Impact of Climate Change, Land Use and Land Cover, and Socio-economic Dynamics on Landslides

Preface
About This Book
Contents
Editors and Contributors
Part I Climate Change and Extreme Events On Landslide
1 Association of Climate Change to Landslide Vulnerability and Occurrences in Bhutan
1.1 Introduction
1.2 Study Area
1.3 Geology of Bhutan
1.4 Climatic Geohydrology
1.5 Climatic Data
1.6 Methodology
1.6.1 Data Collection
1.6.2 Spatial Analysis
1.7 Landslide Inventory
1.7.1 Landslides in Phuentsholing
1.7.2 Landslides in Sarpang Dzongkhag
1.7.3 Samdrup Jongkhar-Trashigang–Mongar Landslide
1.8 Climate Change and Landslide Vulnerabilities
1.9 Conclusions
References
2 A Framework for Assessing Landslide Risk in Hilly Terrains
2.1 Introduction
2.2 Overview of the Framework
2.2.1 Landslide Susceptibility Zonation (LSZ)
2.2.2 Landslide Vulnerability Assessment
2.2.3 Landslide Risk Assessment (LRA)
2.3 Case Study and Implementation of the Framework
2.4 Results
2.5 Conclusions
References
3 Landslide Dam Outburst in Myagdi, Nepal: Early Warning and Preparedness Key to Minimizing Disaster
3.1 Background
3.2 Physical Causes and Consequences
3.3 Recent Landslide Dams in Nepal
3.4 Landslide in Myagdi District
3.4.1 Baisari Land/rock-Slide Dam
3.4.2 Landslide Dam Outburst Flood
3.5 Disaster Management and Preparedness
3.5.1 Monitoring Water Level Downstream
3.5.2 Calculation of Discharge from Landslide Failure Flood in Kaligandaki
3.5.3 Disaster Management Plans
3.5.4 Communication of Warning and Moving People to Higher Grounds
3.6 Lessons Learnt
3.6.1 Pre-emptive Action—Critical
3.6.2 Proper Landuse Planning—A Key
References
4 Landslide Risk Along the Sichuan-Tibetan Railway
4.1 Introduction
4.2 Environments of Study Area
4.2.1 Plateau Uplift and Geomorphic Pattern
4.2.2 Climate and Climate Change
4.2.3 Mountain Hydrology
4.2.4 Vegetation Types
4.3 Geohazard Characteristics
4.3.1 Geohazard Types
4.3.2 Landslide Distribution
4.3.3 The Way of Mass Movement and Its Influence on Railway Engineering
4.4 Landslide Risk
4.4.1 Methodology
4.4.2 Results
4.5 Conclusions
References
5 Landslide, Agricultural Vulnerability, and Community Initiatives: A Case Study in South-East Part of Bangladesh
5.1 Introduction
5.2 History of Landslides in Bangladesh
5.3 Conditions/Characters of Southeast Part of Bangladesh
5.3.1 Stratigraphy
5.3.2 Geomorphology and Topography
5.3.3 Climate: Rainfall and Temperature
5.4 Factors/Causes of Landslide
5.4.1 Weak Soil Structure and Permeability
5.4.2 Rainfall
5.4.3 Nature of Hill Slopes
5.4.4 Earthquake
5.4.5 Erosion
5.4.6 Volcanoes
5.4.7 Weathering
5.4.8 Gravity
5.4.9 Hill Cutting
5.4.10 De-vegetation and Land Use Cover
5.4.11 Establishment of Settlement
5.4.12 Mining
5.4.13 Institutional Factors Triggering Landslide Vulnerability
5.5 Impact of Landslide on Agriculture
5.5.1 Community Dependency on Agriculture in South-Eastern Hilly Areas of Bangladesh
5.5.2 Impact on Crop and Crop Field
5.5.3 Impact on Fisheries, Poultry, and Livestock Sector
5.5.4 Impact on Farmers’ Livelihood
5.5.5 Impact on Socio-economy
5.6 Community Approach to Tackling Landslide
5.6.1 Public Awareness
5.6.2 Disaster Preparedness and Awareness-Raising at the School Level
5.6.3 Promotion and Practicing of Volunteerism
5.6.4 Introduction and Development of Policy
5.7 Conclusion and Recommendations
References
Part II Advanced Geospatial Modelling On Land-Use and Land-Cover Change
6 Landslide, Land Cover, and Land use Changes and Its Impacts in Nepal
6.1 Introduction
6.2 Landslide Hazard Trends in Nepal
6.3 Land Use and Land Cover Change
6.3.1 Status and Pattern of Major LULC
6.3.2 Spatio-temporal variation of LULC
6.4 Landslide Characteristics
6.5 Conclusion
References
7 Comparison Between Two Different Methods Applied to Define Rainfall Thresholds for Landslide Forecasting in Idukki District of Kerala, India
7.1 Introduction
7.2 Study Area
7.3 Material and Methods
7.4 Methods Used
7.4.1 Bayesian Model of Probabilistic Approach
7.4.2 TRIGRS: Physical Model
7.4.3 Comparison of Models
7.5 Result and Discussion
7.5.1 Result of Bayesian Model
7.5.2 Result of TRIGRS Model
7.5.3 Result from Comparison of Models
7.6 Conclusion
References
8 Prediction of Amount of Rainfall on Landslide day Using Artificial Neural Network for Bhutan
8.1 Introduction
8.2 Data and Methodology
8.2.1 Data
8.2.2 Methodology
8.3 Implementation Procedure
8.4 Result and Discussion
8.5 Conclusion
References
9 Measuring Landslide Susceptibility of Phuentsholling, Bhutan Using Novel Ensemble Machine Learning Methods
9.1 Introduction
9.2 Study Area
9.3 Materials and Methods
9.3.1 Preparing the Landslide Inventory Map
9.3.2 Preparing the Landslide Conditioning Factors (LCFs)
9.3.3 Multicollinearity Analysis
9.3.4 Machine Learning Models Used for the Preparation of Landslide Susceptibility Maps (LSMs)
9.3.5 Validation Methods
9.4 Results
9.4.1 Analyzing the Multicollinearity
9.4.2 Analyzing the Landslide Susceptibility Models
9.4.3 Analyzing the Significance of the LSFs Using Boosted Regression Tree (BRT)
9.4.4 Analyzing the Accuracy of the Models
9.5 Discussion
9.6 Conclusion
References
10 Application of RBF and MLP Neural Networks Integrating with Rotation Forest in Modeling Landslide Susceptibility of Sampheling, Bhutan
10.1 Introduction
10.2 Study Area
10.3 Materials and Methods
10.3.1 Preparing the Landslide Inventory Map
10.3.2 Preparing the Landslide Conditioning Factors (LCFs)
10.3.3 Multicollinearity Analysis
10.3.4 Machine Learning Models Used for Landslide Susceptibility Mapping (LSM)
10.3.5 Validation Methods
10.4 Results
10.4.1 Analyzing the Multicollinearity
10.4.2 Analyzing the Landslide Susceptibility Models
10.4.3 Analyzing the Significance of the LSFs Using IGR (Information Gain Ratio)
10.4.4 Analyzing the Accuracy of the Models
10.5 Discussion
10.6 Conclusion
References
11 Use of Probabilistically Generated Scenario Earthquakes in Landslide Hazard Zonation: A Semi-qualitative Approach
11.1 Preamble
11.2 Types of Landslides
11.3 Landslide Causative Factors
11.4 Earthquake-Induced Landslides
11.5 Earthquake-Induced Landslide Hazard Studies for the Himalayan Region
11.6 Challenges in Earthquake-Induced Landslide Hazard Assessment
11.7 Application of Probabilistic Seismic Hazard Assessment (PSHA) for Earthquake-Induced Landslide Analysis: An Alternate Approach
11.8 Application of PSHA for Earthquake-Induced Landslide Hazard Analysis: A Case Study
11.9 Preparation of Landslide Database
11.9.1 Landslide Distribution Map of the Study Area
11.9.2 Digital Elevation Model (DEM) and Its Derivatives
11.9.3 Fault Euclidean Distance Map
11.9.4 Road Euclidean Distance Map
11.10 Probabilistic Seismic Hazard Assessment and Peak Ground Acceleration Map
11.10.1 Poisson Probability Distributions for Inter-arrival Time
11.10.2 Seismotectonic Modelling
11.10.3 Peak Ground Acceleration Map
11.11 Earthquake-Induced Landslide Hazard Analysis
11.11.1 Landslide Hazard Zonation Map Excluding Scenario Earthquakes
11.11.2 Landslide Hazard Zonation Map Under Scenario Earthquakes
11.12 Conclusion
References
12 Predicting the Landslide Susceptibility Using Ensembles of Bagging with RF and REPTree in Logchina, Bhutan
12.1 Introduction
12.2 Study Area
12.3 Materials and Methods
12.3.1 Preparing the Landslide Inventory Map
12.3.2 Preparing the Landslide Conditioning Factors (LSFs)
12.3.3 Multicollinearity Analysis
12.3.4 Machine Learning Models Involved in Landslide Susceptibility Mapping (LSM)
12.3.5 Validation Methods
12.4 Results
12.4.1 Analyzing the Multicollinearity
12.4.2 Analyzing the Landslide Susceptibility Models
12.4.3 Analyzing the Significance of the LSFs Using RF
12.4.4 Analyzing the Accuracy of the Models
12.5 Discussion
12.6 Conclusion
References
Part III Effect On Socio-Economic Aspects Due to Landslides
13 Assessing Social Vulnerability to Landslide Disasters in Chittagong City, Bangladesh
13.1 Introduction
13.2 Survey Methodology
13.3 Study Area Profile
13.3.1 Historic Profile of the Golpahar Area
13.3.2 Socio-physical Characteristics
13.3.3 Institutional Context Associated with Landslide Vulnerability
13.4 Socio-economic Aspects
13.5 Landslide Scenario and People’s Response
13.5.1 Experience of Previous Landslides
13.5.2 Landslide Risk Management and Coping Mechanism
13.5.3 Landslide Vulnerability and people’s Aspirations
13.6 Conclusion
References
14 The Vulnerability of Human Population to Landslide Disaster: A Case Study of Sikkim Himalayas
14.1 Introduction
14.2 Study Area
14.3 Methodology
14.3.1 Database Generation of Elements at Risk
14.3.2 Generation of Landslide Inventory and Susceptibility
14.3.3 Vulnerability Assessment
14.3.4 Human Vulnerability (Vh)/Social Vulnerability
14.4 Results and Discussion
14.4.1 Social Element
14.4.2 Social Vulnerability
14.5 Conclusion
References
15 Integration of Socioeconomic Dynamics and Communities’ Resilience to Landslides in Swat Valley, Pakistan
15.1 Introduction
15.2 The Study Area
15.3 Swat Valley: Socioeconomic Dynamics and Community Resilience to Landslides
15.3.1 Topography
15.3.2 Population
15.3.3 Natural Resources
15.3.4 Climate
15.4 Swat Valley: Landslide and Resilience to Landslides
15.4.1 Methodology and Data Collection
15.4.2 Daral Valley: Socioeconomic Dynamics and Community Resilience to Landslides
15.4.3 Chail Valley: Socioeconomic Dynamics and Community Resilience to Landslides
15.5 Analysis and Discussion
15.6 Conclusion
References
16 Refugee Camps at Landslide Risk: Studying Mitigation Measures
16.1 Introduction
16.2 Literature Review
16.2.1 Vulnerability to Landslide and Mitigation Measures
16.2.2 Living Conditions in the Rohingya Camps
16.3 Methodology
16.4 Results
16.4.1 Landslide Incidents and Consequences
16.4.2 Measures for Reducing Landslide Risks
16.4.3 Community Reactions
16.5 Discussions
16.6 Recommendations
16.7 Conclusions
References
17 Introducing Japanese Landslide Warning System to Sri Lanka: Analyzing the Social Differences for Successful Technology Transfer
17.1 Introduction
17.1.1 Similar Phenomena of Landslides in Sri Lanka and Japan
17.1.2 Similar Topography and Different Land Cover
17.2 Social-Economic Differences in Mountain Area in Sri Lanka and Japan
17.2.1 Socio-Economic Aspect in Sri Lanka
17.2.2 Socio-Economic Aspect in Japan
17.3 Measures Against Landslides
17.3.1 Non-structural Measures in Sri Lanka
17.3.2 Structural Measures in Sri Lanka
17.3.3 Measures Against Landslides in Japan
17.4 Social Background for Developing Early Warning and Evacuation System
17.4.1 Social Background for Effective Early Warning and Evacuation in Japan
17.4.2 Social Background for Introducing Early Warning System in Sri Lanka
17.5 Information System
17.5.1 Information Media for Early Warning in Mountain Area in Japan
17.5.2 Considerable Information Media for Early Warning in Mountain Area in Sri Lanka
17.6 Conclusion
References
18 Land Cover Changes and Landslide Risk in Sri Lanka
18.1 Introduction
18.2 Emerging Trends of Landslides in Sri Lanka
18.2.1 Spatial Dispersion of Landslides
18.2.2 Seasonal Variation of Landslides
18.3 Causes of Landslides in Sri Lanka
18.3.1 Physical Characteristics
18.3.2 Influence of Climate
18.3.3 Anthropogenic Triggers of Landslides
18.4 Impact of Land Cover Changes: Evidence from a Recent Landslide
18.4.1 A Case: Aranayake Landslide
18.4.2 A Case: Meeriyabedda Landslide
18.4.3 A Case: Galaha-Deltota Landslide
18.5 Conclusion
References
19 Urban–Rural Connectivity for Forest Management and Landslide Risk Reduction: Case of Japan
19.1 Introduction
19.2 Japan’s Forests and Forestry Industry
19.3 Forest Management Policies for Landslide Risk Reduction in Japan
19.4 Japanese Strategies of Enhancing Urban–Rural Connectivity for Sustainable Forest Management
19.4.1 Payment for Ecosystem Service (PES) Mechanisms
19.4.2 Social Forestry
19.4.3 Restoration of Satoyama Landscapes
19.4.4 Promoting Regional Circulating and Ecological Sphere (Regional-CES) Approach
19.5 Key Takeaway Lessons
19.5.1 Need for Investing in Rural Ecosystems
19.5.2 Institutionalizing PES Schemes
19.5.3 Building Urban–Rural Synergies for Regional-CES
References
20 Slope Stabilization Using Soil Nails, Practice and Construction Realities: A Case Study on the Construction of Soil Nailed Wall Along Phuentsholing-Thimphu Highway, Bhutan
20.1 Introduction
20.2 Study Area
20.3 Methodology
20.3.1 Earthwork Excavation
20.3.2 Drilling of Holes for Soil Nail
20.3.3 Installation and Grouting of Nail
20.3.4 Sub-horizontal Drain
20.3.5 External Fascia
20.4 Result
20.5 Conclusion
References
21 Cross-Cutting Issues in Landslide Hazard of Japan: Forest Management, Climate Change, Demographic Change and Aging Society
21.1 Introduction
21.2 Landslides in Japan
21.2.1 Landslide-Prone Topography
21.2.2 Landslide-Prone Weather and Climate
21.3 Forest Management and Landslides in Japan
21.3.1 Effect of Forest Management
21.3.2 Forest Management and Ownership of Japan’s Forest
21.3.3 Forestry Management to Forest Management
21.3.4 Deforestation and Landslides
21.4 Climate Change and Landslides in Japan
21.5 Demographic Change and Landslides in Japan
21.5.1 Decreasing Population and Aging Society
21.5.2 Aging Foresters in Mountainous Areas
21.5.3 Forest Management by Non-Resident Forest Owners
21.6 Cross-Cutting Issues in Landslide Hazard
21.7 Conclusion
References