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