Community Based Multi-Hazard Risk Assessment Of Muglu Khola Watershed in Rukum District Nepal -Final Report-

Submitted to: United Nations Development Programme (UNDP) Comprehensive Disaster Risk Management Programme (CDRMP) Lalitpur Nepal

Prepared by: ECO Nepal Kathmandu Nepal And Nepal Public Awakening Forum Khalanga-2, Salle, Rukum

Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Table of Contents

Table of Contents

Assessment Team ...... b Abbreviation ...... c Chapter 1 Introduction ...... - 1 - 1.1 Background ...... - 1 - 1.2 Objectives of the Study ...... - 2 - 1.3 Scope of the Study ...... - 2 - 1.4 Important Terminology ...... - 3 - Chapter 2 Study Area ...... - 5 - 2.1 Study Area ...... - 5 - 2.1.1 An Overview of Rukum ...... - 5 - 2.1.2 Muglu Khola Watershed ...... - 7 - Chapter 3 Climate Change Impact in the Study Area...... - 14 - 3.1 Climate Change Impact in Nepal ...... - 14 - 3.1.1 General Overview ...... - 14 - 3.1.2 Impact on Temperature ...... - 14 - 3.1.3 Impact on Precipitation ...... - 14 - 3.1.4 Impact on Runoff ...... - 15 - 3.1.5 Impact on Agricultural System ...... - 16 - 3.1.6 CC Adoptation in Nepal ...... - 17 - 3.2 Climate Change in Muglu Khola Watershed ...... - 18 - 3.2.1 People's Perception on CC ...... - 18 - 3.2.2 Trend Temperature Changes ...... - 19 - 3.2.3 Impact on Precipitation ...... - 25 - 3.3 Climate Change Impacts and Adaptation Practices ...... - 29 - Chapter 4 Flood Hazard Risk Assessment ...... - 31 - 4.1 General ...... - 31 - 4.2 Study Approach ...... - 31 - 4.3 Data Collection ...... - 32 - 4.4 Study Methodology ...... - 34 - 4.4.1 Flood Analysis...... - 34 - 4.4.2 Flood Hazard Mapping ...... - 37 - 4.5 Results and Discussion ...... - 40 - 4.5.1 Rainfall Analysis...... - 40 -

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Table of Contents

4.5.2 Flood Analysis and Prediction ...... - 43 - 4.5.3 Summary of Results ...... - 45 - 4.5.4 Flood Plain Mapping ...... - 46 - 4.5.5 Flood Risk Assessment ...... - 49 - 4.6 Summary and Conclusions ...... - 53 - Chapter 5 Landslide Hazard Risk Assessment ...... - 55 - 5.1 General ...... - 55 - 5.2 Landslide Processes ...... - 55 - 5.3 Landslides in the Study Area ...... - 57 - 5.4 Landslide Hazard Assessment Approach ...... - 59 - 5.4.1 Statistical Approach ...... - 59 - 5.4.2 Physically-based Approach ...... - 60 - 5.5 Results and Discussion ...... - 63 - 5.5.1 Statistical Method ...... - 63 - 5.5.2 Physically-based Methods...... - 67 - 5.6 Conclusions ...... - 69 - Chapter 6 Socio-Economic Profile ...... - 71 - 6.1 Methodology ...... - 71 - 6.2 District Profile ...... - 73 - 6.3 Demography of Muglu Khola Watershed ...... - 74 - 6.4 Occupation ...... - 75 - 6.5 Food Sufficiency ...... - 76 - 6.6 Health and Sanitation ...... - 77 - 6.7 Land Types, Land Holding and Cropping Pattern ...... - 78 - 6.8 Migration Pattern...... - 78 - 6.9 Energy Consumption ...... - 78 - 6.10 Archaeological and Historical Sites ...... - 78 - 6.11 Gender and Disadvantage Group ...... - 79 - 6.12 People’s Knowhow on Disasters ...... - 79 - 6.13 Institutional Capacity ...... - 80 - 6.14 Conclusions ...... - 82 - Chapter 7 Community Hazard Mapping ...... - 83 - 7.1 Introduction ...... - 83 - 7.2 Historical Time Line ...... - 84 -

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Table of Contents

7.3 Seasonal Calander ...... - 90 - 7.4 Hazard Mapping and Ranking ...... - 93 - Chapter 8 Vulnerability Risk Assessment ...... - 99 - 8.1 General ...... - 99 - 8.2 Methodology ...... - 99 - 8.2.1 Physical Vulnerability ...... - 100 - 8.2.2 Social Vulnerability ...... - 100 - 8.2.3 Perception on Disaster and Vulnerability Reducing Measures ...... - 101 - 8.2.4 Field Visits ...... - 101 - 8.2.5 Secondary Data ...... - 102 - 8.3 Community-based Vulnerability Risk Assessment ...... - 102 - Chapter 9 Watershed Management Plan ...... - 108 - 9.1 Introduction ...... - 108 - 9.2 Guiding Principle to Watershed Management Plan ...... - 108 - 9.3 Legal and Administrative Framework ...... - 109 - 9.4 Watershed Management Efforts in Rukum ...... - 109 - 9.5 Existing Land-use Pattern ...... - 111 - 9.5.1 Land-cover according to Agro-Climatic Zone ...... - 116 - 9.5.2 Land-cover by Slope ...... - 118 - 9.5.3 Land-cover by Aspect ...... - 120 - 9.6 Land Capability Classification ...... - 120 - 9.7 Action Plan for Risk Sensitive Land-use Plan ...... - 122 - Chapter 10 Conclusions and Recommendations ...... - 138 -

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Table of Contents

List of Figures

Figure 2-1: Location of the Study District ...... - 5 - Figure 2-2: Muglu Khola Watershed Location ...... - 8 - Figure 2-3: Muglu Khola Watershed Coverage showing Ward Boundaries ...... - 9 - Figure 2-4: DEM of the Muglu Khola Watershed ...... - 10 - Figure 2-5: Major Tributaries of the Muglu Khola ...... - 11 - Figure 3-1: Annual Maximum Extreme Temperature Analysis ...... - 19 - Figure 3-2: Annual Minimum Extreme Temperature Analysis...... - 20 - Figure 3-3: Trend in Mean Monthly Maximum Temperature Change at Muglu Khola Watershed . - 22 - Figure 3-4: Trend in Mean Monthly Minimum Temperature Change in Muglu Khola ...... - 25 - Figure 3-5: Trend in 24 hours Extreme Event Rainfall ...... - 26 - Figure 3-6: Annaul Rainfall Trend in the Muglu Khola Watershed ...... - 26 - Figure 3-7: Trend in Monthly Rainfall for Different Months ...... - 28 - Figure 3-8: Monsoon and Non Monsoon Rainfall Trend at Muglu Khola Watershed ...... - 29 - Figure 4-1: Land-cover Map of the Study Area from the FRA ...... - 33 - Figure 4-2: Mean Peak Flood versus Catchment Area in Karnali and Gandaki River Basin ...... - 35 - Figure 4-3: Sub-watershed Delineation for the Muglu Khola Watershed ...... - 36 - Figure 4-4: Flow chart illustrating Flood Hazard mapping using HEC RAS ...... - 39 - Figure 4-5: Total Annual and Monsoon Rainfall Pattern at Musikot Airport Station ...... - 41 - Figure 4-6: Analysis Daily Rainfall Extreme versus Return Period with Log Person Type III Method . - 42 - Figure 4-7: Plot of HEC GeoHMS Simulation Results in different Return Periods ...... - 45 - Figure 4-8: Flood Inundation Map of Muglu Khola for 2 Year Return Period ...... - 47 - Figure 4-9: Flood Inundation Map of Muglu Khola for5 Year Return Period ...... - 47 - Figure 4-10: Flood Inundation Map of Muglu Khola for 10 Year Return Period ...... - 48 - Figure 4-11: Flood Inundation Map of Muglu Khola for 50 Year Return Period ...... - 48 - Figure 4-12: Flood Inundation Map of Muglu Khola for 100 Year Return Period ...... - 49 - Figure 4-13: High Flood Level Marking near the Confluence of Muglu Khola with Sani Bheri ...... - 50 - Figure 4-14: Threat to Simratu Bazar due to Bank Cutting and Sediment Transport ...... - 50 - Figure 4-15: Highly Flood Prone Bairagi Thati Bazar ...... - 51 - Figure 4-16: Impact of Flood on Low Land Valley Cultivation in 2 Year Return Period Scenario. Green polygon represents the paddy cultivation area...... - 51 - Figure 4-17: Flood Threat to Cultivation Land in Jhulkhet of Sankh VDC ...... - 52 - Figure 4-18: House at Risk in Muru ...... - 52 - Figure 4-19: River Cutting and Sediment Transport affecting the Valley Cultivation Near Bairagee Thanti ...... - 53 - Figure 5-1: Deep-seated Landslide Characteristics ...... - 56 - Figure 5-2: Schematic Diagram of Shallow Landslides ...... - 56 - Figure 5-3: Images showing Landslide Distribution in the Study Area ...... - 58 - Figure 5-4: Landslide Distribution in the Muglu Khola Watershed ...... - 58 - Figure 5-5: Schematic representation of Infinite Slope Method depicting various Parameters and Variables ...... - 61 - Figure 5-6: Flow chart depicting the present methodology to derive slope stability maps from basic GIS data of topography, land-cover, soil types and precipitation time series ...... - 62 -

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Table of Contents

Figure 5-7: Relationship between Landslides and different Causative Factors in the Muglu Khola Watershed...... - 65 - Figure 5-8: Rate Curve of Hazard Index Value after Weights of Evidence Value...... - 66 - Figure 5-9: Landslide Hazard Prediction using Statistical Approach ...... - 67 - Figure 5-10: Hazard Mapping for 2 Year Return Period Rainfall Event ...... - 68 - Figure 5-11: Hazard Mapping for 100 Year Return Period Rainfall Event ...... - 68 - Figure 6-1: Community Interaction Program for Collecting Primary Data ...... - 72 - Figure 6-2: Institutional Capacity in the Muglu Khola Watershed ...... - 81 - Figure 7-1: Historical Time Line Prepared by Community ...... - 85 - Figure 7-2: Community Preparing Seasonal Calander ...... - 91 - Figure 7-3: Community Hazard Mapping of Muglu Khola Watershed ...... - 94 - Figure 7-4: Hazard Ranking by Community...... - 94 - Figure 7-5: Community Hazard Mapping and Ranking of Bhalakcha VDC ...... - 95 - Figure 7-6: Community Hazard Mapping and Ranking of Bhalakcha VDC ...... - 95 - Figure 7-7: Community Hazard Mapping and Ranking of Chhibang VDC ...... - 96 - Figure 7-8: Community Hazard Mapping and Ranking of Khalanga Musikot VDC ...... - 96 - Figure 7-9: Community Hazard Mapping and Ranking of Khara VDC ...... - 97 - Figure 7-10: Community Hazard Mapping and Ranking of Muru VDC ...... - 97 - Figure 7-11: Community Hazard Mapping and Ranking of Peugha VDC ...... - 98 - Figure 7-12:Community Hazard Mapping and Ranking of Peugha VDC ...... - 98 - Figure 8-1: Community Participation in Vulnerability Risk Assessment ...... - 102 - Figure 9-1: Sub-watershed Delineation in Rukum (Source: Priority Ranking of Sub-Watershed in Rukum) ...... - 110 - Figure 9-2: Land-use Erosion Potential map (Source: Priority Ranking of Sub-Watershed in Rukum) ... - 110 - Figure 9-3: Priority Ranking of the Sub-watersheds in Rukum (Source: Priority Ranking of Sub- Watershed in Rukum) ...... - 111 - Figure 9-4: Existing Land-use Pattern in the Muglu Khola Watershed ...... - 112 - Figure 9-5: Current Land-use Pattern in and around Muskot Khalanga ...... - 112 - Figure 9-6: White Radish Seed Production near the Muskiot Area ...... - 116 - Figure 9-7: Land Capability Classification of the Muglu Khola Watershed ...... - 121 - Figure 9-8: Community Group Discussion in the Workshop and Participant ...... - 122 -

List of Tables Table 2-1: Mean Monthly Rainfall Recorded at Musikot Station ...... - 6 - Table 2-2: Main Land-cover in the District ...... - 6 - Table 2-3: Major Sub-watersheds of the Muglu Khola Watershed ...... - 11 - Table 2-4: Different Land-covers in the Study Area from two Different Data Sources ...... - 12 - Table 2-5: Soil Distribution of the Study Area...... - 12 - Table 3-1: Anticipated Cliamte Change Impacts in Nepal ...... - 16 - Table 3-2: Mean Monthly Maximum Temperature Change Pattern ...... - 22 - Table 3-3: Mean Monthly Minimum Temperature Change Pattern in Muglu Khola ...... - 25 - Table 4-1: Curve Number (CN) used in Modelling ...... - 37 - Table 4-2: Monthly Rainfall Records at Musikot ...... - 41 -

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Table of Contents

Table 4-3: Peak Flood Estimation using HYDEST Method ...... - 43 - Table 4-4: Peak Flood Estimation using Revised WECS-DHM Method ...... - 43 - Table 4-5: Peak Flood Estimation using Dicken Method ...... - 43 - Table 4-6: Observed Peak Flood Discharge for the Stations ...... - 43 - Table 4-7: Median Flood Ratio and Peak Flood Computation for the Muglu Khola ...... - 44 - Table 4-8: Peak Flood Estimation Transposing with Sarada River ...... - 44 - Table 4-9: Peak Flood Prediction from Transposing with Thuli Bheri ...... - 44 - Table 4-10: Flood Prediction using HEC GeoHMS ...... - 45 - Table 4-11: Peak Flood Estimation using Different Methods ...... - 45 - Table 4-12: Peak Flood for Muglu and its Tributaries at their Outlet ...... - 46 - Table 4-13: Flood Inundated Area in Different Return Period...... - 49 - Table 5-1: Landslide Classification ...... - 55 - Table 5-2: Landslide Distribution in Different VDCs of Muglu Khola Watershed ...... - 59 - Table 5-3: Values of safety factor with hazard classification ...... - 61 - Table 5-4: Soil related parameters used in the landslide modelling ...... - 62 - Table 5-5: Landslide related Parameters used in the Landslide Modelling from the Land-use Map . - 63 - Table 5-6: Relationship of various causative factors with the LHI ...... - 65 - Table 5-7: Landslide hazard area classification in the watershed in 2 and 100 year return period rainfall event ...... - 69 - Table 6-1: Comparative Description of the Region and the District ...... - 73 - Table 6-2: Demographic Structure of Muglu Khola Watershed ...... - 74 - Table 6-3: Caste Basis Demographic Composition...... - 74 - Table 6-4: Demographic Distribution According to Age and Sex Group ...... - 75 - Table 6-5: Demographic Ditribution according to Occupation ...... - 76 - Table 6-6: Sampled Landholding Pattern ...... - 76 - Table 6-7: Various Reasons for Leaving Agricultural Land without Cultivation ...... - 77 - Table 6-8: Health and Sanitation Condition in the Project Area ...... - 77 - Table 6-9: People’s Knowledge on Reasons for Disasters ...... - 80 - Table 6-10: Institutional Capacity in the Project Affected VDCs...... - 80 - Table 7-1: Disasters History in Muglu Khola Watershed VDCs in Rukum ...... - 86 - Table 7-2: Seasonal Calanders Prepared by the Communities ...... - 91 - Table 8-1: Data Acquired from Primary and Secondary Sources ...... - 100 - Table 8-2: Quantitative Indicators ...... - 100 - Table 8-3: Qualitative Indicators ...... - 101 - Table 8-4: Risk Assessment of the Muglu Khola Watershed ...... - 103 - Table 9-1: Existing Land-use Distribution in the Project Area VDCs ...... - 113 - Table 9-2: Agro-Climatic Zone of Muglu Khola Watershed ...... - 116 - Table 9-3: Land-Cover in Different VDCs according to Agro-Climiatic Zone ...... - 117 - Table 9-4: Land-use Distribution by Slope in the Study VDCs...... - 119 - Table 9-5: Aspect of the Watershed ...... - 120 - Table 9-6: Land Capability Classification in the Muglu Khola Watershed ...... - 122 - Table 9-7: Details of Workshops Conducted in Different VDCs of the Watershed ...... - 122 - Table 9-8: General Framework of Proposed Plan of Action ...... - 124 -

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Acknowledgement

Acknowledgement The Study Team would like to express its gratitude to UNDP Nepal for providing us an opportunity to undertake this interesting study. We are particularly indebted to Mr. Man Thapa (Program Manager), Ms Krishna Karki (Senior Program Officer) and Mr. Deepak K.C. (Program Officer) Comprehensive Disaster Risk Management Programme (CDRMP) –UNDP for their invaluable support and guidance for this study. Their excellent ideas helped us formulate the work and carryout the work in a smooth way. Without their critical feedback and review, the quality of this report would have suffered. We highly acknowledge to the N-PAF, Rukum and ECO-Nepal Kathmandu for their all kind support during the field visit and desk work to give in its final shape and we are equally thankful to Mr. Amrit Sharma, Project Coordinator and the team for their invaluable support. It is our great pleasure to extend our sincere thanks to various government organizations in Rukum such as District Development Committee (DDC) Rukum, District Soil Conservation Office (DSCO), District Forest Office (DFO), District Agriculture Development Office (DADO), District Administration Office (DAO) for providing valuable information and data; the report would not be produced in this form without their help. Our sincere thanks also go to International Centre for Integrated Mountain Development (ICIMOD) and Forest Resources Assessment Project; they provided us high resolution recent satellite image of the project area. Our sincere appreciations are also extended to all the experts whose contributions were significant in bringing out this report. Finally, this study would not be possible without active participation and support from the local level; we would like to thank all of them.

Assessment Team N-PAF, Rukum and ECO-Nepal, Kathmandu 2012

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Study Team

Assessment Team Dr. Govind Acharya Team Leader, Hazard Geotechnical/GIS Expert Dr. Ramesh Man Tuladhar, Engineer, Structural and Bio-engineer Dr. Parameshor Pokheral, Land-use Watershed Management Expert Dr. Bindu Pokharel Socio-economist/Social Vulnerability Analyst Mr. Nawa Raj Shrestha, Research Associates Mr. Sanjeevan Shrestha, Research Associates

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Abbreviation

Abbreviation amsl : above mean sea level ANUDEM : Australian National University Digital Elevation BS : Bikram Sambat CC : Climate Change CCA : Climate Change Adaptation CBDRM : Community Based Disaster Risk Management CDRMP : Comprehensive Disaster Risk Management Programme CF : Community Forest CN : Curve Number CRR : Climate Risk Reduction DADO : District Agriculture Development Office DAO : District Administration Office DDC : District Development Committee DDRC : District Disaster Relief Committee DEM : Digital Elevation Model DFO : District Forest Office DHM : Department of Hydrology and Meteorology DIO : District Irrigation Office DPP : Disaster Preparedness Plan DoF : Department of Forestry DoS : Department of Survey DRR : Disaster Risk Reduction DSCO : District Soil Conservation Office DSCWM : Department of Soil Conservation and Watershed Management DTM : Digital Terrain Model ECO Nepal : Environment and Child concern Organization Nepal FGD : Focus Group Discussion FINIDA : Finnish International Development Agency GCM : General Circulation Model GDI : Gender Related Development Index

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Abbreviation

GDP : Gross Domestic Product GEM : Gender Empowerment Measure GIS : Geographic Information System GLOF : Glacier Lake Outburst Flood GoN : Government of Nepal GPS : Global Positioning System ha : Hectare HDI : Human Development Index HEC-GeoHMS : GIS extension of HEC-HMS HEC-GeoRAS : GIS extension of HEC-RAS HEC HMS : Hydrologic Engineering Centre Hydraulic Modelling System HEC RAS : Hydrologic Engineering Centre River Analysis System HH : Household ICIMOD : International Centre for Integrated Mountain Development IPCC : Intergovernmental Panel on Climate Change LGCDP : Local Governance and Community Development Program LHI : Landslide Hazard Index LRMP : Land Resource Mapping Project LUEP : Land Use Erosion Potential ISDR : International Strategy for Disaster Reduction m : meter N-PAF Rukum : Nepal Public Awakening Forum Rukum PAR : Pressure And Release RS : Remote Sensing SCS : Soil Conservation Service sq.km. : Square Kilometre TIN : Triangulated Irregular Network UNDP : United Nations Development Program UNEP : United Nations Environment Programme USDA : United States Department of Agriculture VDC : Village Development Committee WECS : Water and Energy Commission Secretariat

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 1 Introduction

Chapter 1 Introduction

1.1 Background Landlocked between India and China, Nepal is a located in the arc of Himalaya extending from between 26˚22’ – 30˚27’N in latitude and 80˚4’ – 88˚12’E in longitude in a roughly rectangular shape with a total area of 147,181 km2. Average length of the country is 885 km in east west and 192 km in north south direction. Altitude varies very widely from about 60 m to 8848 m at the world’s peak the Mount Everest. Nepal covers nearly 0.1% of the earth’s land surface. Geologically, the country may be divided into five major tectonic units: Terai Zone, Siwaliks or Churia Zone, Lesser Himalayan Zone, Higher Himalayan Zone and Tibetan-Tethys Zone. Weak geological structures, steep and rugged land surfaces and extreme climatic conditions result in high degree of fragility. Moreover, hilly and mountain systems are characterized by substantial differences in environmental characteristics due to rapid and sharp changes in altitude leading to: (a) specific dynamics of hydrological processes with important positive and negative consequences (high water yield due to high amount of precipitation, disastrous landslide, debris flow and floods with soil losses resulting in high sediment loads in rivers), and (b) distinct altitude-specific patterns of vegetation and land-use structures. Weak and unstable geological structures also trigger various seismic events. Looking at the geological characteristics, topographical features and climatic condition, Nepal’s disaster scenarios can be categorized as high in terms of magnitude, intensity and extent. The country has been experiencing high in magnitude and intensity of natural disasters like flood, landslide, earthquake, fire, hailstorms, Glacier Lake Outburst Flood (GLOF), cloudburst, drought, epidemics. These cause loss of lives of hundreds of people, damage of property having the worth of billions of Rupees and leaving the adverse environmental (physical, biological and socio-economic and cultural) impacts in the affected areas. Nepal is thus a disaster hot spot due to the vulnerability of the population and frequent occurrence of different natural hazards. Nepal has been ranked 23rd in the world in terms of the total natural hazard-related deaths in the last two decades whereas it is in 7th position in terms of loss of lives due to flood, landslide, debris flow, avalanches etc. Despite these fragile circumstances, significant numbers of poor and vulnerable people often reside in such environments, adopting typical socio-economic activities. It is therefore essential to provide appropriate knowledge about probable hazards such as landslides, debris flow, flood etc. and possible improvements for human welfare and sustainable development. The knowledge, tools and techniques to be developed need to focus rural community to make them aware on disaster because rural hilly community is highly disaster prone area in Nepal. Recently, climate variability and change processes have added multiple vulnerabilities to the people of hilly and mountainous region in Nepal. They have thus presented an opportunity to closely examine the dynamics so that they may be effectively dealt with, to reduce future hazard risk. This requires a detailed risk assessment which will figure out where the risks from multiple hazards, both natural and man-made, are concentrated in Nepal, and also examine who is affected and how. A risk assessment is analytically based on documenting and assessing the hazard, followed by an

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 1 Introduction

evaluation of the vulnerability of a population or region to this hazard. Risk assessment would have two components: (a) multi-hazard assessment and (b) vulnerability assessment. The formulation and implementation of community based Disaster Risk Reduction (DRR) initiatives is one of the important activities of UNDP where integrated approach of Disaster Risk Reduction (DRR) and Climate Change Adaptation (CCA) will lead to build a sustainable society. Present study mainly focuses on multi-hazard risk assessment with particular emphasis on flood and landslide in Muglu Khola watershed in Rukum district. Hazard assessment includes hazard maps, computation and illustrations. Hazard maps provide clear, attractive pictures of the geographic distribution of potential hazard sources and impacts. These maps frequently provide motivation for risk management actions that would be difficult to obtain without a compelling visual. The colours and detail of the map should reflect the application. Some motivational maps for the public, for example, would best be very simple. Mapping hazards provides an easily accessible tool for displaying the threat to a community. This assessment was assigned to ECO-Nepal. Other project components such as capacity building through training and preparation and implementation of action plan through community mobilization are being carried out by Nepal Public Awakening Forum (N-PAF) Rukum. The findings of the assessment are used in designing capacity building activities and action plans for DRR.

1.2 Objectives of the Study The primary objective of the assessment is to carryout community based hazard, vulnerability and risk assessment of the Muglu Khola watershed and to propose preparedness, response and mitigation action plan covering the proper land use planning. It is to prepare community based climate risk sensitive integrated watershed management plan of the study area. The specific objectives of the study are: . to prepare the gender and socio-economic baseline for analysing the social vulnerability situation of the community of the watershed. . to prepare existing land-cover and land-use map and suggest the proper land use plane in line with climate risk and disaster risk reduction and livelihood supporting. . to prepare and analyse hydro-meteorological hazard and risk map of the study area with particular focus on landslide and floods. . to prepare the integrated watershed management action plan considering climate change and disaster risk management. . to create an enabling environment during the assessment process that local government and communities (particularly vulnerable groups) could participate and understand the climate variation, change and disaster risk and could plan, implement and monitor measures to address those risks.

1.3 Scope of the Study Followings will be the scope of the assessment: . Compile community baseline data on health, nutrition, cropping patterns, livelihood options, agricultural practices, literacy and women empowerment etc. and other environmental, spatial and socio-economic data of the study area and community as to link with the hydro- meteorological hazards.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 1 Introduction

. Collect, prepare details baseline GIS/RS database including land use/ land cover, river network, road and trails, contour, settlements, VDCs. . Assess and understand the hydro-meteorological hazards and trends in terms of frequency, magnitude, intensity and timing focusing on climate variability and change based on recorded/reported hydro-meteorological data and perception/experience of the local people. . Collection of detail socio-economic information and identify the more vulnerable area and community in the watershed. . Review the existing land use practice and suggest the proper land use plan in line of the CRR and DRR . Review of existing livelihood and income generating activities and suggest better options that suit with climate and disaster risk. . Examine the existing agricultural practices especially crops grown, cropping pattern, productivity and food sufficiency situation . Prepare inventory of the past hydro-meteorological hazard particularly landslide and flood and assess its impacts the coping and adaptation measures (indigenous technology) of local individuals, households and communities in the study area. . Identify and quantify the elements exposed to different hydro-meteorological hazards and assess their vulnerability. . Document key activities and initiatives including traditional coping systems and mechanisms, community knowledge and practices (Indigenous Knowledge and Practices) related to risk mitigation, preparedness and response, early warning dissemination and traditional water harvesting/conservation practices, impact of climatic hazards on livelihoods and other key sectors (agriculture and food security, water resources and energy , climate induced disasters, forest and biodiversity, public health and urban settlement and infrastructure ) related dimensions of community’s knowledge related to risk reduction and recommendations for mitigating impacts of climate risks. . Prepare an integrated watershed management action plan with logical framework.

1.4 Important Terminology Disaster: A disaster is a natural or man-made (or technological) hazard resulting in an event of substantial extent causing significant physical damage or destruction, loss of life, or drastic change to the environment. It is a phenomenon that can cause damage to life, property and destroy the economic, social and cultural life of people. Hazard: A dangerous phenomenon, substance, human activity or condition that may cause loss of life, injury or other health impacts, property damage, loss of livelihoods and services, social and economic disruption, or environmental damage. Hazard is therefore a potentially damaging physical event, phenomenon or human activity that may cause the loss of life or injury, damage to property, social and economic disruption and environmental degradation. . Natural hazards include anything that is caused by a natural process, and can include obvious hazards such as volcanoes to smaller scale hazards such as loose rocks on a hillside. . Man-made hazards are created by humans, whether long-term (such as global warming) or immediate (like the hazards present at a construction site). These include activity related hazards (such as flying) where cessation of the activity will negate the risk.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 1 Introduction

Vulnerability: Vulnerability is the characteristics and circumstances of a community, system or asset that make it susceptible to the damaging effects of a hazard. Risk: Risk is the combination of the probability of an event and its negative consequences. Risk is the potential that a chosen action or activity (including the choice of inaction) will lead to a loss (an undesirable outcome). Risk Assessment: A methodology to determine the nature and extent of risk by analysing potential hazards and evaluating existing conditions of vulnerability that together could potentially harm exposed people, property, services, livelihoods and the environment on which they depend. Risk Management: Risk Management is the systematic approach and practice of managing uncertainty to minimize potential harm and loss. It comprises risk assessment and analysis, and the implementation of strategies and specific actions to control, reduce and transfer risks. Coping Capacity: This is the ability of people, organizations and systems using available skills and resources to face and manage adverse conditions, emergencies or disasters. The capacity to cope requires continuing awareness, resources and good management, both in normal times as well as during crises or adverse conditions. Preparedness: The knowledge and capacities developed by governments, professional response and recovery organizations, communities and individuals to effectively anticipate, respond to, and recover from, the impacts of likely, imminent or current hazard events or conditions. Disaster Risk Reduction: The concept and practice of reducing disaster risks through systematic efforts to analyse and manage the causal factors of disasters, including through reduced exposure to hazards, lessened vulnerability of people and property, wise management of land and the environment, and improved preparedness for adverse events. Disaster Risk Reduction Plan: A document prepared by an authority, sector, organization or enterprise that sets out goals and specific objectives for reducing disaster risks together with related actions to accomplish these objectives. Disaster Risk Management: It is the systematic process of using administrative directives, organizations, and operational skills and capacities to implement strategies, policies and improved coping capacities in order to lessen the adverse impacts of hazards and the possibility of disaster. Response: The provision of emergency services and public assistance during or immediately after a disaster in order to save lives, to reduce health impacts, to ensure public safety and to meet the basic subsistence needs of the people affected is the Response. Recovery: It is the restoration and improvement where appropriate, of facilities, livelihoods and living conditions of disaster-affected communities, including efforts to reduce disaster risk factors. Mitigation: The lessening or limitation of the adverse impacts of hazards and related disasters. Mitigation measures encompass engineering techniques and hazard-resistant construction as well as improved environmental policies and public awareness. It should be noted that in climate change policy, “mitigation” is defined differently, being the term used for the reduction of greenhouse gas emissions that are the source of climate change.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 2 Study Area

Chapter 2 Study Area

2.1 Study Area

2.1.1 An Overview of Rukum Location and Accessibility

The study area is located in Rukum district, in the northern part of Rapti Zone in Mid-western Development, Nepal (Figure 2-1). It is one of the remotest districts in the country and is the origin of the Maoist Movement where a large number of people have lost their lives during the “armed conflict”. Geographically, the district extends from 28°29'- 29°00' N latitude and 82°12'- 82°83' E longitude. Topographically, the district has the altitudinal variations ranging from 762 m to 6602 m above mean sea level (amsl) at Sisne Himal. Rukum contains various trans-valleys, small hills, high hills and mountains; the mountains extend over the northern part of the district and border with the Dolpa in the north. The district covers a total area of 2930.91 sq.km. The district is bordered by Dolpa in north, Jajarkot in west, Salyan and Rolpa in south and Baglung and Myagdi districts in east. There are 43 VDCs in the district and Musikot Khalanga is the district headquarter of Rukum.

Figure 2-1: Location of the Study District

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 2 Study Area

Rukum is connected by both air and road transport. There are two airports in the district: Chaurjahri (established in 1972) and Salle (established in 1995). Different airline companies are delivering frequent air flights from Nepalgunj and Kathmandu to Rukum. Sallyan-Musikot Highway constructed by the Nepal Army has now connected the district with other parts of the country. Availability of road transport to the district headquarter has played vital role in connecting the district headquarter to various VDCs; DDC Rukum and respective VDCs are using their development fund to construct various rural roads in the VDCs that connect them with each other and with Musikot. However, overall quality of these road networks still need much improvement in terms of narrow road width, steep gradient, and uneven cutting and filling of the excavated materials. Such low quality of rural roads has resulted not only various road accidents but also landslides along the road alignment. Climate, Hydrology and Meteorology

Rukum is characterized by sub-tropical to sub-alpine climate. Thirty one years (1980-2010) daily temperature data available at Musikot Airport Station show that mean annual maximum and minimum temperature are calculated to be 33.60°C (range 41.90 to 30.40°C) and 1.65°C (range 4 to - 0.5°C) respectively. The values of mean annual maximum and minimum relative humidity in the station have been recorded to be 99.37% (range 97.30 – 100%) and 22.93% (range 53.00 – 4.70%). Table 2-1 depicts mean monthly rainfall derived from 31 years daily rainfall data (1980-2010) at Musikot Airport Station.The mean annual rainfall has been estimated to be about 2200 mm. The records also reveal that maximum daily rainfall ranges from 52 mm (on 8th September 1981) to 212.2 mm (18th July 1888) giving the average maximum daily rainfall of 109 mm.

Table 2-1: Mean Monthly Rainfall Recorded at Musikot Station

Jan Feb Mar April May June July Aug Sept Oct Nov Dec Total 24.4 37.2 41.9 47.9 124.6 300.3 588.2 574.9 330.0 88.5 17.4 17.7 2192.9 There are 15 perennial rivers in the district; some of the them include Thuli Bheri, Sani Bheri, Muglu Khola etc. There are altogether 97 different sub-watersheds in the district; the area of these watersheds ranges from 10.38 to 108.62 sq. km. Rukum is also known for its 52 lakes located in different part of the district. Land-use and Land-cover Forest is the dominant land-cover in the district covering about 47% of the district’s land followed by grass land (17.62%). Significant portion of the area in the district is covered by terrace land (13.58%), barren land (11.83%) and bush land (8.67%). Table 2-2 presents main land-cover in the district.

Table 2-2: Main Land-cover in the District

S. N Land-use Area (sq km) % Coverage 1 Cutting Area 3.21 0.11 2 Cultivation 397.96 13.58 3 Forest 1377.40 47.00 4 Orchard 0.02 0.00 5 Grass Land 516.28 17.62 6 Bush Land 254.16 8.67 7 Sand 23.35 0.80

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 2 Study Area

8 Barren Land 346.74 11.83 9 Water Body 8.72 0.30 10 Glacier 1.57 0.05 11 Pond or Lake 1.50 0.05 Total 2930.91 100.00

Rukum is rich in different forest types owing to variations in physiography and climate. Particularly three types of forest are available in the district: Riverine Forest, Hill Forest at Mahabharat Range and High Hill Forest. Forest species such as Sisso (Dalbergia sisso), Khayar (Acacia catechu) and Simal (Bombax ceiba) are mainly found in Riverine Forest that occurs in along the river bank extending elevation up to 1500 m amsl. Hill Forest extends from 1200 – 2300 m amsl in Mahabharat range and main species found in the forest include Khotesall (Pinus roxburghii), Uttis (Alnus nepalensis), Kafal (Murica esculenta), Khanayo (Ficus semicordata), Kaulo (Persea odoratissima), Sal (Shorea robusta), Amala (Phyllanthus emblica) etc. High Hill Forest is primarily found above the elevation 2500 m amsl. In the lower belt hill Sal (Shorea robusta) forest is abundantly available. Riverine forest is also available in the riverside of Bheri River. In higher elevation, different types of coniferous species are found. Species variation is as per the altitudinal variation. Typically, large grass land and snow- capped mountain is the key feature of this forest type. Paddy, wheat, and maize are the main crops found in cultivation land-use type category. Paddy is dominant in low land and valley where irrigation facilities are available whereas wheat and maize are observed along sloping agricultural land.

2.1.2 Muglu Khola Watershed The Muglu Khola, a tributary of Sani Bheri is a perennial river in Rukum district draining water from a catchment of about 172 sq.km. area. The Muglu Khola Watershed is located in the southern part of Rukum district covering 9 VDCs: Musikot, Sankh, Chokhabang, Rugha, Khara, Muru, Bhalakcha, Peugha, and Chhibang (Figure 2-2 and Figure 2-3).

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 2 Study Area

Figure 2-2: Muglu Khola Watershed Location

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 2 Study Area

Figure 2-3: Muglu Khola Watershed Coverage showing Ward Boundaries

Topography A 10 m grid-cell resolution Digital Elevation Model (DEM) of the Muglu Khola watershed was developed using the contour map made available from the Department of Survey, Government of Nepal (GoN). Contour elevation datasets were interpolated using ‘Topo to Raster’ tool in ArcGIS 9.3 to develop the DEM of the area. The Muglu Khola’s DEM shows that the elevation of the study area ranges from 847 m amsl at the outlet of the Muglu (i.e. confluence of Muglu Khola and Sani Bheri Nadi) to 2851 m amsl.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 2 Study Area

Figure 2-4: DEM of the Muglu Khola Watershed

Topographic attributes computed from the DEM were the local (grid-cell to grid-cell) slope angle (θ), stream networks, hillslopes (sub-catchments), spatial distribution of flowpaths, and upslope contributing area. The slope map derived from the 10 m grid-cell resolution DEM show that slope angle ranges from 0 to 67° averaging about 32°. The watershed is characterized by six major sub- catchments (Table 2-3 and Figure 2-5).

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 2 Study Area

Figure 2-5: Major Tributaries of the Muglu Khola

Table 2-3: Major Sub-watersheds of the Muglu Khola Watershed

SN Name Area (sq.km.) 1 Sankh Khola Sub-watershed 36.74 2 Tewa Khola Sub-watershed 19.68 3 Khara Khola Sub-watershed 12.77 4 Muru Khola Sub-watershed 12.26 5 Rugha Khola Sub-watershed 23.15 6 Peugha Khola Sub-watershed 25.12 7 Pane Khola 14.26 Land-cover Land-cover map of the project area was obtained from two sources: Land Resource Mapping Project (LRMP) 1984 from the Department of Survey, a recent remote sensing image made available from the ICIMOD. There are nine basic land-cover types observed in the LRMP’s map that include Barren Land, Bush, Cultivation, Cutting Area, Forest Land, Grass Land, Lake, River and Sand with the Forest (44.3%) as the dominant type followed by Agricultural Land (37.74%) and Bush (14.3%). The recent remote sensing image of the area has identified five classifications on its land-cover: Barren Land, Bush, Agricultural Land, Forest and Grass Land. These land-cover types are further categorized into different sub-groups, for example Forest is divided into Conifer Forest, Hardwood Forest, Mixed Forest, Protected Conifer Forest and Protected Hardwood Forest; Agricultural Land

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 2 Study Area

into Level Terrace, Sloping Terrace and Valley Cultivation. The classification however, does not identify River, Lake and Cutting Area; these are classified in LRMP’s map. As depicted in Table 2-4, ICIMOD’s land-cover map shows about 7.71 sq. km. (2.83%) less Forest area than the LRMP’s map and this decrease is attributed to the intense deforestation due to increase in population growth. This decrease in Forest Area leads to the increase in agricultural land and grass land owing to increase human encroachment in forest area; Agricultural Land and Grass Land were increased by 14.33 sq. km. and 10.75 sq. km. in the ICIMOD’s land use map.

Table 2-4: Different Land-covers in the Study Area from two Different Data Sources

Land-use Map Source LRMP ICIMOD SN Land-cover Area (sq.km.) SN Land-cover Area (sq.km.) 1 Barren Land 0.12 1 Barren Land 0.62 2 Bush 24.65 2 Bush 7.85 3 Agricultural Land 65.21 3 Agricultural Land 79.54 4 Cutting Area 0.02 4 Cutting Area - 5 Forest 76.52 5 Forest 68.81 6 Grass Land 4.78 6 Grass Land 15.53 7 Lake 0.02 7 Lake - 8 River 0.09 8 River - 9 Sand 1.36 9 Sand - Soil Types Nepal has very coarse soil data; entire country is divided into single or combination of two or more soil types of 12 classifications. The Muglu Khola Watershed is sub-divided into three soil groups according to soil classification done by Ministry of Land Reforms and Management. The three soil groups are combination of two or more soil types: (a) Dystrochrepts, Haplustalf, Rhodustalfs (b) Dystrochrepts, Haplustalf, Rhodustalfs – Calcareous Materials and (c) Dystrochrepts, Haplumbrept, Haplustalf according to USDA classification (Table 2-5). Dystrochrepts is characterized by coarse- loamy over sand or sandy skeletal or mixed type on the other hand Haplustaff is fine loamy or mixed soil type. It is an acid brown soil. The soil is excessively drained, fine loamy with loamy surface and has slight stoniness. Haplumbrepts occur in association with moderately deep, somewhat excessively drained, coarse-loamy Typic Udorthents with loamy surface, having slight stoniness. Rhodustalfs have, in all sub-horizons in the upper 100 cm of the argillic horizon or throughout the entire argillic horizon if less than 100 cm thick, more than 50% colours.

Table 2-5: Soil Distribution of the Study Area

SN Soil Group Area (sq.km.) 1 Dystrochrepts, Haplustalf, Rhodustalfs 61.23 2 Dystrochrepts, Haplustalf, Rhodustalfs – Calcareous Materials 9.90 3 Dystrochrepts, Haplumbrept, Haplustalf 101.60

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 2 Study Area

Geology Geology of the project area is grouped under Ranimatta Formation, Lokharpata Formation, Siuri Formation and Surbang Formation. The dominant rock types in the project area are slates, intercalation of phyllite and quartzite, dolomite and phyllite. The Ranimatta Formation is dominated by clastic materials but contains minor amphibolites and a felsic orthogneiss. It is usually correlated with the Ulleri augen gneiss; although neither Ulleri nor other felsic orthogneisses ubiquitously bear augen structure. The Ranimata Formation is composed of grey, greenish-grey, gritty phyllite and phyllitic quartzite, metasandstone and conglomerate beds with white, massive quartzite and basic rocks are intrusion. Thick bedded, fine-grained, grey to dark grey dolomite and dolomitic limestone intercalation with black to grey shale is the main lithology of the Lakharpata Formation. The Siuri Formation is represented by the garnetiferous schist and gneiss. The Surbang Formation is crystalline limestone inter-bedded with schist.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 3 Climate Change Impact in the Study Area

Chapter 3 Climate Change Impact in the Study Area

3.1 Climate Change Impact in Nepal

3.1.1 General Overview Limited previous studies analysing regional changes due to global CC in South Asia – even more so in Nepal are limited, especially in relation to climate-induced hazards, because of the difficulty in scaling down the General Circulation Models (GCMs), a lack of long-term climate records, and the natural high variability of water supply. Additionally, GCM outputs do not have sufficient spatial resolution to provide information on changes across the different elevation zones. A variety of different non-climate factors that have varying effects on water resources and agricultural systems in the region, including pervasive resource mismanagement and rapid population growth, also cloud effects of CC. There are, however, general trends that have been corroborated by ground level observations of various communities in Nepal do at least give a basic framework of the identified and projected changes including glacial melt, changes in precipitation patterns and increasing water stress into the 20th century, with most of South Asia projected to be under water stress by 2050. The following section summarizes information that is available in existing literature on the primary climate variables i.e. temperature, precipitation and runoff for Nepal.

3.1.2 Impact on Temperature Some observed studies on climate trends suggest that from 1960-2003 there have been no increases in annual temperature over Nepal. Other some studies depict an increase in temperature in recent years with more pronounced warming at higher altitude. There has been a small but significant increase in the frequency of hot nights and a significant decline in the annual frequency of cold days and nights. Hot nights have increased by 2.5%. GCMs predict that the country is expected to become warmer with more frequent heat waves and less frost. Average temperature is predicted to rise significantly by 0.5 to 2.0° C by 2030, 1.3 to 3.8° C by 2060 and 1.8 to 5.8° C by 2090 . The number of days and nights considered hot by current climate standards is projected to increase, occurring on 11 to 18% of nights by the 2060s. The greatest increase in projected to occur during the months of June to August.

3.1.3 Impact on Precipitation Projected mean annual precipitation for Nepal does not show a clear trend with reference to both increases and decreases: -34 to +22 % by the 2030s; -36 to +67% by the 2060s and -43 to +80% by the 2090s. This is, in part, because the exact effects of CC on precipitation levels in the region are based on complex factors governing the Asia monsoon and their interaction with increased carbon dioxide (CO2) levels, which is not well understood. Nevertheless, there is general agreement in recent models and studies that the monsoon will at the very least become more variable in the coming decades. Various studies, including those from the Intergovernmental Panel on Climate Change (IPCC), indicate that on a general level the summer monsoon (July to August) will become more 'intense', but also variable, meaning, meaning more frequent heavy rainfall events even as the number of rainy days decreases. Although monsoon rainfall projections for Nepal do vary, more models suggest an increase rather than a decrease towards the end of the century: -14 to +40% by the 2030; -40 to +143% by the 2060; and -52 to +135% by 2090.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 3 Climate Change Impact in the Study Area

Further studies indicate that multiple variables, including major land use changes, increase aerosols emissions and elevated CO2 levels due to CC, could all potentially trigger abrupt transitions between two stable states of the monsoon in a "roller coaster scenario", leading to either a more dry monsoon, with significantly less precipitation than current levels or a more wet monsoon with much greater rainfall intensity. These authors conclude that the monsoon would most likely be weakened initially, leading to a dryer state in the short term due to the effects of land use changes and greater aerosol production from increasing industrialization on the India subcontinent, followed by a more wet monsoon in the long-term as the effects of increase CO2 levels become increasing significant. Further conflating any understanding of predicted changes to precipitation levels are these effects of aerosols like black carbon or soot. Such effects are primarily felt through atmospheric brown clouds, 'regional scale plumes of air pollution that consist of copious amount of tiny particles of soot, sulphate, nitrate, fly ash and many other pollutants' that hover over parts of the globe (including South and East Asia) with concentrated industrial emissions, limiting summer monsoon, contributing to glacial retreat in mountainous regions, and ultimately affecting crop yields. According to United Nations Environment Programme (UNEP), 'atmospheric brown clouds induced dimming' of surface solar radiation is the primary cause for reduced rainfall in India over the last 20 years. Previous studies had indicated that the effects of atmospheric brown clouds actually offset some of the negative impacts of increased CO2 levels but more recent work indicates that the overall combined effects of atmospheric brown clouds and increases in green house gas emission negatively impact crop yields.

3.1.4 Impact on Runoff The effects of the changes in precipitation and temperature are expected to change the balance between 'green water' and 'blue water'. 'Green water' is the water that is used or lost in catchment before it reaches the rivers, while 'blue water' is the runoff that reaches the rivers. Glacial melting and retreat, rapidly thawing permafrost and continually melting frozen soils in higher elevations is already being observed. In the sub-basins dominated by glaciers, this will mean increased downstream flows in the short term, but in the long term, runoff is expected decreasing with the retreating glaciers, causing reduction in flow and significantly downstream livelihoods and ecosystems. In the winter months, more precipitation is falling as rain, which also accelerates deglaciation and in turn means a shorter winter and earlier snow melt, ultimately affecting river basins and agricultural systems dependant on surface water diversion for the summer growing season. Another particularly significant in the Himalayas and directly correlated to rising temperatures are glacial lake outburst floods (GLOFs) that result from rapidly accumulating water into glacial lakes that then burst, sending flash floods of debris and water from high elevations, wreaking havoc on downstream communities and damaging valuable infrastructure like hydropower facilities and roads. There are approximately 9,000 such lakes in the Himalayas, of which 200 are said to be in danger of bursting. High rates of glacial melt due to increases in temperature are adding to this threat, as the rate of such incidents increased between the 1950s and 1990s from 0.38 to 0.54 events per year.

Table 3-1 summarizes the anticipated climate change impacts in Nepal.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 3 Climate Change Impact in the Study Area

Table 3-1: Anticipated Cliamte Change Impacts in Nepal

Parameters Impacts Temperature Significant rise in temperature . 0.5 to 2.0 °C by the 2030s . 1.3 to 3.8 °C by the 2060s . 1.8 to 5.8 °C by the 2090s . Increase in the number of days and nits considered hot by current climate standards . Highest temperature increases during the months of June to August and at higher elevations Precipitation Wide range of mean annual precipitation changes . -34 to +22% by the 2030s . -36 to +67% by the 2060s . -43 to +80% by the 2090s Increase in monsoon rainfall towards the end of the century . -14 to 40% by the 2030s . -40 to 143% by the 2060s . -52 to +135 by the 2090 Runoff Higher downstream flows in the short term, but lower downstream flows in the long term due to retreating glaciers and snowmelt and ice- melt . Shift from snow to rain in winter months . Increased extreme events, including floods, drought and GLOFs

3.1.5 Impact on Agricultural System The effects of CC on agriculture in Nepal can be divided between systems that are dependent on the summer monsoon and those that are dependent on snow, ice and glacial melt. Agricultural systems dependent on water sourced from snow, ice and glacial melt will see an immediate increase in water supply, but will also be in grater danger of GLOFs that threaten crops, water infrastructure and mountain livelihoods, in general. Whether such an increase will consequently increase productivity in the short term is unknown, as very little exists in terms of water storage in Nepal, however primitive, to harvest such an excess of water supply. Long-term, the effects of reduced water storage and variability of supply from earlier thawing of the snowpack and deglaciation have the potential to be significant, with glacial melt accounting for 30% of per capita consumption in some low land regions and increase in temperature causing consequent increases in agricultural water demand. Unfortunately, because these effects are not likely to be felt for decades, the short-term benefits of increased runoff will likely delay any comprehensive long-term proactive management plans. For systems dependent on the summer monsoon, multiple scenarios are possible due to the pervasive uncertainty in the models and lack of data, where the monsoon could abruptly be transition between 'dry' and 'wet' states. In the short-term, however, when taking into account the effects of increased aerosol production and atmospheric brown clouds, there is more certainty that less precipitation is likely to occur during the summer months as the number of rainy days decreases, even though the frequency of intense rainfall events increase. Increasing variability of precipitation patterns will have a significant effect on crop productivity as farmers will have to adapt to changing onset and termination dates of the monsoon. Later start dates significantly impacted

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 3 Climate Change Impact in the Study Area

rice crops in 2009, as many seedlings were lost due to the delay in rainfall, and many did not have enough time to mature enough for viable yield. The impacts of less water during the dry months are much easier to visualize, as recent winter droughts have continued to show the effects of low water supply. During the drought of fall 2008 to spring 2009, agricultural systems experienced significantly reduced crop yields resulting in food insecurity for millions. Such effects would be augmented by a more intense dry season. Western regions will be the most detrimentally affected because they rely heavily on winter rains and cannot depend as reliably on summer monsoon rains, which are not as intense in the west due to natural pattern of rainfall intensity from east to west. Though determining how agricultural systems in Nepal will be affected by the potential impacts of CC is difficult due to lack of data in the country and the uncertainty in the climate models, there is nevertheless little doubt that significantly more pressure will be placed on food systems that are already incapable of feeding the domestic population. Extreme poverty and high levels of malnourishment make even the slightest fluctuation in climate potentially disastrous to the economy. The population is thus extremely vulnerable not only to longer term CC that will ultimately reduce water availability and limit crop productivity, but even more so to the immediate threats of increasingly frequent GLOFs, landslides, flash floods and droughts.

3.1.6 CC Adoptation in Nepal There are two main branches of adaptation commonly cited in the literature: autonomous and strategic. Autonomous adaptation refers to the actions of individuals taken at the household level to make changes that reduce vulnerability to a changing climate, regardless of planning, policies and strategies implemented at the national level. For instance, agricultural households can apply different management techniques that involve less water use, greater cropping intensity, crop diversification, micro-irrigation, micro-hydro and small-scale storage or any thing that improves the resilience of the income base during fluctuating conditions. In the near-term, autonomous adaptation in agro-economics, such as Nepal, will focus on shifts in agricultural and water management; however, income diversification is likely to become the primary autonomous adaptation strategy in the long-term. Major changes like migration to urban centres, off-farm employment, remittances from abroad, or new business that capitalize on greater access to markets provided by advances in information technology and other infrastructure are already used as a means of adapting to changing circumstances. The word autonomous is to some extent misleading, as many of the autonomous adaptation options available directly depend on 'systematic factors that enable people and organizations to take advantages of opportunities'. It is the baseline systems, whether ecological (agriculture), information technology or transportation infrastructure, on which the versatility of local livelihoods directly depend, and how autonomous adaptation is directly connected to strategic planning. In many cases, without some national level strategic planning, those autonomous adaptation options mentioned above are not possible. For instance, in many cases, income diversification is inherently dependent on infrastructure that can only be provided from the top down. Thus, although autonomous adaptation involves automatic actions taken at the household level in response to changing conditions, the variety of options for those actions is in many cases entirely dependent on national level strategic planning.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 3 Climate Change Impact in the Study Area

Strategic adaptation refers to planning, policies or strategies at the national level that proactively responds to the potential effects of CC. This includes direct construction of infrastructure, capacity building, disaster relief planning or a host of different methods that increase national resilience to potential impacts of CC on both ecosystems and human population. Because most of these impacts will be felt primarily in water resources, in both developed and developing countries, strategic adaptation planning is fundamentally about water management. For a country like Nepal that is so heavily dependent on agriculture for livelihoods and Gross Domestic Product (GDP), the impacts of CC on water resources are of critical importance. Strategic planning will thus entail emphasizing newer more sustainable agricultural techniques that are less water intensive, refocused efforts on the rehabilitation of water infrastructure and development via expansion in storage and irrigation and re-evaluating water management within the context of the impacts of CC. Though the majority of CC impacts will be felt in water resources, understanding how they are connected to basic development and poverty alleviation at the household level is also a crucial part of any strategic adaptation planning. In a broad lesson from water resources development in the past, such planning should not be limited solely to water resource issues, but should also focus on 'enabling autonomous adaptation processes by supporting the development of flexible, resilient and accessible social and physical infrastructure systems'. This means that many of the current projects and avenues for expanding development and improving the livelihoods of the millions of poor in South Asia through the creation of greater access to markets via infrastructure like roads, electricity and telecommunications would also be included in the strategic adaptation process.

3.2 Climate Change in Muglu Khola Watershed

3.2.1 People's Perception on CC Local people of the project area had a wide range of perception on CC; some revealed that there was a CC in the project area whereas some did not. Interaction with the community at the Chokhabang illustrated that previously there were no mosquito seen in the project area before 25 to 30 years during summer months. However, mosquito net has become essential now days. They further stated there was a decreasing trend on yield of ground water on springs, decrease in river flow. According to them, this is probably a result of CC particularly effect of global warming.

This contrasts with the statements made by the local people of Sankh. They said that their project area was hot before and is cold now indicating that temperature has been decreasing gradually. According to them, summer days have been decreasing. Thus, they ignored the CC and global warming.

In the interaction with local people, it was found there was a changing pattern of rainfall in terms of time, intensity and amount. They reported that rainfall time has been shifting to mid July to August with the decrease in annual rainfall amount. In the past they mostly experienced less rainfall and more snowfall and frost in the village. But its pattern has changed as they have been experiencing more rain and very less snowfall. In all the villages of the watershed, Monsoon rain has become uncertain sometime it starts earlier while sometime it stars late. However, the intense rainfall amount has been increasing with no distinct time frame.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 3 Climate Change Impact in the Study Area

3.2.2 Trend Temperature Changes Extreme event temperature data were first analysed to see how the maximum and minimum temperatures are changing in the Muglu Khola Watershed as a preliminary analysis. The 30 years daily maximum and minimum temperature data from Musikot Khalanga Airport Station were used for the analysis. In the studied duration, the maximum extreme annual temperature in the watershed ranged from 30.4°C to 35.6°C. Based on the data, a linear trend line was developed and the line (Figure 3-1) showed that there was an increasing trend of maximum annual extreme event temperature at the rate of 0.0167°C per year. Some previous studies also reported that in Nepal the average increasing rate in temperature is estimated to be 1.8°C in the last 32 years; the rate is even higher in higher elevation areas.

Figure 3-1: Annual Maximum Extreme Temperature Analysis

Mimimum extreme temperatues at the Musikot Airport Station range from -0.5°C (in 1999) to 4°C (in 1990) Minimumu extreme temperature for the study period (1980-2010) also showed that the temperatue is also increasing (Figure 3-2). The increasing rate is however less than that for the maximum extreme annual temperature; in this case the increasing rate was observed to be 0.0008°C per year.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 3 Climate Change Impact in the Study Area

Figure 3-2: Annual Minimum Extreme Temperature Analysis

After the preliminary analysis of extreme maximum and minimum temperature, climate change impact on temperature was extended to maximum and minimum temperature for each month of the study duration. Mean Monthly Maximum Temperature for each month was derived averaging maximum daily temperature. Trend in Mean Monthly Temperature for various months has been presented in Figure 3-3. The results show that mean monthly maximum temperatures are in increasing trend for eight months such as January, February, March, April, May, October, November, and December whereas they are in decreasing trend for the rest 4 months like June, July, August and September. This indicates there is a decreasing trend of mean monthly maximum temperature in monsoon months and an increasing trend for the rest of other summer and winter months.

A: January B: February

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 3 Climate Change Impact in the Study Area

C: March D: April

E: May F: June

G: July H: August

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 3 Climate Change Impact in the Study Area

I: September J: October

K: November L: December Figure 3-3: Trend in Mean Monthly Maximum Temperature Change at Muglu Khola Watershed

Based on the observed data and trend analysis of the observed maximum mean monthly temperature, temperature change patterns for various months have been estimated and presented Table 3-2. The positive values in the Table indicate increasing trend and the negative ones imply decreasing trend. The results show that the increasing trend in maximum mean monthly temperatures are more pronounced in November and December; the temperature increases are estimated to be 0.13°C and 0.12°C per year for those months respectively. On the other hand, June month has been observed more effective in terms of decrease in mean monthly maximum temperature; the temperature decrease has been computed at the rate of 0.0345°C per year for the month.

Table 3-2: Mean Monthly Maximum Temperature Change Pattern

SN Month Temperature Change Trend (°C per year) 1 January +0.0799 2 February +0.0919 3 March +0.0755 4 April +0.073 5 May +0.0392 6 June -0.0345 7 July -0.0063 8 August -0.00075 9 September -0.0013

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 3 Climate Change Impact in the Study Area

10 October +0.0574 11 November +0.130 12 December +0.1218 Figure 3-4 presents changing pattern of Mean Monthly Minimum Temperature for each month at Musikot Airport Station which is the representative climate station of Muglu Khola Watershed. The Mean Monthly Minimum Temperature was calculated averaging daily minimum temperature for all months. The results show that mean monthly minimum temperatures are increasing for only six months such as February, March, April, October, November and December. In the other six months, the mean monthly minimum temperatures are in decreasing order. Unlike in mean monthly maximum temperature changes trend, the mean monthly minimum temperaturs are decreasing for January and May.

A: January B: February

C: March D: April

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 3 Climate Change Impact in the Study Area

E: May F: June

G: July H: August

I: September J: October

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 3 Climate Change Impact in the Study Area

K: November L: December Figure 3-4: Trend in Mean Monthly Minimum Temperature Change in Muglu Khola

Based on the observed data and trend analysis of the observed mean monthly minimum temperature, temperature change patterns for various months have been estimated and presented Table 3-2. The positive values in the Table indicate increasing trend and the negative ones imply decreasing trend. The results show that the increasing trend in mean monthly maximum temperature is more pronounced in November; the temperature increase is estimated to be 0.0917°C per year for the month. The increasing rate is significantly less than that of the mean monthly maximum temperature; the increasing rate for mean monthly maximum temperature was computed to be +0.130°C per year. On the other hand, June month has been observed more effective in terms of decrease in mean monthly maximum temperature; the temperature decrease has been computed at the rate of 0.0629°C per year for the month.

Table 3-3: Mean Monthly Minimum Temperature Change Pattern in Muglu Khola

SN Month Temperature Change Trend (°C per year) 1 January -0.0008 2 February +0.0287 3 March +0.0358 4 April 4 +0.0207 5 May -0.035 6 June -0.0629 7 July -0.0515 8 August -0.0312 9 September -0.0298 10 October +0.0454 11 November +0.0917 12 December +0.0238

3.2.3 Impact on Precipitation Daily rainfall data from the Musikot Airport Station were obtained for the period 1980-2010. The 24 hour extreme event rainfall data of each year were acquired from the daily rainfall data. The data were plotted and fitted with a linear trend line (Figure 3-5). The results show that 24 hours extreme event rainfalls are in decreasing trend at a computed rate of 0.919 mm per year. The results, however, represent 24 hour daily rainfall events but not the short term (sub-daily or hourly) extreme rainfall. This is because high temporal resolution rainfall data was not available for the station.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 3 Climate Change Impact in the Study Area

Figure 3-5: Trend in 24 hours Extreme Event Rainfall

Figure 3-6 presents precipitation pattern in the Muglu Khola Watershed and shows that there is an increasing trend in precipitation in the study catchment. Some previous studies also reported that there was no distinct long-term trend in the precipitation records in Nepal during 1948-1994, though there was significant variation on annual and decadal time scales. Some of the previous studies revealed that there was a strong relationship between all-Nepal monsoon precipitation and the El- Nino- Southern Oscillation. Another study based on the precipitation records from 80 stations for the period 1981-1998 across Nepal revealed that the hills and mountains in the north showed positive trends while the plains in the south were experiencing negative trends.

Figure 3-6: Annaul Rainfall Trend in the Muglu Khola Watershed

Daily rainfall data were used to compute monthly rainfall for the Musikot Airport Station and the monthly rainfall data were further studied to see how the monthly rainfalls are changing. The results show there is a mixed trend on the changes on rainfall indicating that in some months

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 3 Climate Change Impact in the Study Area

monthly rainfall are in decreasing order whereas in other months they are increasing. For example, rainfalls are in increasing trend for the eight months such as January, February, May, June, August, September, October and November on the other hand monthly rainfalls are in decreasing trend for other four months like March, April, July and December (Figure 3-7). Three out of four monsoon months such as June, August and September show increasing trend of monthly rainfall whereas July reveals a decreasing trend in the monthly rainfall.

A: January B: February

C: March D: April

E: May F: June

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 3 Climate Change Impact in the Study Area

G: July H: August

I: September J: October

K: November L: December Figure 3-7: Trend in Monthly Rainfall for Different Months

Figure 3-8 presents rainfall pattern during monsoon and non-monsoon months. May, June, July, August, September and October are taken as monsoon months; May and October are also included in the monsoon period because there are some influence of monsoon in these two months. Other months are included in the dry months i.e. non-monsoon months. The results of rainfall in the monsoon and non-monsoon show that there are increasing trend of cumulative rainfall in those months. In both periods, the rainfall amount is in increasing trend. The results of dry period rainfall indicate that there is no long drought faced in the period. It is however important to note that the results are cumulative and do not represent the specific month drought faced. There are significant

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 3 Climate Change Impact in the Study Area

individual dry months that have nil rainfall as shown in Figure 3-7 for example there is only 0.3 mm of cumulative rainfall in the October, November and December 1993.

A: Non Mosoon Rainfall B: Monsoon Rainfall Figure 3-8: Monsoon and Non Monsoon Rainfall Trend at Muglu Khola Watershed 3.3 Climate Change Impacts and Adaptation Practices Increasing trend of temperature from October to May reveals that the project area has been influenced by the climate change. Local people of Chokhabang VDC reported us that they have faced drought events in 2040, 2066 and 2069 BS. These drought events have caused huge loss of agricultural production from the VDC. People from other VDC of the project area did not report such long and impacting drought events. Climate change effects on agriculture are very adverse types. Mostly the effects are negative although it has some positive effects too. Its effect on agriculture are i) early ripening of crops, ii) decreasing productivity, iii) sever effect to a few earlier grown crops, iv) decreasing soil fertility and quality, v) deteriorating food taste, vi) decreasing livestock number, and vii) prospect for growing new crops and increases in production. Increasing rate of maximum average temperature based on the daily maximum temperature show the project area's maximum monthly temperature is increasing at the rate of 0.052 °C per year which is slightly lower than national figure which is about 0.06 °C per year as reported in the National Disaster Report (NDR) 2011. The warming in winter is more pronounced for example the temperature increase rates for November and December are computed to be 0.13 and 0.1218 °C per year . Local people have observed one month early ripening of crops such as wheat, potato, radish and 15 to 20 days earlier in the lower elevation. It has observed decreasing productivity even in a situation of similar inputs such as seeds, manure, labor input. It has not exactly traced out the percent of productivity declining, but it was reported that about 20 percent productivity has decreased. It has highly threatened the household food security. A few crops that used to grow in the past have almost been impossible to grow. People claim that it is due to the increment in soil temperature. The another effect is that people cannot get good harvest without using chemical fertilizer by which soil has become infertile and soil quality has been decreased. Analysis of rainfall data from the Musikot Airport Station does not reveal any significant trend. The 24 hours daily extreme event rainfall data depict decrasing trend whereas annual cumulative rainfall

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 3 Climate Change Impact in the Study Area

data are in increasing trend. These two results are contrary with the results from the national results as reported in the NDR 2011 for example NDR 2011 reports that there is an increasing trend in rainfall extremes and decreasing trend in annual rainfall in the country. Monthly rainfall data do not show any specific trend in the climate change; they show rather mixed trend. However, cumulative monsoon and non-monsoon rainfalls are increasing trend in the project area. It is yet to conform that whether new types of health problems are due to climate change or not, local people claim that climate change has effected on their health as certain new diseases, symptoms have experienced. Feeling of dizziness and becoming senseless during the day time has noticed among young people. Unlike before, people in all VDCs reported that they have a feeling of having weak bones that break or fractured with minor injuries since last few years. Health problems such as headache and prolong common cold have rapidly increased. Small hurt, ghau, khatira have increased. Bacterial infection cases have increased. Cases of nimonia, dysentery, eye infection, mouth diseases to human have also increased. It has also observed more flies, mosquitoes in the villages. Local people have embedded knowledge to their environment and resources. Local people use indigenous means like smell, flowing voice of the river and behavior of the amphibians. The local communication and warning system is not specific to landslide. People have realized the increasing and erratic rainfall but have not been able to warn themselves about the possibility of landslide occurrence in particular settlement. They know that some areas are weak and potentially dangerous and some strong, safe, areas in the village. Local people of the watershed have three different types of traditional means of communication such as i) by making laud sound from the top place, ii) by announcing the message, iii) by visiting in person or group to the concerned place, and iv) communicating through mobile. In the project area VDCs, there is no good early warning systems equipped with recent technology. Therefore, there is a need of establishment of early warning system particularly for river flood through establishment of gauge station, employment of gauge reader siren establishment in the Muglu Khola near Simratu Bazar and Bairagee Thati.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 4 Flood Hazard Risk Assessment

Chapter 4 Flood Hazard Risk Assessment

4.1 General About 80% of the Nepal’s land area is hilly and many villages are situated on or adjacent to unstable hill slopes. Monsoon rainfall that accounts about 80% of total annual rainfall is mainly caused by the influence of both south-east and south-west monsoon resulting in floods, landslides with debris flows. Nepal’s flood system is broadly categorized into four types: Flash Floods, Monsoon Floods, Local Floods and Glacier Lake Outburst Floods. Flash Floods are the events with very little time lapse between the start of the flood and peak discharge e.g. Lele in 1981, Kulekhani in 1993 and Syangja in 1998. They are often associated with short intervals between storm occurrences and arrival of the flood wave. Floods of this type are particularly dangerous because of the suddenness and speed with which they occur. Flash floods are common with isolated and localized intense rainfall originating from cloud burst. Monsoon flood is generated by intense rain during monsoon months of June to September. Monsoon floods from the major rivers generally rise slowly in the southern Terai Plains and the period of rise and fall may extend up to 12 to 24 hours or more. Inundation of large areas due to floods overflowing the river banks causes extensive damage. The flood water erodes the banks causing permanent damage to the adjacent agricultural land. Local floods are triggered by high localized rainfall of long duration in the monsoon season that generates water volume in excess of local drainage capacity. Another important flood type in Nepal is the Glacier Lake Outburst Flood. Glacier lakes are common in the Northern Himalayan region of the country. Altogether 2315 glacier lakes are identified in Nepal; some potentially dangerous lakes include Upper Barun, Imja, Lower Barun, Tsho Rolpa, Sabou, Dudh Kunda etc. These lakes are located in geologically fragile areas and contain huge volumes of water; they may burst at any time causing great loss of life and physical property. About 14 such glacier lake outburst floods have been experienced in Nepal from 1953-1991. In the study area, glacier lakes were not observed and thus the impact associated with GLOF is estimated to be nil. In the Muglu Khola Watershed, Flash Floods, Monsoon Floods and Local Floods are common resulting in huge loss of life and physical properties. Local community reported that at least 2-3 people are flooded every year by an individual tributary of the Khola; tributaries of Muglu Khola include Peugha Khola, Pane Khola, Muru Khola, Khara Khola, Sankh Khola etc. This indicates need of proper flood assessment through the preparation of community based hazard mapping along with public awareness on flood hazard risk. The mapping provides input to planner and manager to illustrate local hazards, land-use planners seeking to base settlement locations to reduce hazard impacts and to combine with other information to illustrate community risks. Muglu Khola watershed is an un-gauged watershed and predicting flood response in un-gauged watersheds is one of the major issues in the hydrological sciences. Predictions are particularly difficult to make in areas where fine spatial and temporal data are not available.

4.2 Study Approach The approach to be adopted for carrying out the study includes: . Collection, review and analysis of similar type of works carried out in Nepal

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 4 Flood Hazard Risk Assessment

. Interaction with local communities of the watershed . Literature (scientific publication) review, study of project report related to hazard assessment . Collection of digital data for topography, land-use, soil, geology in GIS environment . Collection and study of daily climate data such as rainfall data, temperature, humidity etc. . Collection and study of socio-economic data from secondary sources . Direct field measurements on various parameters . Stream flow simulations with HEC HMS . Flood estimation for different return periods using different methods . Flood inundation modelling with HEC RAS and analysis of results . Model calibration and validation using primary and secondary data . Identification of most flood prone communities . Flood risk assessment in the project area

4.3 Data Collection Topography: The topography of the Muglu Khola Watershed was developed from the 20 m interval contour map of the Rukum district prepared by the Department of Survey (DoS). The DoS developed the digital map by digitizing the topo-sheet prepared during topographical survey conducted by the Department with the financial aid from the Government of Finlad. A 10 m grid-cell resolution DEM of the study area was prepared by interpolating the contour value of the contour map using the ‘Topo to Raster’ function in ArcGIS.The ‘Topo to Raster’ uses an interpolation method specifically developed to generate hydrologically correct DEM using ANUDEM program. Topographic attributes computed from the DEM were slope angle, watershed and sub-watersheds delineation, stream network, flow accumulation, flow direction, upslope contributing area and longitudinal profile of the river etc. River Cross-section: During field visit, the study team was involved to measure the cross-section of the river at different locations of the Muglu Khola and its major tributaries. In the cross-section, high flood level was marked either through field observation or by enquiring local community or both. Other required cross-sections were developed in GIS environment. Land-use: Digital land-use map of the study area was obtained from three sources. In the present study, land-use map was derived from the 5 m resolution satellite image obtained from the Forest Resource Assessment (FRA), a project under the Department of Forestry. Areas occupied by different land-cover were estimated by the land-use map. Different plant species and their availability in the watershed were noted during the field visit.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 4 Flood Hazard Risk Assessment

Figure 4-1: Land-cover Map of the Study Area from the FRA

Soil: The study area has coarse soil map having three soil classifications according to USDA classification as depicted in the Table 2-5. The detail information on these soil types was gathered from existing literature and lookup table. Further, soil samples were collected from 10 different locations and soil properties were obtained from laboratory tests. The measured soil properties included particle size distribution, saturated hydraulic conductivity, angle of internal friction and cohesion using the standard method of practices. Climate Data: Daily rainfall, maximum and minimum temperature and relative humidity data (1980- 2010) were collected from rain gauge station located at Musikot Airport Station (Figure 2-3). The station lies within the study watershed. The north-western slopes of the catchment are exposed to the dry north-west winds in summer, while the eastern slopes are exposed to the cooler drying north-easterly winds. Temperature reduces with an increase in altitude. Stream Flow Data: The Muglu Khola is an un-gauged station and therefore no time-series flood data are available for the Khola. Time-series flood data are also not available for Sani Bheri River; Muglu Khola is one of the tributary of the Sani Bheri River. The nearest stream gauging station is located at

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 4 Flood Hazard Risk Assessment

Rimna(28°42’30” latitude and 82°17’30”) along Thuli Bheri River. Daily stream flow data of the station were obtained for the period 1979-2008. Annual instantaneous peak flood data for different duration were obtained for different river basins within the Karnali river basin. These include Karnali (Lalighat), Sinjha Khola (Diware), Karnali (Asaraghat), Karnali (Benighat), Seti (Gopaghat), Thuli Bheri (Rimna), Bheri (Samajighat), Bheri (Jamu), and Karnali (Chisapani). Other Data: Other data required for hydrological computation, modelling and simulations were obtained from literature, manual or look-up table.

4.4 Study Methodology

4.4.1 Flood Analysis The study methodology primarily include flood estimation in the Muglu Khola Watershed using prevailing numerical models such as HYDEST (i.e. a computer based hydrological model developed by WECS and DHM), revised WECS-DHM 2004, Dickens model, HEC-HMS etc. These models were used to predict mean monthly and instantaneous peak floods however, due emphasis was given on instantaneous peak floods because flood predication is the main theme of the present study. HYDEST: It is a computer-based hydrological model developed by WECS and DHM in 1999. The model is based on the long-term flow records of DHM primary gauges. After detailed checking of data quality, the monthly flow was generated in a multiple regression analysis involving up to 14 catchment parameters such as basin area, main stream length, area of catchment below 5000 m elevation, etc. Total drainage basin area, basin area below 5000 m elevation, basin area below 3000 m elevation and monsoon wetness index are the input for the model. It simulates mean monthly flow, daily and instantaneous peak flow in a programmed Excel spread-sheet. This is an empirical model derived from the regression analysis of different river basins in Nepal. In computing of mean monthly flow, the empirical coefficients are month dependent i.e. a set of 12 regression equations are derived which can be used to predict the mean monthly flow whereas instantaneous peak floods for different return periods are derived using following equations:

Equation 3.1

Where σ1 = ln (Q100/Q2)/2.326, S is the standard normal variate

0.8767 0.7342 Q2 = 1.88 (A<3k+1) and Q100 = 14.63 (A<3k+1) for 3k = 3000 m elevation.

The peak elevation in our study watershed is 2851, A<3k is 172 sq. km. Revised WECS-DHM 2004: The WECS-DHM method was revised in 2004 for evaluating the hydrological characteristics of an un-gauged catchment. The method is based on statistical models using multiple regression approach. The statistical models used to develop the method are: (a) Transposition of Frequency Data, (b) Rational Method (c) SCS method, (d) Regional Flood Frequency Analysis (e) Envelop Curve and (f) Regional Unit Hydrograph. The approach differs from WECS-DHM 1990 in terms of methodology because the revised method employs multiple regression approach on different statistical mode thus differing on empirical coefficients to estimate long-term mean monthly flow, instantaneous peak flow and low flow in different return periods. The peak flow is computed as:

Equation 3.2

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 4 Flood Hazard Risk Assessment

Where σ1 = ln (Q100/Q2)/2.326, S is the standard normal variate

0.86 0.72 Q2 = 2.29 (A<3k) and Q100 = 20.7 (A<3k) for 3k = 3000 m elevation.

The peak elevation in our study watershed is 2851, A<3k is 172 sq. km. Dickens Model:The Dickens model is an empirical model that depends on the watershed area. The equation is given by:

3 4 Qt Ct A Equation 3.3

Where Ct return period (T) dependent coefficient ad is given as Ct = 2.342 log(0.6 T) log(1185/p)+4. In

this equation p = 100(As+6)/A where As is the snow covered area out of total catchment area A. Regional Flood Frequency Analysis: Annual peak flood data of different stream gauging stations located in Karnali river basin were analysed. A relationship between the peak flood and catchment area was developed. The relationship was good with the value of R2 equating to 0.9251; the relation is defined by the equation y = 1.6363 x0.8638where y is the instantaneous peak flood and x is the catchment area in sq. km. (Figure 4-2). Extreme event flood data were derived using the statistical tools.

Figure 4-2: Mean Peak Flood versus Catchment Area in Karnali and Gandaki River Basin

Transpose from the Nearest Gauged River: Annual peak discharge of a gauged river basin may be transposed to an un-gauged river basin. In the present, peak flood data were obtained from Sarada (Daaradhunga) and Thuli Bheri (Rimna) and were transposed to Muglu Khola on catchment area basis. Stream flow data for Sarada Khola and Thuli Bheri were available for the period 1972-2011 and 1977-2011 respectively. HEC GeoHMS: HEC GeoHMS is the GIS extension of HEC-HMS. The model was developed by Hydrologic Engineering Centre within the US Army Corps of Engineers. The model was developed beginning in 1992 as a replacement for HEC-1 which has long been considered a standard for hydrologic simulation. The new HEC-HMS provides almost all of the same simulation capabilities, but

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 4 Flood Hazard Risk Assessment

has modernized them with advances in numerical analysis that take advantage of the significantly faster desktop computers available today. It also includes a number of features that were not included in HEC-1, such as continuous simulation and grid cell surface hydrology. It also provides a graphical user interface to make it easier to use the software. The program is now widely used and accepted for many official purposes, such as floodway determinations. The HEC-HMS is designed to simulate the precipitation-runoff processes of dendritic drainage basins. It is designed to be applicable in a wide range of geographic areas for solving the widest possible range of problems. This includes large river basin water supply and flood hydrology, and small urban or natural watershed runoff. Hydrographs produced by the program are used directly or in conjunction with other software for studies of water availability, urban drainage, flow forecasting, future urbanization impact, reservoir spillway design, flood damage reduction, flood plain regulation, and systems operation. The HEC-HMS is a generalized modeling system capable of representing many different watersheds. A model of the watershed is constructed by separating the water cycle into manageable pieces and constructing boundaries around the watershed of interest. Any mass or energy flux in the cycle can then be represented with a mathematical model. In most cases, several model choices are available for representing each flux. Each mathematical model included in the HEC-HMS is suitable in different environments and under different conditions. Making the correct choice requires knowledge of the watershed, the goals of the hydrologic study, and engineering judgement. Topography (i.e. DEM), land-cover, soil data, time series climate data (precipitation, temperature, humidity) are the input in the model. Topography is used to delineate watershed and sub- watersheds, drainage line etc. Streams are defined by providing “Number of Cells to Define Streams” which in this study was given to 4 sq. km. There were 27 sub-watersheds (Figure 4-3) delineated in the Muglu Khola Watershed, the area of which ranges from 0.04 to 25.12 sq.km. Thirty one years (1980-2010) daily time series climate data Musikot Airport Station were used for the hydrological simulations.

Figure 4-3: Sub-watershed Delineation for the Muglu Khola Watershed

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 4 Flood Hazard Risk Assessment

Hydrological simulations for project were carried out using SCS method. The SCS method also known as Curve Number (CN) method is an empirical parameter used in hydrology for predicting direct runoff or infiltration from rainfall excess. The runoff curve number was developed from an empirical analysis of runoff from small catchments and hillslope plots monitored by the USDA. It is widely used and is an efficient method for determining the approximate amount of direct runoff from a rainfall event in a particular area. The runoff curve number is based on the area's hydrologic soil group, land use, treatment and hydrologic condition. References, such as from USDA indicate the runoff curve numbers for characteristic land cover descriptions and a hydrologic soil group. During hydrological modeling in the present study, hydrologic soil group of two soil types (i.e. soil types 1 and 3 in Table 2-5) were adopted as ‘B’ whereas soil type 2in Table 2-5 was referred to hydrologic soil group ‘C’. The applied Curve Number for the modeling purpose is illustrated Table 4-1.

Table 4-1: Curve Number (CN) used in Modelling

SN Land use CN Value for Hydrological Group B C 1 Conifer Forest 60.00 73.00 2 Shrub Land 69.00 79.00 3 Sloping Terrace 73.00 79.00 4 Valley Cultivation 5.00 8.00 5 Grazing Land 61.00 74.00 6 Hardwood Forest 55.00 70.00 7 Level Terrace 72.00 79.00 8 Rock outcrop 96.00 99.00 9 Lake 100.00 100.00

River cross-sectional area, wetted perimeter and hydraulic radius of Muglu Khola and its tributaries were provided from direct field measurements during field survey and from DEM. Daily rainfall data from the Musikot airport station available for the period 1980-2010 were used for the daily flow simulation. Lag Method was used for water routing in the Muglu Khola. The channel cross-section, gradient were derived from the DEM whereas value of ‘Manning’s Coefficient’ were obtained from literature of similar river type; in this present study The hydrological simulation was done for the Muglu outlet i.e. the confluence between Muglu and Sani Bheri River. The daily simulated flows were used to predict flood for different storm events.

4.4.2 Flood Hazard Mapping

HEC-GeoRAS: After hydrological (flood) analysis for different return periods as computed from the models illustrated above, HEC GeoRAS was used for flood and inundation mapping along the Muglu Khola and its tributaries. It is a GIS extension that provides the user with a set of procedures, tools and utilities for the preparation of GIS data for import into HEC-RAS.

HEC-RAS supports steady and unsteady flow water surface profile calculations, sediment transport computation and water temperature analysis. It is capable of performing one-dimensional water surface profile calculations for steady gradually varied flow in natural or constructed channels. Main inputs for HEC-RAS are geometric data, Manning’s roughness coefficient and extreme event stream

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 4 Flood Hazard Risk Assessment

discharge. The general procedures adopted for floodplain analysis and flood risk assessment in the present study involve following five steps (Figure 4-4):

. Preparation of TIN . GeoRAS pre-processing to generate HEC-RAS . Running HEC-RAS to simulate water surface profiles . Post-processing of HEC-RAS results and floodplain mapping . Flood Hazard Mapping

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 4 Flood Hazard Risk Assessment

Figure 4-4: Flow chart illustrating Flood Hazard mapping using HEC RAS

Floodplain modeling and mapping was done in five different scenarios of extreme events (2, 5, 10, 50 and 100 year return period) using the HEC GeoRAS. The flood data were compiled using the methods illustrated above. Geometric data such as river’s center line banks and out banks required for the model were obtained from GIS by developing; river cross-section reach lengths were derived

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 4 Flood Hazard Risk Assessment

from DEM. High resolution satellite impages and images from the Google Earth were useful for visual interpretation while developing these geometric data. The geometric data extracted from the TIN using HEC GeoRAS was used to develop the HEC RAS model. The steps involved to run HEC RAS model are: Import and completion of geometric data: The geometric data of river cross-sectionswere read from the HEC-RAS GIS import file in the HEC-RAS. Theimported geometric data consists of cross- sections including reach lengths and bankstations. In many cross sections, the bank stations were found not to be properlylocated and they were corrected manually with the help of images from Google Earth. Manning's n values: Manning's n coefficients are also the part of the geometric datathat need to be specified in the HEC-RAS model. The selected values of n were 0.05 forchannel and 0.06 for overbanks. Steady flow data: Steady flow data are entered for the flow return periods of 2, 5, 10,50 and 100 year flood return periods. As no downstream boundary condition inthe form of rating curve or observed water level was available, normal depth wasused as the boundary condition. HEC-RAS Steady flow simulation: After the completion of the geometric data andthe steady flow data, the HEC-RAS system was executed for the mixed flow profile. HEC-RAS output: After a satisfactory HEC-RAS output, the simulation data was exported into GIS in HEC GeoRAS environment.

4.5 Results and Discussion

4.5.1 Rainfall Analysis Figure 4-5 depicts the annual and monsoon rainfall pattern at the Musikot airport station which lies in the study watershed. The result shows that about 81% of the annual rainfall falls during monsoon. The highest annual rainfall occurred in 1985 with the value 2948 mm, lowest (1373 mm) in 1989; average rainfall is 2192 mm.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 4 Flood Hazard Risk Assessment

Figure 4-5: Total Annual and Monsoon Rainfall Pattern at Musikot Airport Station

Table 4-2 depicts mean monthly rainfall recorded at the Musikot Airport Station. The data show that amount of annual and monsoon rainfall are high compared to those of the country. This confirms that Rukum is highly prone to water induced disaster. Table 4-2: Monthly Rainfall Records at Musikot

Year Jan Feb Mar Apr May Jun Jul Aug Sept Oct Nov Dec Max Max daily Day 1980 6.50 29.80 50.20 0.00 110.60 458.10 937.50 531.20 353.40 60.00 0.00 0.90 138.40 1-Sep 1981 16.80 3.30 68.40 35.80 171.30 118.90 613.20 418.10 248.20 6.60 48.50 10.70 52.00 8-Sep 1982 36.50 36.50 112.50 24.50 109.60 266.20 234.20 689.70 198.20 11.50 55.00 12.50 78.40 4-Aug 1983 43.20 0.00 16.80 70.70 143.70 43.40 624.40 655.90 475.00 189.30 0.00 34.40 118.70 1-Jul 1984 42.50 4.60 3.90 32.50 80.90 447.40 750.40 580.80 299.00 8.00 2.50 17.20 108.00 17-Apr 1985 33.90 0.00 5.00 28.00 126.00 209.50 716.10 642.10 896.20 228.90 0.00 62.20 122.00 8-Sep 1986 0.00 23.70 11.10 109.20 107.20 338.80 801.40 618.60 248.80 69.60 3.00 94.20 120.00 10 Aug 1987 7.00 45.70 37.50 71.60 171.60 207.10 503.90 603.50 275.40 49.20 0.00 16.50 96.00 12-Aug 1988 7.00 19.00 59.90 40.90 128.60 367.50 1132.80 242.40 0.00 26.00 0.00 36.00 212.60 18-Jul 1989 0.00 6.60 9.50 28.00 47.20 0.00 199.80 727.80 210.90 124.30 16.70 2.30 94.00 25-Aug 1990 0.00 100.40 94.50 21.60 127.60 269.20 754.90 622.40 402.10 57.80 0.00 14.90 88.30 18-Aug 1991 37.80 25.50 34.00 49.10 70.00 291.80 437.70 602.00 312.00 0.00 6.00 23.40 92.80 4-Aug 1992 35.30 28.00 0.00 19.20 63.30 182.80 474.90 689.60 442.80 47.90 6.50 10.20 96.50 15-Aug 1993 39.10 16.40 91.60 127.00 80.00 322.60 346.70 459.70 205.70 0.30 0.00 0.00 141.00 22-Jun 1994 35.50 46.20 0.00 32.40 110.20 330.40 576.40 514.80 394.30 0.00 2.00 0.00 170.00 21-Aug 1995 27.50 49.80 52.70 22.40 82.90 646.30 334.60 819.10 237.70 0.00 74.90 7.60 129.40 6-Aug

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 4 Flood Hazard Risk Assessment

1996 46.60 84.30 17.60 27.60 1.90 454.30 457.90 618.70 326.60 152.00 0.00 0.00 119.20 14-Jun 1997 32.20 7.80 13.90 135.00 113.80 378.30 699.60 582.80 316.70 65.70 26.30 99.30 142.50 5-Aug 1998 1.10 25.30 109.50 93.30 72.50 390.80 516.20 616.10 393.00 86.90 51.30 0.00 95.20 30-Jun 1999 17.00 1.00 109.50 13.20 235.50 327.80 808.30 639.00 473.40 117.10 0.00 4.20 103.60 8-Jul 2000 32.10 55.30 33.30 170.90 225.30 600.10 550.70 730.00 438.10 3.50 4.00 0.00 129.20 20-Apr 2001 7.30 29.60 15.30 64.60 189.70 534.90 617.80 621.90 243.30 48.00 0.00 1.00 84.00 Jul-21 2002 80.80 75.50 14.60 45.50 227.90 244.70 469.60 703.20 292.20 56.10 4.70 21.20 113.00 3-Jul 2003 0.00 94.30 69.70 11.30 37.00 366.80 662.40 0.00 467.80 15.70 11.40 10.40 97.50 17-Sep 2004 25.50 6.00 0.00 59.00 303.40 116.80 720.00 685.40 182.50 177.00 3.00 26.00 95.80 1-Aug 2005 68.50 41.80 58.10 4.90 13.50 204.60 818.90 689.80 254.10 101.90 0.00 0.00 92.20 7-Jul 2006 0.00 24.00 65.20 62.40 115.80 77.10 535.70 484.10 6.70 48.00 38.50 37.00 96.20 15-Jul 2007 22.20 96.20 121.50 25.50 156.50 250.20 468.70 466.90 314.90 16.00 0.00 7.00 70.00 8-Aug 2008 39.00 22.50 5.00 60.30 237.30 535.20 578.60 496.40 351.80 0.00 63.00 0.00 67.00 25-Jul 2009 0.00 21.70 18.60 0.00 28.50 133.50 271.50 473.20 512.50 479.50 91.00 0.00 70.00 5-Oct 2010 14.00 131.00 0.00 0.00 172.00 195.50 618.60 595.60 457.10 495.30 30.00 0.00 98.00 9-Feb

The rainfall data show that 24 hours daily maximum rainfall ranges from 52 to 212.2 mm. To determine the rainfall extremes, the daily rainfall series record from 1980-2010 were analyzed using the Smada 6.0 software, which gives not only the extreme values but also the return period. From this, it is possible to estimate the likely maximum daily rainfall event in a particular time span. Rainfall extremes range from 101 to 215 mm per day at 2 to 100 year return period respectively (Figure 4-6).

Figure 4-6: Analysis Daily Rainfall Extreme versus Return Period with Log Person Type III Method

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4.5.2 Flood Analysis and Prediction HYDEST

Table 4-3: Peak Flood Estimation using HYDEST Method

Return period 2 5 10 50 100 Standard Normal 0 0.842 1.282 2.054 2.326 Variate Discharge 173 279 357 552 643

Revised WECS-DHM 2004

Table 4-4: Peak Flood Estimation using Revised WECS-DHM Method

Return period 2 5 10 50 100 Standard Normal 0 0.842 1.282 2.054 2.326 Variate Discharge 157 255 328 510 596 Dickens Model

Table 4-5: Peak Flood Estimation using Dicken Method

Return period 2 5 10 50 100

Ct 4.47 6.83 8.61 12.76 14.54 Discharge 212 324 409 606 691 Regional Flood Analysis The regional flood frequency analysis is one of the most widely used methodologies for estimating the design floods for different return periods in an un-gauged catchment. The gauging stations used in this analysis in the present study are 440, 439.3, 430, 428, 415, 690, 640, 406.5, 680 and 410 Gandaki and Karnali River basins.

The design flood is given by the relation:

QT = Median Flood Ratio x Mean Flood

3 Where, QT = Discharge of T-Year return period in m /s. The median flood ratio and the mean floods are determined by the flood frequency analysis of the peak flood value from the stations mentioned above. The highest floods observed in the stations are illustrated in Table 4-6.

Table 4-6: Observed Peak Flood Discharge for the Stations

Station Mean peak flood discharge (m3/s) Catchment area (km2) 440 312.8 308 439.3 67.4 151 430 444.7 582 428 163.7 160 415 575.8 476 690 3387.6 5640 640 42.6 87 406.5 703.8 601

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680 6429.0 17600 410 1980.3 6630 In order to determine the median flood ratio for different return periods, the flood values for different return periods for each station under consideration are divided by the corresponding mean flood value (QT/Q2.33) and are givenTable 4-7.

Table 4-7: Median Flood Ratio and Peak Flood Computation for the Muglu Khola

Return Period 2 2.33 5 10 50 100 Median flood ratio 0.91 1.00 1.38 1.68 2.36 2.65 Peak flood of Muglu Khola 128.26 140.45 193.41 236.55 331.49 371.63 Transpose from the Nearest Gauged River

Sarada River has 39 years daily discharge starting from 1972 and the data were used to derive the peak flood for the Muglu Khola. Peak floods were estimated using Normal, Log-normal, Pearson type III, Log-pearson III, Gumbel distribution methods. The results are given in Table 4-11. Peak Floods from Gumble Distribution Method were used for further analysis.

Table 4-8: Peak Flood Estimation Transposing with Sarada River

Return period in years Method 2 5 10 50 100 Normal 86.8 139.7 167.3 216.0 227.6 Lognormal 103.2 122.1 151.8 317.7 Pearson Type III 70.9 128.8 170.4 261.7 299.9 Logpearson III 83.7 138.7 169.2 225.9 246.8 Gumbel* 76.5 132.1 168.9 249.9 284.1 Thirty one year daily discharge flow data from 1977 are available for the Thuli Bheri River (Rimna). Peak flood data for different year return periods were estimated using different distribution methods and the values from the Gumbel Distribution Method was used for further analysis.

Table 4-9: Peak Flood Prediction from Transposing with Thuli Bheri

Return period in years Method 2 5 10 50 100 Normal 63.3 72.6 77.5 86.1 88.2 Lognormal 66.1 69.5 74.7 104.1 Pearson Type III 60.4 70.7 78.0 94.2 101.0 Logpearson III 62.7 72.4 77.8 87.9 91.6 Gumbel* 61.4 71.3 77.8 92.1 98.2 HEC GeoHMS Results from daily flow simulation using HEC GeoHMS were used to predict different year return period peak flood using the annual peak flow (Figure 4-7). The plots gives good relationship with the value of R squared of 0.9416. This relation was used to predict the flood for different return periods as given Table 4-10.

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Figure 4-7: Plot of HEC GeoHMS Simulation Results in different Return Periods

Table 4-10: Flood Prediction using HEC GeoHMS

Return period 2 5 10 50 100 Discharge 159 201 228 290 315

4.5.3 Summary of Results As illustrated in Table 4-11, instantaneous peak floods were estimated using different methods for various return period. Results show that peak flood estimation by transposing from Sarada Khola and Thuli Bheri Rivers is relatively low compared to similar gauged catchment in Nepal. These data were not taken into account for further analysis and flood inundation modeling purposes.

Table 4-11: Peak Flood Estimation using Different Methods

Return Peak Discharge from Different Method (m3/s) Period HYDEST Revised Dickens Regional Transpose Transpose HEC HMS WECS-DHM Flood from from Thuli Analysis Sharada Bheri 2 Year 173 157 212 128 77 61 159 5 Year 279 255 324 193 103 71 201 10 Year 357 328 409 237 132 78 228 50 Year 552 510 606 331 250 92 290 100 Year 643 596 691 372 284 98 315 Dickens, HYDEST and Revised WECS-DHM methods estimated peak floods to higher side. These methods are said not to be reliable for predicting peak floods particularly for higher return periods. HEC HMS and Regional Flood Analysis methods provided comparable estimations. Regional Flood

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Frequency Analysis yielded lower values of peak floods in smaller return period than HEC HMS method but slightly higher values in larger return period. In this study, estimations from HEC HMS method was therefore used for further analysis and flood plain modeling. Flood simulation using HEC HMS follows use of topography, watershed characteristics and climate data of the study watershed which represents more realistic scenario compared to other empirical approaches. Although validation of HEC HMS was not possible due to non-availability of the time series stream flow data, previous studies report that HEC HMS provides reasonably good results at different storm events. HEC HMS flood data were used for flood plain mapping.

4.5.4 Flood Plain Mapping Flood plain mapping done for different return periods (2, 5, 10, 50 and 100 years) using the HEC RAS model are presented in Figure 4-8 to Figure 4-12. For the flood inundation mapping, the peak flood for those storm events for the Muglu Khola and its tributaries were computed and the values are presented in Table 4-12.

Table 4-12: Peak Flood for Muglu and its Tributaries at their Outlet

Watershed Return Period (yr) Name 2 year 5 year 10 year 50 year 100 year Khara khola 11.789 14.829 16.905 21.502 23.356 Muru Khola 11.324 14.244 16.239 20.655 22.435 Ruga Khola 21.378 26.891 30.656 38.992 42.354 Peuga Khola 23.193 29.173 34.842 42.301 45.948 Tewa Khola 18.173 22.86 26.06 33.146 36.004 Sankh Khola 52.164 65.532 74.707 95.022 103.213 Pane Khola 13.164 16.559 18.877 24.01 26.803 Muglu Khola 159 200 228 290 315

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Figure 4-8: Flood Inundation Map of Muglu Khola for 2 Year Return Period

Figure 4-9: Flood Inundation Map of Muglu Khola for5 Year Return Period

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Figure 4-10: Flood Inundation Map of Muglu Khola for 10 Year Return Period

Figure 4-11: Flood Inundation Map of Muglu Khola for 50 Year Return Period

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 4 Flood Hazard Risk Assessment

Figure 4-12: Flood Inundation Map of Muglu Khola for 100 Year Return Period

4.5.5 Flood Risk Assessment Various methods were used to estimate flood for different return periods (2, 5, 10, 50, and 100 year). The used methods include WECS DHM 1990, Revised WECS DHM 2004, Dickens Method, Regional Flood Frequency Analysis, HEC HMS and Transpose from the nearby river basins (Thuli Bheri, and Sharada Khola). HEC HMS simulated results were used for further flood plain modeling using HEC RAS because the HEC HMS simulated results were based on daily time series climate data. The HEC HMS also takes topographic characteristics, soil and land-cover features into account. The results were comparable with the flood frequency analysis conducted for the Karnali Basin: the Muglu Khola watershed lies within the basin. Table 4-13 presents the flood inundated area along the Muglu Khola for different return period. The depth of the flow in all cases ranges from few cm to slightly more than 3 m. The total inundated area distinctly increases from 2 to 10 through 5 year return periods however, gradually from 50 to 100 year return period.

Table 4-13: Flood Inundated Area in Different Return Period

2 Flood Flood inundated area (m ) SN Depth 2 year 5 year 10 year 50 year 100 year 1 Up to 1 m 1,204,700 1,175,000 1,169,700 1,136,700 1,129,200 2 1 to 2 m 5,015 513,300 529,000 565,900 560,900 3 2 to 3 m 2,022 2,703 280,900 299,800 269,800 4 > 3 m 35. 3,800 21,800 64,700 121,900 Total 1,211,772 1,694,803 2,001,400 2,067,100 2,081,800

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The flood and inundation level along the river was also marked along different sections of the river through the high flood level marking and enquiring with local dwellers (Figure 4-13). They reported that highest level markings have risen up to 2.5 m which is comparable to our modeling results.

Figure 4-13: High Flood Level Marking near the Confluence of Muglu Khola with Sani Bheri

In hilly and mountainous regions, river bank erosion due to flood is the main hazards rather than flood inundation. The river bank erosion generally leads threat to human settlements, market areas, and agricultural areas particularly paddy fields located along Muglu Khola corridor. Generally, human settlements are quite far away from river channel network except Bairagi Thati, Simratu Bazar and Julkhet. These settlements possess high risk. Additionally, paddy cultivation areas from different villages are also in threats due to bank erosion which can be seen Figure 4-14 to Figure 4-19.

Figure 4-14: Threat to Simratu Bazar due to Bank Cutting and Sediment Transport

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Figure 4-15: Highly Flood Prone Bairagi Thati Bazar

Local people reported us that the flooding scenarios have been adversely impacting to the low land valley cultivation. Peak flow along the steep stream could have two direct impacts: (a) bank erosion and river cutting, and (b) transport of high sediment. There are several villages (Figure 4-16) that show the effect of flood on low land paddy cultivation areas through river cutting and high sediment transport (Figure 4-19). In one hand, river cutting would lead to decrease in cultivated area and on the other hand transport of sediment along the land would decrease the fertility of the land because of interference of transported material into fertile soils.

Figure 4-16: Impact of Flood on Low Land Valley Cultivation in 2 Year Return Period Scenario. Green polygon represents the paddy cultivation area.

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Figure 4-17: Flood Threat to Cultivation Land in Jhulkhet of Sankh VDC

Figure 4-18: House at Risk in Muru

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Figure 4-19: River Cutting and Sediment Transport affecting the Valley Cultivation Near Bairagee Thanti 4.6 Summary and Conclusions Muglu Khola is a perennial river that originates from lesser Himalaya and it is one of the tributaries of Sani Bheri. The Khola has seven major tributaries namely Sankh, Tewa, Khara, Muru, Rugha, Peugha and Pane Khola and all the tributaries are perennial types. Since no lakes are found in the watershed, no hazard associated with the GLOF was identified during the study. However, there are several issues related to flash flood.

The flood in the Khola and its tributaries were estimated different methods for various return periods and the estimation from the HEC HMS modelling was adopted for modelling the flood inundation mapping using HEC RAS. HEC HMS results were comparable with those of flood frequency analysis done for Karnali River Basin and simulated results are based on the time series climate data. HEC RAS Modelling results show that Simratu Bazar, Jhulkhet and Bairagee Thanti are highly prone to flood; our field observations also confirm this. In these areas, bank cutting, transport of huge sediment and boulders by the Khola are severe.

The Khola may possess high threats to the low land paddy cultivation different areas of the watershed. Potentially affected valley cultivation areas include from Musikot 5 and 6, Chibang 2, Peugha 1, 2, 6 and 8, Sankh 8, and Bhalakcha 7. The study has identified that the potential loss could be as high as 4.6 ha of paddy field.

The analysis of rainfall runoff relationship shows that the meteorological flash floods are associated with intense and local rainfall for short duration. In the absence of recorded meteorological and hydrological data within the study area, it is difficult to identify the trends in extreme precipitation events in this area. However, one study at national level shows that the frequency of extreme

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precipitation event in Nepal has been increasing. Extreme precipitation event is also associated indirectly in triggering flood hazard by supplying large quantity of sediments due to landslide and debris flow initiation. A threshold of 100 mm precipitation within 24 hours for the initiation of landslide and debris flow in Nepal Himalaya has been reported. It is in this context that the risk of flood hazard has been increasing.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 5 Landslide Hazard Risk Assessment

Chapter 5 Landslide Hazard Risk Assessment

5.1 General The term ‘landslide’ is generally used to denote a downslope movement of mass of earth, debris or rock down a slope due to the action of external forces such as rainfall, snowmelt, volcanic eruption, earthquakes, anthropogenic activities etc. Any landslide is generally classified and described by two nouns: the first describes the materials (e.g. earth, debris or rock); and the second, the type of movement (e.g. falls, topples, slides, flows, spread etc.). As shown in Table 5-1, a fall starts with detachment of soil or rock from a steep slope along a surface on which little or no shear displacement takes place. The material then descends largely through air by falling or rolling. A toppling occurs as a result of overturning of blocks rather than sliding or falling. It is a forward rotation, out of the slope, of a mass of soil or rock about a point axis below the gravity of the displaced mass. A slide, on the other hand, is the downslope movement of a soil or rock mass occurring dominantly on the surface of rupture or relatively thin zones of intense shear strain. The term ‘spread’ refers to an extension of cohesive soil or rock mass combined with a general subsidence of the fractured mass of a cohesive material into softer underlying material. The spread may result in from liquefaction or flow of softer materials. In flows, materials move as a coherent but constantly changing mass, involving internal shear or mixing of the mass and even sorting based on particle size and position in the flow. The distribution of velocities in displacing mass resembles that in a viscous fluid.

Table 5-1: Landslide Classification

Type of movement Type of material Bedrock Soil Coarse Fine Fall Rock fall Debris fall Earth fall Topple Rock topple Debris topple Earth topple Slide Rotational Rock slide Debris slide Earth slide Translation Spread Rock spread Debris spread Earth spread Flow Rock flow Debris flow Earth flow Complex Combination of two or more

5.2 Landslide Processes Deep-seated landslides Storms that produce intense rainfall for periods as short as several hours, or a more moderate and low intensity lasting several days, have triggered abundant landslides in many parts of the world. Water-induced landslides are often grouped as shallow and deep-seated landslides depending on the depth and mode of failures. The frequency and magnitude of rainfall events, together with other

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 5 Landslide Hazard Risk Assessment

factors such as lithology, morphology and land-cover, influence the type of landslide. Landslides in which the sliding surface is mostly deeply located below the maximum rooting depth of trees (typically a depth greater than 10 metres) are called deep-seated landslides. A typical example of a deep-seated landslide is shown in Figure 5-1. It is usually believed that the deep-seated landslides are triggered by moderate rainfall intensity distributed over long periods. Deep-seated landslides are generally slow moving in nature and rarely claim lives, but may cause high property damage. The failure modes in such cases are generally rotational or complex types.

Figure 5-1: Deep-seated Landslide Characteristics

Shallow landslides Landslides in which the sliding surface is located within the soil mantle or weathered bedrock (typically to a depth from a few decimetres to several metres) are categorized as shallow landslides. The surface of the slope in steep hilly and mountainous regions is quite often underlain by a plane of weakness lying parallel to it and therefore, shallow landslides are predominant. A schematic diagram of a shallow landslide has been presented in Figure 5-2.

Figure 5-2: Schematic Diagram of Shallow Landslides

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 5 Landslide Hazard Risk Assessment

In many cases, the shallow landslides are fast-moving and are extremely destructive, causing wide- spread damage and casualties. Shallow landslides can pose grave threat to life and property. Shallow landslides are often triggered in hilly and mountainous regions in short duration intense rainfall events. Rainfall events increase the pore pressure in the soil. Generation of high pore pressure may also result in liquefaction. Liquefaction is a process by which the soil suddenly loses a large proportion of its shear strength and is also a reason for fluidised landslides. Fluidised landslides that travel a long distance at high speed are one of the most dangerous types of landslides, resulting in extensive property damage and loss of lives. Fluidised slope failures are common both in artificial cut slopes and in natural slopes. As well as soil properties, changes in land-cover due to human interferences also influence the occurrence and distribution of shallow landslides. In particular, forest logging, fire and cultivation on hillslopes are considered the most important in triggering shallow landslides. For example, change in the forest cover, particularly from clear-cut harvesting affect various hydrological processes such as interception and transpiration. It is well established that forests in sloping ground possess high transpiration and interception rates that increase soil moisture deficit (making the soil drier) allowing reduced pore pressures. The harvesting reduces vegetation surcharge and root cohesion (binding action), resulting in decrease in slope stability and increase in the distribution of shallow landslides. Therefore, re-vegetation is often recommended for slope stabilization.

5.3 Landslides in the Study Area Landslides in the study area are basically characterized by shallow failure mode. They are shallow in depth and translational failure mode. Images of typical landslides are presented Figure 5-3. During field survey, study team was reported that most of the landslides were triggered by intense rainfall. However, there are some cases of anthropogenic activities such as rural road construction without proper planning using heavy machine that help to initiate and trigger landslides in the monsoon.

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Figure 5-3: Images showing Landslide Distribution in the Study Area

There were no historic data on the relationship between landslide occurrence and triggering conditions in the Muglu Khola watershed. A landslide inventory (Figure 5-4) was prepared during field survey using Global Positioning System (GPS), satellite image, and Google Earth’s map. The landslide inventory shows that a total of 207 landslide scars were mapped which were mostly found on steeper foot slopes, downstream ends of steep and un-channelled valley. The source length of these landslides varies from less than 1 m to more than 100 m.

Figure 5-4: Landslide Distribution in the Muglu Khola Watershed

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Table 5-2 depicts the landslide distribution in different VDCs of the study watershed. The table shows that Musikot which is the district headquarter of Rukum has the highest number of landslides. Musikot is then followed by Khara where 39 small and large landslides observed. Bhalakcha has the lowest number (7) of landslides.

Table 5-2: Landslide Distribution in Different VDCs of Muglu Khola Watershed

SN VDC Landslides Number 1 Musikot 40 2 Sankh 11 3 Chhokahbang 22 4 Rugha 18 5 Khara 39 6 Muru 16 7 Peugha 25 8 Chhibang 29 9 Bhalakcha 7

5.4 Landslide Hazard Assessment Approach A region is said to be susceptible to landslides when the terrain conditions at that site are comparable to those in the region where a slide has occurred. Landslide modelling is generally done for landslide hazard assessment and landslide modelling is based on a variety of approaches and models. Statistical and physically-based approaches are widely adopted tools in landslide modelling.

5.4.1 Statistical Approach The statistical methods are based on conceptual models. These models first require identification and mapping of a set of landslide causing (geological and geo-morphological) factors that are directly or indirectly related to slope failures. Then, it involves an estimate of the relative contribution of these factors in generating slope failures, and classification of land surfaces into zones of different hazard or susceptibility. Bivariate and multivariate statistical methods are the most commonly used for these predictions. The bivariate statistical analysis is a method that describes the relationship between two variables. In landslide modelling, the bivariate method links each landslide causing factor to the landslide distribution map. On the other hand, in multivariate statistical analysis, the weighted factors controlling the landslide occurrence indicate a relative contribution of each of these factors to the degree of landslide hazard within a defined land unit. The common property of these analyses is their nature of being based on the presence or absence of stability phenomena within these previously defined land units. The statistical approach can provide an insight into the multifaceted processes involved in landslide occurrence, and useful assessments of susceptibility to landslide hazard in large areas. However, the results are very sensitive to the data set used in the analysis and it is not straightforward to derive the hazard (i.e. probability of occurrence) from the susceptibility. The Landslide hazard mapping was based on quantitatively defined weight-values of different parameter class. The Landslide Hazard Index (LHI) was calculated based on the weight-values of different parameter class. A weight-value for a parameter class, such as a certain lithological unit or a certain slope class is defined as the natural logarithm of the landslide density in the class divided

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 5 Landslide Hazard Risk Assessment

by the landslide density in the entire map. This calculation of weight-values for each parameter class is based upon the following formula:

 Npix1   Npix  Npix    1 2  Wi  ln Equation 5-1  Npix3     Npix3  Npix 4 

 Npix 2   Npix  Npix    1 2  Wi  ln Equation 5-2  Npix 4     Npix3  Npix 4 

Where,

Npix1 is the number of pixels representing presence of both potential landslide causative factor and landslides

Npix2 is the number of pixels representing presence of landslides and absence of potential landslide causative factor

Npix3 is the number of pixels representing presence of potential landslide causative factor and absence of landslide

Npix4 is the number of pixels representing absence of both potential landslide causative factor and landslides

+ - + - The landslide hazard map was derived as the difference between Wi and Wi (i.e. Wi -Wi ). The resulting total weights directly indicate the importance of each causative factor. If the total weight is positive, the factor is favorable for the occurrence of landslides and if it is negative it is not.

5.4.2 Physically-based Approach This section of the report deals with the landslide modelling using physically based approach. This approach deals with the spatially-distributed and physically-based models by coupling a slope stability equation with a subsurface hydrological model. The slope stability model obeys the Coulomb failure criterion. The criterion describes the state of stress on surfaces where failure occurs. The physically-based landslide modelling is generally done with the infinite slope method. In the infinite slope method, the soil slope is assumed to slide on a slip surface parallel to the ground surface, and the slope is assumed to be infinite in extent at an inclination. Previous studies have confirmed that when the thickness of the soil is much less than the length of the slope, the edging effects are negligible and the infinite slope method is assumed to be valid. This method is widely used in modelling shallow landslides in hilly and mountainous catchments. The geometry of the slope, failure plane and other variables assumed in the method are shown in Figure 5-5. In this method, the safety factor is generally computed using the equation proposed using the Equation 5- 3.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 5 Landslide Hazard Risk Assessment

Figure 5-5: Schematic representation of Infinite Slope Method depicting various Parameters and Variables

Cs  Cr  γ w  tanφ Fs   1 m  Equation 5-3 Dγ ssinθ  γ s  tanθ

-2 Where Fs (-) is the safety factor, Cs and Cr (Nm ) are the soil and root cohesion related to the soil and the vegetation types; D (m) is the depth of the overlying soil. φ (°) is the angle of internal friction; θ -3 (°) is the local slope angle, γs (Nm ) is the unit weight of water. The term, m (-) is the wetness index that expresses the relative water table height (i.e. hw/D), where hw (m) is the water table height i a above the underlying bedrock. The value is computed as m  . Where i is the rainfall k Dsinθ intensity (m s-1), a (m) is the specific upslope contributing area and is equal to A/b, k is the hydraulic conductivity i.e. the contributing area per width or contour length. The equation computes the safety factor and the value of safety factor was related to the type of potential hazard as mentioned in Table 5-3.

Table 5-3: Values of safety factor with hazard classification

SN Value of Safety Factor Hazard Classification 1 < 1.00 Very High Hazard 2 1 to 1.25 High Hazard 3 1.25 to 1.5 Moderate Hazard 4 > 1.5 Low Hazard The DEM yields the soil slopes (θ) and specific upstream contributing areas (a) for ground water flow. From the soil type map, hydraulic conductivity (K), dry and saturated soil specific weight (γs), soil cohesion (Cs) and soil friction angle (φ) can be determined, using attribute tables that link values of these parameters to soil types based on the literature or field experience. Similarly, surcharge and root cohesion are estimated according to the prevailing land-use pattern in the study area, with values based on data given in the literature for similar types of land covers. The values of soil and land cover related are given in Table 5-4 and

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Table 5-5. Methodology used for landslide hazard mapping using physically based approach is schematically illustrated in Figure 5-6.

Figure 5-6: Flow chart depicting the present methodology to derive slope stability maps from basic GIS data of topography, land-cover, soil types and precipitation time series

Table 5-4: Soil related parameters used in the landslide modelling

-2 -2 -1 SN Soil Group C (kN m ) Φ (°) γs (kN m ) Ks (m s ) 1 Dystrochrepts, Haplustalf, Rhodustalfs 1.5 35 18 3.5x10-4 2 Dystrochrepts, Haplustalf, Rhodustalfs – Calcareous Materials 0.8 34 17 6.0 x10-6 3 Dystrochrepts, Haplumbrept, Haplustalf 1.1 36 18 4 x 10-4

Soil depth (D) is one of the most important parameters in the landslide model because it affects the soil infiltration and soil moisture distribution. The depth also affects the landslide prediction due to its presence in the denominator of the landslide modelling component. However, soil depth is rarely mapped. Physically-based landslide modelling has usually relied on either empirical or theoretical models to develop soil depth maps or lumped soil depth mapping approaches according to soil or vegetation types. The soils in the Muglu KholaCatchment are shallow with frequent minor exposed bedrock outcrops. In the present study, the depth of the soil above the failure plane is estimated from the land-use (

Table 5-5). Areas with grass, shrub land and sloping terrace are thought to have a limited root penetration depth due to the shallow underlying bedrock and are assumed to have an effective soil depth of 0.5, 0.5 and 0.75 m respectively; conifer forest 1 m. Hardwood forest and level terrace would have deeper soil profile depth and depths are assumed to be 2.5 and 3.5 m respectively. Valley cultivation area has deeper soil profile because of deeper sediment deposition and the failure depth is assumed to be 6 m.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 5 Landslide Hazard Risk Assessment

Table 5-5: Landslide related Parameters used in the Landslide Modelling from the Land-use Map

-2 SN Land-cover Cr (kN m ) Depth (m) 1 Conifer Forest 3.00 1.00 2 Shrub Land 0.50 0.50 3 Sloping Terrace 0.75 0.75 4 Valley Cultivation 1.00 6.00 5 Grazing Land 0.75 0.50 6 Hardwood Forest 4.00 2.50 7 Level Terrace 0.75 3.50 8 Rock outcrop 0.00 0.00 9 Lake and River 0.00 No Data

5.5 Results and Discussion

5.5.1 Statistical Method A 10 m grid cell resolution DEM was developed for the study area and the various parameters such as slope, relief, slope direction, geology, soil depth etc. were related with the occurrence of landslides (Figure 5-7). Slope is the main factor related to the occurrence of landslides. Slope map of the area was sliced into 7 groups, however, no landslides were observed along the slope greater than 60°. In the Muglu Khola Watershed, landslides are frequent along the Muglu Khola and its tributaries. Thus, location of the landslide from stream network was considered as another geomorphology related causative factor. Distance to stream was subdivided into four groups i.e. >50 m, 50 to 100 m, 100 to 200 m and >200 m. Following rainfall events, water flows from areas of convex curvature and accumulates in areas of concave curvature. This process is known as flow accumulation and is a measure of the land area that contributes surface water to an area where water can accumulate. This parameter was considered as relevant to this study because it defines the locations of water concentration after rainfall and those locations are likely to have a high slope failure incidence. Likewise, one of the controlling factors for the stability of slopes is road construction activity. However, in study area, road access was prime factor of slope degradation. Roads have been constructing without any geological study and without proper mitigative measures. As a result, many landslides are prominent in the slopes. Thus, distance to road factor map was generated as per the hypothesis that landslides may be more frequent along roads, owing to excessive forest declination and drainage from the roads and trails. In order to produce the map showing distance to roads, the road and trail segment map was rasterised and the distance to the transport routes calculated in meters. The resultant map was then sliced to give a raster map showing distance to roads divided into five classes as <250 m, 250 m to 500 m, 500 m to 750 m, 750 m to 1000 m, 1000 m to 1500 m 1500 m to 2000 m and >2000 m.

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Figure 5-7: Relationship between Landslides and different Causative Factors in the Muglu Khola Watershed The landslide hazard map was produced using the Equations 4.1 and 4.2 consisting of a series of GIS commands to support the equations. The resulting total weights directly indicate the importance of each causative factor. If the total weight is positive, the factor is favourable for the occurrence of landslides, and if it is negative, it is not. Some of the factors show relation to a lesser extent with the occurrence of landslides, as evidenced by weights close to 0. The weights are assigned to the classes of each thematic layer, respectively, to produce weighted thematic maps, which were over-laid and numerically added to produce a landslide hazard index (LHI) map. When landslide hazard index is crossed with landslide map of study area, result shows that the various class of causative parameters have +ve susceptibility index (Table 5-6).

Table 5-6: Relationship of various causative factors with the LHI

Slope Flow Direction Distance to Stream 0-10° -0.39121 North 0.274879 0-50 0.185359 10-20° -0.21538 North East 0.21224 50-100 -0.0355 20-30° -0.42471 East 0.618884 100-200 -0.06449 30-40° 0.249125 South East 0.619939 200-500 -0.37157 40-50° 0.33273 South 0.304543 Soil Depth 50-60° -0.64286 South West -1.08426 >1 m 0.980181 Curvature West -1.87584 1 to 2 m -1.23525 Concave 0.433993 North west -0.75771 2 to 3 m -0.79537 Planar 0.152301 Geology 3 to 4 m -2.38321 Convex -0.81077 Ranimatta Formation 1.449769 4 to 5 m 1.201641 Relief Lakharpata Formation -2.17394 > 5 m -0.13853 >1200 0.557944 Siuri Formation 0.21369 Distance to Road 1200 to 1500 0.936249 Surbang Formation -1.24632 <250 m 1.11467 1500 to 1800 -0.18926 Wetness Index 250 to 500 m 0.569507 1800 to 2100 -0.82723 >5 -0.17427 500 to 750 m 7.66E-05 2100 to 2400 -0.94483 5 to 6 -0.13453 750 to 1000 m -2.01752 >2400 -3.49953 6 to 7 -0.05894 1000 to 1500 m -0.54012 7 to 8 -0.14061 1500 to 2000 m -0.11523 8 to 9 -0.06515 >2000 m -1.06029 9 to 10 0.043189 >10 0.239523

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Total 207 landslides data were used landslide hazard mapping through LHI. The prediction rate curve of hazard map is shown in Figure 5-8. To obtain the prediction rate curve for each LHI map, the calculated index values of all pixels in maps were sorted in descending order.Then the ordered pixel values were categorised into 100 classes with 1% cumulative intervals and classified LHI maps were prepared with slicing operation in GIS. These classified LHI maps were crossed with landslide inventory map. Then success rate and prediction rate curves were prepared from cross table value. The results show that 40% of the study areas where the LHI had a higher rank value and could explain about 75% of the observed landslides.

Figure 5-8: Rate Curve of Hazard Index Value after Weights of Evidence Value

Looking at the Rate Curve of Hazard Index Value, the 40% of LHI higher value could predict as high as 75% of the observed landslides. This range of LHI could be predicted as Very High Hazard. Next 10% i.e. 40 to 50% LHI value has captured another 15% of the observed landslide and this range is now treated as High Hazard, 50 to 60% as Moderately High Hazard, 60-70% as Low Hazard and more than 70% as Very Low Hazard. With this classification, landslide hazard map was developed as shown in Figure 5-9. About 86% of the watershed lies in very high to moderately high hazard zone whereas about 14% of the watershed in the low and very low hazard zone.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 5 Landslide Hazard Risk Assessment

Figure 5-9: Landslide Hazard Prediction using Statistical Approach

5.5.2 Physically-based Methods Figure 5-10 and Figure 5-11 present landslide hazard mapping for the 2 year and 100 year return period respectively. The 2 and 100 year return period rainfall amounts correspond to 101 and 215 mm per day respectively.

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Figure 5-10: Hazard Mapping for 2 Year Return Period Rainfall Event

Figure 5-11: Hazard Mapping for 100 Year Return Period Rainfall Event

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 5 Landslide Hazard Risk Assessment

About 50% (Table 5-7) of the total area is observed landslide prone area (very high hazard) even in the 2 year return period rainfall event. The area increased to more than 65% of the total watershed area when the rainfall increased to 215 mm per day at 100 year return period which should be considered as sites for possible landslides as these areas are located on steep slopes between 24 to more than 65°. About 19% of the total watershed is safe and stable in the 2 year return period rainfall event.

Table 5-7: Landslide hazard area classification in the watershed in 2 and 100 year return period rainfall event

SN Hazard Category Hazard Prone Area (%) (2 year (100 year return return period) period)

1 Very High Hazard 50.53% 68.16% 2 High Hazard 19.96% 13.64% 3 Moderate Hazard 10.77% 6.60% 4 Low Hazard 18.74% 11.60%

Local slope gradient has a great influence on the susceptibility of a slope to landsliding. The landslides in the Muglu Khola Watershed were probably triggered by a transient water table above the interface between the soil surface and impermeable underlying bedrock, resulting from infiltration and subsurface seepage. An analysis was carried out to assess the relationship between the stream network and landslide occurrence. About 55% of the landslides were within 300 m of the nearest stream. As the distance from the stream network increased, landslide probability generally decreased. This may be attributed to the hydrological triggering of landslides due to increased soil moisture closer to streams. The success of landslide modelling is typically evaluated by comparing the location of the known landslides with the simulated. An ideal landslide susceptibility map maximizes the agreement between the known and the predicted landslide locations. Figure 5-4 shows 207 observed landslides displayed. The model captured all observed landslides even in the 2 year return period and the observed landslides fall in the very high hazard zone. The model prediction has been observed relatively high compared to the observed landslide in terms of their area. The over-estimation of the landslide prone area may be related to the soil parameterization i.e. under-estimation of soil and root cohesion: soil and land cover parameterization is relatively crude in this study. Another important factor is that present landsliding area does not necessary represent all landslide hazard zones. There are other huge areas that have similar land cover and soil characteristics to the landsliding area but no slope failures are triggered in these areas. These areas are to be considered as very high hazard. It is also important to note that there only 207 landslide scars are captured in the present study which may exclude may other old landslides that are covered by dense vegetation etc.

5.6 Conclusions Landslides are one of the most visible and commonly perceived as destructive phenomena in hilly and mountainous terrain. Weak geological structures, steep and rugged land surfaces and extreme climatic conditions result in a high degree of fragility. Land degradation is a common problem in

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fragile and steep slopes of the study area, where pressure from human intervention and infrastructure development are extensively high. All road networks are constructed with less engineering norms and standards. Debris flow, debris slide and gully erosions are the major land degradation processes in the area. There are 207 landslides of different sizes that were spatially mapped in the study watershed during field survey and using satellite images and Google Earth images. Landslide hazard modelling for the Muglu Khola Watershed was carried out statistical and physically- based methods. Infinite slope method of slope stability analysis was used as physically based approach. The method involves parameterization of land cover and soil related parameters associated with the rainfall characteristics. The parameters were estimated from literature and look up table for the similar soil types. Hazard was done for 2 and 100 years return period. The results showed that about 50% of the watershed has been predicted as very high hazard zone even at 2 year return period. The hazard zone increased with the increase in rainfall amount in higher return periods. The approach was able to capture all observed landslide scars. Statistical approach was also used considering the effect of slope, relief, slope direction, geology, soil depth, geology formation, and distance to stream, distance to transport, wetness index and curvature on the occurrence of landslides. Importance of each causative factor on the observed landslides was computed and hazard mapping was developed. Results showed that about 86% of the watershed lies in very high to moderately high hazard zone whereas about 14% of the watershed in the low and very low hazard zone. There were consistent results on the total hazard areas between physically based and statistical approach. However, from the visual interpretation it is found that spatial distribution pattern of hazard areas differ, for example, major portions of Musikot, Sankh and Chibang fall in very high hazard zone less in other VDCs like Khara, Chhokhabang etc. The physically based approach, on the other hand predicted higher areas very high hazard zone in Khara, and Chhokhabang VDCs. It is found from the field observations that Khara and Chhokhabang are also more important from landslide hazard point of view. Wide range of landslides should be managed properly in the area. Muglu Khola and its tributaries have very dynamic flow morphology as well as many have records of previous debris flow event also. As a result, the predicted hazard zones are subject to change every year after monsoon. Therefore, the hazard zonation maps should be renewed time to time. Specially, when landslides on roadside slope mitigate properly with the existing engineering norms, hazard zones along the road will be reduced naturally. High hazard zones should be managed in terms of sustainable slope management. Riparian forest development in the risky slope should be encouraged and road and other construction practice should be stopped.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 6 Socio-Economic Profile

Chapter 6 Socio-Economic Profile

This chapter of the report presents the socio-economic conditions of the communities of the study catchment. Basically it shows the relation between their level of vulnerability in terms of location and livelihood strategies. It also discusses the perception of local people on climate variability and change and its consequences. People’s preparedness and adaptation measures have been identified and discussed. Social economic factors that increase or decrease people’s vulnerability are analysed.

6.1 Methodology Secondary as well as primary sources of data and information were used in preparing community profile and assessing vulnerability of the communities. Secondary data were collected from published and unpublished documents from different organizations consisting information about those areas. Those were useful to understand the processes of change over a period. The secondary sources of information include: . Village profile of all VDCs in the Muglu Khola Catchment . District Profile of Rukum District . Documents from the District Forest Office, Rukum . Documents from the District Soil Conservation Office, Rukum . Documents from the District Agriculture Office, Rukum . Documents from the District Vetenry Office, Rukum . Documents for Various National and International Non-Government Organizations . Documents from the District Disaster Relief Committee Primary data were collected by structured questionnaire and different participatory approaches. Different methods were used and necessary tools were prepared for the collection of primary information. The following are the methods and tools used in gathering primary data. Household Survey Firstly, the household survey was conducted in all VDCs with structured questionnaire. Questionnaire were made to collect basic information on caste/ethnicity, family size, sex composition, main occupation of the household head, types of residence (permanent, temporary), house ownership (own or rented in) and history of migration of the households. The household heads were asked to fill the questionnaire (Annex-1). Total 529 households from eight VDCs were randomly selected from the list obtained from District office. Focus Group Discussion (FGD) Focus group discussion in each community was conducted in order to collect information on community level resources, service infrastructures, institutions and other development activities. The number of participants for group discussion ranged from only six to nine. In the discussion, participants were invited from different caste/ethnicity, occupation, class, gender, and from different areas (human settlement pockets), to make it representative. Checklists were prepared to guide the discussion and record information during focus group discussion. The participants were invited to discuss the topic in question and to build consensus while reporting information.

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Figure 6-1: Community Interaction Program for Collecting Primary Data

Key Informant Interview Old and experienced people from different sectors – agriculture, forestry, and water resources were interviewed to collect information on climate change since past 30 years and its impact. A checklist was prepared to record trend and variability in different climatic elements, crop types and cropping pattern, resource availability and use and other activities. Attempts were also made to collect the impact of climate change using proxy indicators such as change in flowering and fruiting time of flora, migration, nesting and hatching time of fauna, occurrence of water induced disasters. Similarly, information on the sensitivity of climate change on agriculture, forestry and biodiversity, disaster, water resources and other socioeconomic activities was also collected through key informant interviews. Transect Walk Information on drainage, trails, bridges and land use/land cover was transferred from topographical map into enlarged grid map manually. Transect walk following all the trails, roads, river bank was conducted for direct observation, measurement and mapping. All the relevant information such as buildings, infrastructure facilities, probable sites for landslides, erosion, sedimentation, bank cutting, inundation etc. were marked in the drawing sheets. It was made with the help of local experts (who have knowledge on local geography). Observations of the area affected by disasters were made to experience the affect. Observations were useful to know the way people are using their lands. People’s activities on different types of lands their land use pattern was also observed.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 6 Socio-Economic Profile

6.2 District Profile Socio-economic Status Table 6-1 presents that Human Development Index (HDI), Gender Related Development Index (GDI) and Gender Empowerment Measure (GEM) measures of the region (mid-western region) and Rukum. This district is in the 64th rank among the total 75 districts of Nepal on the basis of Human Development Index. The value of HDI, GDI, and GEM in this district are lower in than the mid- western regional average value.

Table 6-1: Comparative Description of the Region and the District

Nepal Mid-Western Rukum Rank Best Amongst the region district Regions HDI =0.509 0.452 0.270 64th Central Hill = 0.602 GDI = 0.499 0.441 0.238 - Central Hill = 0.589 GEM= 0.496 0.431 0.093 - Eastern Mountain = 0.538 Source: UNDP (2009) Nepal Human Development Report –State Transformation and Human Development and District Profile Total population of the district is 215,270 based on CBS projection 2065 comprising 106,249 male and 109,021 female from 36,781 total households giving the average family size of 5.9. The households in the district are of different castes; 3.43% Brahmin, 63.50% Chhetri, 23.79% Newar, Gurung and Magar, and 5.81% are Dalit and 3.47% Islam and Jain, Sikh etc. In the National census 1991 about 98.28% population are reported Hinduism as major religion in the district followed by Buddhism (0.94%), Christian (0.22%). Most of people of Rukum are dependent in agriculture (89%). The district is famous for seed farming of vegetable, which gives a significant value at national level. The district has opportunity for the cash production including from horticulture sector. For examples orange, ginger, bee farming are the potential areas for economic development of the district. This district has also some historical places such as 'Baisyai Rajya; Rukumkot, Musi Kot, Gotam Kot, Aathabis Kot, Kot Jahari, Syarpudaha, Kamaldaha. These can be potential touristic places indicating that tourism development is also opportunity for its development. In the district, there are 377 educational institutions of which 259 is Primary, 66 Lower Secondary, 34 Secondary School. There are 15 Higher Secondary Schools and 3 campuses available in the district. The literacy rate of the district is 50.4%. However, there is a big gap between male and female literacy. Infrastructure, Facilities Context Currently, the district lacks black-top (bituminous) road, Musikot (i.e. the district headquater) is connected to southern neighbouring district Salyan by a Gravel Road and the road is now being . But the road network to headquarter is expected to be a black-top road (Salyan-Rukum Highway) in near future. Now 44 km earthen road is ready for transportation but the road network is also seasonal road. The district has 2 airports: Chaurjahari and District Headquarter-Musikot Khalanga. But the flight schedule is very irregular. Electricity for the district headquater is electrified with a small

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 6 Socio-Economic Profile hydropower from which only 1200 households are benefited from this facility. Other areas of the district are also electrified either through Health, Sanitation and Drinking Water Context The population density of Rukum is 74 per sq. km. and annual population growth is estimated to be 2.06. According to data of District Public Health Office, the reproductive rate is 4.1 and child death rate is 64 per thousand. In the district, there are 46 health organizations indicating that about 4283 population has only one health facility. From the total population, 20.58% of people are using family planning. The water availability from different sources is like public tap 77.33%; private tap 0.09%; informal sources (2.63 % from River; spring 3.66%; 14.66 % direct from sources). Toilet facilities in the district are as follows: with 16.73% HHs water-shield; 28.56%informal and other 71.22%.

6.3 Demography of Muglu Khola Watershed Muglu Khola Watershed includes eight VDCs that are Muru, Rugha, Khara, Chhibang, Peugha, Bhalakcha, chaukhabang and Musi Kot Khalanga. The Village Profiles of the eight VDCs of the Muglu Khola Watershed show that total population of the watershed is about 49,000 from about 7,500 households (Table 6-2). Khalanga Musikot has the highest population in the area. The reason behind this is attributed to migration of local community in the Khalanga for the better employment opportunity. Being a headquarters it is the most mixed and dense populated VDC in this district.

Table 6-2: Demographic Structure of Muglu Khola Watershed

Average VDC HH Population Male Female HH Muru 659 4090 2036 2054 6 Rugha 689 4566 2322 2244 7 Khara 1065 6867 3396 3471 6 Chhibang 976 5915 2997 2918 6 Peugha 688 5669 3009 2660 8 Bhalakcha 514 3233 1560 1673 6 Chaukhabang 593 3806 1889 1917 6 Khalanga 2332 14566 7134 7432 6

Total 7516 48712 24343 24369 Majority of the population in these VDCs are Brahmin/Chhetri (74%), Magar (9%) and Dalit occupational groups (8%) Kami (ironsmith) and Damai (Tailor)) are other two major populations. Un- identified caste groups account fourth largest group (6%) in the project area VDCs (Table 6-3).

Table 6-3: Caste Basis Demographic Composition

VDC Caste Brahmin Magar Kami Damai Un-identified Others /Chhetri

Muru 2132 1249 413 163 66 52 Rugha 3339 712 175 153 166 Khara 4836 371 384 193 849 234

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Chhibang 3598 6 152 770 37

Peugha 4139 50 405 220 141 Bhalakcha 1079 298 479 491 Chaukhabang 2812 311 413 57 32 74 Khalanga 7918 700 181 111 77 349

Table 6-4 presents the demographic distribution according to age and sex groups. The data reveals that about 54% of the total population falls in th economically active group and rests are in either children and elderly population. Male to female ratio in the project area is 1.04.

Table 6-4: Demographic Distribution According to Age and Sex Group

Age Sex Bhalakcha Chhibang Chhaukhabang Khara Muru Musikot Peugha Rugha 0-14 Male 717 1194 602 1093 764 1854 941 897 Female 772 1173 601 1236 781 1802 950 951 15-59 Male 1142 1428 884 1500 925 2689 1080 1027 Female 1090 1375 841 1423 935 2586 1062 1023 Above Male 68 110 71 107 95 202 98 126 60 Female 69 83 55 67 68 203 72 117

After agriculture, remittance is the major source of income for people living in this VDC. Agriculture is the major occupation though very few are able to satisfy their needs only by it. Members of a household are engaging in various activities to bring cash.

6.4 Occupation Almost all people in this district are doing agriculture though very few can live their life solely on it. Wheat, barley, millet, maize and buck wheat and paddy are cereals produced in this district. People are involving on vegetable production. People are using land near house for vegetable production and land far from houses along the Muglu Khola and its tributaries' corridor for cereal production. People are being attracted towards vegetable seed production and dried ginger. Inadequate irrigation facilities are the one obstacle that majority of the farmers are facing. Male members are working for clearing and preparing land and female in all other activities. Feminization of agriculture can be experienced in this area. Because of male migration and women coming out of the house for cash the quantity and quality of women’s participation in agriculture is increasing. Members of a family are engaging in various activities to bring cash. Migration to cities and to abroad is a major source of income for lots of families of this district. Collection of wild food and herbs are other attractive source of income. People are also involving in vegetable production. Remittances are major source of income for several households. Historically going to India has been one way for having employment for the people of this district. Beside India young people are going other parts of the world particularly in the middle east gulf countries.

Table 6-5 presents demographic distribution of the project influenced VDCs according to the prevailing occupation. The data show that agriculture is the main occupation on which about 68 % of the project's population are dependent followed by remittance (10%) and labour (9%).

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Table 6-5: Demographic Ditribution according to Occupation

VDC Occupation Agriculture Business Teaching Labour Remittance Shop Others Muru 1446 52 63 65 201 78 Rugha 1544 69 71 257 397 79 Khara 3485 87 84 329 421 104 Chhibang 2303 67 64 152 259 68 Peugha 1520 50 82 51 228 74 Bhalakcha 1731 121 76 143 319 86 Chaukhabang 1371 72 94 198 418 73 Khalanga 5452 852 1141 1213 477 201

6.5 Food Sufficiency Rukum is one of the food deficit areas in Nepal. The district was in food deficits by 1924 MT in 2065/066. According to the production in 2065/066, the produced and required foods in the district were 46273 MT and 48197 MT respectively in the year. Major food production like paddy and wheat is less than the demand. Majority of the families do not have production sufficient for the whole year. Members of a family have to engage in various other income generating activities to meet the demands. People are attracted to collect wild herbs, fruits and flowers to get cash but no one from the surveyed VDCs said that they are collecting any wild food, herbs or medicinal plants that may be practiced by northern VDCs.

One hundred seventy five households were surveyed to study the agriculture land type owner pattern in the study catchment and the results shows that most of the agricultural lands do not have all year irrigation (Table 6-6). This table further confirms that most of whole year irrigation lands are owned by Brahmins and Chhetris.

Table 6-6: Sampled Landholding Pattern

Agriculture land type Owner Frequency Brahmin/Chhetri Hill Dalit Janjati Other Total Irrigated throughout 56 4 7 2 69 year Irrigated in monsoon 75 15 14 2 106 In the project area, only about 22% households have enough agricultural production to meet throughout a year demand. About 26% households are able to produce cereal crops for up to 9 months, 29% for up to 6 months and rest about 23% for up to three months in a year. Among the sampled households for the socio-economic survey, it was found that 265 households were affected by some sort of disasters (Table 6-7). They reported that they left significant amount of their lands barren due to various reasons including disasters. This table shows that landslide is the major cause of land degradation either due to landslide itself or due to downslope transport of the failure materials to paddy cultivation area. People had to leave their land barren because landslide destroyed their land.

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The food production is not sufficient to meet their annual requirement. People are therefore gradually attracted to other activities like trade and business, daily wages worker urban areas of the country. Daily wages rate for the skilled and unskilled labor is NRs. 600 and NRs. 400 respectively. The local people meet their daily household expenses from either daily wages labor or through other business.

Table 6-7: Various Reasons for Leaving Agricultural Land without Cultivation

Ethnicity Reasons for leaving land barren Total

Flood Landslides Non- Others availability of seeds Brahmin/Chhetri 2 46 10 120 178 Hill dalit 0 9 1 35 45 Janjati 1 13 0 27 41 Others 0 0 0 1 1 Total 3 68 11 183 265

6.6 Health and Sanitation Many settlement pockets of various VDCs and their wards have now been benefitted through the tapped water supply schmemes. For example all wards have tapped water supply facilities in Chhaukhabang, Musikot Khalanga, Rugha. However some wards like Khara 3 & 8, Muru 1, 3 & 6, Peugha 1, 2, & 7, Chhiwang 1 & 5 and Bhalakcha 1, 2, 5, 6, 7 & 8 are still deprived on tapped water supply. The people from these areas are to rely on natural springs for which they have to walk a long distance in every day. People from these areas have little knowledge on health and sanitation. About 50 % of the total households are supposed to have toilets.

Table 6-8: Health and Sanitation Condition in the Project Area

VDC Tapped Water Natural Spring Public Toilet Health Centre Woman Health Worker Muru 119 21 1 1 at ward 7 9 in all wards Rugha 100 72 No 4 9 in all wards Khara 117 25 2 1 3 in ward 4,5 & 6 Chhibang 244 25 No 1 at ward 6 9 in all wards Peugha 41 27 No No 4 in ward 1,3,5 & 6 Bhalakcha 21 42 No No 9 in all wards Chaukhabang 143 68 No 1 at ward 4 9 in all wards Khalanga 3281 59 8 10 including a 9 in all wards district hospital There are no primary health care centres, medical halls in Peugha and Bhalakcha VDCs. In other VDCs, there are primary health centres. There is a district hospital located at Musikot Khalanga, the district headquater of Rukum. Musikot Khalanga also possesses other private clinical services. People of the project area have to visit Musikot Khalanga for normal treatment and emergency cases and go either to Nepalgung or Kathmandu or India when special treatment processes are required. In all project VDCs, female health workers are providing their services. Their coverage areas are throughout the VDCs except in Khara and Peugha VDC. In these VDCs, the service coverages of

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 6 Socio-Economic Profile female health workers are extended in Khara 4, 5 & 6 and Peugha 1, 3, 5 & 6. Other wards of these VDCs are still deprived of female health workers. Looking on data, it can be concluded that health and sanitation of the project VDC is poor and there is still much to do to improve the health condition of the local people.

6.7 Land Types, Land Holding and Cropping Pattern In the hills, farmers have more upland (Bari and Pakho) than the low lands (Khet). In the project area, entire khet is irrigable (low land areas), which are mostly in river valleys or lower terraces. In the project area, about 29% of the toal population possess 0.75 to 1 ha land; 22% have 1 to 1.5 ha. Similarly, approximately 30% of the population have land between 0.5 and 0.75 ha. About 11% of the population are either landless or possess land less than 0.5 ha. Rest 8% has the land greater than 1.5 ha. In the project area, coarse grain like rice, wheat, potato, maize are grown. Agricultural production yield of paddy is about 200 kg per Ropani, maize 100 kg per Ropani and potato 400 kg per Ropani. Land transaction such as buying and selling land is very limited and the land price depends on type of land (lowland or upland), the land category fixed by government like Abbal, Doyam, and location (market centers, less accessible, settlements). Land market has not been developed for the area and transaction cases of land buildings and other physical structures are also very few. The land price varies from NRs. 100,000 per Ropani for low land (Khet), NRs. 50,000 per Ropani for upland (Bari) and NRs. 20,000 per Ropani for Grazeland (Khar Bari).

6.8 Migration Pattern Infrastructure development is very low in the project area. Small-scale business is partly supplying the services and requirement to the people. The agriculture product is not sufficient to meet the requirement and food deficiency is prevalent. To compensate this, most of the young people from the project area migrate to Nepalgung, Kathmandu or to other Market area of the country or in India or in Gulf Countries. In average one member of each household are migrated out in searching job.

6.9 Energy Consumption The main sources of energy in the project area are firewood, kerosene oil and electricity. Nepal Electricity Authority has been electrifying Musikto Khalanga through its micro-hydropower project. Other VDCs have been using solar panel or kerosene for electricity.

The people of the area have been employing electricity for lighting, while people are using firewood for cooking. In average 3-5 Bhari per week firewood and 1 liter per week of kerosene oil are consumed in each family. The firewood demand is fulfilled from the private, and community forests and the kerosene oil is purchased from Musikot Khalanga, Bairagee Thati, Simratu, Jhulneta etc.

6.10 Archaeological and Historical Sites The entire community within the project area has strong conviction for religion. More than 90% of the local communities in the project affected VDCs practice Hinduism followed by Buddhism. There are 72 temples, archaeological and historical sites in the Muglu Khola Watershed comprising 16 in

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Peugha, 7 in Rugha, 2 in Khara, 23 in Musikot Khalanga, 9 in Chaukhabang, 8 in Muru, 4 in Chhibang, and 3 in Bhalakcha VDC.

6.11 Gender and Disadvantage Group The population of the project area contains almost equal of males and females but the influence of the society is male dominated. Women have least influence in family affairs. The general status and role of women in the project area is primarily that of bearing, rearing and caring of children. In order to provide the daily ‘survival needs’ for family members, most of the women are engaged in household works like cooking, cleaning, washing, food processing, household maintenance, hygienic and sanitation activities. As with the general status of Nepalese women, women of the area have also no property inheritance right.

6.12 People’s Knowhow on Disasters According to the District budget for 2069/070 B.S. program related to UNFPA has made one disaster management committee and developed a disaster management fund and a guideline to work. The budget has a separate section for forest, environment and soil conservation. Activities decided to do in these sections are concerned with the conservation of natural resources but not having program related to disaster indicating that the district do not have clear planning related to the actions for disaster; not much preparation to deal with disasters;no program to strengthen people’s capacity to face such disaster, no early warning system. Development activities are concerned with infrastructures that are concentrated on road construction. Road construction and suspension bridge construction are mentioned in different types of programs like LGCDP (Local Governance and Community Development Program), social infrastructure development and even in model village development program. The district has a significant strength and opportunity, but weakness and the threats simultaneously exist in the district. The district lags behind the development because there is no blood bank in the district and lack of surgery facility in the district hospital, no regular flight schedule even the district has two airports. No opportunity has been provided to the children and teachers about the preparedness to cope with epidemic and fire hazards. Ignorance about bio-engineering can be noticed seeing the plantation works in old landslide zones. Similarly, the lack of shelters identification in those VDCs which were affected by the last year diarrhoea outbreak; inadequacy of medicine and no regular presence of health workers in the health centres; no effective communication mechanism to communicate needs and requirements for rescue during disasters; lack of trained volunteers with first aid and rescues; lack of resources especially rich with rescued equipment with political venders at village level; lack of emergency fund; no proper network with media-especially community based radios and other means some more weaknesses accounting for the poor situation of the district. Generally, people define disaster as loss of property and life. During socio-economic survey in the watershed areas, 529 people were asked about the disasters and their impact on community. Flood and landslides are the most frequent nature’s events that the people have experienced; about 18% of sampled population reported landslides as the major disaster events . People consider landslide, earthquake, flood, and any problem in nature as disasters. About 15% of the sampled population

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 6 Socio-Economic Profile said they did not know about disasters and how disasters occur. People’s experiences related to changes in the nature are related to the availability of water, food and events negatively affecting their livelihood.

Table 6-9: People’s Knowledge on Reasons for Disasters

Reasons Disaster Events Frequency Per cent

Landslide 94 17.8 Flood 21 4.0 Earthquake 1 .2 Natural Process 67 12.7 Don’t Know 79 14.9 Problem in Nature 61 11.5 Flood/landslide 127 24.0 Others 79 14.9 Total 529 100.0

Mostly people fear of landslide as it was the most destructive disaster they have experienced. People consider rainfall as main cause of flood and landslide. Majority 66% consider deforestation and high rain 25% as the two major reasons of natural disaster mainly landslide. People consider tree plantation and forest conservation as the most suitable actions to reduce the impact of disasters.

6.13 Institutional Capacity Table 6-10 presents the existing governmental and non-governmental institutional set up in the project area. All VDCs of the project area have their own buildings. Currently, VDC secretaries are delivering their local people from their own offices. All VDCs have post offices located in the respective VDCs. In all areas, mobile service networks are strong enough to be connected. It has been estimated that about 50% of the total population are using mobile phone.

Table 6-10: Institutional Capacity in the Project Affected VDCs

VDC VDC Cooperative Agriculture Post Nepal Mother Educational Citizen Youth Police Office Service Service Office Red Group Institution Ward Group Post Centre Centre Cross Forum Muru 1 - - 1 1 In all wards 8 In all wards 1 1 Rugha 1 1 1 1 - In all wards 8 In all wards 1 - Khara 1 1 1 1 1 In all wards 10 In all wards - 1 Chhibang 1 - - 1 1 In all wards 8 In all wards 1 - Peugha 1 1 1 1 1 In all wards 8 In all wards - - Bhalakcha 1 1 1 1 - In all wards 8 In all wards 3 - Chaukhabang 1 - - 1 1 In all wards 8 In all wards 2 - Khalanga 1 1 1 1 1 In all wards 9 In all wards 4 1 All VDCs lacks proper early warning system for the disaster risk management. They do not know about life jackets and their use. There are about 50 small scale industries in the watershed. These are related to NTFP, agricultural- based, dairy product and furniture. Rugha, Khara, Peugha, Bhalakcha and Khalanga VDCs each has cooperative service and agriculture service centres located in the VDCs. Nepal Red Cross society also has its branches in all VDCs of the watershed. All VDCs have citizen ward forums and mother groups functioning well.

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Muru and Khara are equipped with police station. Khalanga being the district headquater has district police office, district administration office, army barrack etc. Other district level organizations like DDC, DADO, DFO etc. are also located in the district headquarter. Various NGOs and INGOs are also working in the Khalanga. Some of them include United Mission to Nepal, Care Nepal, NPAF Rukum, Rukumeli Bikas Samaj etc. There are altogether 68 educational institutions which include primary, lower secondary, secondary, three higher secondary and two colleges in Musikot Khalanga.

These institutions are useful from disaster management point of view particularly in early response and recovery. However, adequate training and skills are to be provided to them particularly to the local youth group, local bodies etc. Local bodies are also to be trained on mainstreaming DRM CRM on local planning processes for the proper planning of local development because many un-planned development activities particularly road constructions have generated various new hazards leading to disasters.

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¥£L Army # Citizen Ward Forums )" Cooperative Office "$g Police # Mother Groups $ VDC Office [¾ Youth Club GF Nepal Red Cross # Agriculture Centre nm Educational Institutions !P Post Office 0 2000 4000 8000 m

Figure 6-2: Institutional Capacity in the Muglu Khola Watershed

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 6 Socio-Economic Profile

6.14 Conclusions Majority of the people consider agriculture as their major occupation though very few are able to meet their needs only by it. In the study watershed, more than half of the agricultural land is deprived of irrigation facilities in every season. Members of a family are involving in different types of activities to bring cash for various purposes. Majority of the surveyed population are using solar energy for lighting and mobile charging.

The study shows that landslide, flood and hailstorm are the most destructive natural disasters in these VDCs. People’s experiences of climate change are related to change in temperature, rainfall time and quantity, snowfall, and availability of water. People consider events of disaster like earthquake, landslide, flood and hailstone as natural disaster. Tree-plantation and forest conservation are two ways suggested by the people to reduce disaster. People are not involving in any organization working for disaster management. They think Red Cross, DDC and Conservation Office as the organizations working to reduce impact of disaster. No one from the sampled household is trained from the disaster management. Though people seem to be aware of the negative impact of deforestation they are not yet organized to stop it. They are not organized at community level to prepare before the disaster occurs. Mostly they are depending on outsider’s support in relief and preparation.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 7 Community Hazard Mapping

Chapter 7 Community Hazard Mapping

7.1 Introduction In the context of disaster risk management, a community is defined as people living in one geographical area, who are exposed to common hazards due to their location. They may have common experience in responding to hazards and disasters. However, they may have different perceptions of and exposure to risk. Groups within the locality will have a stake in risk reduction measures (either in favor or against). In the Muglu Khola Watershed, Community Based Disaster Risk Management (CBDRM) approach was also adopted to identify and map potential hazards, and to assess vulnerability and risk in the project area. CBDRM is a process of disaster risk management in which at risk communities are actively engaged in the identification, analysis, treatment, monitoring and evaluation of disaster risks in order to reduce their vulnerabilities and enhance their capacities. This means that the people are at the heart of decision making and implementation of disaster risk management activities. The involvement of the most vulnerable is paramount and the support of the least vulnerable is necessary. Community involvement is essential in the development process because of the following practical considerations: . Nobody can understand local opportunities and constraints better than the local communities themselves who therefore need to be involved in the identification and resolution of disaster vulnerability issues. Community involvement is essential because nobody can understand the local situation better than the local communities themselves. . Nobody is more interested in understanding local affairs than the community whose survival and well-being is at stake. Therefore the information should be generated in a manner and language that is understood by the community. There is growing evidence to show that most top-down disaster risk management and response programs fail to address specific local needs of vulnerable communities, ignore the potential of local resources and capacities, and may in some cases even increase people’s vulnerability. As a result, a broad consensus has been reached among disaster risk management practitioners to put more emphasis on community-based disaster risk management programs. This means the vulnerable people themselves are involved in planning and implementing disaster risk management measures along with local, and national entities through partnership. The aim of CBDRM is to reduce vulnerabilities and to strengthen peoples’ capacity to cope with the disaster risks they face. The direct involvement of the community in undertaking local level risk reduction measures is a must. Experiences in the implementation of CBDRM point to the following essential features: . The focus of attention in disaster risk management is the local community. The CBDRM approach recognizes that the local people are capable of initiating and sustaining their own development. Responsibility for change rests with those living in the local community.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 7 Community Hazard Mapping

. The main strategy is to enhance capacities and resources of most vulnerable groups and to reduce their vulnerability in order to avoid the occurrence of disasters in future. . CBDRM should lead to general improvement in people’s quality of life and the natural environment. The approach assumes that addressing the root causes of disasters, e.g. poverty, discrimination and marginalization, poor governance and bad political and economic management, would contribute towards the overall improvement in the quality of life and environment. . The community is the key actor as well as the primary beneficiary of the disaster risk management process. . CBDRM brings together the many local community and even national stakeholders for disaster risk management to expand its resource base. . Lessons learned from practice continue to build into the theory of CBDRM. The sharing of experiences, methodologies and tools by communities and CBDRM practitioners continues to enrich practice. . Specifically, men and women who may have different understanding and experience in coping with risk also may have a different perception of risk and therefore may have different views on how to reduce the risks. It is important to recognize these differences. . Different individuals, families and groups in the community have different vulnerabilities and capacities. These are determined by age, gender, class, occupation (sources of livelihoods), ethnicity, language, religion and physical location. In CBDRM of the Muglu Khola Watershed, various activities were performed involving community for their own benefits. These include seasonal calander, extracting historical time line, hazard mapping, hazard ranking etc.

7.2 Historical Time Line Timeline is a very simple tool that narrates the disaster history and significant events that happened in the community. One column gives the year and the other column lists down the events that took place. Main objectives are to learn what are the significant disaster events that occur in the community. The historical disaster databases were gathered during field trip made at different intervals for all wards of the watershed VDCs. The people of those communities with emphasis on elderly people were interviewed to gather disaster history and disaster loss. The timeline disaster details of each VDC have been presented in

Table 7-1. The data show that every year flood and landslides cause huge loss of lives and properties in the area and the landslide is the major contributing factor for such loss. Local people made us note 42 disaster events in Musikot Khalanga VDC which is the highest number of the events from the entire watershed VDCs. However, catastrophic event occurred in Khara on the 5 Bhadra 2068 that caused loss of life of 5 people, 4 injured and loss of 10 houses, 1 buffalos, 2 oxen and 5 toilets. Total loss from the disaster was estimated to be about Rs. 210 million. The damage patterns by different events vary with events. People did not remember all disaster events and they did not remember the events before 2028. Every year, heavy rainfall events caused flood and landslides that destroyed agriculture land and infrastructures. Some events claimed

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 7 Community Hazard Mapping human loss also. The disaster trend in Muglu Khola Watershed is similar to that of the entire Nepal and the world; the human deaths are decreasing and economic losses are increasing. Everyone in the watershed experienced an increase in number of disaster events. However, they also expressed that the catastrophes are not unusual events as they occurred in the past.

Figure 7-1: Historical Time Line Prepared by Community

People attributed the development activities, mainly road constructions for the foremost cause for increasing disaster damage. They ranked the increase in population leading to encroachment on forest resources as the second cause for the increase in disaster events. Road construction has been intensively carried in the area. Road development is exacerbating the disaster in three ways. Firstly, the road construction has made the sloping area weak due to disturbances caused by application of bull-dodgers and rock blasting. Slope stabilization and drainage management are generally neglected in the road construction projects. The weal land and improper drainage cause frequent landslides along the roads. Consequently, people noticed that the annual damage to agricultural lands due to landslides has increased after the commencement of Salyan-Musikot Road. According to local people residing along the road, every year landslides occur in their fields during monsoon rains. Secondly, lack of management of extra soil road construction is also enhancing landslides and floods. Since last few years the government, DDC and VDC have allocated budget for rural road construction so that each village has access to the Salyan-Musikot Road and Musikot. The excavated soils from the road construction have not been managed properly. These soils are being dumped along the roadside. These soils were brought to floodplains as sediments, which also contributed to rise the riverbed level. Thirdly, the increase in disaster is due to the establishment of human settlements, market area along the road alignment.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 7 Community Hazard Mapping

Table 7-1: Disasters History in Muglu Khola Watershed VDCs in Rukum

1. Bhalakcha VDC

SN Year Ward Disaster Loss Details Type 1 2033 1, Dagri Landslides 3 houses, 2 ha agriculture land, Rs. 1,500,000 2 2042 7, Boksir Landslides 15 houses, 15 Ropani agriculture land, Rs. 1,700,000 3 2042 6, Jatara Pakhre Landslide 2 Rpani agriculture land, Rs. 100,000 4 2043 7 Kharkhare Landslides Community forest area, Rs. 500,000 5 2045 5,1 and 4 Salleri Landslides 3 houses 2 Ropani agriculture land, one people and a Pakha, Bolam, buffalo, Rs. 30,000,000 Basi Danda Kofal Bot 6 2045 1, Thula Chaur Diarrhoea 2 people Ghanabot 7 2046 6, Pitibang Landslides 7 houses, Rs. 1,500,000 8 2047 5, Dharkalna Landslide 1 Ropani, Rs. 400,000 9 2049 7, Chisapni Flooded by 10 Ropani agriculture land, Rs 500,000 wetland 10 2051 7, Ghorneti Landslides, Agriculture land loss from 15 households Rs. 1,500,000 Floods 11 2053 1, Chakhal Danda Cloud Two buffalos, Rs. 20,000 lighting 12 2059 9, Lahu Kushum Landslides Two roomed school building, Rs. 700,000 13 2059 6, Sisneri Patala Fire 20 ha Forest Area and Water Supply Pipe Line, Rs. CF 1,200,000 14 2060 9, Dwang Landslide Sloping land and forest area, Rs. 35,000 15 2066 6, Khalchaur Fire 2 houses, water supply pipe line, and community forest area, Rs.1,000,000 16 2067 8,5 Dhagechhari, Landslide 15 Ropani agriculture land, Community Forest, Rs. Simalbot 2,000,000 17 2067 2,3 & 4 Sankh Flood 15 Ropani agriculture land (paddy field), Rs. 3,000,000 Khola 18 2068 5,6,7 & 8 Lahu Flood Agriculture land (paddy field), water mill, wooden river Khola crossing, Rs. 10,000,000 19 2068 7, Kalya Dhara Landslide Three roomed school building, three toilets of the school, sloping land, Rs. 1,400,000 20 2069 7,3 Swawang Windstorm Roof of a secondary school, a primary school and toilets. Lahu Rs. 700,000 2. Chokhabang VDC

SN Year Ward Disaster Type Loss Details 1 2069 Jestha, All wards Drought 400 households affected due to non-availability of water Ashadh on agricultural land 2 2069 Shrawan All wards Landslides 13 houses at high risk, Women Cooperative Building, Rs. 6,000,000 3 2068 Shrawan All wards Landslides 12 houses, 17 toilets, 3 km road, 15 water supply sources, distribution pipe lines, 200 ha sloping land and partial impact on 275 houses, Rs. 30,000,000 4 2068 Jestha All wards Windstorm 10 houses, loss on crops (20 ha), Rs. 7,600,000 5 2068 7 & 8 Snowstorm Potato farming (50 ha), Cauliflower, cabbage farming (60 ha), Rs. 3,000,000 6 2067 Falgun 4,5,6,7,9 Windstorm School buildings, house, forest area (10 ha), Rs. 500,000

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 7 Community Hazard Mapping

7 2066 All wards Droughts Agriculture production 8 2059 4 Fire 9 2044 Aswin 9 Flood Two people died, and a water mill 10 2043, Shrawan 9 Epidemic Five people died 11 2041, Baishakh All wards Drought 150 households affected 12 2054 5 Flood 5 houses 13 2067 Falgun 5 Cloud Lighting 1 house and 4 people injured 15 2039 6,7,8 & 9 Landslide Rs. 1,500,000 in public places 16 2040 All wards Droughts & Lost agriculture production in 200 ha hailstorm 17 2045 All wards Earthquake Landslides in forest area in ward number 5, 6, & 7 3. Chhibang VDC

SN Year Ward Disaster Type Loss Details 1 2028 3 & 1 Landslides 18 houses and agriculture lands, Rs. 3,000,000 2 2045 5,7 & 8 Landslides 7 houses, 11 water mills, 2 people died, Rs. 5,000,000 3 2047 9 Harale and Landslides 5 house and agriculture land, Rs. 2,000,000 Syale Geira 4 2047 4 & 9 Fire Entire forest area, Rs. 3,000,000 5 2049 6 & 7 Landslides 100 Ropani Agriculture land, Rs. 2,500,000 Shrawan 6 2056 2 Keura Pani and Landslides 7 houses, 13 water mills, 500 Ropani Valley Cultivation Bhadra Kaule Chaur Land, Rs. 5,000,000 7 2058, 6 Cloud lighting 2 houses, 4 buffalos, Rs. 500,000 Baishakh 8 2067, 2, 6 & 9 Epidemic 6 people died Shrawan 9 2067 8 & 9 Windstorm Roof of 1 school building, 11 houses and loss on agriculture production, Rs. 1,000,000 10 2067 8 Landslides 8 Ropani agriculture land, Rs. 500,000 11 2068 3,4 & 9 Windstorm Roof of a school building and 25 houses, loss on agriculture production, Rs, 2,000,000 12 2068 1,2,4,5, & 9 Flood Thousands of Ropani valley cultivation land 4. Khalanga VDC

SN Year Ward Disaster Type Loss Details 1 2059 9 Sisne Khola Landslides Loss of 20 Ropani agriculture land, and impact on 12 Bhadra households 2 2059 9, Sisne Khola Landslides 2 houses, 2 cattle sheds, 15 Ropani agriculture land, Aswin impact on 5 households 3 2039 9, Puran Danda Landslides 40 households at risk, 30 Ropani agriculture land Shrawan 4 2050 9, Kamerokhani & Landslides Loss of 2 houses and 50 Ropani agriculture land, risk at Shrawan Sisnekhola 40 households, 5 2068 1 Khalanga Bazar Landslides Two labours working on road near to the District Court Magh died 6 2067 2 Salle Landslides 2 water mills along Ghatte Khola 7 2067 2 Salle Landslides One house and a buffalo, Rs. 300,000 Ashadh 8 2056 2 Salle Landslides One house and a buffalo Bhadra 9 2055 All wards Hailstorm Loss of wheat production from the entire VDC, Rs. Baishakh 10,000,000 10 2060 All wards except Hailstorm Loss of wheat production, Rs. 5,000,000 Baishakh 5 & 6

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11 2063 1,2,3,4&7 Snowstorm Community Forest Area Magh 12 2054 4, Tharpu Digre Cloud lighting 1 buffalo and two goats 13 2042 1 Khalanga Cloud lighting 1 Buffalo Baishakh 14 2035 2 Salle Cloud lighting 1 buffalo Bhadra 15 2021 3, Seri Gaun Flood 1 people died and a water mill Jestha 16 2060 7, Thar Dhunga Landslides 60 Ropani Community Forest Area and 20 Ropani Shrawan Agriculture Land 17 2031 6 Dalkhet Basti Flood and 5 houses and 60 Ropani land Bhadra landslides 18 2058 6, Dhardhunga Flood and 15 Ropani valley cultivation land and irrigation canal Shrawan landslides 19 2031 6, Dhardhunga Landslides 30 Ropani valley cultivation land and paddy Bhadra 20 2042 6, Kharasar Basti Flash flood 4 houses, 50 Ropani maize and paddy field shrawan 21 2064 6, Solawang Landslides 4 houses along the main road, 5 Ropani land, police post Shrawan and cooperative buildings and another 30 Ropani land at risk 22 2032 6 Magare Khola Flash flood 2 school building, 1 house, 24 Ropani, 1 school building Shrawan Basti and market area at risk 23 2065 6 Khatri Dera Flash flood 3 houses, 9 Ropani Shrawan Solabang 24 2068 6, Bhalumare Flash flood Loss on 2 irrigation canal and forest area Shrawan gahira 25 2054 6 Dalkhet Fire 2 houses with their contents, Rs. 800,000 Jestha 26 2056 6 Solabang Fire 3 houses, Rs. 1,500,000 Baishakh 27 2062 6, Kotghar Fire 2 houses, Rs. 500,000 Falgun 28 2068 6 Kotghar Fire Roof of a house Chaitra 29 2057 6 Epidemic to Entire domestic animal affected Chaitra animal 30 2053 6 Epidemic Entire community affected 31 2064 5 Machhimi Landslides Mule trail 32 2067 5 Machhami Landslides Risk at Jan Hit Lower Secondary School Shrawan 33 2068 5 Machhimi Landslides Loss of irrigation canal in 1 km segment Bhadra 34 2068 9 Purandanda Landslides Loss of irrigation in 25 m segment Bhadra 35 2066 7, Tiya Khola Landslides 30 Ropani forest area in community forest and 7 Ropani valley cultivation land 36 2051 7, Tangtunge Fire 15 ha forest area in community forest area segment Jestha number 5 37 2055 7, Tangtunge Fire 15 ha forest area in community forest area segment Jetha number 3 38 2062 7, Tangtunge Flash flood 5 ha forest area 39 2052 7, Chisa Khola & Landslides 25 Ropani valley cultivation land Bhuri Khola

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 7 Community Hazard Mapping

40 2069 4, Degree Landslides Damage on temple, 3 houses and 30 Ropani valley Shrawan Saikumari temple cultivation land at high risk 41 2068 1 & 9 Windstorm Roof of Tribhuvan Janata Higher Secondary School and Baishakh Mahakali proposed secondary school 42 2069 All wards Windstorm Roof of 8 school buildings Jestha 5. Khara VDC

SN Year Ward Disaster Type Loss Details 1 2069 1,2,3,6,7 & 9 Hailstorm Loss of wheat, barley, mustard oil-seed, Rs. 2,000,000 2 2069 1,7 & 9 Windstorm Roof of a school building and 15 houses, Rs. 1,000,000 3 2068 1,2,3,4,5,6 & 7 Landslides 5 people died, 4 injured, 10 houses, 1 buffalo, 2 oxen, 5 toilets, Rs. 210,000,000 4 2068 1,2,3,4 & 5 Floods 1 ha valley cultivation land, Rs. 3,000,000 5 2067 1,2,3,4,7,8 & 9 Windstorm & 4 school buildings, 9 houses, 6 Ropani valley cultivation landslides land, 15 houses at high risk, Rs. 3,900,000 6 2066 1,3 & 9 Landslides 2 houses, 4 toilets, 4 goats, Rs. 1,000,000 7 2061 2,3,4 & 5 Landslides 1 ha land, Rs. 2,000,000 8 2052 1,2,4,7 & 9 Landslides 4 Ropani valley cultivation land, Rs. 500,000 9 2044 All wards Hailstorms Wheat production, Rs. 1,500,000 10 2043 2,8 & 9 Landslides 4 Ropani, Rs. 200,000 11 2063 3 & 7 Cloud lighting 2 buffalos, Rs. 100,000 6. Muru VDC

SN Year Ward Disaster Type Loss Details 1 2039 4, Rithyang Landslides 4 Ropani valley cultivation land, Rs. 200,000 2 2039 2,3 & 4 Sthani Landslide 20 Ropani valley cultivation, 3 ha national forest and 2 Pipal Muru Khola houses Rithyang 3 2039 3 & 5 Karagja Landslide 6 Ropani valley cultivation land, 2 ha forest area,7 water Khola, mills, Rs. 1,500,000 Melpokhari 4 2042 1,2,3,4 & 5 Muru 11 Ropani valley cultivation land, 7 water mills, Rs. Khola 1,200,000 5 2043 4, Rithyang Landslides 2 houses 6 2044 4, Rithyang Hailstorm 4,000 Muri cereal crops 7 2051 2,3 & 5 Cloud lighting 2 buffalos, 1 goat 8 2058 4 Rithyang Landslides 3 houses at risk 9 2067 6 Jila Flood 10 Ropani valley cultivation land and 20 Muri cereal crops 10 2068 All wards Landslides Playground of school buildings, 2 houses at risk 11 2068 1,2,3,4, & 5 Muru Flood 2 people died, 3 water mills and 7 Ropani agriculture Khola land, Rs. 1,400,000 12 2069 5,7 & 8 Windstorm Roof of higher secondary school, 1 solar panel, women community building’s roof. Rs. 400,000 7. Peugha VDC

SN Year Ward Disaster Loss Details Type 1 2030 All wards Drought Loss of agricultural production 2 2041 1,2, & 8 Salghari Flood 1 people died, 50 Ropani agricultural land, Rs. 10,000,000 3 2048 4 Maf Gaun Landslides 2 houses, 5 buffalos 4 2049 1,2,3,7 & 8, Pedikhet Flood Impact on land fertility

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 7 Community Hazard Mapping

5 2053 1 & 8 Mulpani & Landslides Loss of land, Rs. 500,000 Khoriya 6 2035 5 Gyangna Landslides 4 people died, 2 cows, 3 buffalos & 6 goats 7 2053 1,2,3,4,7 & 8 Flood Loss of valley cultivation, Rs. 200,000,000 8 2061 1, 3 Chautar, lampat Fire 4 houses, Rs. 400,000 9 2067 1,2,3,7 & 8 Chisapani, Flood 40 houses Chautar 10 2068 1 & 9 Hailstorms Cultivated land, Rs. 2,500,000 11 2068 5,8 & 9 Cloud 4 buffalo, 2 sheep, 5 goat, 1 solar panel lighting 12 2069 1,2,3,7 & 9 Windstorm Roof of 3 school building, 1 health post, and 17 houses 13 2069 1,2,3 & 6 Chisapani Flood 81 Ropani valley cultivation land, Rs. 810,000,000 14 2069 7 Gyangna Landslides 1 house 8. Rugha VDC

SN Year Ward Disaster Loss Details Type 1 2069 8 Flood Water mill Shrawan 2 2069 1,2,5,6 & 8 Landslides Loss cultivated land, forest area, water mill, micro- Shrawan hydropower project, Rs. 2,700,000 3 2069 Jestha 1,2,3,4,5,6,& 7 Windstorm Roof of school buildings and houses. Rs. 250,000 4 2069 Bhadra 2,4,5,6,7,8 & 9 Landslides 20 Ropani valley cultivation land, school’s playground, 3 houses, 2 toilets, Rs. 9,000,000 5 2069 Bhadra 1 & 2 Flood 1 wooden river crossing, 18 Ropani valley cultivation land, 1 water mill, 3 toilets (Rs. 5,500,000 6 2068 All wards Snowstorm Loss of wheat, potato, mustard oil-seed, maize, Rs. 8,000,000 7 2066 1 and 2 Flood 2 wooden river crossings, 5 Ropani valley cultivation land, Rs. 1,200,000 8 2065 4,5,7 & 9 Cloud 3 buffalos, 4 oxen, 1 solar panel lightening 9 2064 1,2,7 & 8 Flood 2 people and 2 oxen died 10 2059 2 Landslide 2 houses, Rs. 800,000 11 2047 5,6,8 & 9 Hailstorm Loss of horticulture 12 2041 1,2, & 7 Flood 1 people died, 4 water mills, 12 valley cultivation land, Rs. 140,000 13 2039 1,4,5,8 & 9 Landslides 1 cow sheds, 11 Ropani landslide, Rs. 700,000 14 2038 1,3,3,5 & 7 Fire 7 houses, loss of fore lands from Siddhakali, Salleri, ratamata Community Forest

7.3 Seasonal Calander The seasonal calendar contains a lot of information about seasonal changes and related hazards, diseases, community events and other information related to specific months of the year. Using ten stones (ten being the highest score) indicates degree, severity or extent of the change. Main objective of preparing seasonal calander is to learn about seasonal activities, hazards and disasters. Seasonal calander was prepared mobilizing the local community in the project area. For each VDCs, local communities themselves prepare the seasonal calander for various hazards that they have identified and faced to.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 7 Community Hazard Mapping

Figure 7-2: Community Preparing Seasonal Calander

Communities have prepared seasonal calanders for landslides, flood, fire, thunderbolt, earthquake, hailstorm, drought, windstorm, agriculture diseases, snow fall, wild animal attack and epidemics. The results of preparing seasonal calander are presented Table 7-2.

Table 7-2: Seasonal Calanders Prepared by the Communities

A: Bhalakcha VDC

Hazards Baishakh Jestha Ashadh Shrawan Bhadra Aswin Kartik Marg Poush Magh Falgun Chaitra Ladslides Flood Fire Thunderbolt Earthquake Hailstorm Drougth Windstorm Agriculture Disease Epidemics

B: Choukhabang VDC

Hazards Baishakh Jestha Ashadh Shrawan Bhadra Aswin Kartik Marg Poush Magh Falgun Chaitra Landslides

Flood

Agriculture Disease

Windstorm

Fire

Hailstorm

Snowfall

Thunderbolt

Earthquake

Epidemic

Drought

C: Chhibang VDC

Hazards Baishakh Jestha Ashadh Shrawan Bhadra Aswin Kartik Marg Poush Magh Falgun Chaitra Landslide

Flood

Thunderbolt

Fire

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Epidemic

Winderstorm

Hailstorm

Earthquake

Agriculture disease

Wild Animal

D: Musikot Khalanga VDC

Hazards Baishakh Jestha Ashadh Shrawan Bhadra Aswin Kartik Marg Poush Magh Falgun Chaitra Landslides

Windestorm

Flood

Thunderbolt

Epidemic

Fire

earthquake

Hailstorm

Agriculture Disease

Wild Animal

E: Musikot Khalanga VDC

Hazards Baishakh Jestha Ashadh Shrawan Bhadra Aswin Kartik Marg Poush Magh Falgun Chaitra Landslides

af9L Flood

Windstorm

Fire

Thunderbolt

Epidemic

Snowfall

v8]/L Drought

Vehicle Accident

Hailstorm

Agriculture Disease

F: Muru VDC

Hazards Baishakh Jestha Ashadh Shrawan Bhadra Aswin Kartik Marg Poush Magh Falgun Chaitra Landslide

Flood

Drought

Epidemic

Windstorm

Thunderbolt

Fire

Agriculture Diese

Hailstorm

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 7 Community Hazard Mapping

G: Peugha VDC

Hazards Baishakh Jestha Ashadh Shrawan Bhadra Aswin Kartik Marg Poush Magh Falgun Chaitra Landslides

Flood

Drought

Epidemic

Windstorm

Thunderbolt

Fire

Agriculture Disease

Hailstorm

H: Rugha VDC

Hazards Baishakh Jestha Ashadh Shrawan Bhadra Aswin Kartik Marg Poush Magh Falgun Chaitra Landslides

Flood

Fire

Windstorm

Thunderbolt

Earthquake

Epidemic

Hailstrom

Drought

Agriculture Dieses Snow fall

7.4 Hazard Mapping and Ranking Community members know the hazards that confront their communities. For their sake alone, they do not have to draw the hazard map. Hazard maps are made for the benefit of “outsiders” like NGO workers. But hazard and resource mapping is a tool that allows community members to identify graphically the vulnerable members of the community especially the elderly and disabled who are put at risk by hazards like floods. This tool also enables community members to look at their resource base and make an inventory of their capacities. Communities of the project area were involved in preparing hazard map of the watershed (Figure 7-3). The objectives of the community hazard mapping were . To identify areas at risk from specific hazards and the vulnerable members of the community . To identify available resources that could be used by community members in disaster risk management.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 7 Community Hazard Mapping

Figure 7-3: Community Hazard Mapping of Muglu Khola Watershed

It is possible to rank hazards on a simple graph that plots magnitude of impact on an individual or community against the probability and frequency of a specific hazard occurring. Risk is high where an event has a high magnitude of impact and a high probability of occurring in a short time span. In the flooding example used above, it can be deduced that the most probable flooding is that of the twice yearly ‘not severe’ type, but this has a very low impact. The type of flooding that has the most impact is the ‘very severe’ that occurs every fifteen years or so, and which has a low probability of occurring. The ‘severe’ flooding that occurs every two years or so and has a fairly high probability and has a medium high impact.

Figure 7-4: Hazard Ranking by Community

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 7 Community Hazard Mapping

Based on the hazard mapping and ranking by members of the Muglu Khola Watershed, hazard and ranking has been prepared for each VDC of the watershed. The hazard map was prepared on VDC's base map.

Figure 7-5: Community Hazard Mapping and Ranking of Bhalakcha VDC

Figure 7-6: Community Hazard Mapping and Ranking of Bhalakcha VDC

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 7 Community Hazard Mapping

Figure 7-7: Community Hazard Mapping and Ranking of Chhibang VDC

Figure 7-8: Community Hazard Mapping and Ranking of Khalanga Musikot VDC

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 7 Community Hazard Mapping

Figure 7-9: Community Hazard Mapping and Ranking of Khara VDC

Figure 7-10: Community Hazard Mapping and Ranking of Muru VDC

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 7 Community Hazard Mapping

Figure 7-11: Community Hazard Mapping and Ranking of Peugha VDC

Figure 7-12:Community Hazard Mapping and Ranking of Peugha VDC

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 8 Vulnerability Risk Assessment

Chapter 8 Vulnerability Risk Assessment

8.1 General Vulnerability assessment is the analysis of factors that determine vulnerability and identification of specific stakeholders to reduce that vulnerability. The analysis includes the identification of system at risk and of the root causes behind it. Under these definitions, vulnerability assessment provides information about options of adaption to decision makers in taking actions for disaster reduction. The decision making can be at individual, community, national and international levels. Vulnerability assessment may play an important initial role in DRM of developing countries like Nepal where both technological and financial capabilities are limited. The application of multi-dimensional vulnerability assessments has shown that human vulnerability to environmental factors is compounded by a broad range of issues, including demographic pressure, declining ecosystems, poverty, conflicts and vulnerable rural livelihoods. In this context, climate change is best understood as exacerbating these underlying structural factors of vulnerability. A vulnerability assessment includes those elements of an area that relate to the status of the community in question. These elements are categorised and divided into health, social, economic and environmental indicators to adequately illustrate the degree of vulnerability in a given area. In vulnerability assessment, generally following aspects are considered: physical vulnerability and social vulnerability. Physical vulnerability can be defined as a condition resulting from physical factors and processes that increase the susceptibility of a community to the impact of a hazard. In this study, only buildings and agricultural assets in Muglu Khola Watershed have been considered due to limited data on other important assets. Assessment of physical vulnerability and risk has been carried out for flood, landslide and multiple hazards for all inhabited areas in the watershed. Social Vulnerability on the other hand is defined as a condition resulting from social factors or processes, which increases the susceptibility of a community to the impact of a hazard. Social vulnerability refers to the inability of people, organizations and societies to withstand adverse impacts from multiple stressors to which they are exposed. Often the social factors in question are directly linked to physical or economic factors, and may need to take these into consideration as secondary factors or indicators. Social vulnerability in the Muglu Khola Watershed is a result of the low economic condition, poor public awareness and weak institutional setup and strength.

8.2 Methodology This section deals with the methodology adopted for preparing both physical and social vulnerability. To prepare physical vulnerability map, first a landslide hazard map was prepared as discussed in Chapter 5. Since wards are considered as the unit of analysis, the ward-wise landslide hazard map was prepared by classifying the percentage of area of high landslide hazard zone of the wards. The flood hazard zone was delineated based on the criteria of distance from the river and slope of the river banks and flood plain. It is the area that lies within 300 m from the river and slope equal to or less than 10 ° using GIS. These flood zones were also verified in the field visits.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 8 Vulnerability Risk Assessment

8.2.1 Physical Vulnerability Four exposure indicators have been selected as physical vulnerability measures for each ward. These include: (a) total population, (b) total household number, (c) total agriculture land and (d) total (major road length. Each of these parameters was rated and total score for each ward was obtained by adding the ratings in these four exposures and multiplied by hazard frequency. The data used for this assessment is summarized in Table 8-1.

Table 8-1: Data Acquired from Primary and Secondary Sources

Parameter Database Source

Demographic/socio-economic Population/socio-economic . District Profile, Village Profiles indicators at ward level, district level . Field Survey

Damage by floods and landslides Loss of lives and properties . DDRC Rukum, . Nepal Red Cross, Rukum . Field Survey

Landslide/Flood Hazard/disaster locations . Field Mapping . Modelling in GIS . Historical Timeline

People’s perception . Field Survey/interaction with people

8.2.2 Social Vulnerability The Social Vulnerability is a function of adaptive capacity of the society in a certain physically vulnerable zone. Adaptive capacity is a function of social and economic processes. The Pressure And Release (PAR) Model of risk is used for assessing social vulnerability and PAR model of risk defines how the unsafe condition arises due to varying economic, political and institutional process and societal attitudes. Development of new settlements along the roads for economic growth is one good example of the processes that increase vulnerability to rainfall induced landslides. Similarly, case studies on flood hazard in two river basins in Nepal have shown that the areas with access to communication, institutions, banks, market and diversified income sources have stronger adaptive capacity than the one without these facilities. Moreover, the adaptive capacity may either be quantitative or qualitative. The selected quantitative and qualitative adaptive capacity indicators are listed in Table 8-2 and Table 8-3 respectively. These indicators are selected based on availability of data on the suggested list of adaptive capacity indicators. The data on quantitative indicators are at ward level and the quantitative indicators were rated and the rates are combined to get the final score of social vulnerability. The indicators that are not possible to quantify are subjectively analysed. Finally, the total vulnerability for landslide and flood were obtained by combining the ratings of corresponding physical vulnerability map with social vulnerability map.

Table 8-2: Quantitative Indicators

SN Parameters Adaptive Capacity Indicators 1 Accessibility Road Density (total road length/ward area) in m/km2 2 Health Number of health institution/1000 population 3 Communication Number of telephones/1000 population

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 8 Vulnerability Risk Assessment

4 Government Institutions Number of Government’s Institution/1000 population 5 NGO Number of NGO/1000 population 6 Economic Number of financial institution/1000 population 7 Loss sharing measures Amount of revolving fund 8 Economic diversity Percentage of families with number of types of income source

Table 8-3: Qualitative Indicators

SN Qualitative Indicators 1 Emergency facilities 2 Warning system 3 Loss reduction measures 4 Awareness and attitude 5 Income generating activities

8.2.3 Perception on Disaster and Vulnerability Reducing Measures Since the degree of vulnerability to disaster is also determined by human behaviour towards a disaster, it is very essential to incorporate people’s perception. In the past disaster management in Nepal, there was a lack of an idea as to how local people perceive disasters. People in the society are of different solidarities. Therefore, the varying response/attitude is very much crucial in understanding how people are going to consider the adaption measures to disaster. To obtain the perceptions, open-ended and semi –structured questionnaires were used during the interviews with key informants. Few interviews were also conducted to obtain oral history and memory story of the disaster events. The interviews were conducted with three kinds of informants: the local people (victims and non-victims), policy makers (government organizations) and NGOs and private organizations using three kinds of questionnaires. The analysis focused on the disjunction between people’s and policy maker’s views on disaster and on possible measures for reducing vulnerability.

8.2.4 Field Visits A series of field visit was conducted in all VDCs and wards of the Muglu Khola Watershed. The major aims of the field visits were: (a) to acquire primary data on landslide and flood and to collect those socio-economic data which are not available from secondary sources (b) to verify the data acquired from secondary sources and (c) to conduct interviews for people’s perception. The interviews in the Muglu Khola Watershed were made with the local people (victims and non- victims) and with the local organizations. The questionnaires were focused on obtaining the information and perception on: . Causes of water induced disasters . Existing and potential informal and formal loss transferring and sharing measures . Structural and non-structural preventive measures . Responsibilities in loss-reducing measures

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 8 Vulnerability Risk Assessment

8.2.5 Secondary Data The data required for the study were also obtained from various secondary sources. Different data layers used in this study and their sources are listed in Table 8-1. The other set of data, basically socio-economic and damage data, were acquired from both field visits and secondary sources.

8.3 Community-based Vulnerability Risk Assessment An extensive field survey was conducted in the Muglu Khola Watershed VDCs and local communities were interacted to prepare a vulnerability and risk assessment of the watershed (Figure 8-1). Involving the communities in the preparation of the vulnerability assessment can improve the assessment’s effectiveness and ensure that the assessment is relevant to those who are the most at risk. Also, meaningful community involvement helps improve awareness about the risks posed by certain hazards and motivate community members and organizations to take steps to be become more prepared. The community-based vulnerability assessment helps communities understand the social and cultural context within which a disaster occurs and build on local resources and knowledge about disasters and their impact. Finally, the vulnerability assessment describes and illustrates the community to prepare maps of vulnerable areas, identify vulnerable facilities, estimate the number of people at risk and identify key people to contact during an emergency. Community-based vulnerability assessment is primarily based on the poverty of the households, physical facilities available in the area and physical condition of the houses.

Figure 8-1: Community Participation in Vulnerability Risk Assessment

As depicted in Table 8-4, about 107 human settlements of the area are at risk to disaster; total number of vulnerable households has been estimated to be 324 which accounts to about 14% of the total households of the area. Among these vulnerable communities, Rithyang of Muru 2 and Thuli

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 8 Vulnerability Risk Assessment

Khoriya of Khara 4, Khumcheri, Saune Pani and Khadka Tol of Khara 6, Dhawa Khola of Bhalakcha 5, Ghor Neti of Bhalakcha 7, Sangini Gaura of Chaukhabang 4 and Mathillo Tol of Chaukhabang 8 are identified as the most vulnerable communities in the areas. In these communities, more than 50% of households are vulnerable.

Table 8-4: Risk Assessment of the Muglu Khola Watershed

SN VDC Most Ward Settlement Settlement Total Vulnerable Loss of last Community vulnerable Number households households year Forest (CF) village

1 Muru Rithyan 4 Rithyan 5 39 8 Landslide Jhakri Pani damaged 3 CF Kural 32 2 houses and agricultural Ghoralekot 10 2 land

Dhankamd 3 1

Jhakripani 6 1

2 Kharneta 5 Kharneta 8 8 3 Loss of Dim Khola agriculture CF Jathabang 10 2 land

Khar Chaur 9

Chaukhi 3 Dhunga

Lachhi Kot 40

Jala Thana 3

Chota Bari 6

Daha Chaur 3

3 Purnapani, 6 Rautebar 11 32 2 Loss of Sir Chaur Patala agriculture CF, Pang Bhurtibang 26 2 production Rang CF due to Bardhanau 17 1 landslide

Pangrang 8 2

Janabang 9

Nayabasti 13 2

Kaulachaur 10 1

Timkhaur 12

Purnapani 9 4

Patala 9 3

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 8 Vulnerability Risk Assessment

Hiukhola 7

4 Khara Salli Danda, 2 Salli Danda 10 25 3 5 person Suki Daha Thuli Khorya died, and 2 CF, Majhau Thuli 12 5 houses lost Gaura CF, Khoriya Jhakrimul CF Ollo 32 3 Hangbang

Pallo 28 4 Hangbang

Daya 10 5

Junge Pani 8 2

Ragu Mare 5 2

Jyamire 35

Dawang 11

Rangchepu 10 3

5 Pokhari 5 Pokhari 4 30 3 2 houses Bagh Khor flooded CF Kalimati 32

Purna Khara 25

Balidera 16

6 Damdu, 6 Damdu 8 39 2 houses Salli Danda Salleri and CF, Batheni Khumcheri 47 10 agricultural CF land swept Saune Pani 15 9

Musiya 6 Pakha

Gaun Tol 12

Khadak Tol 16 8

Sau Ghar 7 Tol

Danda Gaun 5 Tol

7 Liredanda, 3 Tallo 5 12 3 Loss of Bagh Khor Mathillo Hampal agriculture CF and Hampal production Karateni CF Mathillo 3 2 due to flood Hampal

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 8 Vulnerability Risk Assessment

Dar Kanle 15 7

Lire Danda 5 2

Kural 25 5

8 Chhibang Ram Khola. 2 Kaule Chaur 4 115 35 Loss in Okhar Patal Kaule Chaur wheat and CF Rage Khola Jhum vegetable Phalame Phalame production Dunga Likhe Dhunga due to due Danda to hailstorm Likhe Danda and cow shed due to fire

9 Bhaljula 3 Bhaljula 3 120 5 Agricultural Patal CF Khopikhelne land swept Jyamadanda Khopikhelne due to flood

Jyamadanda

10 Sadan 1 Chautara 1 125 4 Valley Chaur cultivation swept

12 Peugha Tallo Kharka 9 Tallo Kharka 3 99 2 Loss of Salghari CF wheat Todke Todake production Daman Daman due to Pakha Pakha hailstorm, land due to Sal Ghari Sal Ghari landslides

13 Basnet Tol 4 Majh Gaun 2 65 12 Loss of land Melgairi CF and house Juge Pani due to landslides

14 Thandara 8 Thandara 2 111 19 Loss of Thula Bhir Rajkhet wheat CF Rajkhet production due to hailstorm, land due to landslides

15 Khahare 3 Chautara 1 95 8 Loss of land Melgairi CF and agriculture

16 Peugha 7 Lulungna 2 111 11 Loss of land Gurgure CF Danda and Peugha agriculture Danda

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17 Mathi Gaun 5 Mathi Gaun 1 85 12 Loss of land Jurepani CF and house due to landslides

18 Armali Tol 6 Peugha 1 86 9 Loss of land Deupanna and house CF due to landslides

19 Bhalkcha Lahu Khola 7 Jamuwaban 6 50 6 Loss of land Panlo Patal Pipal Tara g CF, Pangar Khola CF Dhawa 8 4 Khola

Bugeri 20

Pangar 13

Simal Bot 8 2

Kauche 13

20 Ghor Neti 5 Ghor Neti 7 13 6 Loss of land Kharkhare due to CF Palne Khola 15 landslides

Bhagbhage 15 4

Kukribang 23 2

Jugena 16

Morabang 17

Godbang 24

21 Koche 1 Ghanabot 6 10 2 Loss of land Bheri Patal Ghanabot due to CF landslides Koche 21

Rampacha 18

Rithabot 14 2

Kaulachaur 17

Bolamkhal 23 2 Chaur

22 Sibhri, Khani 8 Khani Khola 5 8 1 Loss of land Bheri Patal Khola Lam due to CF Danda Sibhri 35 3 landslides

Ghati Gaura 13

Chhot 12

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 8 Vulnerability Risk Assessment

Danda

Lam Danda 11 1

23 Khalanga Solabang 6 Solabang Loss of land area due to both landslide and flood

24 Rungha Simrutu 2 Simrutu School and Bazar area bazaar area are at high risk due to flood and community people are also in high risk of Landslide

25 Chokhabang Danda Tol, 4 Danda Tol 4 12 5 Loss of 2 Badalekanla Tallo Tol, houses, 2 CF, Lali Mathillo Tallo Tol 18 3 toilets and Gurans CF Tol, Hol land due to Tara Hol Tara 10 4 landslides

Mathillo Tol 20 10

26 Jhad Dari, 6 Jharunga 3 6 3 Loss of land Mauari CF, Jharanga, due to Sindure Khadka Tol Khadka Tol 40 6 landslides Hariyali CF

Jhad Dari 14 8

27 Sangini 8 Khurpani 5 25 1 Loss of land Shreejansil Gaira, Del due to CF Dara, Sangini 8 8 landslides Khurpani Gaura

Del Danda 25 5

Bheri Khola 35 3

Chaur 40 4

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 9 Watershed Management Plan

Chapter 9 Watershed Management Plan

9.1 Introduction Land-use planning provides a set of useful planning tools for DRR into community development processes, such as mapping, zoning and participatory planning. It is important because the location of settlements and infrastructure is a key vulnerability factor. Land-use plans lay down regulations and guidelines for future developments, and can set controls on the expansion of existing settlements and infrastructure in disaster prone areas. Land-use plans can also provide details on any adjustments in land-use and building techniques required to enhance public safety, without depriving communities’ access to resources and opportunities. The main purpose of the land-use planning is to provide regulations for development of a particular area to serve the desired purpose efficiently and to preserve its character. It also provides for the kind of buildings to be constructed. Zoning regulations are legal tools for guiding the use of land and protection of public health, welfare and safety. Such regulations also include provisions for the use of premises/property and limitations upon shape, size and type of buildings that are constructed or occupy the land. Further, these provide both horizontal as well as vertical use of land. These regulations also improve the quality of life at a community level. For instance in flood zones, the land use may be parks, playground and gardens while restricting any building activity in such vulnerable areas. Similarly, along the drains green belts can be planned which may facilitate improvements of these drains in future. Life line structures should also be protected likewise while either proposing land uses or otherwise. In order to promote a healthy and balanced development, it is necessary to apply reasonable limitations on use of lands and buildings. For desirable development, an area is divided into a number of ‘use zones’ such as residential, commercial, industrial, recreational, etc. For each zone, specific regulations are provided for. A single set of regulations cannot be applied for the whole area. Risk-sensitive land-use planning is informed by an assessment of risks including hazards and vulnerability. Risks can be mapped throughout a community, village, city or nation to show the zones with different levels of risk. If risk maps are overlaid on land-use maps, patterns of land-use can be correlated with susceptibility to disasters.

9.2 Guiding Principle to Watershed Management Plan A watershed has basically four elements: hydrologic cycle, the biotic community, human activities and the land itself. These elements are connected through a complex web of relationships. Changes in one part affect the health and function of the whole watershed. The more we understand about watershed function and relationships, the better we will be able to protect natural processes. Sound management choices need to be based on up-to-date, interdisciplinary science coupled with on-going assessment. Monitoring is vital to understanding and continually improving the success of management and restoration actions. Monitoring also allows us to observe and document trends in the health of our watersheds over time.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 9 Watershed Management Plan

About 40% of the Muglu Khola Watershed is in private ownership. The leadership and committed participation of the people who live and work in the watershed is essential for effective planning, restoration, and on-going management. Watershed management requires a vast range of skills, from community organizing to designing various development programs. Interagency coordination and partnerships with local watershed residents bring multiple perspectives and durability into watershed efforts. Education builds enduring connections between people of all ages and their watersheds. Being able to see ourselves as much a part of our local ecosystems as live oaks or salmon provides a deep and compelling sense of stewardship. Zoning, land protection programs, and land use policies can help protect natural resources and balance human needs with healthy watersheds. Restoration can extend, connect, and enhance natural habitats.

9.3 Legal and Administrative Framework Concept of Watershed Management Plan in Nepal started from the Fourth Five Years National Plan (1970-1975) aiming to focus on Churia Conservation because Churia range is geologically very fragile leading to triggering various disasters. However, in the initial days of the plan, more concentrations were made on implementation of physical structures and a forestation in watershed conservation. Department of Soil Conservation and Watershed Management (DSCWM) was established in 1974 as a leading government agency to implement soil conservation and watershed management activities in Nepal. To resolve the degradation of watershed, the Department of Soil Conservation and Watershed Management (DSCWM) was established and since then it is continuously working in conservation and sustainability of watersheds. The Department is also responsible for executing various government’s program at the field level. It is also to formulate and publish guidelines, policies, manual and handbook with regard to watershed management. Integrated Watershed Management in Sub-watersheds has now been lunched by the GoN since Ninth Five Year Plan. The Tenth Five Year Plan focuses on Agriculture Perspective Plan with the emphasis on conservation of mountain and promotion of community participation in conservation. The Tenth Five Year Plan prioritized on afforestation and soil conservation programs in mountain watershed aiming to minimize loss of lives and properties due to natural disasters such as landslides, flood, GLOF etc. The Interim Plan focuses on forest’s role on climate change. All Periodic Plans thus focus on watershed management, and biodiversity basically experiencing previous spatio-temporal land degradation in hilly and mountainous regions.

9.4 Watershed Management Efforts in Rukum District Soil Conservation Office, Rukum has been implementing various activities in the Rukum district as an effort of Integrated Watershed Management in the district. In this approach each district is divided into a number of functional sub-watersheds of 15-25 km2 that are prioritized on critical basis. There are 56 sub-watershed delineated in the district (Figure 9-1). Since there are many sub-watersheds in the district, it is difficult to address all issues on soil conservation and watershed management in the district due to limited financial and human resources. Therefore, sub-

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 9 Watershed Management Plan watersheds are prioritized according to vulnerability and necessity and accordingly activities are to be undertaken with optimal use of available resources.

Figure 9-1: Sub-watershed Delineation in Rukum (Source: Priority Ranking of Sub-Watershed in Rukum)

DSCO Rukum has prepared Land Use Erosion Potential (LEUP) by marking high, moderate and low erosion potential areas based on land-use on the 1:50,000 scale LRMP 1984. In view of varying degrees of soil erosion in different watersheds lying in different topographical and ecological zones, it is expedient to classify the watersheds in a district into three classes such as, high, medium and low, in order of severity of erosion condition. Classification criteria are based on Sub watershed prioritization guidelines developed by the DSCWM. In this study, our project area mostly falls in the moderate erosion potential area.

Figure 9-2: Land-use Erosion Potential map (Source: Priority Ranking of Sub-Watershed in Rukum)

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 9 Watershed Management Plan

Sub-watersheds in the districts were then prioritized based on the erosion potential map and the population in the sub-watershed which was referred to as sub-watershed priority cumulative value. In this study, Musikot Khalanga is the first priority and Ranmamaikot under Dhorpatan Hunting Reserve is ranked as 56. In the ranking, Muglu Khola Watershed falls in highly prioritized zone (Chibang = 1, Peugha = 2, Muru = 4, Rugha = 6, Chaukhabang, Khara and Musikot = 10, Bhalakcha = 16) in terms of the sub-watershed priority cumulative value. This indicates that proper Watershed Management Plan needs to be implemented in the area.

Figure 9-3: Priority Ranking of the Sub-watersheds in Rukum (Source: Priority Ranking of Sub- Watershed in Rukum)

DSCO has been implementing various watershed management activities in the in the district. The activities basically include nursery establishment, supporting community in implementing structural and non-structural (bio-engineering) measures as river training and landslide protection works. 9.5 Existing Land-use Pattern As depicted in Table 9-1, a recent remote sensing image made available from the FRA has identified 9 land-use classifications in the Muglu Khola Watershed. These include Conifer Forest, Grazing Land, Hard Wood Forest, Lake, Level Terrace, River, Rock Outcrop, Shrub Land, Sloping Terrace and Valley Cultivation. This classification reveals that major portion of the land is occupied by sloping terrace (42.40%) being used for agricultural production. Hard Wood Forest Area and Conifer Forest Area also account to significant amount of land covering about 25.60% and 12.80% of the total watershed’s area.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 9 Watershed Management Plan

Figure 9-4: Existing Land-use Pattern in the Muglu Khola Watershed

Figure 9-5: Current Land-use Pattern in and around Muskot Khalanga

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 9 Watershed Management Plan

Table 9-1 presents ward-wise land-use distribution in the watershed VDCs. Chaukhabang contains largest hardwood forest area; about 55.6% of the VDC’s total land is occupied by the hardwood forest. Khara (43.18% of Khara’s Area), Rugha (38.57% of Rugha’s total area) also contain significant portion of Hardwood Forest. Musikot (6.21% of its area) and Chibang (1.53% of Chibang’s total area) have significantly lower portion of hardwood forest. Although Peugha and Bhalakcha have lower hardwood forest, they are supplemented by Conifer Forest; Confier Forest in Peugha and Bhalakcha are 40.58 % of Peugha’s area and 34.53% Bhalakcha’s area respectively.

Table 9-1: Existing Land-use Distribution in the Project Area VDCs

Muru Ward Area km2 Hard Conifer Grazing Level Rock Shrub Sloping Valley Wood Lake River Forest Land Terrace outcrop land terrace cultivation Forest 1 0.073 0.205 0.000 0.000 0.376 0.000 0.000 0.601 0.378 0.000 2 0.227 0.622 0.000 0.0010 0.455 0.000 0.000 0.142 0.372 0.000 3 1.161 0.017 0.000 0.000 0.000 0.024 0.000 0.000 0.864 0.000 4 0.173 0.000 0.180 0.000 0.004 0.007 0.000 0.000 1.247 0.000 5 0.209 0.330 0.739 0.000 0.000 0.022 0.000 0.000 0.903 0.000 6 0.040 0.006 1.259 0.000 0.000 0.055 0.000 0.000 2.158 0.046 7 0.310 0.470 0.000 0.000 0.014 0.000 0.000 0.000 0.779 0.000 8 0.709 0.021 0.000 0.000 0.000 0.000 0.000 0.000 0.850 0.000 9 0.194 0.053 0.017 0.000 0.000 0.000 0.000 0.673 1.032 0.000 Total 3.096 1.724 2.195 0.0010 0.849 0.108 0.000 1.416 8.583 0.046

Rugha Area km2 Hard Ward Conifer Grazing Level Rock Shrub Sloping Valley Wood Lake River Forest Land Terrace outcrop land terrace cultivation Forest 1 0.000 0.073 0.970 0.000 0.000 0.057 0.000 0.000 0.869 0.000 2 0.129 0.292 0.077 0.000 0.691 0.048 0.000 0.000 0.052 0.000 3 0.000 0.202 0.000 0.000 0.230 0.000 0.000 0.000 0.000 0.000 4 0.203 0.546 0.048 0.000 0.071 0.000 0.000 0.000 0.927 0.000 5 0.052 0.620 0.693 0.000 0.000 0.000 0.000 0.000 1.829 0.000 6 0.381 0.056 1.213 0.000 0.000 0.001 0.000 0.000 0.590 0.000 7 0.000 0.128 0.975 0.000 0.000 0.002 0.000 0.000 1.125 0.000 8 1.328 0.000 0.731 0.000 0.000 0.031 0.000 0.000 0.419 0.000 9 0.070 0.000 2.720 0.000 0.000 0.017 0.000 0.000 0.788 0.000 Total 2.163 1.917 7.427 0.000 0.992 0.156 0.000 0.000 6.599 0.000

Khara Area km2 Hard Ward Conifer Grazing Level Rock Shrub Sloping Valley Wood Lake River Forest Land Terrace outcrop land terrace cultivation Forest 1 0.156 0.449 0.000 0.000 0.000 0.033 0.000 0.000 2.261 0.000 2 0.000 0.195 3.541 0.000 0.000 0.000 0.000 0.000 1.300 0.000 3 0.000 0.097 0.964 0.000 0.000 0.000 0.000 0.000 0.285 0.000 4 0.000 0.157 0.000 0.000 0.000 0.046 0.000 0.000 1.734 0.000

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 9 Watershed Management Plan

5 0.000 0.000 1.127 0.000 0.000 0.000 0.000 0.000 1.299 0.000 6 0.000 0.000 1.856 0.000 0.000 0.000 0.000 0.000 1.121 0.000 7 0.000 0.007 0.859 0.000 0.022 0.054 0.000 0.000 2.133 0.000 8 0.000 0.030 1.801 0.000 0.000 0.001 0.000 0.000 1.758 0.000 9 0.000 0.844 1.973 0.000 0.000 0.008 0.000 0.000 1.963 0.000 Total 0.156 1.779 12.121 0.000 0.022 0.142 0.000 0.000 13.854 0.000

Chhibang

Area km2 Hard Ward Conifer Grazing Level Rock Shrub Sloping Valley Wood Lake River Forest Land Terrace outcrop land terrace cultivation Forest 1 0.000 0.000 0.000 0.000 0.096 0.025 0.000 0.000 0.000 0.336 2 0.000 0.312 0.000 0.000 0.548 0.077 0.000 0.000 0.548 0.206 3 0.000 0.753 0.000 0.000 0.195 0.000 0.000 0.000 0.004 0.000 4 0.000 0.870 0.000 0.000 0.004 0.047 0.000 0.000 1.194 0.035 5 0.000 0.006 0.000 0.000 0.000 0.000 0.000 0.000 0.057 0.000 6 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 7 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 8 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 9 0.000 0.536 0.113 0.000 0.043 0.034 0.000 0.000 1.355 0.000 Total 0.000 2.477 0.113 0.000 0.886 0.183 0.000 0.000 3.158 0.577

Peugha Area km2 Hard Ward Conifer Grazing Level Rock Shrub Sloping Valley Wood Lake River Forest Land Terrace outcrop land terrace cultivation Forest 1 1.304 0.000 0.000 0.000 0.000 0.007 0.000 0.000 0.460 0.116 2 1.008 0.100 0.000 0.000 0.000 0.007 0.000 0.000 1.015 0.088 3 1.109 0.086 0.000 0.000 0.000 0.000 0.000 0.000 0.341 0.184 4 0.832 0.018 0.000 0.000 0.000 0.000 0.000 0.000 0.509 0.000 5 0.493 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.980 0.000 6 0.341 0.000 0.000 0.000 0.000 0.030 0.000 0.000 0.989 0.065 7 0.455 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.764 0.000 8 0.450 0.000 0.157 0.000 0.000 0.028 0.000 0.000 1.269 0.465 9 0.193 0.000 0.059 0.000 0.000 0.007 0.000 0.000 1.313 0.000 Total 6.185 0.204 0.216 0.000 0.000 0.079 0.000 0.000 7.640 0.918

Bhalakcha Area km2 Hard Ward Conifer Grazing Level Rock Shrub Sloping Valley Wood Lake River Forest Land Terrace outcrop land terrace cultivation Forest 1 0.022 0.299 0.806 0.000 0.000 0.000 0.000 0.000 1.053 0.000 2 0.788 0.000 0.119 0.000 0.000 0.015 0.000 0.000 0.699 0.068 3 1.078 0.000 0.488 0.000 0.000 0.008 0.000 0.000 0.440 0.065 4 0.901 0.001 0.006 0.000 0.000 0.055 0.004 0.000 0.544 0.348 5 0.047 0.107 0.249 0.000 0.501 0.059 0.000 0.000 0.252 0.000

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 9 Watershed Management Plan

6 0.159 0.044 0.353 0.000 0.209 0.017 0.000 0.098 0.592 0.000 7 0.539 0.074 0.209 0.000 0.074 0.067 0.000 0.404 1.104 0.000 8 1.710 0.209 0.000 0.000 0.148 0.017 0.000 0.037 0.780 0.000 9 0.979 0.000 0.109 0.000 0.000 0.000 0.000 0.000 1.069 0.000 Total 6.223 0.734 2.339 0.000 0.932 0.238 0.004 0.539 6.533 0.481

Chaukhabang Area km2 Hard Ward Conifer Grazing Level Rock Shrub Sloping Valley Wood Lake River Forest Land Terrace outcrop land terrace cultivation Forest 1 0.000 0.000 0.868 0.000 0.000 0.000 0.000 0.000 0.839 0.000 2 0.000 0.000 0.086 0.000 0.000 0.004 0.000 0.000 0.330 0.000 3 0.013 0.000 0.139 0.000 0.000 0.004 0.000 0.000 0.139 0.000 4 0.000 0.108 1.727 0.000 0.000 0.013 0.000 0.000 0.853 0.000 5 0.297 0.441 1.162 0.000 0.000 0.050 0.090 0.000 1.424 0.000 6 0.000 0.000 2.081 0.000 0.103 0.020 0.000 0.000 0.212 0.000 7 0.000 0.363 0.311 0.000 0.007 0.025 0.145 0.000 0.788 0.000 8 0.000 0.084 2.127 0.000 0.000 0.000 0.000 0.000 1.100 0.000 9 0.000 0.396 2.430 0.000 0.446 0.000 0.000 0.189 0.245 0.000 Total 0.310 1.392 10.931 0.000 0.556 0.116 0.235 0.189 5.930 0.000

Khalanga/Musikot

Area km2 Hard Ward Conifer Grazing Level Rock Shrub Sloping Valley Wood Lake River Forest Land Terrace outcrop land terrace cultivation Forest 1 0.000 0.000 0.000 0.000 0.000 0.000 0.000 2.070 1.780 0.000 2 0.000 0.317 0.000 0.000 0.000 0.000 0.000 0.531 0.261 0.000 3 0.000 0.303 0.000 0.000 0.413 0.000 0.000 0.000 1.123 0.000 4 0.000 0.207 0.014 0.001 0.088 0.000 0.000 0.728 1.162 0.000 5 0.000 0.163 0.040 0.000 0.000 0.127 0.000 0.000 1.305 0.248 6 0.013 0.314 0.947 0.000 0.000 0.069 0.166 0.000 0.707 0.510 7 0.000 0.596 0.000 0.002 0.000 0.056 0.186 0.000 1.464 0.178 8 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.009 0.032 0.000 9 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Total 0.013 1.900 1.001 0.003 0.501 0.252 0.352 3.338 7.834 0.936

In all VDCs, significant portion of their respective lands are occupied by sloping terrace. Peugha has the highest amount of sloping terrace, about 50% of its total land falls under the slope terrace category. Musikot (50% of its total land), Khara (49% of its total land) and Muru (47% of its total area) have also significant land area covered by the sloping terrace. The land-cover map has not identified valley cultivation (paddy field) in Rugha, Khara and Chaukhabang VDCs. However, about 6.2% of Peugha’s and 5.80% of Musikot’s total land areas are occupied by the valley cultivation in these VDCs.

Maize and milletare the main cereal crops in the sloping and level terrace in the study catchment. Cash crops like cauliflower, ginger, garlic and other vegetables are also grown in different parts of the catchment. The area is famous in producing and exporting radish and onion seed (Figure 9-6) in

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 9 Watershed Management Plan other parts of the country and abroad. Paddy, wheat and potato are grown in the low land valley cultivation area where irrigation facilities are available.

Figure 9-6: White Radish Seed Production near the Muskiot Area

The Muglu Khola Watershed has the diverse forest type due to variation in physiographical and climatic variations; the elevation of the catchment ranges from about 850 and 2850 m above the mean sea level. Forest species available in the watershed is altitudinal dependent. In the lower belt of the watershed Sal forest is available. Other main forest species observed in the watershed include Sisoo, Khaire, Sallo in Riverine Forest that occurs along the river bank up to 1500 m amsl. Other abundant forest species in the higher elevation include Khotesalla, Uttis, kafal, Khanoy, Kaulo, Amala, Dante Okhar etc. Vegetation such as ketaki, khar, babiyo, kans, amriso, nigalo, bans, bains etc. that are frequently used as bio-engineering measures are also abundantly found in the study catchment.

9.5.1 Land-cover according to Agro-Climatic Zone The Muglu Khola Watershed ranges from 857 to 2857 m above mean sea level in terms of elevation. The catchment can thus be divided into four categories in terms of agro-climatic zone; these include upper sub-tropical zone, warm temperate zone, cool temperate zone and sub-alpine zone. The watershed contains significant amount of area in the warm temperate zone with about 62 % of the total watershed's area followed by cool temperate zone (30.04 %) and upper sub-tropical zone (8.05%). There is very small amount of sub-alpine zone in the watershed. Table 9-2: Agro-Climatic Zone of Muglu Khola Watershed

SN Agro-Climatic Zone Elevation Range (m) Area (km2) Area (%) 1 Upper sub-tropical (monsson) 800-1200 13.91 8.05 2 Warm temperate (monsoon) 1200-1900 106.93 61.90 3 Cool temperate (monsoon) 1900-2800 51.89 30.04 4 Sub-alpine (monsoon) 2800-4100 0.008 0.01

Table 9-3 presents land-cover distribution in the Project VDCs according to agro-climatic zone. Major portion (about 34 %) of the total watershed area falls in the sloping terrace where various crops like maize, millate are grown. The sloping terrace is mostly found in the warm temperate zone.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 9 Watershed Management Plan

Significant area of the sloping terrace (about 5 % of the total watershed area) is observed in the cool temperate zone. This is the area where human enchroachment is extensive leading to frequent landslides.

Table 9-3: Land-Cover in Different VDCs according to Agro-Climiatic Zone

Landuse Elevation VDC Total Total Range (%) (m) Bhalakcha Chhibang Choukhabang Muru Musikot Khara Peugha Rugha Confer 800-1200 1.19 - - 0.08 0.01 - 0.00 0.03 1.31 0.93% Forest 1200- 4.76 - 0.29 2.91 - 0.16 5.79 0.90 14.80 10.45% 1900 1900- 0.28 - 0.02 0.11 - - 0.40 1.07 1.88 1.33% 2800 2800------0.00% 4100 Grazing 800-1200 0.36 0.72 - - 0.55 - - - 1.63 1.15% Land 1200- 0.21 1.76 0.91 1.66 0.99 1.35 0.20 1.61 8.69 6.13% 1900 1900- 0.16 - 0.48 0.07 0.18 0.42 0.01 0.31 1.62 1.15% 2800 2800------0.00% 4100 Hardwood 800-1200 0.39 0.11 - 0.15 0.70 0.00 0.06 0.02 1.43 1.01% Forest 1200- 1.56 - 4.18 2.03 0.29 3.70 0.16 3.15 15.05 10.63% 1900 1900- 0.39 - 6.75 0.02 0.01 8.41 - 4.26 19.85 14.02% 2800 2800------0.00% 4100 Lake 800-1200 ------0.00% 1200- - - - - 0.00 - - - 0.00 0.00% 1900 1900- - - - 0.00 0.00 - - - 0.00 0.00% 2800 2800------0.00% 4100 Level 800-1200 0.68 0.73 - - - 0.02 - 0.19 1.63 1.15% Terrace 1200- 0.25 0.16 0.39 0.85 0.50 - - 0.80 2.95 2.08% 1900 1900- - - 0.16 - - - - - 0.16 0.12% 2800 2800------0.00% 4100 River 800-1200 0.24 0.18 - 0.06 0.25 0.07 0.01 0.05 0.85 0.60% 1200- - - 0.12 0.05 0.00 0.07 0.07 0.11 0.42 0.30% 1900 1900------0.00% 2800 2800------0.00% 4100 Rock 800-1200 0.00 - - - 0.12 - - - 0.13 0.09% Outcrop 1200- - - 0.23 - 0.23 - - - 0.46 0.33% 1900 1900------0.00% 2800 2800------0.00% 4100 Shrub Land 800-1200 0.12 ------0.12 0.08% 1200- 0.42 - - 1.42 1.41 - - - 3.25 2.30% 1900 1900- - - 0.19 0.00 1.93 - - - 2.11 1.49% 2800

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 9 Watershed Management Plan

2800------0.00% 4100 Sloping 800-1200 1.33 1.47 - 0.04 1.38 0.20 0.01 0.05 4.48 3.16% Terrace 1200- 4.89 1.69 4.08 7.98 5.48 12.40 7.10 4.19 47.81 33.76% 1900 1900- 0.31 - 1.85 0.56 0.98 1.44 0.53 2.36 8.02 5.67% 2800 2800------0.00% 4100 Valley 800-1200 0.44 0.58 - - 0.92 - - - 1.93 1.36% Cultivation 1200- 0.04 - - 0.05 0.02 - 0.92 - 1.03 0.73% 1900 1900------0.00% 2800 2800------0.00% 4100

Hardwood and conifer forests also account significant amount of watershed area. Most of the hardwood forest (about 14 % of the watershed's area) is found in the higher elevational area raning from 1900 to 2800 m. Conifer trees and hardwood forest each has a coverage of about 10 % of the total watershed in the warm temperate zone. Paddy fields are generally found in the low land area called valley cultivated area. The valley cultivation is generally observed along the Muglu Khola and its tributaries' corridor. About 2 % of total watershed area is valley cultivation out of which about 1.4 % of the total watershed falls in the upper sub-tropical monsoon whereas about 0.7 % of the watershed area is located in the warm temperate zone. Agricultural practices are generally concentrated in valley cultivation, level terrace and sloping terrace. The practices are more focused in the lower elevation areas; for example about 34 % total watershed area is in sloping terrace in the elevation range of 1200-1900 and about 2 % of the total watershed's area is in level terrace in the same elevation range.

9.5.2 Land-cover by Slope The details analysis of present land use land cover situation has analyzed based on the slope class as proposed by LRMP. Slope class I refers to the slope below 3 degree, class II to 3‐15 degree, class III to 15‐30 degree, class IV to 30‐60 degree and class V refers to slope above 60 degree.

Table 9-4 presents land-use distribution in all VDCs according to slope classification made by LRMP. The data shows that the project area contains cultivated land (valley cultivation, sloping terrace and level terrace) even in the higher sloping area. Major portion of the sloping terrace falls in the III and IV sloping classes; about 16 and 24% of the toal watershed areas are in the III and IV sloping classes. Similarly, 1.8 % of watershed area falls in the sloping class IV that is being under cultivation through level terrace. Valley cultivation is also being done in higher sloping areas, for example more than 2 % of the total watershed area fall under higher sloping area that is under valley cultivation. Forest areas that comprise hardwood forest and conifer forest are obviously in the higher sloping areas. About 25% of total watershed have hardwood forest are also in the higher sloping area of class III and and IV. Similarly, about 12% of total watershed is conifer forest also lie in the sloping class III and IV.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 9 Watershed Management Plan

Table 9-4: Land-use Distribution by Slope in the Study VDCs

Landuse Slope VDC Total Total Class (%) Bhalakcha Chhibang Choukhabang Muru Musikot Khara Peugha Rugha Confer I 0.01 - - 0.01 0.00 - 0.01 0.00 0.03 0.02 Forest II 0.19 - 0.01 0.19 0.00 0.00 0.28 0.06 0.74 0.52 III 1.47 - 0.07 1.05 0.00 0.08 2.38 0.62 5.66 3.99 IV 4.52 - 0.23 1.85 0.00 0.08 3.51 1.49 11.69 8.25 V 0.02 0.00 0.00 - - 0.00 - 0.02 0.02 Grazing I 0.00 0.01 0.00 0.01 0.00 0.00 - 0.00 0.03 0.02 Land II 0.03 0.06 0.06 0.07 0.11 0.04 0.00 0.03 0.39 0.27 III 0.21 0.49 0.34 0.75 0.51 0.43 0.10 0.42 3.25 2.29 IV 0.50 1.92 0.98 0.89 1.09 1.31 0.10 1.47 8.25 5.82 V - - 0.01 - - - - 0.00 0.01 0.00 Hardwood I 0.01 0.00 0.01 0.00 0.01 0.02 0.00 0.01 0.06 0.04 Forest II 0.11 0.01 0.30 0.10 0.08 0.32 0.01 0.26 1.19 0.84 III 0.61 0.03 2.23 0.56 0.43 2.80 0.04 1.79 8.49 5.99 IV 1.61 0.08 8.36 1.52 0.48 8.98 0.17 5.37 26.57 18.7 V 0.00 - 0.02 0.01 - 0.00 - 0.00 0.03 0.02 Lake I - - - 0.00 - - - - 0.00 0.00 II - - - 0.00 0.00 - - - 0.00 0.00 III - - - - 0.00 - - - 0.00 0.00 IV - - - - 0.00 - - - 0.00 0.00 V ------0.00 Level I 0.01 0.00 0.00 0.00 - 0.00 - 0.00 0.01 0.01 Terrace II 0.14 0.05 0.02 0.05 0.04 0.00 - 0.08 0.39 0.28 III 0.30 0.32 0.20 0.36 0.27 0.01 - 0.37 1.83 1.29 IV 0.49 0.51 0.33 0.43 0.19 0.01 - 0.54 2.50 1.77 V - 0.00 ------0.00 0.00 River I 0.06 0.06 0.01 0.02 0.10 0.01 0.02 0.01 0.28 0.20 II 0.14 0.09 0.06 0.06 0.13 0.08 0.05 0.09 0.69 0.49 III 0.03 0.03 0.03 0.02 0.02 0.04 0.01 0.05 0.23 0.17 IV 0.00 0.00 0.01 0.01 0.00 0.01 0.00 0.02 0.06 0.04 V ------0.00 Rock I 0.00 - 0.00 - 0.00 - - - 0.00 0.00 Outcrop II 0.00 - 0.01 - 0.01 - - - 0.02 0.01 III - - 0.04 - 0.09 - - - 0.13 0.09 IV - - 0.19 - 0.25 - - - 0.44 0.31 V - - 0.00 - - - - - 0.00 0.00 Shrub I - - 0.00 0.00 0.01 - - - 0.01 0.01 Land II 0.01 - 0.01 0.06 0.51 - - - 0.59 0.42 III 0.15 - 0.04 0.74 1.50 - - - 2.43 1.71 IV 0.38 - 0.13 0.62 1.32 - - - 2.45 1.73 V ------0.00

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Sloping I 0.02 0.04 0.01 0.03 0.06 0.02 0.04 0.02 0.25 0.17 Terrace II 0.42 0.12 0.29 0.55 1.07 0.68 0.59 0.41 4.13 2.91 III 2.36 0.91 1.89 3.77 3.48 4.98 3.11 1.76 22.25 15.7 IV 3.72 2.09 3.73 4.24 3.23 8.36 3.90 4.40 33.66 23.7 V 0.01 0.01 0.01 0.00 - - 0.00 0.01 0.03 0.02 Valley I 0.03 0.02 - 0.00 0.06 - 0.03 - 0.14 0.10 Cultivation II 0.16 0.15 - 0.00 0.38 - 0.33 - 1.02 0.72

III 0.13 0.27 - 0.02 0.34 - 0.30 - 1.05 0.74 IV 0.16 0.15 - 0.03 0.16 - 0.26 - 0.75 0.53 V ------0.00 - 0.00 0.00

9.5.3 Land-cover by Aspect Aspect is the direction that a slope faces. It identifies the steepest down slope direction at a location on a surface. Aspect identifies the down slope direction of the maximum rate of change in value from each cell to its neighbors. Aspect can be thought of as the slope direction. The values of the output raster will be the compass direction of the aspect. Aspect is measured counterclockwise in degrees from 0 (due north) to 360 (again due north,coming full circle). The value of each cell in an aspect grid indicates the direction in which the cell's slope faces. Flat slopes have no direction and are given a value of ‐1. Most of the watershed areas (about 40.24%) are North, West and North‐West faced and very few area is East and South‐East faced (Table 9-5)

Table 9-5: Aspect of the Watershed

SN Aspect Area (km2) Area (%) 1 Flat 0.2818 0.16% 2 North 25.619 14.83% 3 North East 21.7048 12.56% 4 East 13.6769 7.92% 5 South East 15.9596 9.24% 6 South 23.5423 13.63% 7 South West 28.0706 16.25% 8 West 20.6212 11.94% 9 North West 23.2663 13.47%

9.6 Land Capability Classification Land capability is defined as the inherent capacity of land to be productive under sustained use and specific management methods. Land capabilities are derived by combining the land systems information with climatic, agronomic, and forestry data. There are altogether six capability classes. Classes I, II and III have landscape and climate suited to arable cropping and are separated from each other on the basis of slopes. Due to the limitations imposed by the slope, class III land can be cultivated only with terracing. The upper limit of cultivation with terracing is considered to be 30 degrees (about 60 percent slope).

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Class IV land is too steep or too cold to support agriculture, but supports productive forest suited for exploitation. Class V land is either too cold for natural forest or is geomorphologically unstable but supports vegetation suited for grazing. Class VI land is too steep and too unstable to support normal forest use and is very sensitive and liable to degrade rapidly even with very slight disturbances. Elevation Class Map, Slope Class Map and Aspect Map of the Muglu Khola Watershed were overlaid to prepare a land capability of the area. In the area, only 4 (I to IV) land capability classifications exist (Figure 9-7).

Musikot

Ü Sankh Chhibang

Bhalakcha Peugha

Muru Chokhabang

Rugha Classifications Khara 1 2 3 0 2,000 4,000 8,000 4 m

Figure 9-7: Land Capability Classification of the Muglu Khola Watershed

Table 9-6 presents distribution pattern of land capability classifications in the Muglu Khola Watershed. As depicted in the table, major portion of the area falls in the classification 4; about 68 % of the total watershed area lies in this category. Similarly, potential agricultural lands that include classifications I, II and III contain about 32 % of the total land area. In all VDCs, very small amount of land falls in the land unit I and II. In land unit I, agricultural practice particularly paddy cultivation is possible with proper flood protection works whereas in unit II, suitable cultivation is possible after terracing or countouring to control soil erosion and conservation measures with maintenance of ground is required for sustained foresty related uses. On the other, the third land unt is suitable for agro-forestry and for fodder production when terracing is to be carried. Finally, land-unit 4 is appropriate for fuel wood, fodder and timber production when a good, permanent vegetative cover is maintained to minimize erosion.

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Table 9-6: Land Capability Classification in the Muglu Khola Watershed

Land VDC Area (km2) Unit Bhalakcha Chhibang Choukhabang Muru Musikot Khara Peugha Rugha I 0.14 0.12 0.04 0.07 0.25 0.06 0.10 0.05 II 1.21 0.48 0.76 1.09 2.34 1.12 1.30 0.94 III 5.05 2.05 2.79 6.92 5.23 5.89 5.47 2.72 IV 11.62 4.75 16.14 9.93 8.16 21.20 8.39 15.90

9.7 Action Plan for Risk Sensitive Land-use Plan Action Plan for a risk sensitive land-use plan in the Muglu Khola Watershed has been prepared after a series of interactions and workshops conducted in different VDCs. A one day workshop was conducted in each of the watershed VDCs (Table 9-7). The district representatives from DSCO, DVO, DADO, DDC etc. also participated in the workshops. The community participation in the program was encouraging. Table 9-7: Details of Workshops Conducted in Different VDCs of the Watershed

VDCs Date Venue Participation Chaukhawang 20th September VDC Office Chaukhawang 27 2012 Peugha and 21st September Krishi Upaj Sakalan Kendra, Solabang, 48 Chhiwang Khalanga Bhalakcha and 22nd September Triveni Higher Secondary School, Simrutu 40 Rungha Khara and Muru 23rd September Triveni Higher Secondary School, Simrutu 33 Khalanga 25th September Karmachari Milan Kendra, Khalanga 30

The communities were briefed about the hazard, disaster, hazard and risk. They were also introduced about the climatic and geographic condition of the country and Rukum district. The local people were shared with the preliminary outcome of the Multi Hazard Risk Assessment of the Muglu Khola Watershed, its approach and area coverage. The communities were grouped to rank the hazards and risk in different areas of their villages and VDCs (Figure 9-8). Their voices are now reflected in the Table 9-8.

Figure 9-8: Community Group Discussion in the Workshop and Participant

This plan of action is the output of multi-hazard risk assessment and land use plan workshop. On the basis, the plan of action has been prepared for upcoming five years categorizing in three phases i.e

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<1 year, 1-3 years and 3-5 years. Some noticeable points from the watershed management point of view are as given below;  The forest area should be increased in the upper level/part while crop and vegetable ( Chilli, Onion, Tomato etc) in the lower part of the project area  Promotion of goat rearing project  Promotion of plantation of some medicinal plants like Sugnadhakokila, Rudraksha and Kurilo along with Alainchi, Lemon and Orange farming  Promotion of Bio-briquette and plantation of Jatropha Species for bio-diesel  Bio-enginering and Terrace improvement (Annex-3) is strongly recommended in the project area  Peugha-9, Todke and Bhalakcha-1, Rampa6a, there should be the promotion of rain water harvesting and water source protection  Khalanga and Chhiwang area are highly recommended for the Organic farming  River Bank conservation and road side bioengineering should be promoted  School area should be in the safe zone and risk should be reduced in time On the basis of these recommendations and from direct observation along with Multi-hazard risk Assessment, some remarkable proposed plan are; 1. Plantation Programme: Plantation for the river bank protection is dire need in the project area and nearly we can plant 25000 plants species from Simrutu-Bairagithanti-Muglukhola nearly the distance of 8Km. This plantation project not only safe the river bank cutting problem but also make safe the road side environment. The recommended plant species for the plan are; Bamboo- 4000, Nigalo- 8000, Amliso- 12000 and Bains, Okhar, Malagiri-1000 2. School Safety Programme: The most of the school area are vulnerable due to the landslide and flood, so to make them safe, there is strong need of school safety programme. The VDC wise school safety interventions include; Peugha-Balkalyan Secondary School; water resource conservation, piping, Toilet construction, Small mitigation in nearby area of school, Chhiwang- Prabhat Secondary School; Library Support, Small mitigation in nearby school area Chaukhawang- Malika Secondary School, Small mitigation activities, Dhupi Plantation and Nursery Establishment Bhalakcha- Janakalyan Secondary School; Small Mitigation, Plantation, Library support Muru,-Janashakti Secondary School; Small mitigation, plantation, Library construction, Toilet female/male Khara-Janajagaran; Small mitigation, Plantation, Toilet Rungha, Tribeni HSS Plantation, Small mitigation, bioengineering and structural Khalanga-Balkalyan Secondary School, Solabang, Small mitigations Runga: Triveni Higher Secondary School; Plantation, Children park development, bio- engineering for river cutting and flood control

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3. Water Source Protection Programme: Even the sources of water are several but these are not properly managed. Hence, water source protections are equally important for both gully control and fulfill the deficiency of water to the local. Altogether, VDC and ward wise land use plan with potential options for risk reduction are given below;

Table 9-8: General Framework of Proposed Plan of Action

1. VDC Chaukhawang SN Activity Description Time Beneficiaries Responsible Supporting Frame HH Agency Agencies 1 Landslides Severe landslide at <1 70 DSCO DDC, Sanginigaira, Chaur and year DWIDP, Deldanda, ward no 8 VDC, Community, NGO, INGO Severe landslide at Tallo <1 80 DSCO DDC, hole, mathillo hole ward no year DWIDP, 4. VDC, Community, NGO, INGO Landslide protections at 1-3 10 DSCO DDC, Sindurejhang of ward no 6. year DWIDP, VDC, Community, NGO, INGO Landslide protection at 1-3 5 DSCO DDC, Galamparti of ward no 9 year DWIDP, VDC, Community, NGO, INGO Landslide protection at 3-5 20 DSCO DDC, Nunasimal and Chauribot, years DWIDP, Choukhabang 2 VDC, Community, NGO, INGO 2 Flood Flood protection in the bank of 1-3 20 DWIDP DSCO, DDC, Chun Khola. 2 km long protection year VDC, is required with gabion retaining Community, wall. NGO, INGO 3 Irrigation Thandari Khola irrigation of <1 15 DADO DDC, VDC, ward no 1 year Community, NGO Baiyala Khola irrigation of ward <1 20 DADO DDC, VDC, no 2 year Community, NGO 4 Water Source Spring conservation in <1 10 DSCO DDC, VDC Conservation Bakbasne of ward no.2 year Napcho Khola spring <1 13 DSCO DDC, VDC conversation of ward no 3 year Pagarpani spring <1 15 DSCO DDC, VDC conversation of ward no. 4 year Spring restoration at Khang <1 10 DSCO DDC, VDC

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of ward no 6 year Lire Khola spring conversation <1 20 DSCO DDC, VDC of ward no 7 year 5 Horticulture Promotion of Citrus farming in 1–3 160 DADO DDC, VDC, Danda Tol, Tallo Hole, Mathillo year DSCO, DFO, Hole, Holtara, Jhadhdari, Community Jharunga, Khadka Tol, Sangani Gaira, Deldada, Kharsupani 6 Agriculture Promotion of Potato farming 1–3 593 DADO DDC, VDC, and masala farming (Ginger, year Community Garlic, Turmeric, Timur) and , Aalaichi farming in the entire VDC 7 Plantation Plantation of species such as 1-3 593 DFO DDC, VDC, Salla, Dhupi, Datewokhar, year Community, Dalchini, Lapsi, Rudrakshya in Forest User Badale Kanla, Laligurans, Group Mauwabari, Sindure and Sirjansil Community Forest 8 Terrace Terrace Improvement in Danda 1-3 160 DSCO DDC, VDC, Improvement Tol, Tallo Hole, Mathillo Hole, year Community Holtara, Jhadhdari, Jharunga, Khadka Tol, Sangini Gaira, Deldara, Kharsupani 9 River bank Conservation of Thandari 1-3 40 DSCO DDC, VDC, protection khola of ward no 1 and Chun year Community Khola riverside of ward no 6 using baas, bais, nigalo, uttis, amriso 10 Others . Promotion of goat 1-3 300 DVO, Community, farming in the upper year DADO, DDC, District part of the sub VDC, Education watershed DWIDP Office, . Promotion of animal NGO, INGO farming in the lower part of the sub watershed . Forest and Horticulture Nursery establishment . Water supply in Bakbasne of ward no 1 . Water supply at Lingur, Tallo hole, Mathillo hole of ward no 4 . Water supply in Daldanda Sangini Gaira of ward no 8 . Landslide protection in - Sarsawati primary school of ward no 3 . Landslide protection in

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Suryadaya primary school of ward no 4 . Landslide protection in Janachetana primary school of ward no 8 . Maintenance of trail roads in ward no 4 . Road side bioengineering

2. VDC Chhiwang SN Activity Description Time Beneficiaries Responsible Supporting Frame HH Agency Agencies 1 Landslides Landslide protection 1-3 10 DSCO DDC, Sadanchaur of ward no 1 years DWIDP, VDC, Community, NGO, INGO Landslide protection in <1 20 DSCO DDC, Chaulachaur year DWIDP, Phalamedhunga of ward no VDC, 2 Community, NGO, INGO Landslide protection in 1-3 10 DSCO DDC, Dhada Chibang, Ghairibari, year DWIDP, Jungalebara, Kharkhare VDC, Khola, Ghatte Khola of ward Community, NGO, INGO no 3 Landslide protection in <1 15 DSCO DDC, Thalighau, Salghari, year DWIDP, Vhumtole of ward no 4 VDC, Community, NGO, INGO Landslide protection <1 10 DSCO DDC, Haibang, Lamadanda of year DWIDP, ward no 5 VDC, Community, NGO, INGO Landslide protection in <1 20 DSCO DDC, Soragaun, Barigaun, year DWIDP, Pakhagaun, Ukaladanda, VDC, Viring Khola, Trisule Basti of Community, ward no 8 NGO, INGO Landslide protection in Harale, <1 DSCO DDC, sawar khola, baribote, raute year DWIDP, khola of ward no 9 VDC, Community, NGO, INGO 2 Flood Flood protection in <1 20 DWIDP DSCO, DDC, Bhaunchaur, Maletibagar of year VDC, ward no 2 of 100 m Community, NGO, INGO Flood protection in <1 20 DWIDP DSCO, DDC, Chisapani Niya khola of year VDC, ward no 4 of 200 m Community,

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NGO, INGO Kange Khola, Saware Khola 1-3 70 DWIDP DSCO, DDC, flood protection of ward no year VDC, 9 of 500 m Community, NGO, INGO 3 Irrigation Irrigation canal from <1 10 DADO DDC, VDC, Chibang Khola to Khadkdera year Community, of ward no 1 NGO Irrigation canal from 1-3 60 DIO DADO, DDC, Chibang Khola to loriwang year VDC, Ghau (5km) of ward no 6 Community, NGO Irrigation canal from Bedh <1 10 DADO DDC, VDC, Khola of ward no 7 year Community, NGO Irrigation in Isaku of ward no <1 10 DADO DDC, VDC, 9 year Community, NGO 4 Water Source Juge Khola spring <1 5 DSCO DDC, VDC Conservation conversation of ward no 1 year Jaham Khola Khatpani spring <1 10 DSCO DDC, VDC conversation of ward no 5 year

Sudarpani, Bedh Khola <1 10 DSCO DDC, VDC spring conversation of ward year no 7 5 Horticulture Promotion of Citrus farming in 1–3 150 DADO DDC, VDC, Ram Khola, Kauli Chaur, Bhum year DSCO, DFO, Phalame Dhunga, Likhe Danda, Community Bhaljula, Khopi Khelne, Jyam Danda, Sadhan Chaur, Danda Gaun 5 Agriculture Promotion of fresh vegetables 1 – 3 976 DADO DDC, VDC, and masala farming (Ginger, year Community Garlic, Turmeric, Timur) and Aalaichi farming in the entire VDC 6 Plantation Plantation of species such as 1-5 976 DFO DDC, VDC, Salla, Dhupi, Datewokhar, year Community, Dalchini, Lapsi, Rudrakshya in Forest User Okharipatal, Patal, Hattisar Group Community Forest 7 Terrace Terrace Improvement in Ram 1-3 150 DSCO DDC, VDC, Improvement Khola, Kauli Chaur, Bhum year Community Phalame Dhunga, Likhe Danda, Bhaljula, Khopi Khelne, Jyam Danda, Sadhan Chaur, Danda Gaun 8 River bank Ghor Khola and Ghate Khola 1-3 110 DSCO DDC, VDC, protection side protection of ward no 3 year Community (1 km) using baas, bais, niyalo, uttis, amriso

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Chibang Khola river side conversation of ward no 6 (1 km) using baas, bais, niyalo, uttis, amriso Sudarpani riverside conservation of ward no 7 (1 km) using baas, bais, niyalo, uttis, amriso Viring Khola side protection of ward no 8 (1 km) using baas, bais, niyalo, uttis, amriso Kange Khola side protection of ward no 9 (2 km) using baas, bais, niyalo, uttis, amriso 9 Others . Mitigation measures in 1-3 300 DVO, Community, the premises of Nepal year DADO, DDC, District Rastiya Primary School VDC, Education of ward no 3 DWIDP Office, . Water supply in NGO, INGO Nayaghau, Mathillo tole of ward no 4 . Protection measures in Janapriya Primary School of ward no 5 . Landslide protection in Satipole Primary School of ward no 7 . Landslide protection Trisule primary school of ward no 8 . Micro hydro in Kange Khola and . Water supply in Isaku of ward no 9 3. VDC Khalanga SN Activity Description Time Beneficiaries Responsible Supporting Frame HH Agency Agencies 1 Landslides Shari Gaun, Jhamidanda 1-3 10 DSCO DDC, landslide protection in ward year DWIDP, no 3 VDC, Community, NGO, INGO Digre landslide protection in 1-3 5 DSCO DDC, ward no 4 year DWIDP, VDC, Community, NGO, INGO Landslide protection at 1-3 15 DSCO DDC, Dhodeni and Shimeni in ward year DWIDP, no 5 VDC, Community,

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NGO, INGO Pana Khola, Kuineta landslide <1 30 DSCO DDC, protection in ward no 6 year DWIDP, VDC, Community, NGO, INGO Tya Khola, Mathillo 1-3 30 DSCO DDC, Tharadhunga landslide year DWIDP, protection in ward no 7 VDC, Community, NGO, INGO 2 Flood Flood protection along bank 3-5 50 DWIDP DSCO, DDC, of Muglu Khola year VDC, Community, NGO, INGO 3 Irrigation Small Irrigation in ward no 6 <1 10 DADO DDC, VDC, year Community, NGO 4 Water Source Sisne Khola spring <1 5 DSCO DDC, VDC Conservation conservation in ward no 6 year Sital Pokhari, Bhaun Panera <1 10 DSCO DDC, VDC spring conservation in ward year no 7 Aapcha Dholgore spring <1 10 DSCO DDC, VDC conservation in ward no 8 year 5 Horticulture Promotion of Citrus farming 1– 3 415 DADO DDC, VDC, year DSCO, DFO, Community 5 Agriculture Fresh vegetable production 1– 3 415 DADO DDC, VDC, and vegetable seeds year Community production 6 Plantation Plantation of species such as 1-3 220 DFO DDC, VDC, Salla, Uttis, Dhupi, year Community, Datewokhar, Dalchini, Lapsi, Forest User Rudrakshya in Community Group Forest 7 Terrace Terrace Improvement 1-3 150 DSCO DDC, VDC, Improvement Shaunepani, Mogare Basti, year Community Bhaun Deta, Dhalakhel in ward no 6 8 River bank Chera to Muglu river bank 1-3 40 DSCO DDC, VDC, protection conservation in ward no 5 year Community (500 m) Muglu river bank conservation in ward no 6 (300 m) 9 Others . Roadside 1-3 415 DVO, Community, bioengineering year DADO, DDC, District . Income generation VDC, Education Training DWIDP Office, NGO, INGO . Nursery Establishment <1 N-PAF and DDC, DSCO, year DSCO NGOs

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VDC Khara

SN Activity Description Time Beneficiaries Responsible Supporting Frame HH Agency Agencies 1 Landslides Landslide protection at 1-3 7 DSCO DDC, Dhaireni of ward no 1 years DWIDP, VDC, Community, NGO, INGO Landslide protection in <1 25 N-PAF DSCO, DDC, Haibang of ward no 2 year DWIDP, VDC, Community, NGO, INGO Landslide protection at 1-3 15 DSCO DDC, Lidedanda and Saunepani year DWIDP, of ward no 3 VDC, Community, NGO, INGO Landslide protection in <1 12 DSCO DDC, Salleri Pakha of ward no 4 year DWIDP, VDC, Community, NGO, INGO Landslide protection Saleri <1 18 DSCO DDC, Tole, Damdu tole of ward no year DWIDP, 6 VDC, Community, NGO, INGO Landslide protection at <1 5 DSCO DDC, Jhulke of ward no 7 year DWIDP, VDC, Community, NGO, INGO Aantari Khosya landslide <1 5 DSCO DDC, protection of ward no 9 year DWIDP, VDC, Community, NGO, INGO 2 Flood Flood protection along bank <1 80 DWIDP DSCO, DDC, of Khara Khola, ward no 4 year VDC, Community, NGO, INGO 3 Irrigation Small irrigation in Salli <1 30 DADO DDC, VDC, Danda, Thula Khoriya ward year Community, no 2 NGO 4 Water Source Dhaireni spring conservation <1 10 DSCO DDC, VDC Conservation of ward no 1 year jhulneta water spring conversation of ward no 2

Bheri khola, khumcheri <1 5 DSCO DDC, VDC spring conservation ward no year 6

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Khali padheri spring <1 5 DSCO DDC, VDC conservation ward no 7 year Kunbang spring conservation <1 5 of ward no 9 year 5 Horticulture Promotion of Citrus farming in 1 – 3 350 DADO DDC, VDC, Salli Danda, Thuli Khorya, year DSCO, DFO, Pokhari, Damdu, Salleri, Community Liredanda, Mathillo Hampal 5 Agriculture Promotion of Potato farming, 1– 3 350 DADO DDC, VDC, Lemon Farming, masala year Community farming, Alaichi farming in the VDC 6 Afforestation Plantation of species such as 3-5 250 DFO DDC, VDC, Salla, Uttis, Dhupi, year Community, Datewokhar, Dalchini, Lapsi, Forest User Rudrakshya in Suki Daha, Group Majhau Gaura, Jhakrimul, Bagh Khor, Salli Danda CF, Batheni, KarateniCommunity Forest 7 Terrace Terrace Improvement in Salli 1-3 110 DSCO DDC, VDC, Improvement Danda, Thuli Khorya, Pokhari, year Community Damdu, Salleri, Liredanda, Mathillo Hampal 8 River bank Kunewang , Hairung in ward 1-3 80 DSCO DDC, VDC, protection no. 9 (1 km) year Community 9 Others . Nursery establishment 1-3 350 DVO, Community, of Lemon year DADO, DDC, District . Goat farming VDC, Education . Land restoration DWIDP Office, . Herbs production NGO, INGO

4. VDC Muru SN Activity Description Time Beneficiaries Responsible Supporting Frame HH Agency Agencies 1 Landslides Thula Khorya landslide 1-3 10 DSCO DDC, protection of ward no 3 year DWIDP, VDC, Community, NGO, INGO Rithang/Pakhepani landslide <1 36 N-PAF and DDC, protection ward no 4 year DSCO DWIDP, VDC, Community, NGO, INGO Chetabari Gaun ,Basnet Tole 1-3 15 DSCO DDC, landslide protection in ward year DWIDP, no 5 VDC, Community, NGO, INGO Landslide protection at <1 10 DSCO DDC, Patalbasti, Murtibang of year DWIDP, ward no 6 VDC,

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 9 Watershed Management Plan

Community, NGO, INGO Raumare, Ghairabari <1 10 DSCO DDC, landslide protection of ward year DWIDP, no 8 VDC, Community, NGO, INGO 2 Flood Flood protection along bank 1-5 60 DWIDP DSCO, DDC, of Muru Khola near year VDC, Shimrutu Community, NGO, INGO 3 Irrigation Small irrigation from Muru <1 40 DADO DDC, VDC, Khola year Community, NGO 4 Water Source Spring restoration at Mingri <1 5 DSCO DDC, VDC Conservation Dagi mood in ward no 3 year Rithang, Kural, Ghorlekot, <1 15 DSCO DDC, VDC spring conservation in ward year no 4 Saunepani, Kharipani, <1 15 DSCO DDC, VDC Padera, Dharapani spring year conservation ward no 5 5 Horticulture Promotion of Citrus farming in 1– 3 550 DADO DDC, VDC, Rithyan, Kharneta, Purnapani, year DSCO, DFO, Patala Community 5 Agriculture Promotion of fresh vegetables 1– 3 550 DADO DDC, VDC, and masala farming (Ginger, year Community Garlic, Turmeric, Timur) and Aalaichi farming in the entire VDC 6 Plantation Plantation of species such as 1-3 310 DFO DDC, VDC, Salla, UttisDhupi, Datewokhar, year Community, Dalchini, Lapsi, Rudrakshya Forest User inJhakri Pani, Dim Khola, Sir Group Chaur, Pang Rang Community Forest 7 Terrace Terrace Improvement in <1 280 N-PAF and DDC, VDC, Improvement Rithyan, Kharneta, Purnapani, year DSCO Community Patala 8 River bank Muru Khola side 1-3 60 DSCO DDC, VDC, protection conservation using baas, year Community nigalo, uttis, aamriso etc. 9 Others . Shree Bhim lower 1-3 550 DVO, Community, secondary school year DADO, DDC, District landslide protection in VDC, Education ward no 1 DWIDP Office, . Road side NGO, INGO bioengineering . Goat farming in ward no 3 . Herds plantation in ward no 4

Submitted to UNDP - 132 - Prepared by ECONEPAL and NPAF Rukum

Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 9 Watershed Management Plan

. Rautebara pond conservation in ward no 6 . Landslide protection in shree bhim lower secondary school in ward no 9 . Plastic pond, ward no 4 <1 36 HH N-PAF and I/NGOs, . Nursery Establishment year DSCO and DDC Cooperative 5. VDC Peugha

SN Activity Description Time Beneficiaries Responsible Supporting Frame HH Agency Agencies 1 Landslides Khoriya, Thuladhunga 1-3 10 DSCO DDC, landslide protection in ward years DWIDP, no 1 VDC, Community, NGO, INGO Vhag Gaun landslide 3-5 5 DSCO DDC, protection in ward no 4 year DWIDP, VDC, Community, NGO, INGO Khare Khola , Saune Pagera 1-3 15 DSCO DDC, landslide protection in ward year DWIDP, no 5 VDC, Community, NGO, INGO Landslide protection at <1 10 DSCO DDC, Patalbasti, Murtibang in year DWIDP, ward no 6 VDC, Community, NGO, INGO Peughadanda, Botbang <1 5 DSCO DDC, landslide protection in ward year DWIDP, no 7 VDC, Community, NGO, INGO Sallaghari, Dalsingh, <1 10 DSCO DDC, Torkedamar, Thakura, year DWIDP, Khatghara landslide VDC, protection in ward no 9 Community, NGO, INGO 2 Flood Flood protection in Chautara <1 30 DWIDP DSCO, DDC, Khahare Khola, Ghairikhet to year VDC, Tunib in ward no 3 Community, NGO, INGO 3 Irrigation Maintenance of irrigation <1 10 DADO DDC, VDC, canal in ward no 2 year Community, NGO Irrigation canal construction 3-5 15 DIO DADO, DDC, in ward no 3 year VDC, Community, NGO

Submitted to UNDP - 133 - Prepared by ECONEPAL and NPAF Rukum

Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 9 Watershed Management Plan

Small irrigation in ward no 5 <1 8 DADO DDC, VDC, year Community, NGO 4 Water Source Kowin Khola, Dhamai Dhara, 1-3 10 DSCO DDC, VDC Conservation Chalokot spring year conservation in ward no 2

Spring restoration at 1-3 15 DSCO DDC, VDC Chautara, Khuri Khola, year Vhaitakura of ward no 3 Gangal khola, Jhughapani 1-3 15 DSCO DDC, VDC spring conservation in ward year no 7 Paneri Khola, Vhukya Khola, 1-3 15 DSCO DDC, VDC Panidhara, Mulpani spring year conservation in ward no 8 Goganpani/Todke water <1 30 DSCO DDC, VDC restoration in ward no 9 year 5 Horticulture Promotion of Citrus, banana 1– 3 400 DADO DDC, VDC, and mango farming in Tallo year DSCO, DFO, Kharka, Tolke, Damarpakha, Community Salghari, Khandara, Rojkhet, Khahare, Peugha Danda, Mathigaun Armali Tol, Basnet Tol 5 Agriculture Promotion of potato, 1– 3 400 DADO DDC, VDC, vegetable seeds and masala year Community farming (Ginger, Garlic, Turmeric, Timur) and Aalaichi farming in the entire VDC 6 Plantation Plantation of species such as 1-3 310 DFO DDC, VDC, Salla, Uttis, Sisoo, Dhupi, year Community, Datewokhar, Dalchini, Lapsi in Forest User Salghari, Thulabhir, Bhomke, Group Melgairee, Gurgure, Jurepani, Deupanna, Mailgairee Community Forest 7 Terrace Terrace Improvement in Tallo 1-3 290 DSCO DDC, VDC, Improvement Kharka, Todke, Damarpakha, year Community Salghari, Khandara, Rojkhet, Khahare, Peugha Danda, Mathigaun Armali Tol, Basnet Tol 8 River bank Peugha Khola side 1-3 60 DSCO DDC, VDC, protection conservation using baas, year Community nigalo, uttis, aamriso etc. (2 km) 9 Others . Water supply in 1-3 30 DDC Community, Machipole, Jhalekharka, year NGO Trisule

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 9 Watershed Management Plan

6. VDC Rugha SN Activity Description Time Beneficiaries Responsible Supporting Frame HH Agency Agencies 1 Landslides Sintubang, Bhulung Khola, 1-3 20 DSCO DDC, Khalti Khola landslide years DWIDP, protection ward no 1 VDC, Community, NGO, INGO Landslide protection in Thakuri <1 5 DSCO DDC, Tole of ward no 2 year DWIDP, VDC, Community, NGO, INGO Landslide protection at Pani 1-3 5 DSCO DDC, Ghaira of ward no 5 year DWIDP, VDC, Community, NGO, INGO 2 Flood Flood protection around <1 300 N-PAF DSCO, DDC, Simrut Bazaar and Trivedi year VDC, high school Community, NGO, INGO 3 Irrigation Irrigation canal construction <1 20 DADO DDC, VDC, at ward no.2 year Community, NGO 4 Spring Saunepani, Khoripani, <1 10 DSCO DDC, VDC Source Vhulung Khola spring year Conservation conservation in ward no 1 Bedh Khola spring <1 5 DSCO DDC, VDC conservation in ward no 4 year Spring conservation at Pani <1 5 DSCO DDC, VDC Ghaira of ward no 5 year Kara Gaun spring <1 5 DSCO DDC, VDC conservation in ward no 7 year Beljura and Danchuk spring <1 5 DSCO DDC, VDC restoration in ward no 9 year 5 Horticulture Promotion of Citrus farming in 1–3 410 DADO DDC, VDC, Tali Gaun, Jibari, Balle Jure, year DSCO, DFO, Daban, Jhulka, Hairu Community 5 Agriculture Promotion of potato, and 1–3 410 DADO DDC, VDC, masala farming (Ginger, Garlic, year Community Turmeric, Timur) and Aalaichi farming in the entire VDC 6 Plantation Plantation of species such as 1-3 380 DFO DDC, VDC, Sal, Uttis, Salla, Sisoo, Dhupi, year Community, Datewokhar, Dalchini, Lapsi in Forest User Community Forest, ward no 2 Group and 5 7 Terrace Terrace Improvement in Tali 1-3 250 DSCO DDC, VDC, Improvement Gaun, Jibari, Balle Jure, Daban, year Community Jhulka, Hairu 8 River bank Riverbank conservation in 1-3 70 DSCO DDC, VDC, protection Khalti Khola of ward no 1 year Community

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 9 Watershed Management Plan

using baas, nigalo, uttis, aamriso etc. 2 km Rugha khola bank protection in ward no 2 using baas, nigalo, uttis, aamriso etc. 1km 9 Others . Nursery establishment 1-3 300 DVO, Community, . Jumle pokhari water year DADO, DDC, District supply in ward no 2 VDC, Education . Landslide protection DWIDP Office, near school building NGO, INGO ward no 7

7. VDC Bhalakcha SN Activity Description Time Beneficiaries Responsible Supporting Frame HH Agency Agencies 1 Landslides Rithabot Tole landslide 1-3 5 DSCO DDC, DWIDP, protection in ward no 1 years VDC, Community, NGO, INGO Landslide protection in 3-5 20 DSCO DDC, DWIDP, Jamdanda, Mathi Gaun, Sakha year VDC, Khola of ward no 2 Community, Basi Danda, Khasini Ghadi NGO, INGO Landslide protection of ward no 1-3 15 DSCO DDC, DWIDP, 4 year VDC, Jumlabang, Samibo, Charakatla Community, NGO, INGO Landslide protection of ward no <1 5 DSCO DDC, DWIDP, 5 year VDC, Community, NGO, INGO Landslide protection at <1 10 DSCO DDC, DWIDP, pitibang, Umm Khola, Bugeri of year VDC, ward no 6 Community, NGO, INGO Landslide protection in <1 15 DSCO DDC, DWIDP, Ghorneti, Bhagbhage, year VDC, Gharpang of ward no 7 Community, NGO, INGO Chari Khola, Kusum Danda, <1 20 DSCO DDC, DWIDP, Pairata landslide protection of year VDC, ward no 9 Community, NGO, INGO 2 Flood Sakha Khola and Bairagi Thandi <1 40 N-PAF DSCO, DDC, flood protection year VDC, Community, NGO, INGO Kala Khola, Mistri Khola flood <1 20 DWIDP DSCO, DDC, protection in ward no 2 year VDC, Community, NGO, INGO 3 Irrigation Small Irrigation in ward no 2 <1 20 DADO DDC, VDC, year Community, NGO

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 9 Watershed Management Plan

Irrigation canal from Kalpa Khola to 3-5 40 DIO DADO, DDC, Gharpang ward no 7 year VDC, Community, NGO 4 Spring Vhaira Dhar, Dabre Ghakri, Kala Khola <1 10 DSCO DDC, VDC Source spring conservation in ward no 1 year Conservation Balam Khola and Khasini Gadhi spring <1 10 DSCO DDC, VDC conservation in 4 year Spring restoration at Ruma Khola in <1 5 DSCO DDC, VDC ward no 6 year Kalpadhara, Jugena, Dhumta, <1 20 DSCO DDC, VDC Dhagbhage spring conversation ward year no 7 Ghati gaura, Lamidanda, Shivri spring <1 10 DSCO DDC, VDC conservation ward no 8 year Thula Padhera, Simpani,Chari Khola <1 10 DSCO DDC, VDC spring conservation of ward no 9 year 5 Horticulture Promotion of Citrus farming in Lanhu 1– 3 360 DADO DDC, VDC, Khola, Pipal Tara, Ghorneti, Titibang, year DSCO, DFO, Kauchhe, Ghanabot, Bolamkhalchaur, Community Sivri, Khani Khola, Lam Danda 5 Agriculture Promotion of potato, masala farming 1– 3 360 DADO DDC, VDC, (Ginger, Garlic, Turmeric, Timur), year Community vegetable seed and Aalaichi farming in the entire VDC 6 Afforestation Plantation of species such as Sal, Uttis, 1-3 280 DFO DDC, VDC, Salla, Sisoo, Dhupi, Datewokhar, Dalchini, year Community, Lapsi in Palno Patal, Pangar Khola, Forest User Kharkhare, Argale, Dur Khola, Bheripatal Group Community Forest 7 Terrace Terrace Improvement in Lanhu Khola, 1-3 190 DSCO DDC, VDC, Improvement Pipal Tara, Ghorneti, Titibang, Kauchhe, year Community Ghanabot, Bolamkhalchaur, Sivri, Khani Khola, Lam Danda 8 River bank Lahu Khola bank protection (2 km) 1-3 80 DSCO DDC, VDC, protection using baas, nigalo, uttis, aamriso etc. year Community 9 Others . Animals farming 1-3 DVO, DADO, Community, . Herbs production year DDC, VDC, District . Nursery establishment DWIDP Education Office, NGO, INGO

Submitted to UNDP - 137 - Prepared by ECONEPAL and NPAF Rukum

Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 10 Conclusions and Recommendations

Chapter 10 Conclusions and Recommendations

For Multi-hazard Risk Assessment, particularly landslide and flood hazard have been focused. Altogether, there was the risk sensitive land use plan prepration after convening the land use plan workshop in each VDC. During the MHRA; in case of Landslides the area is basically characterized by shallow failure mode. They are shallow in depth and translational failure mode. The landslide hazard mapping identified the highest number of landslide in Khalanga and Khara. During field survey, study team was reported that most of the landslides were triggered by intense rainfall. However, there are some cases of anthropogenic activities such as rural road construction without proper planning using heavy machine that help to initiate and trigger landslides in the monsoon. The flood and inundation had direct adverse impact on socio-economic impact. The study identifies, Simratu Bazar of Rungha and BaragiThati in Balakcha are highly flood prone area in the study area. Altogether, Khara-4, and Jhulkhet (near the border of Sankh and Chaukhawang VDC) are also notified for the highly flood prone area. It is identified some causative factors responsible to accelerate the vulnerable situation of hazard which are; Haphazard road construction and settlement, unmanaged urbanization, deforestation, poor quality of infrastructure, lack of appropriate technology, excess exploitation of rocks, gravel and sand, lack of bearing accountability, and lack of awareness. In case of socio-economic survey, agriculture is the main occupation and most of the people depending on subsistence agriculture. It is further identified, no opportunity has been provided to the children and teachers about the preparedness to cope with epidemic and fire hazards. Ignorance about bio-engineering can be noticed seeing the plantation works in old landslide zones. Similarly, the lack of shelters identification in those VDCs which were affected by the last year , Inadequacy of medicine and no regular presence of health workers in the health centres; no effective communication mechanism to communicate needs and requirements for rescue during disasters; lack of resources especially rich with rescued equipment with political venders at village level; lack of emergency fund; no proper network with media-especially community based radios and other means some more weaknesses accounting for the poor situation of the district. The whole Muglukhola Watershed is highly vulnerable to the landslide and for its risk reduction; there should be proper land use plan. The proposed land use plan identifies the potential options for the risk reduction by bioengineering options, terrace improvement, water source conservation etc. where, plantation and agro-forestry activities along with livelihood promotion activities will be highly significant in the area.

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Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 10 Conclusions and Recommendations

Annex-1 Socio-economic Survey Questionnaire

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Submitted to UNDP - 139 - Prepared by ECONEPAL and NPAF Rukum

Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 10 Conclusions and Recommendations

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Submitted to UNDP - 140 - Prepared by ECONEPAL and NPAF Rukum

Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 10 Conclusions and Recommendations

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Submitted to UNDP - 141 - Prepared by ECONEPAL and NPAF Rukum

Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 10 Conclusions and Recommendations

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@)= tkfO{+sf] v]tjf/ldf nufpg ;lsg] jfnL, t/sf/L tyf, kmnkm'nsf] ljj/0f lbg'xf];\ qm= ;= jfnLsf] lsl;d klxnf] k|fyldstf bf];|f] k|fyldstf t];|f] k|fyldstf rf}fyf] k|fyldstf kfFrf}+ k|fyldstf ! vfBGg afnL @ t/sf/L # kmnkm"n $ Uf}/ sfi7 ag k}bfj/ % kz'kfng df5fkfng @!= tkfO{+sf] s'g} gofF afnLgfnL nufpg] of]hgf 5 < tn lbOP cg';f/ ljj/0f lbg'xf];\ qm=;= vfBfGg afnL t/sf/L afnL kmnkm"n Uf}/ sfi7 ag k}bfj/ kz'kfng÷df5fkfng lsl;d If]qkmn lsl;d If]qkmn lsl;d If]qkmn lsl;d If]qkmn lsl;d ;+Vo f /If]qkmn ! @ # $ %

@@= kfgLsf] ;+sng tyf pkef]u qm=;= pkef]usf] k|sf/ ;|f]t ;+sng ug{ nfUg] ;do pknAwtf k|j[lQ ! lkpg] kfgL @ hgfj/nfO{ v'jfpg] kfgL # l;+rfO{sf] nflu ;|f]t: gbL jf vf]nf, d"n, kf]v/L, kfOkaf6, cGo -v'nfpg]_ pknAwtf: kof{Kt, cefj, 4G4 k|j[lQ: :yL/, a9\bf] qmd, 36\bf] qmd

@#=tkfO{+sf] kl/jf/sf s'g} ;b:o s'g} ;+3 ;+:yf tyf ;fdflhs sfo{df ;+nUg 5g < 5g\ 5}gg\ . olb 5g\ eg] lgDgfg';f/sf] ljj/0f lbg'xf];\ qm= ;+= ;+:yfsf] gfd ;b:o ;b:otfsf] k|sf/ sfd ug]{ If]q ;+nUg ultljlw s}lkmot ! ;fd'bflos jg k' d @ jrt tyf C0f ;d"x # o'jf Snj $ cfdf ;d"x % hn pkef]Qmf ;d"x ^ ;xsf/L & ;fd'bflos ;+:yf ÷ u};; * cGo sf]8 : 1. :yfgLo -uflj;leq_ 2. lhNnfleq 3. b]ze/ 4. cGo, -v'nfpg]_ 1. ;fdflhs ultljlw 2. ;fd'bflos a}7s, 3. /fhlglts a}7s ÷ sfo{zfnf 4. Snj a}7s ÷ultljlw 5. ;fdflhs ljsf; lgdf{0f 7. ;fj{hlgs ;'g'jfO{ 8. ;fd'bflos lg0f{o 9. cGo -v'nfpg]]______@$= clxn] tkfO{+n] pkef]u ul//xg'ePsf] ;]jfx¿sf] cj:yf / u'0f:t/sf] lgDgfg';f/ ljj/0f lbg'xf];

qm= ultljlw ÷;]jfsf] kx'Fr pknAwtf nfUg] cf};t Ufflj;df pknAw ;]jf ;]jfsf] u'0f:t/ (sf]8 s}lkmo ;+= ;do (sf]8 k|of]u ug)]{ k|of]u ug]{ t 5 5}g ) 3/fo;L pkof]usf ;]jfx¿ ! kfOkaf6 ljtl/t lkpg] kfgL @ Zf}rfno -k|fOj]6_ # ljh'nL $ 6]lnkmf]g÷ df]afOn % /]l8of] ^ 6]lnlehg & ;fdflhs tyf ;fj{hlgs :jf:Yo ;]jf * Kf|ylds ljBfno ( dfWolds ljBfno !) pdflj ÷ sn]h !! :jf:Yo ÷ pk :jf:Yo rf}sL

Submitted to UNDP - 142 - Prepared by ECONEPAL and NPAF Rukum

Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 10 Conclusions and Recommendations

!@ kl/jf/ lgof]hg tyf lzz' :ofxf/ s]Gb| !# lhNnf c:ktfn !$ oftfoft ;]jf !% ;]jf k|bfos ;+:yfx¿ !^ Uflj; sfof{no !& lhlj; sfof{no !* s[lif ;]jf s]Gb| !( kz';]jf s]Gb| @) ;xsf/L @! ljlQo ;+:yf a}+s @@ art tyf C0f ;d"x @# k|x/L rf}sL @$ u};; tyf ;fdflhs ;+:yf k"jf{wf/sf] cj:yf @% :yfgLo ahf/ @^ ;8s @& ljh'nL @* ;fj{hlgs 6]lnkmf]g @( AolQmut ;]jf #) k|Oe]6 :j:Yo ;]jf #! k|Oe]6 kz' ;]jf #@ wfdL emFfqmL ## ;'8]gL sf]8 : 1. 5, 2. 5}g. 1. /fd|f] , 2. l7s}, 3. ;fdfGo, 4. Yffxf 5}g @%= 3/fo;L pkef]u / vr{sf] ljj/0f qm= j:t' Dffqf (k|lt jif{_ d"No (¿) cfˆgf] pTkfbg -dfqf_ lsg]sf] -dfqf_ s}lkmot ;+= vfBfGg ! ds} @ wfg # ux'F $ sf]bf] % cfn' ^ bnxg & t]n ÷ 3Lp * b'Uw pTkfbg ( lrgL !) df;' ÷c08f !! lrof, skmL, sf]s !@ kmnkm"n t/sf/L !# /S;L, hfF8, r'/f]6 v}gL !$ cGo v'nfpg] u}/ vfB ;fdu|L !% n'ufkmf6f] !^ lzIff !& :jf:Yo !* oftfoft !( s//rGbf @) Hofnf @! ;fdflhs rf8kj{ @@ OGwg @# ljh'nL/dl§t]n @$ ;fj'g, sfOFof], Aof6L«, 6r{nfO6 cflb @% cGo v'nfpg'xf]; \ nufgL -kl5Nnf] % jif{df_

@^ hUuf lsGg

Submitted to UNDP - 143 - Prepared by ECONEPAL and NPAF Rukum

Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 10 Conclusions and Recommendations

@& hUuf ;'wf/ ug{ @* l;+rfO{sf] nflu @( 3/÷uf]7 agfpg #) v]tLkftLsf] nflu #! kz' kIfL lsGg #@ cGo -pNn]v ug]{_

@^= ljutdf k|fs[lts k|sf]kaf6 ePsf Iflt tyf gf]s;fgLsf] ljj/0f lbg'xf];\ qm= k|fs[lts k|sf]ksf] k|sf/ 36gf ePsf] Iflt / gf]S;fgL ;+= jif{ d[To' 3fOt] 3/ eTs]sf] huuf -/f]kgL_ afnL gf]S;fg hgfj/ cGo ¿_ gf]S;fg ;DklQ (¿) -;+Vof_ ! klx/f] @ Aff9L # e"Ifo $ ;'Vvf v8]/L % cl;gf ^ lxdkft÷lxdklx/f] & cfunfuL * ls/f tyf /f]u ( e"sDk ÷ cGo gf]6M ljutdf Iflt ePsf] ljj/0f eP, ;fdfGo cj:yfdf cfpg slt ;do nfUof] jf nfUg]5 < / ;fdfGo cj:yfdf Nofpg s:tf s:tf ljlw tyf pkfox¿ ckgfOof] < (migration, extensification or intensification of land, outside aid and grants)¿ ;s];Dd lj:t[t / dfqfTds ¿kdf pnn]v ug'{xf];\ @&= hnjfo' kl/jt{g ------;DaGwL wf/0ff tyf a'emfO{ qm= hnjfo'sf tTj kl/jt{gsf] dx;'; k|f]S;L ;"rs k|efj cg's'ngsf nflu ul/Psf ;+= pkfox¿ ! Tffkqmd @ aiff{ -jfli{fs_ # d';nwf/] jif{sf 36gf $ s'lx/f]sf] 9sfO % x':;' ^ lxdkft & t';f/f] * cfFwL a]x/L ( Rf6\ofË !) zLt nx/

afnLgfnL kfgLsf] ;|f]t, jg h}ljs ljljwtf, ljkb\, dfgj :j:Yo / k"jf{wf/df k/]sf] k|efj lj:t[t ¿kdf pNn]v ug{ clGtd k]hsf] k|of]u ug]{

@*= hnjfo' kl/jt{gsf] hf]lvd 36fpg ul/Psf pkfox¿ pNn]v ug'{xf]; . qm= ultljlwx¿ -pkfox¿_ nufgL s'g} aflx/L ;xof]u k|fKt ePsf] ;xof]usf] dfqf ;+ gub >lds eP, s'g ;+:yfaf6 gub >lds ! @ #

29= k|fs[lts k|sf]k eg]sf] s] xf] < ======

30= k|fs[lts k|sf]ksf] sf/)f s] xf] < ======

#!= af9L, klx/f], ls/f tyf /f]usf] k|sf]k tyf hf]lvd sd ug{ ckgfpg'kg]{ pkox¿ s] s] x'g ;S5g\ < ;emfj lbg'xf];\ .

Submitted to UNDP - 144 - Prepared by ECONEPAL and NPAF Rukum

Community Based Multi-Hazard Risk Assessment Muglu Khola Watershed in Rukum District Chapter 10 Conclusions and Recommendations

qm= ;+ pkfox¿ ultljlw of]ubfg ug]{ OR5f -gub jf lhG;L pNn]v ug]{_ ! @ #

#@= k|fs[lts k|sf]ksf] hf]lvd sd ug{] pkfox¿ < ======

qm= ;+ pkfox¿ ls|ofsnfk ug{ ;Sg] of]ubfg gub jf >d

! @ #

33= k|fs[lts k|sf]ksf] hf]lvd sd ug{] / lakbdf ;xof]u ug{] ;:+yfx¿sf] laa/)f ======

34= %}g eg] s:tf] ;:+yf xÚgÚ k%{ ======

35= k|fs[lts k|sf]ksf] hf]lvd sd ug{ tkfOsf] ;Úemfj ======wGojfb

Annex-2: Inventory for Purpose of Land Use Planning

Community Based Disaster Risk Management Project, Rukum Inventory for purpose of Land-use Planning

VDC -uflj;):…………………Ward no. (j8f +):…………Village/Tole(ufpF÷a:tL):………………………………….

Submitted to UNDP - 145 - Prepared by ECONEPAL and NPAF Rukum