Triggering Rainfall of Large-Scale Landslides in Taiwan: Statistical Analysis of Satellite Imagery for Early Warning Systems

Typhoon Morakot had a serious impact on Taiwan, especially the uncommon type of landslide called large-scale landslide (LSL), not many in number but serious in effect, the origin of which the study induced. To establish a specific relationship between LSL and triggering rainfall for future applications of LSL early warning predictions, relevant cases from satellite imagery, along with field investigation data, major event reports, and seismic data from 2004 to 2016, were collected. All collected cases are distributed around the mountainous area in Taiwan, and a total of 107 cases which were mainly distributed in the southern part of the mountainous area were finally selected, including 28 occurrence-time-known cases and 79 occurrence-time-unknown cases. In addition, 149 potential areas identified by the Soil and Water Conservation Bureau (SWCB) were used for improving bounding estimates. Based on the concept of safety factor, two dimensionless quantities, rainfall/landslide depth (R/D) and friction angle/slope (ϕ/θ), were analyzed by linear regression. In addition, D was assumed to be nonlinearly dependent on R, θ, and ϕ, and the parameter uncertainties were evaluated by the resampling with bootstrap method. Based on the currently obtained data, there were 8% Type-I errors in the results of the linear regression analysis, and 1% Type-II errors in the results of the nonlinear regression analysis. Through the comparison of statistical indicators, the results of nonlinear regression analysis have a better correlation trend. Based on the needs of early warning operations, more conservative indicators can reduce the risks faced by management operations. Therefore, according to the results of this study, the lower boundary values from nonlinear analysis could be used as the LSL early warning management settings. Incorporated with real-time rainfall forecasts, the variation of statistical indicators will provide the trend information dynamically, and will help to increase the response time for relevant evacuation operations, that will be welcome for the further extended applications to guide the evacuation operations of early warning systems.

[1]  Meei-Ling Lin,et al.  Investigation of Geological Structures Using UAV Lidar and Its Effects on the Failure Mechanism of Deep-Seated Landslide in Lantai Area, Taiwan , 2021, Applied Sciences.

[2]  Chien-Chih Chen,et al.  Electrical Resistivity Tomography (ERT) Monitoring for Landslides: Case Study in the Lantai Area, Yilan Taiping Mountain, Northeast Taiwan , 2021, Frontiers in Earth Science.

[3]  I. Towhata,et al.  Mechanism and future risk of slope instability induced by extreme rainfall event in Izu Oshima Island, Japan , 2020, Natural Hazards.

[4]  Duc-Tan Tran,et al.  Design and implementation of site-specific rainfall-induced landslide early warning and monitoring system: a case study at Nam Dan landslide (Vietnam) , 2017 .

[5]  C. Lo.  Evolution of deep-seated landslide at Putanpunas stream, Taiwan , 2017 .

[6]  Chris Phillips,et al.  Identifying Spatio-Temporal Landslide Hotspots on North Island, New Zealand, by Analyzing Historical and Recent Aerial Photography , 2016 .

[7]  Wei Hu,et al.  Evaluation of parameter uncertainties in nonlinear regression using Microsoft Excel Spreadsheet , 2015, Environmental Systems Research.

[8]  J. Zêzere,et al.  Rainfall thresholds for landslide activity in Portugal: a state of the art , 2015, Environmental Earth Sciences.

[9]  Javier Murillo,et al.  2D dry granular free-surface flow over complex topography with obstacles. Part I: experimental study using a consumer-grade RGB-D sensor , 2014, Comput. Geosci..

[10]  Pilar García-Navarro,et al.  2D dry granular free-surface transient flow over complex topography with obstacles. Part II: Numerical predictions of fluid structures and benchmarking , 2014, Comput. Geosci..

[11]  Ching-Weei Lin,et al.  Detecting Large-Scale Landslides Using Lidar Data and Aerial Photos in the Namasha-Liuoguey Area, Taiwan , 2013, Remote. Sens..

[12]  Nazri Ali,et al.  A review of three-dimensional slope stability analyses based on limit equilibrium method , 2013 .

[13]  Samuele Segoni,et al.  Rainfall thresholds for the forecasting of landslide occurrence at regional scale , 2012, Landslides.

[14]  Jyr‐Ching Hu,et al.  Assessments of serious anthropogenic land subsidence in Yunlin County of central Taiwan from 1996 to 1999 by Persistent Scatterers InSAR , 2012 .

[15]  Zhong Lu,et al.  Large-area landslide detection and monitoring with ALOS/PALSAR imagery data over Northern California and Southern Oregon, USA , 2012 .

[16]  Jyr‐Ching Hu,et al.  Monitoring of active tectonic deformations in the Longitudinal Valley (Eastern Taiwan) using Persistent Scatterer InSAR method with ALOS PALSAR data , 2012 .

[17]  Vladimir Greif,et al.  Monitoring of post-failure landslide deformation by the PS-InSAR technique at Lubietova in Central Slovakia , 2012, Environmental Earth Sciences.

[18]  Veronica Tofani,et al.  Persistent Scatterers Interferometry Hotspot and Cluster Analysis (PSI-HCA) for detection of extremely slow-moving landslides , 2012 .

[19]  C. Terranova,et al.  Tracking and evolution of complex active landslides by multi-temporal airborne LiDAR data: The Montaguto landslide (Southern Italy) , 2011 .

[20]  Kang-Tsung Chang,et al.  Landslide mapping with multi-scale object-based image analysis – a case study in the Baichi watershed, Taiwan , 2011 .

[21]  Meei-Ling Lin,et al.  Initiation and displacement of landslide induced by earthquake — a study of shaking table model slope test , 2011 .

[22]  Shin-Ping Lee,et al.  Reflection of typhoon morakot — the challenge of compound disaster simulation , 2011 .

[23]  Chung-Pai Chang,et al.  Surface deformation from persistent scatterers SAR interferometry and fusion with leveling data: A case study over the Choushui River Alluvial Fan, Taiwan , 2011 .

[24]  C. Shieh,et al.  An overview of disasters resulted from Typhoon Morakot in Taiwan. , 2010 .

[25]  Martin Charlton,et al.  Dual-scale validation of a medium-resolution coastal DEM with terrestrial LiDAR DSM and GPS , 2010, Comput. Geosci..

[26]  F. Chou,et al.  應用永久散射體差分干涉法觀測台灣北部地區之地表變形; Measurement of Surface Deformation in Northern Taiwan by Using PSInSAR Techniques , 2009 .

[27]  J. Roering,et al.  Automated landslide mapping using spectral analysis and high-resolution topographic data: Puget Sound lowlands, Washington, and Portland Hills, Oregon , 2008 .

[28]  M. Eeckhaut,et al.  Tracking landslide displacements by multi-temporal DTMs: A combined aerial stereophotogrammetric and LIDAR approach in western Belgium , 2008 .

[29]  M. Rossi,et al.  Rainfall thresholds for the initiation of landslides in central and southern Europe , 2007 .

[30]  K. Miyamoto.  Two dimensional numerical simulation of landslide mass movement , 2002 .

[31]  N. Newmark.  Effects of Earthquakes on Dams and Embankments , 1965 .

[32]  Tsai-Tsung Tsai,et al.  Critical Rainfall Analysis of Large-scale Landslide Occurrence , 2018 .

[33]  S. Chi,et al.  Landscape evolution analysis of large scale landslides at Don-Ao Peak, Taiwan , 2015, Environmental Earth Sciences.

[34]  Yong-Seok Seo,et al.  Suggestion of a Landslide Early Warning Method Using a Gradient of Volumetric Water Content , 2014 .

[35]  A. Bichler,et al.  IDENTIFICATION, MAPS AND MAPPING Canadian Technical Guidelines and Best Practices related to Landslides: a national initiative for loss reduction , 2012 .

[36]  W. Z. Savage,et al.  TRIGRS - A Fortran Program for Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Analysis, Version 2.0 , 2002 .

[37]  B. Efron.  Bootstrap Methods: Another Look at the Jackknife , 1979 .