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Seismic and acoustic signals induced by rock falls and rock avalanches always contain abundant information about movement processes. By simultaneously monitoring and analyzing the characteristics of the two physical signals, there is a better opportunity to closely interpret the behaviors of the processes closely. This study conducted small-scale rock fall field tests on a creek bank. Three types of field tests including single large rock fall, single small rock fall, and rock-mixture fall tests were carried out. Low cost and easy-to-install accelerometers and microphones were used to record both seismic and acoustic signals, respectively. The results affirm that the characteristics of the seismic and acoustic signals are generally similar and correlated due to the signals being caused by the same event energy sources. The attenuation of acoustic signals was less than that of seismic signals and high-frequency portion of the seismic signals attenuates quickly in stratum. It was also shown how the surface wave velocity of the stratum of the test site was estimated. In addition, the larger the rock mass, the lower the seismic frequency was found to be. The possible practical significance of this study is provided, and the simultaneous use of acoustic and seismic signal monitoring to rock falls/landslides is promoted.

Landslides and floods occur with a significant generation of energy release producing seismic and acoustic signals. The analysis of these signals aims to identify vital and specific characteristics of landslide and flood events, such as frequency content, spectral magnitude, energy variation, and timing of the events. This study examined the seismic and acoustic signals recorded during a large-scale physical dam model failure test. The tests were conducted on the streambed under the No. 2 Bridge in Huisun Forest Experimental Station in Nantou, Taiwan. A dam and a slope model were constructed, and dam failure and slope erosion tests were induced by releasing water to slowly accumulate at the upstream side of the dam and letting water overtop the dam, causing a breach. After dam overtopping, the lowering of the dam crest led to dam failure, causing a large volume of floodwater, resulting in erosion of the toe of the slope model, triggering landslides. Accelerometers and microphones were installed to collect the acoustic and seismic signals produced by the water flow and landslides generated. Unmanned aerial vehicles were used to continuously capture the topography of the slope to produce elevation models to calculate the volumes of the six landslides. Hilbert–Huang transform (HHT) was performed to evaluate the time–frequency spectra for the seismic and acoustic signals, and their spectral magnitudes were discussed. The results showed that the acoustic signals depicted and reacted to the failure event earlier than seismic signals; however, both types of signals were in agreement. The velocity of the flood energy was estimated to be 5.71 and 5.06 m/s by monitoring the seismic signals at different locations of the riverbank and through the analysis of spectral magnitude, respectively. Furthermore, the Arias intensity and the landslide volumes were found to be correlated through a quadratic relationship.

Dam models were constructed in an indoor flume to test dam breach failure processes to study the seismic signals induced. A simple dam breach model was also proposed to estimate hydrographs for dam breach floods. The test results showed that when the retrogressive erosion due to seepage of the dam continues, it will eventually reach the crest at the upstream side of the dam, and then trigger overtopping and breaching. The seismic signals corresponding to the failure events during retrogressive erosion and overtopping of the dam models were evaluated. Characteristics of the seismic signals were analyzed by Hilbert–Huang transform. Based on the characteristics of the seismic signals, we found four types of mass movement during the retrogressive erosion process, i.e., the single, intermittent, and successive slides and fall. There were precursor seismic signals found caused by cracking immediately before the sliding events of the dam. Furthermore, the dam breach modeling results coincided well with the test results and the field observations. From the test and modeling results, we confirmed that the overtopping discharge and the lateral sliding masses of the dam are also among the important factors influencing the evolution of the breach. In addition, the widening rate of the breach decreases with decreased discharge. The proposed dam breach model can be a useful tool for dam breach warning and hazard reduction.

Seismic signals are usually generated during landslides or movement of soil mass due to collisions and friction among the soil particles and masses. The seismic signals will be different when different sliding (movement) types occur. This study discusses the landslide process and seismic signals produced by soil ruptures to understand the nature of the signals, which could help in predicting landslides as well as understanding different landslide processes. Physical model tests were performed to record the seismic signals generated during the sliding processes. The self-potential (SP), pore water pressure (PP), and volumetric water content (VWC) were also measured to assist the interpretation of the failure processes. Based on the characteristics of the seismic signals recorded, three slide types were identified: intermittent slide, successive slide, and single slide. Precursor signals prior to the single slide event were found in both the seismic and SP signals and therefore the monitoring of these two kinds of precursors has the potential for real-world application in landslide prewarning. In addition, the landslide areas of the tests were correlated with Arias intensities (IA) in a linear relationship. The relationship has the potential to be implemented in estimating a landslide’s scale for a fast landslide response decision.

Floods and erosion often cause landslides of riverbanks and induce problems such as river blockage, shift of river center, or flooding from rising riverbeds. Instrumentation and monitoring are often used to explore landslide and erosion behavior of riverbanks. Therefore, this study identified landslide types and characteristics of their seismic signals due to toe erosion of riverbanks through riverbank models with various instrumentation sensors in a laboratory flume. To induce landslides in the riverbank model, a test was set up for water to flow through the toe of the riverbank model. Seismic signals of each landslide event were measured during the tests with accelerometers. Nonpolarized electrodes were installed for observing the self-potential changes during the test. Water content and pore water pressure gauges were installed in the riverbank model. In addition, water levels were recorded. The Hilbert&ndash, Huang transform method was used to analyze the characteristics of seismic signals caused by water flow and riverbank landslides. Time points, landslide frequency distributions, and the characteristics of several landslide events in the riverbank models were estimated using the seismic signals. This study identified three types of landslides: single, intermittent, and successive. Moreover, changes in self-potential signals, pore water pressure, and water content during the tests were examined and were found to correspond to the landslide process of the riverbank model.

When a coseismic landslide is triggered by an earthquake, seismic stations close to the location of the landslide will simultaneously record the seismic signals caused by the earthquake and landslide, causing confusion between the two signals. This complicates the separation of the two signals, and subsequently the explanation of the coseismic landslide process from the signals recorded. Therefore, the use of a numerical approach is a more practical methodology for systematic analysis of the characteristics of seismic signals generated by the motion of coseismic landslides. In addition, in-depth study of various factors (parameters) that affect the seismic signals of coseismic landslides can be rapidly achieved. This study proposed a dynamic numerical coupling approach, which can simultaneously simulate the earthquake response of the ground and the behavior of the coseismic landslide process as well as trace the seismic signals generated by the two geological phenomena. PFC and FLAC codes were coupled to accomplish the numerical approach. The PFC was to simulate the sliding process of the masses, including rupture and dispersal of the rock masses during movement and collisions as well as the deposition patterns of the masses. The FLAC enabled the input of acceleration history at the base of the FLAC model and the calculation of the propagation of the seismic waves in the strata and the interaction of the seismic disturbances with the PFC model. The Tsaoling coseismic landslide due to the 1999 Chi-Chi earthquake was chosen to serve as an example for the approach, due to the presence of the strong motion station CHY080 in close proximity to the main scarp of the Tsaoling landslide, and its recordings of the seismic signals induced by the coseismic landslide and the Chi-Chi earthquake. The study shows that the numerical evaluation of the energy contribution of the Tsaoling coseismic landslide is approximately 66% of the energy contribution to the seismic signal of the monitoring station in the simulation. A parametric study was also performed on input acceleration, friction of the sliding surface, particle friction, particle bond strength and Rayleigh damping. This study concludes that the major key parameters are normal parallel bond strength, Rayleigh damping and the residual friction of ‘wall elements’ in that they are very sensitive and significantly influence the landslide process and seismic signals of the simulations. The results of the simulations were able to account for most of the physical mechanisms of the coseismic landslides. The coupling approach employed can provide a quantitative basis for evaluating the effects of the parameters on the characteristics of the seismic signals. It can also be extended to assess seismic signals generated from other types of coseismic mass movements.