Characterization of Seismic Signal Patterns and Dynamic Pore Pressure Fluctuations Due to Wave-Induced Erosion on Non-Cohesive Slopes
Source abstract
Abstract
Wave erosion of slopes can easily trigger landslides into marine environments and pose severe threats to both the ecological environment and human activities. Therefore, near-shore slope monitoring becomes crucial for preventing and alerting people to these potential disasters. To achieve a comprehensive understanding, it is imperative to conduct a detailed investigation into the dynamics of wave erosion processes acting on slopes. This research is conducted through flume tests, using a wave maker to create waves of various heights and frequencies to erode the slope models. During the tests, seismic signals, acoustic signals, and pore pressure generated by wave erosion and slope failure are recorded. Seismic and acoustic signals are analyzed, and time-frequency spectra are calculated using the Hilbert–Huang Transform to identify the erosion events and signal frequency ranges. Arias Intensity is used to assess seismic energy and explore the relationship between the amount of erosion and energy. The results show that wave height has a more decisive influence on erosion behavior and retreat than wave frequency. Rapid drawdown may potentially cause the slope to slide during cyclic swash and backwash wave action. As wave erosion changes from swash to impact, there is a significant increase in the spectral magnitude and Power Spectral Density (PSD) of both seismic and acoustic signals. An increase in pore pressure is observed due to the rise in the run-up height of waves. The amplitude of pore pressure will increase as the slope undergoes further erosion. Understanding the results of this study can aid in predicting erosion and in planning effective management strategies for slopes subject to wave action.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Coastal and Marine Dynamics · Ocean Waves and Remote Sensing · Seismic Waves and Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Soil and Water Conservation, National Chung Hsing University, Taichung 402, Taiwan
Innovation and Development Center of Sustainable Agriculture, National Chung Hsing University, Taichung 402, Taiwan
Funding
Innovation and Development Center of Sustainable Agriculture
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