DEVELOPMENT OF A SIMPLE LABORATORY-SCALE LANDSLIDE SIMULATION SYSTEM USING A SHAKING TABLE AND ARTIFICIAL RAINFALL
DOI:
10.29303/ipr.v9i3.636Downloads
Abstract
A landslide mitigation system is essential to reduce the potential risks of disasters. Historical records of both localized and widespread landslide events indicate that the development of sensor-based early warning systems is an effective approach. The design of such systems requires an understanding of landslide characteristics and sensor response to physical changes in soil. Therefore, this study developed a laboratory-scale landslide simulation model to investigate landslide behaviors. The model incorporates two primary triggering factors, namely vibration and A landslide mitigation system is essential to reduce the potential risks of disasters. Historical records of both localized and widespread landslide events indicate that the development of sensor-based early warning systems is an effective mitigation approach. The design of such systems requires an understanding of landslide characteristics and sensor responses to physical changes in soil. Therefore, this study developed a simple laboratory-scale landslide simulation system integrating a shaking table, an artificial rainfall, and a sensor system. The novelty of this work lies in integrating two different triggering factors, vibration through a shaking table and rainfall, using artificial rainfall. Two different materials, laterite and soil, were used to obtain ground movement characteristics. The results indicate that each material responded differently to the applied triggering factors. Laterite soil with clayey characteristics became soft and exhibited plasticity behavior under wet conditions and hardened under dry conditions. Consequently, vibration-induced movement in zones with weak soil bonding, while the addition of water primarily caused fluid flow associated with rainfall. In contrast, for sand samples, both vibration and artificial rainfall reduced pore size and enhanced soil bonding. However, an optimal pore size was observed, as excessive saturation led to fractures and collapse. Excess water also promotes fluid flow and liquefaction. Furthermore, the sensor system effectively detected and responded to the observed changes during the experimental procedure.
Keywords:
Landslide Model Laboratory Scale Rainfall Earthquake Soil Moisture Accelerometer SensorReferences
[1] M. N. Hidayat, H. Hazarika, M. Murai, H. Kanaya, and Y. Fukumoto, “Development and Evaluation of Landslide Early Warning System for Mitigating Rainfall Induced Disasters,” Indian Geotech. J., 2024.
[2] V. F. De Blasio, Introduction to the physics of landslides. New York: Springer, 2011.
[3] E. D. Atmajati, E. Yuliza, H. Habil, I. A. Sadisun, M. M. Munir, and K. Khairurrijal, “A Simple Landslide Model at a Laboratory Scale,” in AIP Conference Proceedings, 2017, vol. 1857(1), pp. 1–7.
[4] S. K. Chaulya, P. K. Mishra, N. Kumar, V. Kumar, and V. K. Rawani, “Landslide monitoring and prediction system using geosensors and wireless sensor network,” Discov. Geosci., vol. 2, no. 1, 2024.
[5] S. G. Kumar and S. Sarkar, “Large-Scale Experimental Simulation Studies on Rainfall-Induced Landslides Using Artificial Rainfall Simulator and Its Evaluation Using Conventional- and Optical-Based Monitoring Method,” Indian Geotech. J., 2024.
[6] R. Hidayat, S. J. Sutanto, A. Hidayah, B. Ridwan, and A. Mulyana, “Development of a landslide early warning system in Indonesia,” Geosci., vol. 9, no. 10, pp. 1–17, 2019.
[7] M. T. Abraham, N. Satyam, B. Pradhan, and A. M. Alamri, “IoT-based geotechnical monitoring of unstable slopes for landslide early warning in the Darjeeling Himalayas,” Sensors (Switzerland), vol. 20, no. 9, 2020.
[8] E. Putriani, Y. M. Wu, C. W. Chen, A. Ismulhadi, and D. I. Fadli, “Development of landslide susceptibility mapping with a multi-variance statistical method approach in Kepahiang, Indonesia,” Terr. Atmos. Ocean. Sci., vol. 34, no. 1, 2023.
[9] R. A. Yuniawan et al., “Revised Rainfall Threshold in the Indonesian Landslide Early Warning System,” Geosci., vol. 12, no. 3, 2022.
[10] M. Sharma and S. Laskar, “Soil Moisture Sensor-Based Landslide Monitoring: A Laboratory-Based Approach for Guwahati City,” Int. J. Environ. Eng. Dev., vol. 2, pp. 27–34, 2024.
[11] A. Hojat et al., “Geoelectrical characterization and monitoring of slopes on a rainfall- triggered landslide simulator,” J. Appl. Geophys., vol. 170, p. 103844, 2019.
[12] D. J. Peres and A. Cancelliere, “Comparing methods for determining landslide early warning thresholds: potential use of non-triggering rainfall for locations with scarce landslide data availability,” Landslides, vol. 18, no. 9, pp. 3135–3147, 2021.
[13] F. Faris and F. Wang, “Stochastic analysis of rainfall effect on earthquake-induced shallow landslide of Tandikat, West Sumatra, Indonesia,” Geoenvironmental Disasters, vol. 1, no. 1, pp. 1–13, 2014.
[14] S. Bai, P. Lu, and B. Thiebes, “Comparing characteristics of rainfall- and earthquake-triggered landslides in the Upper Minjiang catchment, China,” Eng. Geol., vol. 268, no. January, p. 105518, 2020.
[15] S. Kumar, S. D. Panda, S. P. Pradhan, and P. Chattopadhyay, Identification of potential failure zones in large progressive landslides: a method to optimize the cost of landslide early warning, no. 0123456789. Springer Netherlands, 2024.
[16] P. K. Indukala, U. G. Gosh, and M. Vinodini Ramesh, “IoT-Driven Microseismic Sensing System and Monitoring Platform for Landslide Detection,” IEEE Access, vol. 12, no. June, pp. 97787–97805, 2024.
[17] M. Sapena, M. Gamperl, M. Kühnl, C. Garcia-Londoño, J. Singer, and H. Taubenböck, “Cost estimation for the monitoring instrumentation of landslide early warning systems,” Nat. Hazards Earth Syst. Sci., vol. 23, no. 12, pp. 3913–3930, 2023.
[18] R. Ramkrishnan, A. Sharma, K. Viswanathan, and D. Ravichandran, “Determination of critical phreatic level for landslide assessment using a scaled-down laboratory model,” Int. J. Geotech. Eng., vol. 16, no. 2, pp. 239–255, 2022.
[19] F. Guzzetti et al., “Geographical landslide early warning systems,” Earth-Science Rev., vol. 200, no. September 2019, p. 102973, 2020.
[20] N. Casagli, E. Intrieri, V. Tofani, G. Gigli, and F. Raspini, “Landslide detection, monitoring and prediction with remote-sensing techniques,” Nat. Rev. Earth Environ., vol. 4, no. 1, pp. 51–64, 2023.
[21] G. Pecoraro, M. Calvello, and L. Piciullo, “Monitoring strategies for local landslide early warning systems,” Landslides, vol. 16, no. 2, pp. 213–231, 2019.
[22] P. S. Thapa, B. R. Adhikari, R. Shaw, D. Bhattarai, and S. Yanai, “Geomorphological analysis and early warning systems for landslide risk mitigation in Nepalese mid-hills,” Nat. Hazards, vol. 117, no. 2, pp. 1793–1812, 2023.
[23] M. V. Ramesh and V. P. Rangan, “Data reduction and energy sustenance in multisensor networks for landslide monitoring,” IEEE Sens. J., vol. 14, no. 5, pp. 1555–1563, 2014.
[24] Z. Liao et al., “Prototyping an experimental early warning system for rainfall-induced landslides in Indonesia using satellite remote sensing and geospatial datasets,” Landslides, vol. 7, no. 3, pp. 317–324, 2010.
[25] T. F. Fathani, D. Karnawati, and W. Wilopo, “An Adaptive and Sustained Landslide Monitoring and Early Warning System,” vol. 2, no. 2, 2014.
[26] H. Habil, E. Yuliza, M. M. Munir, M. Irsyam, and Khairurrijal, “Instrumentation system design and laboratory scale simulation of landslide disaster mitigation,” J. Phys. Conf. Ser., vol. 739, no. 1, 2016.
[27] K. M. P. Ebrahim, S. M. M. H. Gomaa, T. Zayed, and G. Alfalah, “Recent Phenomenal and Investigational Subsurface Landslide Monitoring Techniques: A Mixed Review,” Remote Sens., vol. 16, no. 2, 2024.
[28] K. Lee, J. Suk, H. Kim, and S. Jeong, “Modeling of rainfall-induced landslides using a full-scale flume test,” Landslides, no. April 2020.
[29] Rudiansyah, Adriani, and I. Barkiah, “The Behavior of Residual Shear Strength of Laterite Soil Due to the Addition of Coarse Sand and Low Plasticity Clay Fraction,” Int. J. Geomate, vol. 21, no. 86, pp. 100–107, 2021.
[30] D. Chandrasasi, S. Marsudi, and E. Suhartanto, “Determination of Types and Characteristics of Laterite Soil as Basic Land for Building Construction,” IOP Conf. Ser. Earth Environ. Sci., vol. 930, no. 012041, 2021.
[31] G. S. Kumar, P. K. Saini, R. Deoliya, A. K. Mishra, and S. K. Negi, “Characterization of laterite soil and its use in construction applications : A review,” Resour. Conserv. Recycl. Adv., vol. 16, no. November, p. 200120, 2022.
[32] J. I. Aguwa, “Performance of Laterite-Cement Blocks as Walling Units in Relation to Sandcrete Blocks,” Leonardo Electron. J. Pract. Technol., no. 16, pp. 189–200, 2010.
[33] A. Bruand, C. Hartmann, and G. Lesturgez, “Physical properties of tropical sandy soils : A large range of behaviors,” in Management of Tropical Sandy Soils for Sustainable Agriculture, 2005, pp. 148–158.
[34] N. Mitarai and F. Nori, “Wet granular materials,” Adv. Phys., vol. 55, no. 1–2, pp. 1–45, 2006.
[35] E. Yuliza et al., “Stability of granular tunnel,” Granul. Matter, vol. 123, p. 75, 2018.
[36] Z. Nong, S. S. Park, S. W. Jeong, and D. E. Lee, “Effect of cyclic loading frequency on liquefaction prediction of sand,” Appl. Sci., vol. 10, no. 13, 2020.
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