id\":49538742,\"identity\":\"41df4b20-2a92-4485-9ec2-1565d7e7de81\",\"added_by\":\"auto\",\"created_at\":\"2024-01-11 16:12:08\",\"extension\":\"png\",\"order_by\":12,\"title\":\"Figure 12\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":125375,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eTime series of wave run-up heights on dam in H4C17.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure12.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3835232/v1/860162c24ffc1d2b245611c3.png\"},{\"id\":49538744,\"identity\":\"5c7da5b3-6841-4593-9164-a2bb1bf206ba\",\"added_by\":\"auto\",\"created_at\":\"2024-01-11 16:12:08\",\"extension\":\"png\",\"order_by\":13,\"title\":\"Figure 13\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":509166,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e(a) to (d) Variations in key parameters for H\\u003csub\\u003e3 \\u003c/sub\\u003elandslide under different test conditions; (e) to (h) Variations in key parameters for H\\u003csub\\u003e4 \\u003c/sub\\u003elandslide under different test conditions\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"13.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3835232/v1/cd322a624e3feec466626e78.png\"},{\"id\":49538746,\"identity\":\"e1a1b860-609a-48eb-b9f5-1bc0b450fa51\",\"added_by\":\"auto\",\"created_at\":\"2024-01-11 16:20:08\",\"extension\":\"png\",\"order_by\":14,\"title\":\"Figure 14\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":96700,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e(a) Commencement of the sliding process; (b) Midway through the sliding process; (c) Waves generated by deformation body in controlled tests.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage14.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3835232/v1/cd1ccf43140e33bccf3cf8e3.png\"},{\"id\":49538748,\"identity\":\"99dfbbf0-a51e-420e-afb7-7132224c59e2\",\"added_by\":\"auto\",\"created_at\":\"2024-01-11 16:20:08\",\"extension\":\"png\",\"order_by\":15,\"title\":\"Figure 15\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":452875,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003eThe statistical results of the key parameters of the test H4C17 with different sliding body types.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"Figure15.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3835232/v1/e4a9917e33043bf63a38dc55.png\"},{\"id\":69030506,\"identity\":\"10d51184-7caa-4a5f-b8eb-c617484b1835\",\"added_by\":\"auto\",\"created_at\":\"2024-11-14 18:45:57\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":8499713,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-3711802/v2/39d178c8-8871-4d61-be21-1749463a9d13.pdf\"}],\"financialInterests\":\"No competing interests reported.\",\"formattedTitle\":\"Large-scale three-dimensional experimental investigation on potential high position landslide‑induced waves in Gushui Reservoir, China\",\"fulltext\":[{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eLandslide‑induced waves are important formative mode in hazard chain of wading landslides, which have always been practically hot research topics in fields of engineering geology, hydraulic engineering, disaster prevention and mitigation engineering (Panizzo et al. \\u003cspan citationid=\\\"CR31\\\" class=\\\"CitationRef\\\"\\u003e2005b\\u003c/span\\u003e, Sassa \\u003cspan citationid=\\\"CR32\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e, Shanmugam and Wang \\u003cspan citationid=\\\"CR34\\\" class=\\\"CitationRef\\\"\\u003e2015\\u003c/span\\u003e, Tang et al. \\u003cspan citationid=\\\"CR36\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e). Geological disasters such as large-scale landslides and collapses around river channels and reservoirs may block rivers and produce huge surges, which seriously threaten the safety of waterways, residents, and engineering projects along the reservoir area, and even dams and hydropower stations (Ataie-Ashtiani and Nik-Khah \\u003cspan citationid=\\\"CR2\\\" class=\\\"CitationRef\\\"\\u003e2008\\u003c/span\\u003e, Davidson and McCartney \\u003cspan citationid=\\\"CR11\\\" class=\\\"CitationRef\\\"\\u003e1975\\u003c/span\\u003e, De Carvalho and Antunes do Carmo \\u003cspan citationid=\\\"CR12\\\" class=\\\"CitationRef\\\"\\u003e2007\\u003c/span\\u003e, Van Asch et al. \\u003cspan citationid=\\\"CR37\\\" class=\\\"CitationRef\\\"\\u003e2007\\u003c/span\\u003e). The best well-known example is the Vajont landslide in Italy on October 9, 1963. The massive surges caused by nearly 270\\u0026nbsp;million m\\u003csup\\u003e3\\u003c/sup\\u003e of rock debris poured into the reservoir, which obliterated five surrounding towns and killed about 2000 people. The devastating disaster and financial losses shocked the whole engineering and technology industry (Kilburn and Petley \\u003cspan citationid=\\\"CR24\\\" class=\\\"CitationRef\\\"\\u003e2003\\u003c/span\\u003e, Panizzo et al. \\u003cspan citationid=\\\"CR30\\\" class=\\\"CitationRef\\\"\\u003e2005a\\u003c/span\\u003e). In recent years, these hazards have been extremely prevalent all over the world. On July 20, 2009, the Huangtian landslide triggered by rainfall in the Xiaowan reservoir in Southwest China killed approximately 14 people (Huang C et al. \\u003cspan citationid=\\\"CR23\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e, Xu et al. \\u003cspan citationid=\\\"CR41\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). The impulse wave of more than 5 m induced by the Hongyanzi landslide in the Three Gorges Reservoir Area (TGRA) caused 2 deaths on June 24, 2015 (Xiao et al. \\u003cspan citationid=\\\"CR40\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e, Zhou et al. \\u003cspan citationid=\\\"CR50\\\" class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e). A cascading rainfall-landslide-tsunami event occurred on 29 June 2022 in a lake in Southern Chile after 4 days of heavy rains. The landslide with a total volume of 1.05\\u0026times;10\\u003csup\\u003e4\\u003c/sup\\u003e m\\u003csup\\u003e3\\u003c/sup\\u003e that generated a tsunami with an initial tsunami amplitude of about 1 m. The event resulted in the collapse of a pedestrian bridge and overturning other mooring facilities in the lake and the coast (Ar\\u0026aacute;nguiz et al. \\u003cspan citationid=\\\"CR1\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e). The examples reiterated the catastrophic nature of landslide-induced waves.\\u003c/p\\u003e \\u003cp\\u003eThe variation of water level is a major trigger factor to induce new landslides and revive old landslides in reservoirs (Dai et al. \\u003cspan citationid=\\\"CR10\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e, Fujita \\u003cspan citationid=\\\"CR17\\\" class=\\\"CitationRef\\\"\\u003e1977\\u003c/span\\u003e, Zhang et al. \\u003cspan citationid=\\\"CR49\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e). At the initial stage of reservoir impoundment, the slope exposed to air is softened by water immersion, which results in a significant reduction in its shear strength. For the rock landslide with poor permeability, the water buoyancy on the leading edge also aggravates the deformation and failure of the landslide. Meanwhile, large hydropower stations often have tens of meters of water level fluctuation zones during operation. When water level plummets, the dissipation of pore water lags the dissipation of external water, and the pore water pressure and hydrodynamic pressure formed are not conducive to anti-sliding stability of landslides. On the contrary, the rapid rise of water level will sharply raise the groundwater level in the landslide and reduce its slip resistance. The Baihetan Hydropower Station on the lower reaches of the Jinsha River is the second largest hydropower station in China after the Three Gorges Hydropower Station. In the process of reservoir impoundment, the Wangjiashan landslide, Tuandigou landslide and Wulipo landslide have deformed to different degrees (Chen et al. \\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e, Cheng et al. \\u003cspan citationid=\\\"CR9\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e, Yi et al. \\u003cspan citationid=\\\"CR46\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e). Landslides induced by reservoir impoundment have gradually become a contentious issue in the Baihetan reservoir area (Li et al. \\u003cspan citationid=\\\"CR26\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e, Yang et al. \\u003cspan citationid=\\\"CR44\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e). In addition, earthquake, rainfall, artificial disturbance, and other factors will further aggravate the possibility of geological disasters in reservoir area, especially landslide‑induced waves (Demirel and Aydin \\u003cspan citationid=\\\"CR13\\\" class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e, Wang et al. \\u003cspan citationid=\\\"CR38\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e, Yan et al. \\u003cspan citationid=\\\"CR43\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eThe whole process of landslide-generated waves can be divided into five stages: the instability of the landslide, their motion, the generation of waves, their propagation, and the effects of the waves on the affected body, which is an interaction with the gas, liquid and solid (Chen et al. \\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003ea, Laurmaa et al. \\u003cspan citationid=\\\"CR25\\\" class=\\\"CitationRef\\\"\\u003e2018\\u003c/span\\u003e, Mao et al. \\u003cspan citationid=\\\"CR27\\\" class=\\\"CitationRef\\\"\\u003e2020\\u003c/span\\u003e, Tan and Chen \\u003cspan citationid=\\\"CR35\\\" class=\\\"CitationRef\\\"\\u003e2017\\u003c/span\\u003e). Five methods can be adopted to investigate landslide dangers and the catastrophic effects of landslide-induced waves: field analytical investigations, empirical equations, numerical simulations, general physical model tests and prototype physical model tests (Chang and Wang \\u003cspan citationid=\\\"CR5\\\" class=\\\"CitationRef\\\"\\u003e2011\\u003c/span\\u003e, Fritz et al. \\u003cspan citationid=\\\"CR16\\\" class=\\\"CitationRef\\\"\\u003e2009\\u003c/span\\u003e, Yu et al. \\u003cspan citationid=\\\"CR48\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e). Due to the strong occurrence of landslide-induced waves and the rapid disappearance of residual water traces on both sides of the river, the actual measurement data are extremely rare, which leads to the limitation of case study and increases the research difficulty. Most of the general physical model tests mainly focus on the mechanism research of landslide-induced waves, which are simplified without fully considering the complex conditions. And the relationship between each stage of landslide-induced waves is artificially separated (Bregoli et al. \\u003cspan citationid=\\\"CR4\\\" class=\\\"CitationRef\\\"\\u003e2017\\u003c/span\\u003e, Fritz et al. \\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e2004\\u003c/span\\u003e, Heller and Spinneken \\u003cspan citationid=\\\"CR20\\\" class=\\\"CitationRef\\\"\\u003e2015\\u003c/span\\u003e, McFall and Fritz \\u003cspan citationid=\\\"CR28\\\" class=\\\"CitationRef\\\"\\u003e2016\\u003c/span\\u003e). In sharp contrast, prototype physical model tests mainly are used to solve a single practical engineering problem. The whole process of landslide-induced waves can be visually reproduced or rehearsed to obtain mass of data under different constraints. These data are interrelated and can be systematically analyzed (Chen et al. \\u003cspan citationid=\\\"CR8\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003eb, Deng et al. \\u003cspan citationid=\\\"CR14\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e, Xue et al. \\u003cspan citationid=\\\"CR42\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e). Prototype physical model tests are not a widely used method due to the huge cost, large-scale, and long construction time required. However, for such complex research objects, prototype physical model tests are still the best method mentioned above. Yin et al. (\\u003cspan citationid=\\\"CR47\\\" class=\\\"CitationRef\\\"\\u003e2012\\u003c/span\\u003e) took the channel of Baishuihe landslide in TGRA as prototype, established the river physical model in map scale 1:200, and thus developed landslide surge three-dimensional physical model experiment by adopting the experimental control system and measurement system. Han et al. (\\u003cspan citationid=\\\"CR19\\\" class=\\\"CitationRef\\\"\\u003e2022\\u003c/span\\u003e) studied the effects of sharply curved river bends on the wave transmission and run-up features of breaking waves in a 90\\u0026deg; channel bend, and the derived run-up equations were applied to a field case in TGRA. Based on Gongjiafang landslide in TGRA and the Wangjiashan landslide in Baihetan reservoir area, Huang BL et al (\\u003cspan citationid=\\\"CR21\\\" class=\\\"CitationRef\\\"\\u003e2014\\u003c/span\\u003e, \\u003cspan citationid=\\\"CR22\\\" class=\\\"CitationRef\\\"\\u003e2023\\u003c/span\\u003e) set up the large scale three-dimensional physical model with a scale of 1:200 and 1:150, respectively. The law of wave interaction deeply explored, and the difference of attenuation rate between wave propagation and run-up process were described in detail.\\u003c/p\\u003e \\u003cp\\u003eThe above cases are aimed at the surge problem of typical partially submerged landslide, and there are few reports on high position landslide‑induced waves above the water. In this paper, large scale three-dimensional experiments of potential high position landslide‑induced waves were carried out based on the Meilishi (MLS) landslide in Gushui (GS) reservoir area, China. Water level and the maximum sliding velocity into water were selected as independent variables in the experiments. The laws of wave generation and propagation were analyzed under varied test conditions, and the times to reach the dam after the wave generation were predicted. Statistics and methods in this paper contribute to the understanding of high position landslide‑induced waves.\\u003c/p\\u003e\"},{\"header\":\"Overview of the MLS landslide\",\"content\":\"\\u003cp\\u003eThe GS hydropower station is a large-scale step hydropower project in the Lancang River and is located in Deqin County of the Diqing Tibetan Autonomous Prefecture, Yunnan Province (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e), which normal water level, dead water level, and construction water level are 2267m, 2230m, and 2128.65m, respectively. The retaining structure is a concrete faced rockfill dam with a maximum height of 240m. Extensive field survey and engineering investigations of this landslide have been performed by PowerChina Kunming Engineering Corporation Limited. Furthermore, three field investigations were conducted by the authors of this paper in June 2022, August 2022, and April 2023. The geotechnical properties, hydrogeological circumstances, and form features of the MLS landslide were adequately recognized based on these works. As shown in Figs.\\u0026nbsp;\\u003cspan refid=\\\"Fig1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e and \\u003cspan refid=\\\"Fig2\\\" class=\\\"InternalRef\\\"\\u003e2\\u003c/span\\u003e, the MLS landslide is located about 4\\u0026thinsp;~\\u0026thinsp;5km upstream of the dam site, which is composed of four individual landslides with shape of isosceles trapezoid, named H\\u003csub\\u003e3\\u003c/sub\\u003e, H\\u003csub\\u003e4\\u003c/sub\\u003e, H\\u003csub\\u003e5\\u003c/sub\\u003e, and H\\u003csub\\u003e6\\u003c/sub\\u003e, with corresponding volumes of 1907\\u0026times;10\\u003csup\\u003e4\\u003c/sup\\u003e, 1428\\u0026times;10\\u003csup\\u003e4\\u003c/sup\\u003e, 200\\u0026times;10\\u003csup\\u003e4\\u003c/sup\\u003e, and 100\\u0026times;10\\u003csup\\u003e4\\u003c/sup\\u003e m\\u003csup\\u003e3\\u003c/sup\\u003e, respectively. This valley presents a topography with a steep below and gentle above surface. The distribution altitudes of H\\u003csub\\u003e3\\u003c/sub\\u003e and H\\u003csub\\u003e4\\u003c/sub\\u003e are relatively high, approximately between 2600 and 3250 m. The distance between H\\u003csub\\u003e3\\u003c/sub\\u003e and H\\u003csub\\u003e4\\u003c/sub\\u003e is 300m, with the mountain ridge as the boundary. They are formed by the toppling, breaking, and sliding of layered rock masses. The basalt is exposed at their front edges, acting as a large retaining wall. The Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e depicts the typical geological profile of H\\u003csub\\u003e3\\u003c/sub\\u003e, indicates that it is mainly composed of surface colluvium layer, loose accumulation layer, sliding weak zone, and bedrock. There is an obvious boundary between the colluvium layer and the accumulation layer, and the surface of bedrock is more fragmented. The sliding weak zone exposed in exploration adit PD2004 (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig3\\\" class=\\\"InternalRef\\\"\\u003e3\\u003c/span\\u003e) is at the bottom of the landslide, which shows yellow-brown clay mixed with gravel, and the gravel content is between 5 and 10%. The geomechanics of H\\u003csub\\u003e4\\u003c/sub\\u003e and H\\u003csub\\u003e3\\u003c/sub\\u003e are very similar. The altitudes of the landslide toe and head scarp of H\\u003csub\\u003e5\\u003c/sub\\u003e and H\\u003csub\\u003e6\\u003c/sub\\u003e are 2130 and 2400 m, respectively. Their main components were formed by H\\u003csub\\u003e4\\u003c/sub\\u003e accumulated in the valley after sliding.\\u003c/p\\u003e \\u003cp\\u003eWhen the reservoir water level is raised to 2267 m, most of the relatively stable H\\u003csub\\u003e5\\u003c/sub\\u003e and H\\u003csub\\u003e6\\u003c/sub\\u003e landslides will be underwater, so they will not be used as controlling factors in subsequent studies. The local areas of H\\u003csub\\u003e3\\u003c/sub\\u003e and H\\u003csub\\u003e4\\u003c/sub\\u003e are still in the creep deformation stage now. From October 2014 to December 2020, the average deformation rate of H\\u003csub\\u003e3\\u003c/sub\\u003e was 0.77 mm per year, and the average deformation rate of H\\u003csub\\u003e4\\u003c/sub\\u003e was 6.86 mm per year (Guo et al. \\u003cspan citationid=\\\"CR18\\\" class=\\\"CitationRef\\\"\\u003e2021\\u003c/span\\u003e). The stability assessment of H\\u003csub\\u003e3\\u003c/sub\\u003e and H\\u003csub\\u003e4\\u003c/sub\\u003e cannot meet the engineering design requirements, and which are characterized by large scale and high shear crack in narrow valley. Once the landslides become unstable, it is easy to cause chain hazard such as river blockage or surges, which will seriously threaten the safety of dam, waterways, and river coast in reservoir. Therefore, the problem of potential impulse waves induced by high position landslide needs to be paid serious attention.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e\"},{\"header\":\"Methodologies used in the physical experiments\",\"content\":\"\\u003cdiv id=\\\"Sec4\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eSet up of the physical model\\u003c/h2\\u003e \\u003cp\\u003eThe three-dimensional physical model was built at Water Flow Experiment Center of Hohai University, which is mainly consist of landslide scale model, river scale model, the dam scale model, hydraulic structures scale model, water flow circulation system, etc. According to the Froude similarity criterion, when the geometric scale was 1: 150, the time and velocity scale was 1: \\u003cspan class=\\\"InlineEquation\\\"\\u003e\\u003cspan class=\\\"mathinline\\\"\\u003e\\\\(\\\\surd 150\\\\)\\u003c/span\\u003e\\u003c/span\\u003e and the density scale and gravitational acceleration was 1:1. The scaled model had a length of 57 m and a width of 27 m and resembled an about 8 km stretch of the river from MLS landslide location to the dam site area. The average elevation of the bottom of the natural valley is approximately 2060 m, the maximum height of the river scaled model is 3.6 m, and the maximum height of the landslide scaled model is 8 m (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig4\\\" class=\\\"InternalRef\\\"\\u003e4\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003eThe landslide motion is simulated by an adaptive starting device based on velocity equivalence. The device includes a sliding box, jacks, high-pressure oil pumps, starting valves, etc. The elevations of both landslides shear exits are approximately 2600m. The terrain slope in the area below the landslide shear exit is steep, and the slope foot is generally 35\\u0026thinsp;~\\u0026thinsp;40\\u0026deg;. The area is poured with concrete following the original topography. Two sliding boxes are provided above the shearing exit. Since the bottom surfaces of the landslides are all in the shape of a knife and only small areas of the front and rear edges are arc-shaped, the bottom surface of the sliding box can be simplified to a flat slope. The inclination angle of the sliding box is set to the average slope of the actual landslide. Different sliding velocities of landslide body can be obtained by changing the bottom surface material and adjusting the inclination angle of the sliding box with the high-pressure oil pumps and starting valves, which need to be kept within the preset level range. The starting valve is set on the front edge of the sliding box, which controls the downward reversal of the sliding door, allowing the initially stable sliding body to start in place. The river scale model is made of cement, sand, bricks, and steel bars using the fracture plate method, and each panel section is spaced approximately 0.5 m apart. The contour method is used in areas with complex terrain, and each contour line is spaced approximately 0.05 m apart. The water circulation system uses water pumps to pump water from underground reservoirs to achieve model water supply. There are water level probes inside the model to record the water level heights to meet the needs of different water depths in the test. There is also a crane in the upstream area to transport and lift the sliding body during repeated tests and speed up the test progress.\\u003c/p\\u003e \\u003cp\\u003eIn landslide‑induced waves physical tests, landslides are generally simplified into three modes, including rigid body, granular body, and deformation body. The sliding body is made of granular body in this test, and the granular materials are black pebbles. The granular particle density of black pebbles is about 1.5\\u0026thinsp;~\\u0026thinsp;1.6 g/cm\\u003csup\\u003e3\\u003c/sup\\u003e, and the maximum particle size is 6\\u0026thinsp;~\\u0026thinsp;8cm. The Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e is the particle size distribution curve of the landslide body, and regions ①, ②, ③ and ④ correspond to the proportions of 0.075\\u0026thinsp;~\\u0026thinsp;2mm, 2\\u0026thinsp;~\\u0026thinsp;10 mm, 10\\u0026thinsp;~\\u0026thinsp;20mm, 20\\u0026thinsp;~\\u0026thinsp;60mm particle size respectively. According to the actual particle size and scale of the landslide, the four-particle size black pebbles are proportioned according to 2.5: 2.5: 1: 1.5. Different from common landslide-induced wave experiments, this study only used the model similarity of the sliding velocity, not of the rheological behavior of the landslide (Ataie-Ashtiani and Shobeyri \\u003cspan citationid=\\\"CR3\\\" class=\\\"CitationRef\\\"\\u003e2008\\u003c/span\\u003e, Yavari-Ramshe and Ataie-Ashtiani \\u003cspan citationid=\\\"CR45\\\" class=\\\"CitationRef\\\"\\u003e2019\\u003c/span\\u003e). A large amount of data prove that the sliding velocity is one of the most important factors controlling the characteristics of wave height (Fritz et al. \\u003cspan citationid=\\\"CR15\\\" class=\\\"CitationRef\\\"\\u003e2004\\u003c/span\\u003e, Noda \\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e1970\\u003c/span\\u003e, Scheidegger \\u003cspan citationid=\\\"CR33\\\" class=\\\"CitationRef\\\"\\u003e1973\\u003c/span\\u003e, Wang et al. \\u003cspan citationid=\\\"CR39\\\" class=\\\"CitationRef\\\"\\u003e2012\\u003c/span\\u003e).\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec5\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eMeasurement system and technology\\u003c/h2\\u003e \\u003cp\\u003eA full elements measuring system and tracking technology based on hydrodynamics are independently developed, which includes the wave height testing system, the sliding velocity testing system, and the video collection system. The wave height testing system is obtained by outputting electrical signals to the computer from the DYS50-3000 digital wave height collector. The sampling frequency is 50 Hz, and the accuracy is 0.1 mm. The Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig6\\\" class=\\\"InternalRef\\\"\\u003e6\\u003c/span\\u003e shows that the scale model has a total of 22 wave height measurement points, 8 in the near field area, 11 along the river, and 3 near the dam area. The collector at the dam site location is assigned a station ID 0\\u0026thinsp;+\\u0026thinsp;000 m, and the station IDs of the other collectors are respectively 0\\u0026ndash;017 m, 0\\u0026ndash;241 m, 0\\u0026ndash;606 m, 0\\u0026ndash;977 m, 0\\u0026ndash;1293 m, 0\\u0026ndash;1655 m, 0\\u0026ndash;2065 m, 0\\u0026ndash;2573 m, 0\\u0026ndash;3107 m, 0\\u0026ndash;3637 m, 0\\u0026ndash;4161 m, 0\\u0026ndash;4726 m, 0\\u0026ndash;5300 m, and 0\\u0026ndash;5835 m. Contour scales are also drawn on both sides of the river, with a ruler accuracy of 0.01m, to facilitate the observation of climbing waves along the river coast (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig5\\\" class=\\\"InternalRef\\\"\\u003e5\\u003c/span\\u003e). The sliding velocity is measured using an attitude meter and a turntable contact speedometer, respectively. The attitude meter is fixed inside the sliding body, measures its acceleration, and obtains the velocity-time curve by integrating over time. The turntable contact speedometer is used as an auxiliary test equipment, and the error between its test results and the attitude meter is within 2% in the preliminary experiment. The video collection system mainly consists of high-definition cameras, drone photography and real-time collection devices. The 4 high- definition cameras are used to observe the process of landslides falling into water. The 11 high-definition cameras simultaneously recorded at a frequency of 50 fps, basically covering the entire range of the physical model flow field, which had 1600\\u0026times;2500 pixels. Drones are used to assist in capturing landslide or surge images at key locations.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec6\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eDesign of the experimental program\\u003c/h2\\u003e \\u003cp\\u003eThe experimental program is shown in Table\\u0026nbsp;\\u003cspan refid=\\\"Tab1\\\" class=\\\"InternalRef\\\"\\u003e1\\u003c/span\\u003e. Water level and maximum sliding velocity are two independent variables. Since H\\u003csub\\u003e3\\u003c/sub\\u003e and H\\u003csub\\u003e4\\u003c/sub\\u003e slide independently, 9 sets of tests were designed for each landslide. According to the results of landslide stability assessment and instability mode analysis, the potential instability volume of H\\u003csub\\u003e3\\u003c/sub\\u003e and H\\u003csub\\u003e4\\u003c/sub\\u003e are 1907\\u0026times;10\\u003csup\\u003e4\\u003c/sup\\u003e and 1428\\u0026times;10\\u003csup\\u003e4\\u003c/sup\\u003e m\\u003csup\\u003e3\\u003c/sup\\u003e. The equivalent instability volumes converted through similarity criterion are 5.65, and 4.23 m\\u003csup\\u003e3\\u003c/sup\\u003e, respectively. The Water levels are 0.46m, 1.13m, and 1.38m respectively, corresponding to the water level elevations of 2128.65m, 2230m, and 2267m. In order to delineate the impact of sliding velocity on wave height, different materials are used to adjust the friction coefficient of the sliding bottom surface under in same water level. The velocity refers to the maximum sliding velocity corresponding to the barycenter of the sliding body entering the water. Controlling the three-dimensional landslide sliding velocity is challenging, the experimental data are widely dispersed. Therefore, multiple parallel experiments were carried out to control the final data fluctuation within the range of \\u0026plusmn;\\u0026thinsp;0.02 m/s. The data below are the prototype values unless otherwise specified.\\u003c/p\\u003e \\u003cp\\u003e \\u003cdiv class=\\\"gridtable\\\"\\u003e\\u003ctable float=\\\"Yes\\\" id=\\\"Tab1\\\" border=\\\"1\\\"\\u003e \\u003ccaption language=\\\"En\\\"\\u003e \\u003cdiv class=\\\"CaptionNumber\\\"\\u003eTable 1\\u003c/div\\u003e \\u003cdiv class=\\\"CaptionContent\\\"\\u003e \\u003cp\\u003eExperimental design of the MLS landslide under different working conditions\\u003c/p\\u003e \\u003c/div\\u003e \\u003c/caption\\u003e \\u003ccolgroup cols=\\\"8\\\"\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c1\\\" colnum=\\\"1\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c2\\\" colnum=\\\"2\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c3\\\" colnum=\\\"3\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c4\\\" colnum=\\\"4\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c5\\\" colnum=\\\"5\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c6\\\" colnum=\\\"6\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c7\\\" colnum=\\\"7\\\"\\u003e\\u003c/div\\u003e \\u003cdiv align=\\\"left\\\" class=\\\"colspec\\\" colname=\\\"c8\\\" colnum=\\\"8\\\"\\u003e\\u003c/div\\u003e \\u003ctbody\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eWorking condition\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\" morerows=\\\"1\\\" rowspan=\\\"2\\\"\\u003e \\u003cp\\u003eLandslide name\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c4\\\" namest=\\\"c3\\\"\\u003e \\u003cp\\u003eLandslide volume (m\\u003csup\\u003e3\\u003c/sup\\u003e)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c6\\\" namest=\\\"c5\\\"\\u003e \\u003cp\\u003eWater level (m)\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colspan=\\\"2\\\" nameend=\\\"c8\\\" namest=\\\"c7\\\"\\u003e \\u003cp\\u003eMaximum sliding velocity (m/s)\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\"\\u003e \\u003cp\\u003ePrototype\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\"\\u003e \\u003cp\\u003eModel\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\"\\u003e \\u003cp\\u003ePrototype\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\"\\u003e \\u003cp\\u003eModel\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003ePrototype\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003eModel\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eH3C01\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\" morerows=\\\"8\\\" rowspan=\\\"9\\\"\\u003e \\u003cp\\u003eH\\u003csub\\u003e3\\u003c/sub\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\" morerows=\\\"8\\\" rowspan=\\\"9\\\"\\u003e \\u003cp\\u003e1907\\u0026times;10\\u003csup\\u003e4\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\" morerows=\\\"8\\\" rowspan=\\\"9\\\"\\u003e \\u003cp\\u003e5.65\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e \\u003cp\\u003e2128.65\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e \\u003cp\\u003e0.46\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e65.35\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e5.34\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eH3C02\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e71.12\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e5.81\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eH3C03\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e82.16\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e6.71\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eH3C04\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e \\u003cp\\u003e2230\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e \\u003cp\\u003e1.13\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e65.77\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e5.37\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eH3C05\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e74.59\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e6.09\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eH3C06\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e80.71\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e6.59\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eH3C07\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e \\u003cp\\u003e2267\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e \\u003cp\\u003e1.38\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e66.01\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e5.39\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eH3C08\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e70.91\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e5.79\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eH3C09\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e83.53\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e6.82\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eH4C10\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c2\\\" morerows=\\\"8\\\" rowspan=\\\"9\\\"\\u003e \\u003cp\\u003eH\\u003csub\\u003e4\\u003c/sub\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c3\\\" morerows=\\\"8\\\" rowspan=\\\"9\\\"\\u003e \\u003cp\\u003e1428\\u0026times;10\\u003csup\\u003e4\\u003c/sup\\u003e\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c4\\\" morerows=\\\"8\\\" rowspan=\\\"9\\\"\\u003e \\u003cp\\u003e4.23\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e \\u003cp\\u003e2128.65\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e \\u003cp\\u003e0.46\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e69.61\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e5.68\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eH4C11\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e80.33\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e6.56\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eH4C12\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e89.29\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e7.29\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eH4C13\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e \\u003cp\\u003e2230\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e \\u003cp\\u003e1.13\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e72.27\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e5.90\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eH4C14\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e79.70\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e6.51\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eH4C15\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e91.00\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e7.43\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eH4C16\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c5\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e \\u003cp\\u003e2267\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c6\\\" morerows=\\\"2\\\" rowspan=\\\"3\\\"\\u003e \\u003cp\\u003e1.38\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e70.55\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e5.76\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eH4C17\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e83.41\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e6.81\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003ctr\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c1\\\"\\u003e \\u003cp\\u003eH4C18\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c7\\\"\\u003e \\u003cp\\u003e91.61\\u003c/p\\u003e \\u003c/td\\u003e \\u003ctd align=\\\"left\\\" colname=\\\"c8\\\"\\u003e \\u003cp\\u003e7.48\\u003c/p\\u003e \\u003c/td\\u003e \\u003c/tr\\u003e \\u003c/tbody\\u003e \\u003c/colgroup\\u003e \\u003c/table\\u003e\\u003c/div\\u003e \\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Experimental analyses\",\"content\":\"\\u003cdiv id=\\\"Sec8\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eProcess of landslide movement\\u003c/h2\\u003e \\u003cp\\u003eTaking the classic working condition H4C17 as an example, the experimental analysis was carried out. As shown in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig7\\\" class=\\\"InternalRef\\\"\\u003e7\\u003c/span\\u003e, it took about 120 s for the landslide to slide completely into the water. The landslide moved in the form of a debris flow accompanied by white smoke produced by friction. Figure\\u0026nbsp;\\u003cspan refid=\\\"Fig8\\\" class=\\\"InternalRef\\\"\\u003e8\\u003c/span\\u003e showed the time series of the average acceleration and velocity of the landslide in H4C17. It is obvious that the entire process from the start of the landslide to the entry into the water is not uniform acceleration or deceleration. The acceleration of the sliding body fluctuates with time, which is caused by certain differences in the kinetic friction coefficients in each area of the sliding surface. Overall, the acceleration first increases and then gradually decreases with time. Air resistance exists but is basically negligible at this stage. The time series of the average velocity curve can be mainly divided into three stages:\\u003c/p\\u003e \\u003cp\\u003e(1) Slow acceleration stage: The sliding velocity increases slowly and linearly with a lower slope from the beginning to the front edge of the sliding body in contact with water.\\u003c/p\\u003e \\u003cp\\u003e(2) Acceleration stage: The gravitational potential energy of the sliding body is quickly converted into kinetic energy during this stage. Most of the sliding bodies slide out of the shear exit position and further accelerate on the sliding surface along the way. When the barycenter of the sliding body enters the water, the velocity reaches its maximum value.\\u003c/p\\u003e \\u003cp\\u003e(3) Rapid deceleration stage: The landslide quickly decelerates and gradually stops moving under the combined action of scraping friction resistance and water resistance after entering the water. Some of the sliding bodies hit the bottom of the valley, and some of them accumulate on the lower bodies. The velocity curves show a dramatical decline, and the acceleration becomes negative. Ultimately, acceleration and velocity will fluctuate around zero due to inertia.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec9\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eGeneration features of waves in near field\\u003c/h2\\u003e \\u003cp\\u003eThe near field area is a small range of waves-affected area near the water entry point of the landslide body. An obvious arc-shaped wave crater is formed due to the impact of the landslide into the water at high speed (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig7\\\" class=\\\"InternalRef\\\"\\u003e7\\u003c/span\\u003e). The impulse waves propagate to the surroundings in the form of a ring wave and reaches the opposite bank 75 seconds later and then the waves are reflected. Because the river channel is narrow, the reflected wave and subsequent incoming waves meet quickly, creating more reflections and superpositions, and resulting water in oscillating back and forth in the river channel. Figure\\u0026nbsp;\\u003cspan refid=\\\"Fig9\\\" class=\\\"InternalRef\\\"\\u003e9\\u003c/span\\u003e shows time series of free surface elevation of wave height collectors along the sliding direction in H4C17. Different from underwater landslides and partially submerged landslides, subaerial landslides generally generate wave crests first and then troughs, and the wave crests are larger than the wave troughs. In the early stage, the wave height changed drastically, and the digital wave height collectors recorded a total of three waves in 150 s. Results of the experiments show that the general patterns of waves in all series are the same, but the amplitudes and periods vary. The first two waves have similar amplitudes, and the amplitude of the third wave begins to decrease significantly, and the period gradually becomes longer.\\u003c/p\\u003e \\u003cp\\u003eThe MLS landslide is a typical high-altitude landslide, and its high potential energy is converted into high kinetic energy, resulting in a large speed of the sliding body, so the Froude number is much larger than 1. The relative thickness of the landslide is calculated to be between 0.15 and 0.45. So impulse waves are classified as nonlinear transition waves of type B according to the near-field wave theory of Noda (\\u003cspan citationid=\\\"CR29\\\" class=\\\"CitationRef\\\"\\u003e1970\\u003c/span\\u003e). The first wave is generated when the sliding body enters the water, and the height of the first wave is obviously higher than other waves. Then the amplitude decreases rapidly, and the wave shape becomes dispersive. The wave curve shows an oscillating trend over time, and the wave amplitude does not decrease step by step, and the wave amplitude fluctuates up and down in some areas. With the continuous dissipation of energy, the wave gradually tends to fluctuate periodically, and the wave height changes gradually become stable and eventually approach zero.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec10\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003ePropagation features of waves in far field\\u003c/h2\\u003e \\u003cp\\u003eFigure\\u0026nbsp;\\u003cspan refid=\\\"Fig10\\\" class=\\\"InternalRef\\\"\\u003e10\\u003c/span\\u003e and \\u003cspan refid=\\\"Fig11\\\" class=\\\"InternalRef\\\"\\u003e11\\u003c/span\\u003e reflect the surge process in the river channel, especially the interaction process over time and space. The ordinate in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig10\\\" class=\\\"InternalRef\\\"\\u003e10\\u003c/span\\u003e represents the wave heights at different spatial locations. It is obvious that the first four independent impulse waves propagated to the downstream river channel, with a maximum wave crest of 26.85m and a period of about 20s in the gray area ①. With the passage of time and space, the wave trough gradually becomes smaller, and the waves slowly overlap. The shape of waves gradually changes from a single peak to a smooth shape, the amplitude steadily attenuates, and the period becomes longer. When it reaches the dam, the first four rows of solitary waves have formed a large peak wave. At the same time, the large peak wave is followed by some small amplitude waves. This is because the impulse waves will be reflected when they are transmitted to the solid wall of the riverbank. And more reflected waves produced by secondary interaction between the reflected wave and incoming wave. The yellow area ② in Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig10\\\" class=\\\"InternalRef\\\"\\u003e10\\u003c/span\\u003e is the wave propagation process after the interaction between impulse waves and reflected waves. The wave shape in this area is irregular, and the wave curves appear to be multi-peaked in each period. The wave period is extremely unstable, the frequency is accelerated, and larger wave crests can also be formed in the process.\\u003c/p\\u003e \\u003cp\\u003eFigure\\u0026nbsp;\\u003cspan refid=\\\"Fig11\\\" class=\\\"InternalRef\\\"\\u003e11\\u003c/span\\u003e shows the distribution law of waves propagation and attenuation in the river channel. The wave height is affected by changes in the river topography and direction. It shows obvious topographic correlation and is difficult to quantify. The attenuation of the wave amplitude along the center of the river is obviously not a constant attenuation, but an undulating attenuation. The waves climb to a certain extent when it reaches the dam site. The whole process can be divided into a sharp attenuation stage and a gentle attenuation stage. The sharp attenuation stage shows an exponential decline pattern. The wave heights within 1km attenuate by more than 15m, accounting for 58% of the maximum wave height. The average wave attenuation within 100m is 1.5m. Beyond 1km, the wave heights attenuation rate slows down, with an average wave attenuation of about 1.15m per 1km. However, the wave heights still change significantly in the trenches and gullies areas.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec11\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eEffects of impulse wave on the dam area\\u003c/h2\\u003e \\u003cp\\u003eFigure\\u0026nbsp;\\u003cspan refid=\\\"Fig12\\\" class=\\\"InternalRef\\\"\\u003e12\\u003c/span\\u003e shows time series of wave run-up height on dam curve. Among them, the wave heights collected by digital wave height collectors #1, #2 and #3 are 11.75m, 11.88m and 12.15m respectively, corresponding to the left bank, middle and right bank of the dam. There is a large-angle terrain in front of the GS Hydropower Station. When the surge arrived here, it is strongly affected by the change of the river topography on the one hand, and the surge propagates unevenly on the left and right banks. Overall, wave run-up height on dam shows a trend that the right bank is larger than the middle and larger than the left bank. On the other hand, due to the uplift of the dam topography, the surge will climb upward along the dam surface. The data shows that the impulse wave curve is relatively smooth within 880s and propagates in the form of superimposed sine waves. The curve fluctuates unstably up and down after 880 s, which is due to the inability of the energy in the model system to dissipate in time and the water surface to oscillate. Three waves hit the dam, the first of which was the largest, followed by two smaller waves. For the first wave, the crest is slightly larger than the trough, and the fluctuation period is about 100s. The first wave can be used as an ideal waveform input to predict subsequent surge propagation. After 880s, the amplitude of impulse wave is small, the period is relatively chaotic, the crest line is not obvious, and it is difficult to identify the crest and trough directly. This also makes the surge in the formation and propagation process has a certain degree of concealment and confusion, which is not conducive to identification and emergency warning.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e \\u003cdiv id=\\\"Sec12\\\" class=\\\"Section2\\\"\\u003e \\u003ch2\\u003eVariation law of key parameters under different working conditions\\u003c/h2\\u003e \\u003cp\\u003eFigure\\u0026nbsp;\\u003cspan refid=\\\"Fig13\\\" class=\\\"InternalRef\\\"\\u003e13\\u003c/span\\u003e summarizes key parameters such as head wave height, wave run-up height on the opposite bank, wave run-up height on dam, and the propagation time under different test conditions. The head wave height, wave run-up height on the opposite bank, and wave run-up height on dam are positively correlated with sliding velocity. The smoother the sliding surface, the less work the landslide will do to overcome frictional resistance during the sliding process. The more kinetic energy is converted from gravitational potential energy, the greater sliding velocity will be. All the kinetic energy are transmitted to the water body after the sliding body enters the water, which will drive the water and create the head wave height, wave run-up height on the opposite bank, and wave run-up height on dam. For example, working conditions H3C07, H3C08 and H3C09 correspond to sliding velocities of 66.01, 70.91 and 83.53m/s respectively, and wave run-up heights on dam of 14.31, 16.11 and 17.97m respectively. The head wave height, wave run-up height on the opposite bank, and wave run-up height on dam are positively negatively correlated with water level. Different water depths and water volumes have different abilities to consume impact energy. The corresponding water levels of H3C02, H3C05 and H3C08 are 2128.65, 2230 and 2267m respectively, and waves run-up heights on dam are 19.13, 18.92 and 16.11m respectively. In addition, the topography and river curvature caused by different water levels are also different, which also has a great impact on the test results. The data show that the maximum wave run-up height on dam is 17.97 m under the most dangerous working condition (H3C09), which does not exceed the maximum height of dam, so the dam has a certain safety margin. Under different working conditions, the propagation times for the surge to reach the dam shows disorder, but it is basically within the range of 550s-750s. It can be considered that the 550s is the prime time for early warning after landslide occurrence. During this period, residents along the bank and vessels on waterway should be evacuated in a timely manner, and corresponding protective measures should be installed in the dam area. At the same time, it is also necessary to strengthen landslide deformation monitoring and real-time data feedback to lay the foundation for the early identification and early warning of disasters.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003c/div\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eTo explore the impact of sliding body materials on wave height of high position landslide‑induced waves, and to demonstrate the accuracy and reliability of the test results, the deformation body are used as a sliding body material to carry out controlled tests (Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig14\\\" class=\\\"InternalRef\\\"\\u003e14\\u003c/span\\u003e). These bodies have a certain deformation ability and are made of very soft bags filled with granular particle materials, which size is 0.8m\\u0026times;0.4m\\u0026times;0.15m. The Fig.\\u0026nbsp;\\u003cspan refid=\\\"Fig15\\\" class=\\\"InternalRef\\\"\\u003e15\\u003c/span\\u003e shows the statistical results of the key parameters of the test H4C17 using granular bodies and deformation bodies respectively. It is obviously found that the propagation and attenuation laws of wave height obtained by using granular particles and deformation bodies are similar under the same conditions of landslide volume, water level and sliding velocity, and the propagation time is also similar. There is a certain difference between the wave heights in near field and the wave heights in far field are similar. It is preliminarily believed that the sliding body shape affects waves characteristics much more in the near field than in the far field. As for the contribution of far-field wave height, the sliding body shape is much smaller than the sliding velocity factor and water level factor.\\u003c/p\\u003e \\u003cp\\u003eWhen the volume and velocity of the sliding body are the same, the total energy carried by the sliding body during the sliding process is the same. The same water level conditions determine the same energy dissipation capabilities, so the far-field wave heights are close to each other. The individual deformation body carries large amounts of energy, which ability to disturb water is much greater than that of particles, so there is a difference in near-field wave heights between the two. Since the deformation bodies will be limited in their movement posture during the sliding process of high position landslide‑induced waves, the waves will be broken and discontinuous, which will cause the test results to be unstable and have a large degree of discreteness. Therefore, the granular bodies are finally selected for this test as the sliding body material. In addition, considering that during the actual sliding process of the landslide, the landslide body does not completely disintegrate into debris, some deformation bodies can be added to granular particles to simulate the sliding body in subsequent tests.\\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e \\u003cp\\u003e \\u003c/p\\u003e\"},{\"header\":\"Conclusion\",\"content\":\"\\u003cp\\u003eThe following conclusions can be drawn with large-scale three-dimensional prototype physical model experimental investigation on potential impulse waves induced by MLS landslide:\\u003c/p\\u003e\\n\\u003cp\\u003e1. Taking the MLS landslide in the GS reservoir area as the prototype, based on the similarity theory and using a scale of 1:150, the large-scale three-dimensional physical model was established that integrated the interactions of the landslide, the river, and the dam. Water level and the maximum sliding velocity into water were selected as independent variables, and a total of 18 experiments were carried out. The methodologies used in the physical experiments in this paper can be used to predict and study similar high position landslide‑induced waves problems.\\u003c/p\\u003e\\n\\u003cp\\u003e2\\u0026middot; The adaptive landslide motion simulation system based on velocity equivalence was independently developed to simulate process of landslide movement. The landslide moved in the form of a debris flow accompanied by white smoke produced by friction, which had typical high-position long-runout landslide dynamic characteristics. The landslide movement process can be divided into three stages: slow acceleration stage, acceleration stage and rapid deceleration stage.\\u003c/p\\u003e\\n\\u003cp\\u003e3. The impulse waves propagated from the generating point to the surroundings in an arc shape, and they had nonlinear transition wave characteristics in the near field area. The data showed that a total of three larger waves were reflected on the opposite bank, and a total of four larger waves propagated downstream along the river. The superposition and reflection of these waves were all recorded by the full elements measuring system, clearly demonstrating the interaction process of waves during waves propagation.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cspan\\u003e\\u003c/span\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e4. The experimental data carefully depicted the difference in attenuation rates of waves propagation in the river channel. The whole process can be divided into a sharp attenuation stage and a gentle attenuation stage. The sharp attenuation stage showed an exponential decline pattern, and the attenuation rate was as high as about 58%. In the gentle attenuation stage, the wave height attenuation speed slowed down. The wave height was significantly affected by the changes in river topography and direction and was difficult to quantify.\\u003c/p\\u003e\\u003cspan\\u003e\\n \\u003cp\\u003e5. The large-angle terrain change in front of the GS Hydropower Station caused uneven propagation of the surge on the left and right banks. Overall, wave run-up height on dam showed a trend that the right bank is larger than the middle and larger than the left bank. A total of three larger waves were recorded impacting the dam in the form of superimposed sine waves. The crest lines of subsequent waves were not obvious, making it difficult to directly identify the crests and troughs. This also showed that the formation and propagation process of surges had a certain degree of concealment and confusion.\\u003c/p\\u003e\\n\\u003c/span\\u003e\\u003cspan\\u003e\\n \\u003cp\\u003e6. The series of test data showed that the maximum wave run-up height on dam was 17.97 m under the most dangerous working condition, which did not exceed the maximum height of dam, so the dam had a certain safety margin. The golden time of landslide risk prevention and control warning was within 550 s after landslide instability. The key parameters predicted by the tests, such as the head wave height, wave run-up height on the opposite bank, wave run-up height on dam, and the propagation time provided a technical basis and a useful reference for the dam engineering design and safety.\\u003c/p\\u003e\\n\\u003c/span\\u003e\\n\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgements\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003ePowerChina Kunming Engineering Corporation Limited is gratefully acknowledged for providing the study site and geological data.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis work was financially supported by the National Natural Science Foundation of China (51939004) and China Huaneng Group Corporation Limited (HNKJ22-H107).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eData availability\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eDeclaration of interests\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eAr\\u0026aacute;nguiz R, Caama\\u0026ntilde;o D, Espinoza M, G\\u0026oacute;mez M, Maldonado F, Sep\\u0026uacute;lveda V, Rogel I, Oyarzun JC and Duhart P (2023) Analysis of the cascading rainfall\\u0026ndash;landslide\\u0026ndash;tsunami event of June 29th, 2022, Todos los Santos Lake, Chile. Landslides 20: 801-811. https://doi.org/10.1007/s10346-022-02015-1\\u003c/li\\u003e\\n\\u003cli\\u003eAtaie-Ashtiani B, Nik-Khah A (2008) Impulsive waves caused by subaerial landslides. Environmental Fluid Mechanics 8: 263-280. https://doi.org/10.1007/s10652-008-9074-7\\u003c/li\\u003e\\n\\u003cli\\u003eAtaie-Ashtiani B, Shobeyri G (2008) Numerical simulation of landslide impulsive waves by incompressible smoothed particle hydrodynamics. International Journal for Numerical Methods in Fluids 56: 209-232. https://doi.org/10.1002/fld.1526\\u003c/li\\u003e\\n\\u003cli\\u003eBregoli F, Bateman A, Medina V (2017) Tsunamis generated by fast granular landslides: 3D experiments and empirical predictors. Journal of Hydraulic Research 55: 743-758. https://doi.org/10.1080/00221686.2017.1289259\\u003c/li\\u003e\\n\\u003cli\\u003eChang C-H, Wang K-H (2011) Generation of three-dimensional fully nonlinear water waves by a submerged moving object. 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Landslides 13: 589-601. https://doi.org/10.1007/s10346-016-0704-8\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":false,\"highlight\":\"\",\"institution\":\"Hohai University\",\"isAcceptedByJournal\":true,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true},\"keywords\":\"High position landslide‑induced waves, Large-scale three-dimensional experiment, Prototype physical model, Gushui Reservoir, Meilishi landslide\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-3711802/v2\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-3711802/v2\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eThe occurrence of landslides in reservoir areas and the potential secondary disasters near dams are characterized by their sudden and catastrophic nature, often limiting the availability of actual measurement data. To address this challenge, prototype physical model test always proves to be valuable method to replicate or reproduce such geological hazards. In this study, we focused on the Meilishi landslide in the Gushui reservoir area as a case study to analyze the potential threat of high position landslide-induced waves under gravity. Based on field investigations and relevant statistical geological data, a large-scale three-dimensional physical model was carried out that integrated the interactions of the landslide, the river, and the dam. With a scale of 1:150, the model had the dimensions of 57, 27, and 8 m. Water level and the maximum sliding velocity into the water were selected as independent variables, leading to a total of 18 experiments. An adaptive landslide motion simulation system based on velocity equivalence and a comprehensive measurement system with tracking technology based on hydrodynamics were independently developed. Those approaches allowed us to reveal the propagation characteristics and attenuation laws of high position landslide-induced waves in a curved channel under various complex conditions. The data showed that the maximum wave run-up height on dam was 17.97 m under the most dangerous working condition (H3C09). Importantly, this value did not exceed the maximum height of dam, indicating a certain level of safety margin for the dam. Combined with the data of different working conditions, the optimal window for landslide risk prevention and control warnings was within 550 s after the onset of landslide instability. The key parameters predicted by the tests, including head wave height, wave run-up height on the opposite bank, wave run-up height on dam, and the propagation times, provided a technical basis and valuable reference for dam engineering design and safety. These results make significant contributions to the prevention and control of similar surges hazard induced by high position landslides around the world.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Large-scale three-dimensional experimental investigation on potential high position landslide‑induced waves in Gushui Reservoir, China\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":2,\"date\":\"2024-01-11 16:12:03\",\"doi\":\"10.21203/rs.3.rs-3711802/v2\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true}},{\"code\":1,\"date\":\"2023-12-07 02:20:59\",\"doi\":\"10.21203/rs.3.rs-3711802/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"ba613b0f-14c8-437c-b22c-5e678abca7d5\",\"owner\":[],\"postedDate\":\"January 11th, 2024\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"published-in-journal\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2024-11-14T18:45:46+00:00\",\"versionOfRecord\":{\"articleIdentity\":\"rs-3711802\",\"link\":\"https://doi.org/10.1016/j.oceaneng.2024.119723\",\"journal\":{\"identity\":\"ocean-engineering\",\"isVorOnly\":true,\"title\":\"Ocean Engineering\"},\"publishedOn\":\"2024-11-07 00:00:00\",\"publishedOnDateReadable\":\"November 7th, 2024\"},\"versionCreatedAt\":\"2024-01-11 16:12:03\",\"video\":\"\",\"vorDoi\":\"10.1016/j.oceaneng.2024.119723\",\"vorDoiUrl\":\"https://doi.org/10.1016/j.oceaneng.2024.119723\",\"workflowStages\":[]},\"version\":\"v2\",\"identity\":\"rs-3711802\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-3711802\",\"identity\":\"rs-3711802\",\"version\":[\"v2\"]},\"buildId\":\"qtupq5eGEP_6zYnWcrvyt\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}