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研究生:哈里森
研究生(外文):John FranklinHarrison
論文名稱:以多期崩塌資料與潛勢模式評估強降雨災害後臺灣高屏溪流域沉積物輸送、河水濁度狀態與防救災資訊之變動
論文名稱(外文):The application of landslide-inventory based models for assessing sediment transport, turbidity and landslide susceptibility management in the Gaoping River Basin, Taiwan
指導教授:張智華張智華引用關係
指導教授(外文):Chih-Hua Chang
學位類別:博士
校院名稱:國立成功大學
系所名稱:環境工程學系
學門:工程學門
學類:環境工程學類
論文種類:學術論文
論文出版年:2020
畢業學年度:108
語文別:英文
論文頁數:150
外文關鍵詞:landslidesturbiditysediment loadSWATTyphoon MorakotRemote SensingLandslide Susceptibility Index (LSI)modulationGeohazardsHazard PlanningGIS
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Landslides and sediment delivery processes in watersheds have become one of the greatest geological problems facing Southern Taiwan, altering drainage patterns and increasing sediment delivery downstream. The influx of landslide-related sediment input is especially important in drinking water designated watersheds, as drinking water treatment plants are unable to operate during high turbidity events, causing significant stoppages to water services for millions of residents. Moreover, typhoon-induced landslide hazards pose the greatest risk to property and life in Southern Taiwan.
This study examines the impacts of storm-triggered landslides on downstream sediment and turbidity responses in the Gaoping River Basin, Taiwan using the Soil and Water Assessment Tool (SWAT). Attention is given to analyzing the increased and altered baseline of suspended sediment load and turbidity after the disturbances caused by the rainfall and landslides associated with Typhoon Morakot in 2009. The results show alterations in sediment erosion and transport: (1) drastically increased the turbidity baseline and occurrence of high-turbidity; (2) altered coefficient and exponent values of the sediment rating curve; and (3) altered relationship between rainfall and induced turbidity during major rainfall events. The research in this study provides an improved modeling approach to typhoon-induced alterations on river sediment loads and turbidity.
To assess landslide probability, the identification of inventory based landslide susceptibility index (LSI) models based the selection of causative factors, functional relationships between factors and integration to a hazard-warning mode is investigated. Merged landslide inventories of five typhoon-training events and obtained set of data representing environmental conditions where landslides are likely to occur. These well-defined data sets are used to select five representative causative factors, including slope angle, rock strength, drainage, curvature and soil type. Four bivariate statistical model combinations tested include; linear combination, geometric mean, and two mixed combinations. As a result, the modulation effects between (1) rock strength and slope and (2) drainage and curvature were intensified in mixed model 2 (MX2) through factor multiplication. The MX2 LSI was integrated with three multivariate landslide hazards warning models and tested with four triggering factor rainfall parameter sets. Results show threshold models with terrain influenced rainfall can better approximate hazard warning locations. Modulating factor combinations for the hazard warning can also mirror true environmental conditions, which allow for more representative model results.
A framework is developed to assess a mountain community vulnerable geohazards. The combination of a landslide susceptibility index (LSI) model, landslide inventory datasets, and field work is used to identify hazard-prone areas in Maolin District, Taiwan. Furthermore, to identify the challenges and opportunities affecting the sustainable development of mountain communities, a pilot survey was conducted in three such communities (Dona Village, Wanshan Village, and Maolin Village). The results reveal that there are two types of significant mass movement in such areas: debris avalanche and debris flow. The results also show that the LSI map and multi-temporal landslide inventory datasets correlate with landslide locations. Meander is identified as an important factor in landslide activity. The questionnaire results show that the residents of the study area lack awareness of and access to information related to landslide activity. Similarly, the local residents favor increased environmental protection, working within their community, and additional government spending in regard to managing geohazards.
Abstract i
Acknowledgements iv
Table of Contents v
List of Tables viii
List of Figures x
Chapter I – Introduction 1
1.1 Background – Gaoping River Basin (GRB) Overview 1
1.1.1 Physical, Geological and Meteorological Condition 1
1.1.2 Impacts of Typhoon Morakot 2
1.1.3 Landslide Inventory Maps 4
1.1.4 Landslide Susceptibility Modeling Approaches 5
1.1.5 Statistical Modeling Approaches 6
1.2 Goal and Objectives 9
1.3 Research Framework Overview 10
Chapter II - Modeling Typhoon-Induced Alterations on River Sediment Transport and Turbidity Based on Dynamic Landslide Inventories: Gaoping River Basin, Taiwan1 12
2.1 Introduction 13
2.2 Study area 16
2.3 Data collection 18
2.3.1 Turbidity 18
2.3.2 Precipitation 19
2.3.3 River discharge and suspended sediment load 21
2.3.4 Inventory of landslides 21
2.3.5 Landslide updating 23
2.3.6 SWAT 25
2.3.7 Objective functions 28
2.4 Results and Discussion 29
2.4.1 The Alterations in Turbidity and Sediment Regimes after Typhoon Morakot 29
2.4.1.1 Turbidity 29
2.4.1.2 Sediment Load 32
2.4.1.3 Sediment rating curve 34
2.4.2 Simulation of River Flow, Sediment Loads and Turbidity Using SWAT 36
2.4.2.1 River Flow Simulation 36
2.4.2.2 Sediment Load Simulation 38
2.4.2.3 Turbidity Simulation 41
2.4.3 Modeling the Effect of Landslides an Annual Sediment Yields 42
2.4.3.1 Comparison between SWAT Modeling Results with and without the Use of Landslide Updating 42
2.4.3.2 Integration of Landslide Updating and SWAT Modeling 44
2.5 Conclusions 45
Chapter III - Identification of Inventory-Based Susceptibility Models for Assessing Landslide Probability: A case study of the Gaoping River Basin, Taiwan2 48
3.1 Introduction 49
3.2 Material and methods 51
3.2.1 Study area 51
3.2.2 Landslide inventory 54
3.2.3 Factor Selection 55
3.2.3.1 Causative factors 55
3.2.3.2 Triggering factors 61
3.2.4 Identification of inventory-based statistical models 63
3.2.4.1 Bivariate statistical mapping (quantitative spatial analysis) 63
3.2.5 Functional relationships between landslide susceptibility and causative factors 65
3.2.6 Landslide hazard warning models 67
3.2.6.1 Estimation of triggering threshold using simple linear regression (SLR) 67
3.2.6.2 Prediction of landslide occurrence using logistic regression (LR) 68
3.2.6.3 Estimation of triggering threshold using modulation (MOD) 69
3.2.7 Performance evaluation 69
3.3 Results and Discussion 70
3.3.1 The Information Value (IFV) of factors 70
3.3.1.1 IFV for Causative Factors 70
3.3.1.2 Weighting for triggering factors 71
3.3.2. Identification the functional relationships of landslide susceptibility models 71
3.3.2.1 Comparisons based on performance indicator 71
3.3.2.2 Visual interpretation of susceptibility maps 73
3.3.3 Modulation effects 77
3.3.3.1 Slope and rock strength 77
3.3.3.2 Curvature and drainage 78
3.3.4 Combing LSI and triggering factors for landslide warning 78
3.3.4.1 Triggering factors 79
3.3.4.2 Comparisons between warning models 79
3.4 Conclusion 83
Chapter IV - Sustainable Management of a Mountain Community Vulnerable to Geohazards: A Case Study of Maolin District, Taiwan3 85
4.1 Introduction 86
4.2 Materials and Methods 89
4.2.1 Maolin District 89
4.2.2 Framework 90
4.2.3 Landslide Susceptibility Index (LSI) 92
4.2.4 Landslide Inventory 93
4.2.5 Field Work 95
4.3 Results and Discussion 97
4.3.1 Combination of Landslide Inventory and Field Work Analysis 97
4.3.2 Questionnaire Results 101
4.3.3 Landslide Susceptibility Index Map Evaluation 106
4.3.4 Landslide Zone Map Results 110
4.3.5 Discussion 113
4.4 Conclusions 115
Chapter V - Conclusions 117
5.1 Summary 117
5.2 Limitations 119
5.3 Implications and future research 120
References 123
Appendices 142
Appendix A Eleven questions developed and delivered to the residents of Maolin District. 143
Appendix B Questionnaire Results Information and Awareness (1/3) 144
Appendix C Questionnaire Results Economy and Natural Capital (1/3) 147
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