以入滲和無限邊坡整合模式預測降雨引致之山區道路邊坡破壞

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研究生：	阿格西 Agus - Setyo Muntohar
論文名稱：	以入滲和無限邊坡整合模式預測降雨引致之山區道路邊坡破壞 AN INTEGRATED INFILTRATION AND SLOPE STABILITY MODEL FOR PREDICTING RAINFALL INDUCED LANDSLIDES ALONG A MOUNTAIN ROAD IN TAIWAN
指導教授：	廖洪鈞 Hung-Jiun Liao
口試委員:	林美聆 Mei-Ling Lin 卿建業 Jianye-Ching 李維峰 Wei-Fung Lee 林宏達 Horn-Dan lin 冀樹勇 Chi-Shu Yong 蔡光榮 Tsai-Kuang Zhong
學位類別：	博士 Doctor
系所名稱：	工程學院 - 營建工程系 Department of Civil and Construction Engineering
論文出版年：	2008
畢業學年度：	96
語文別：	英文
論文頁數：	121
中文關鍵詞：	無限邊坡、滑坡、機率、破壞時間、1、 logistic 迴歸分析、門檻降雨量、Green-Ampt 模式
外文關鍵詞：	Green-Ampt, infinite slope, landslides, probability, time of failure, threshold rainfall, logistic regression.
相關次數：	點閱：263 下載：16
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The Green-Ampt infiltration model and infinite slope stability model are adopted here to estimate the reoccurrence time of road side slope failure during typhoon in Taiwan. The proposed model is verified with the results obtained from landslides cases in literatures. The ability of proposed model to estimate the initiation time of failure has been verified with deterministic analysis for Tuscany (Italy) and Tung Chung East (Hong Kong) cases, and probabilistic analysis for Boso Peninsula (Japan) and Tungmen (Taiwan) landslides cases. In general, the proposed model is acceptable to be applied for estimating the time of failure and depth of sliding surface of a slope.
By coupling with the probabilistic analysis, a probability-threshold rainfall model to predict the occurrence time of landslides during typhoon is proposed here in terms of hourly rainfall intensity and accumulated rainfall. By using the rainfall records, the failure probability of slope can be calculated from the model. If the failure probability is greater than 0.5, slope is very likely to fail. Otherwise, slope is unlikely to fail. To verify the suitability of the proposed model, some landslide cases reported in the literature are selected and modeled. In general, the results are satisfactory and the applicability of the proposed model as an 'early-warning system' for typhoon induced roadside slope failure is promising. However, since the database used in this model is mainly based on the information gathered from failed roadside slopes, so it is suggested that the model proposed here is only used to predict the occurrence time of reactivated landslides in the area with previous landslide records.

TABLE OF CONTENTS
ABSTRACT	I
ACKNOWLEDGEMENT	II
DEDICATIONS	III
LIST OF FIGURES	VI
LIST OF TABLES	X


CHAPTER I INTRODUCTION	1
1.1	Background	1
1.2	Previous Research Works	2
1.3	Scopes of Study	3
1.4	Outlines of Dissertation	5

CHAPTER II LITERATURES REVIEW	6
2.1	Landslide Types and Processes	6
2.1.1	Causes and Triggering Factors	6
2.1.2	Types of Landslides	6
2.2	Rainfall Threshold for Landslide Initiation	10
2.2.1	Empirical-based model	11
2.2.2	Process-based model	12
2.2.3	Statistical-based	13
2.2.4	Advantages and Limitation of the Rainfall Thresholds	15
2.3	Rain Infiltration – Slope Stability Model	16
2.4	Rainfall Infiltration Model	18
2.4.1	Infiltration Equations	18
2.4.2	Green-Ampt Infiltration Model	20
2.4.3	Rainfall Infiltration under Unsteady Rainfall	25
2.5	Green-Ampt Parameters	26
2.6	Estimating Soil-Water Content Function	34
2.6.1	Basic Theory Arya and Paris (1981) Model	34
2.6.2	Basic Relationship in Pedotransfer Function (PTF)	35
2.7	Slope Stability Model for Shallow Landslide	38
2.7.1	Infinite Slope	38
2.7.2	Incorporation of the Matric Suction in Slope Stability Analysis	39
2.8	Uncertainties and Reliability Analysis in Slope Stability	43
2.8.1	Methods of Reliability Evaluation	44
2.8.2	Calculating the Reliability Index and Probability of Failure	46
2.8.3	Quantification of Variable Uncertainty Measures	48
2.9	Summary of the Literatures Review	50

CHAPTER III MODEL DEVELOPMENT AND ITS APPLICATION	52
3.1	Rainfall Infiltration and Slope Stability Model	52
3.2	Parameter uncertainties, reliability and failure probability	56
3.4	Application of the Model	59
3.4.1	Northern Tuscany Landslides, Italy	60
3.4.2	Tung Chung East landslide, Hong Kong	63
3.4.3	Boso Peninsula Landslide, Japan	67
3.4.4	Tungmen Landslide, Taiwan	70

CHAPTER IV ANALYSIS OF SHALLOW SLOPES FAILURE ALONG T18 ALISHAN MOUNTAIN ROAD	73
4.1	Location of the Study and Slope Properties	73
4.2	Probability Analysis	81
4.3	Failure Probability and Reliability Index of the Slopes	81
4.4	Estimation of the Time of Failure	85
4.5	Threshold Rainfall for Landslide Prediction	88

CHAPTER VI CONCLUSIONS AND RECOMMENDATIONS	97
6.1	Conclusions	97
6.2	Recommendations	98

REFERENCES	100
APPENDICES	110
	Appendix - A: Logistic Regression Method	110
	Appendix - B: SPSS Output of Binary Logistic Regression	112
	Appendix - C: Viate	120

 
LIST OF FIGURES
Figure 1.1	Research strategy and the scopes of study.	4
Figure 2.1	Scheme of the landslide causes and triggering factor.	6
Figure 2.2	Schematics illustrate the major types of landslide movement.	9
Figure 2.3	Empirical threshold for rainfall induces debris flow in Taiwan.	12
Figure 2.4	Comparison of lower boundary thresholds computed using
a Bayesian model with the other global thresholds
proposed in the literature.	14
Figure 2.5	Threshold rainfall for real-time landslide warning during rainstorm.	15
Figure 2.6	Control volume for development of the continuity equation
in unsaturated soils layer.	19
Figure 2.7	Idealization of Green-Ampt infiltration model.	21
Figure 2.8	Infiltration into a column of soil of unit cross-sectional area
for the Green-Ampt model.	21
Figure 2.9	Illustration of Green-Ampt water content profile for sloping land surface.	23
Figure 2.10	Three cases of rain infiltration mechanism calculated from
Green and Ampt equations.	27
Figure 2.11	Flowchart for determining infiltration under unsteady rainfall intensity
using Green and Ampt model.	28
Figure 2.12	Typical of complete soil water characteristics curve for silty soil.	29
Figure 2.13	Hysteresis in soil-water characteristic curves and permeability functions
for natural deposited sand.	29
Figure 2.14	Soil suction versus relative conductivity.	33
Figure 2.15	Determination suction at wetting front (f) for clay soils from
the soil water characteristic curve.	33
Figure 2.16	(a) Particle-size distribution of soils, and (b) the estimated volumetric water content function using Arya and Paris (1981) model.	37
Figure 2.17	Infinite slope model for shallow landslides type.	38
Figure 2.18	Two possible mechanisms for the saturation and the instability
of surficial deposits.	40
Figure 2.19	Several assumptions of the pore-water distribution
on shallow slope failures.	42
Figure 2.20	Probability distribution plots (a) uniform PDF, (b) Gamma PDF,
(c) Normal PDF, and (d) Lognormal PDF.	47
Figure 2.21	Factor of safety distribution (a) Normal distribution of the ln (FS), or
(b) LogNormal distribution of the FS.	47
Figure 3.1	Rainfall infiltration model on infinite slope.	52
Figure 3.2	Infinite slope model (a) Model 1: bedrock or impervious layer is not
presence or very deep (b) Model 2: bedrock or impervious layer is
presence at very shallow depth.	53
Figure 3.3	A flowchart of the Green-Ampt infiltration and slope stability model.	55
Figure 3.4	Distribution of the performance function.	58
Figure 3.5	Calculated factor of safety for slope at Uzzano site, Italy (a) infiltration rate,
(b) wetting front depth, (c) change of factor of safety.	61
Figure 3.6	Calculated factor of safety for slope at Massa e Cozzile site, Italy
(a) infiltration rate, (b) wetting front depth, (c) change of factor of safety.	62
Figure 3.7	Calculated factor of safety for slope at Colodi site, Italy (a) infiltration rate,
(b) wetting front depth, (c) change of factor of safety.	63
Figure 3.8	Tung Chung East study area (Lan et al., 2003).	64
Figure 3.9	Calculated factor of safety for colluvium slope at SP5 site, Tung Chung East, Hong Kong (a) infiltration rate, (b) wetting front depth,
(c) change of factor of safety.	64
Figure 3.10	Calculated factor of safety for colluvium slope at SP6 site, Tung Chung East, Hong Kong (a) infiltration rate, (b) wetting front depth,
(c) change of factor of safety.	65
Figure 3.11	Calculated factor of safety for CDV slope at SP8 site, Tung Chung East,
Hong Kong (a) infiltration rate, (b) wetting front depth,
(c) change of factor of safety.	66
Figure 3.12	Calculated factor of safety for residual soil slope at SP10 site, Tung Chung East, Hong Kong (a) infiltration rate, (b) wetting front depth,
(c) change of factor of safety.	67
Figure 3.13	Slope failure analysis for sandstones site at Boso Peninsula, Japan (a) hourly rainfall and accumulated rainfall, (b) computed depth of wetting front, (c) computed failure probability, (d) distribution plot of the time of failure.	68
Figure 3.14	Slope failure analysis for mudstones site at Boso Peninsula, Japan
(a) hourly rainfall and accumulated rainfall, (b) computed depth of wetting front,  c) computed failure probability, (d) distribution plot of the time of failure.	69
Figure 3.15	Location and watershed of a debris-flow gully behind Tungmen village in Hualien, Taiwan.	70
Figure 3.16	Slope failure analysis at Tungmen, Hualien, Taiwan (a) hourly rainfall and accumulated rainfall, (b) computed depth of wetting front,
(c) computed failure probability, (d) distribution plot of the time of failure.	71
Figure 4.1	Location of the studied slopes at T18 Alishan mountain road.	73
Figure 4.2	Geologic map on T18 Alishan mountain road.	74
Figure 4.3	Cross-section geologic map of the Alishan road.	74
Figure 4.4	Location of soil sampling.	75
Figure 4.5	Subsurface conditions from the bor data.	76
Figure 4.6	Particle size distribution and the estimated soil water characteristics curve.	77
Figure 4.7	Shallow landslide at mileage 26K+100 after typhoon Mindulle.	78
Figure 4.8	Rainfall hyetograph from 1-7 July 2004 during typhoon Mindulle.	79
Figure 4.9	Rainfall hyetograph from 16-20 September 2001 during typhoon Nari.	80
Figure 4.10	Rainfall hyetograph from 29-31 July 2001 during typhoon Toraji.	80
Figure 4.11	Failure probability of the studied-slopes during typhoon Mindulle.	82
Figure 4.12	Failure probability of the studied-slopes during typhoon Nari.	83
Figure 4.13	Failure probability of the studied-slopes during typhoon Toraji.	83
Figure 4.14	Corrlation between accumulated rainfall and failure probability
of the studied slope at T18 mountain road.	84
Figure 4.15	Reliability index and failure probability relationship of the studied-slopes.	85
Figure 4.16	(a) Estimated depth of wetting front, (b) failure probability,
(c) distribution of the time of failure during typhoon Mindulle.	86
Figure 4.17	(a) Estimated depth of wetting front, (b) failure probability,
(c) distribution of the estimated time of failure during typhoon Nari.	87
Figure 4.18	(a) Estimated depth of wetting front, (b) failure probability,
(c) distribution of the estimated time of failure during typhoon Toraji.	88
Figure 4.19	Typical characteristics of rainfall induced landslide.	90
Figure 4.20	Probability threshold rainfall for T18 mountain road: Model TR-1.	92
Figure 4.21	Probability threshold rainfall for T18 mountain road: Model TR-2.	93
Figure 4.22	Probability threshold rainfall for T18 mountain road: Model TR-3.	93
Figure 4.23	Probability threshold rainfall for T18 mountain road: Model TR-4.	94
Figure 4.24	Correlation between Pf (Logit) and Pf (MCSM) for typhoons
(a) Mindulle, (b) Nari, (c) Toraji.	94
Figure 4.28	Rainfall pattern (a) uniformed, (b) delayed, (c) centralized,
and (d) advanced.	95


 
LIST OF TABLES
Table 2.1	Common causes of landslides.	7
Table 2.2	Classification of slope movements.	7
Table 2.3	Intensity-duration empirical thresholds for the initiation of landslides.	12
Table 2.4	Mathematical equations of Soil Water Characteristic Curve (SWCC)	30
Table 2.5	Equations for hydraulic conductivity.	31
Table 2.6	Green Ampt infiltration parameters for typical soils.	32
Table 2.7	Equations for estimating the soil suction head at wetting front.	32
Table 2.8	Values of the model variable .	36
Table 2.9	Common PDF models for continuous random variables.	46
Table 2.10	Statistics of prescribed distributions.	49
Table 3.1	Parameters used for Tuscany and Tung Chung East landslide cases.	59
Table 3.2	Parameters used for Boso Peninsula and Tungmen landslide cases.	59
Table 4.1	Locations of the shallow landslides.	78
Table 4.2	Range, mean and COV of the variables used in the probability analysis.	81
Table 4.3	Estimated time of failure for each location of the studied-slopes.	89
Table 4.4	Logistic regression equation of the threshold rainfall for roadside-slope along T18 mountain road.	91
                                

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