Hazard Mitigation of a Landslide-Prone Area through Monitoring, Modeling, and Susceptibility Mapping
Abstract
:1. Introduction
2. Background of Study Area
2.1. Topography
2.2. Temperature and Rainfall
2.3. Geology
2.4. Google Earth Images Taken between 2006 and 2018
3. Methods of Study
3.1. Ground Investigations
3.1.1. Boreholes Exploration
3.1.2. Electrical Resistivity Tomography (ERT)
3.2. Field Monitoring
Observation Wells
3.3. Inclinometers
3.4. Seepage and Stability Analyses
4. Results and Discussion
4.1. Ground Investigation Results
4.1.1. Slopes Materials
4.1.2. Groundwater Level of Study Slopes
4.1.3. Lateral Displacement of Slopes
4.2. Factors Causing Short-Term Sliding
4.3. Factors Causing Long-Term Sliding
- High susceptibility (red): Evidence of sliding, such as sliding surfaces, indicated by monitoring instruments, new cracks, ground subsidence, or broken drainage ditches within the sliding body, was found during field checking.
- Moderate susceptibility (blue): No evidence of sliding was found; however, signs of impending sliding, such as scarp, tilted ground, old cracks, and colluvium deposits, were observed during field checking.
- Low susceptibility (green): No obvious signs of soil slippage were seen during the field checking but could be inferred from topography features.
4.4. Hazard Mitigation
5. Conclusions
- It was astonishing to learn that the river-bed of the river at the toe of the studied large-scale slope has been raised by more than 30 m within a period of five years as a result of the inundation of debris from upstream after the construction of a dam downstream of the study site.
- The infiltration of rainwater from the surface of the slope, the upraised river-bed elevation, and the erosion of the river bank of the toe of the slopes have altered the landform and the groundwater level of the large-scale slope and eventually triggered several localized slope failures. The results of the uncoupled hydromechanical slope stability analysis where the analyzed slopes were subjected to a designed storm for a 50-year return period in 24 h revealed that a sliding surface was triggered within the depth of the colluvium. The thickness of the simulated sliding surface coincided with that observed on site.
- The landform of the Taibaojiu Ecktreppe at the crest of the study area has somehow crept into a double-crested ridge or ridge-top depression, indicating that the study area is being subjected to large-scale deep-seated gravitational slope deformation (DSGSD) by means of mass rock creep. Although the creeping rate has yet to be quantified, the study’s large-scale slope is believed to be creeping gradually. The orientation of the on-site foliations has also revealed the inherent danger of the northern and southern slopes in which huge and catastrophic landslides could eventually be triggered. Based on field monitoring records and the orientation of the foliations, the associated DSGSD surface was deduced to be developed along the interface of the disturbed (SL1) and undisturbed (SL2) slates.
- An intriguing pattern of resistivity distribution was observed from the results of the Wenner–Schlumberger and pole–pole arrays. Unlike low resistivity-based colluvium that occasionally mingled with some high resistivity readings, areas with a concentrated high resistivity reading were found to be associated with the orientation of the foliated rock mass. Further studies could be conducted to verify the reason for this association.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
921-Jiji | 21 September 1999 Jiji Earthquake |
Cv | Colluvium |
ERT | Electrical Resistivity Tomography |
FOS | Factor of Safety |
SL1 | Disturbed Slate Formation |
SL2 | Undisturbed Slate Formation |
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Month | Jan | Feb | Mac | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec | Yearly |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Average (mm) | 90 | 180 | 213 | 249 | 284 | 330 | 199 | 254 | 204 | 88 | 60 | 60 | 2215 |
Maximum (mm) | 504 | 710 | 786 | 938 | 560 | 920 | 691 | 784 | 1351 | 511 | 325 | 170 | 3771 |
Year | 2016 | 1983 | 1983 | 1990 | 1984 | 2006 | 2004 | 1994 | 2008 | 2007 | 2012 | 2012 | 2005 |
Landslide Locations | Nearest Rainfall Event | Date of Rainfall Recorded | Accumulated Rainfall (mm) | Date of Google Image Taken | Postulated Cause of Failure |
---|---|---|---|---|---|
1, 2, 3 | Typhoon Toraji | 28 July 2001 | 244 | 1 February 2006 | |
4 | Typhoon Mindulle | 1 July 2004 | 645 | 1 February 2006 | rainfall |
5 | Typhoon Morakot | 6 August 2009 | 755 | 29 November 2013 | rainfall |
6 | Low pressure | 8 June 2012 | 674 | 29 November 2013 | rainfall and fluvial attack |
7, 8 | Typhoon Megi | 26 Sept 2016 | 327 | 30 April 2017 | rainfall |
9 | Typhoon Maria | 10 July 2018 | 276 | 30 September 2018 | rainfall |
Material | Unit Weight | Apparent Cohesion | Friction Angle | Saturated Volumetric Water Content | Residual Volumetric Water Content | Saturated Hydraulic Conductivity | a | n |
---|---|---|---|---|---|---|---|---|
(kN/m3) | (kPa) | () | (m/m) | (m/m) | (m/s) | (kPa) | ||
Colluvium | 22 | 0 | 23.5 | 0.30 | 0.02 | 4.6 × 10 | 2.00 | 1.35 |
Slate (SL1) | 25 | 20 | 30.0 | 0.25 | 0.02 | 9.6 × 10 | 0.19 | 1.70 |
Slate (SL2) | 25 | 20 | 30.0 | 0.21 | 0.02 | 3.8 × 10 | 0.19 | 1.70 |
Observation Well No. | Highest Groundwater Level (m) |
---|---|
AH–2 | 5.5 |
AH–3 | 14.0 |
AH–4 | 19.0 |
AH–5 | 13.5 |
AH–7 | 15.5 |
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Gui, M.-W.; Chu, H.-A.; Ding, C.; Lee, C.-C.; Ho, S.-K. Hazard Mitigation of a Landslide-Prone Area through Monitoring, Modeling, and Susceptibility Mapping. Water 2023, 15, 1043. https://doi.org/10.3390/w15061043
Gui M-W, Chu H-A, Ding C, Lee C-C, Ho S-K. Hazard Mitigation of a Landslide-Prone Area through Monitoring, Modeling, and Susceptibility Mapping. Water. 2023; 15(6):1043. https://doi.org/10.3390/w15061043
Chicago/Turabian StyleGui, Meen-Wah, Hsin-An Chu, Chuan Ding, Cheng-Chao Lee, and Shu-Ken Ho. 2023. "Hazard Mitigation of a Landslide-Prone Area through Monitoring, Modeling, and Susceptibility Mapping" Water 15, no. 6: 1043. https://doi.org/10.3390/w15061043
APA StyleGui, M. -W., Chu, H. -A., Ding, C., Lee, C. -C., & Ho, S. -K. (2023). Hazard Mitigation of a Landslide-Prone Area through Monitoring, Modeling, and Susceptibility Mapping. Water, 15(6), 1043. https://doi.org/10.3390/w15061043