2. Development of Spatial Decision Support System for Landslide Vulnerability Study, Management & Mitigation By L.P.Sharma, L.P.Sharma,

3. Contents of presentation Data Collection Data Collection Digitization, attribution, edition & updation Digitization, attribution, edition & updation Assignment of Weights on Each parameters Assignment of Weights on Each parameters Analysis Analysis Buffer Analysis Buffer Analysis Overlay Analysis Overlay Analysis Calculation of Landslide Information Value on the basis of weights assigned. Calculation of Landslide Information Value on the basis of weights assigned. Refinement of Study Area for detailed investigation Refinement of Study Area for detailed investigation Study of role of Soil Parameters in the refined study areaa Study of role of Soil Parameters in the refined study areaa

4. Works Done So Far Data Collection Data Collection  Geological Data (Rock Type, Foliation) (Mines & Geology Department, Govt. of Sikkim) (Mines & Geology Department, Govt. of Sikkim)  Landuse & Land Cover Data (GIS Div. NIC HQ., New Delhi) (GIS Div. NIC HQ., New Delhi)  Road Network (GIS Div. NIC HQ., New Delhi)  Drainage Network (GIS Div. NIC HQ., New Delhi)  Soil Parameters Map (GIS Div. NIC HQ., New Delhi)

5. Landslide is a disaster of Big Concern in the hilly states. Landslide is a disaster of Big Concern in the hilly states. Since 1968 Sikkim has witnessed various landslide hazards that tool the lives of many with tremendous loss to public and private properties and physical as well as mental disturbance in public lives. Since 1968 Sikkim has witnessed various landslide hazards that tool the lives of many with tremendous loss to public and private properties and physical as well as mental disturbance in public lives. Landslide probability is studied in many countries using the Remote Sensing and Geographical Information System Tools and Techniques. Landslide probability is studied in many countries using the Remote Sensing and Geographical Information System Tools and Techniques.

6. Factors Causing Landslides CONDITIONING FACTORS CONDITIONING FACTORS Slope Slope Rock Formation Rock Formation Soil Characteristics Soil Characteristics Land Use and Land Cover Land Use and Land Cover Geomorphology Geomorphology Seismicity Seismicity Tectonic Activities Tectonic Activities TRIGGERING FACTORS TRIGGERING FACTORS Anthropogenic Activities Anthropogenic Activities Deforestation Deforestation Road Construction Road Construction Unmanaged Road Condition and Utilization. Unmanaged Road Condition and Utilization. Unmanaged Drainage System Unmanaged Drainage System Rainfall Rainfall Earthquake Earthquake

7. Data Used Sl. No. Name of Thematic Layer Map Scale Data Source 1 Slope Map 1:50,000 DEM/50k Topo Map 2 Land Use & Forest 1:50,000NIC-GIS 3Geology1:250,000 GSI/Mines & Geology 4 Soil Map 1:50,000NIC-GIS 5 Road Map 1:50,000NIC-GIS 6 Drainage Map 1:50,000NIC-GIS 7 1:25000 Topo- Sheet 1:25000RMDD

9. Digital Terrain Model-East Sikkim

19. After Overlaying all the Layers

20. Division into Revenue Circles

21. Calculation of Landslide Information Value for Each Parcel 15 15 LSIV= Σ W i LSIV= Σ W i i=1 i=1Where W 1 to W 8 = weight on depth, inner texture, erosion, stoniness, drain, slope, depth texture and hydraulic conductivity of the soil W 9 to W 15 = weight on rock type, geological fault, foliation, slope, buffered drainage, buffered road and land use.

22. Categorization of Parcels based on Landslide Information Value LSIV<=14 LSIV<=14 Stable/Data Unknown Zone: No occurrence of landslide. However, parcels with non-availability of data may also fall under this category and it demands a detailed study at micro or meso level (<1:5000 scale) to declare these are as stable and safe zone. Stable/Data Unknown Zone: No occurrence of landslide. However, parcels with non-availability of data may also fall under this category and it demands a detailed study at micro or meso level (<1:5000 scale) to declare these are as stable and safe zone. LSIV>14 and LSIV 14 and LSIV <=23 Unstable Zone: Least Probability of Landslide Unstable Zone: Least Probability of Landslide LSIV>23 and LSIV 23 and LSIV<=27 Vulnerable Zone: Higher Probability of Landslide Vulnerable Zone: Higher Probability of Landslide LSIV>27 LSIV>27 Most Vulnerable Zone: Highest Probability of Landslide Most Vulnerable Zone: Highest Probability of Landslide

23. REFINED STUDY AREA: Sang Revenue Circle-Block Boundaries Over DTM

24. Soil Maps- Sang Revenue Circle

28. Sl.No No of Polygons Area in Hectares. Percentage Area Stability Zone 139197.6715%Stable 2158136.7421%Unstable 3486175.8127%Vulnerable 4466240.9237% Most Vulnerable Total1401651.14100%

29. Sl.No No of Polygons Area in Hectares. Percentage Area Stability Zone 1000%Stable 2181104.2437%Unstable 312476.0727%Vulnerable 4171101.4236% Most Vulnerable Total476281.73100%

30. Sl.No No of Polygons Area in Hectares. Percentage Area Stability Zone 125925.069%Stable 215822.278%Unstable 372689.0832%Vulnerable 4806141.9851% Most Vulnerable Total1949278.39100%

31. Sl.No No of Polygons Area in Hectares. Percentage Area Stability Zone 100.000%Stable 27213.448%Unstable 321870.5642%Vulnerable 426284.0150% Most Vulnerable Total552168.01100%

32. Sl.No No of Polygons Area in Hectares. Percentage Area Stability Zone 100.000%Stable 23373.7236%Unstable 394100.3549%Vulnerable 43830.7215% Most Vulnerable Total165204.79100%

33. Sl.No No of Polygons Area in Hectares. Percentage Area Stability Zone 100.000%Stable 212440.6222%Unstable 3331134.7973%Vulnerable 4479.235% Most Vulnerable Total502184.64100%

34. Sl.No No of Polygons Area in Hectares. Percentage Area Stability Zone 112413.318%Stable 2184.993%Unstable 323553.2532%Vulnerable 430694.8557% Most Vulnerable Total683166.40100%

35. Sl.No No of Polygons Area in Hectares. Percentage Area Stability Zone 114224.2411% Stable/Unknown Data 220128.6513%Unstable 3660110.2050%Vulnerable 433757.3026% Most Vulnerable 1340220.39100%

36. Sl.No No of Polygons Area in Hectares. Percentage Area Stability Zone 119319.319%Stable 212123.6010%Unstable 338340.7719%Vulnerable 4797130.8861% Most Vulnerable Total1494214.56100%

37. Sl.No No of Polygons Area in Hectares. Percentage Area Stability Zone 150.000Stable 212836.8619%Unstable 345695.0649%Vulnerable 435762.0832% Most Vulnerable Total946193.99100

38. Sl.No No of Polygons Area in Hectares. Percentage Area Stability Zone 100.000Stable 213115.298%Unstable 363591.7448%Vulnerable 443784.1044% Most Vulnerable Total1203191.13100%

40. Phygyong Phygyong Tirkutam Tirkutam Nazitam NazitamSl.No No of Polygons Area in Hectares. Percentage Area Stability Zone 100.000Stable 28534.9627Unstable 319482.0361Vulnerable 44617.4813 Most Vulnerable Total325134.47100 Sl.No No of Polygons Area in Hectares. Percentage Area Stability Zone 100.000%Stable 216539.3717%Unstable 3419141.2861%Vulnerable 425950.9522% Most Vulnerable Total843231.60100% Sl.No No of Polygons Area in Hectares. Percentage Area Stability Zone 100.000Stable 25686.4735Unstable 3146135.8855Vulnerable 44724.7110 Most Vulnerable Total249247.05100

41. Sl.No No of Polygons Area in Hectares. Percentage Area Stability Zone 100.000%Stable 2437192.5619%Unstable 3995344.5834%Vulnerable 4924476.3347% Most Vulnerable 23561013.46100%

42. Landslide Probability Maps- Revenue Circle Wise

45. Landslide Probability Map- Duga Revenue Circle

46. Landslide Probability Maps-Revenue Circle

51. Landslide Probability Map-Revenue Circle

54. Study of Role of Soil Statistics in Landslide Vulnerability Methodology Followed:  After the study area is divided into smallest number of polygons with respect to all the available thematic input layers, weights on eight important soil parameters are separately assigned and then the soil stability value (SSV) is computed.  Zonation is done based on SSVs to prepare SSV- zonation map  The SSV-zonation map is compared with LSIV- zonation map produced with Multi Criteria Stability Value.  Percentage of agreement between the two maps is calculated.

55. Study Area..

57. Soil Parameters Considered Sl.No Soil Depth Stability Stability Weight 1.Deep Most Unstable 4 2 Moderate Deep Unstable3 3 Moderate Shallow Stable2 4Shallow Most Stable 1 Sl.No Soil Texture Stability Stability Weight 1 Sandy/Coarse/Gravel Loam Most Unstable 3 2 Silty Loam Moderately Stable 2 3 Clay/Fine Loam Stable1

58. Soil Parameters Considered.. Sl.No Soil Erosion Stability Stability Weight 1.Severe Unstable Unstable3 2Moderate Moderately Stable 2 3LowStable1 Sl.No Soil Surface Texture Stability Stability Weight 1. Sandy/Coarse/Gravel Loam Most Unstable 3 2 Silty Loam Moderately Stable 2 3 Clay/Fine Loam Stable1

59. Soil Parameters Considered.. Sl.No Soil Stoniness Stability Stability Weight 1.Slight/Low Most Unstable 3 2ModerateUnstable2 3HighStable1 Sl.No Soil Slope Stability Stability Weight 1. Very Steep (>50%) Most Unstable 3 2 Steep (30% to 50%) Unstable2 3 Moderate Steep (15% to 30 % Stable1

60. Soil Parameters Considered.. Sl.No Soil Drainage Stability Stability Weight 1. Excessively Drained Unstable3 2 Somewhat Excessively Drained Moderately Stable 2 3 Well Drained Stable1 Sl.No Hydraulic Conductivity Stability Stability Weight 1.High Unstable Unstable3 2Moderate Moderately Stable 2 3LowStable1

61. Parameter Wise Thematic Maps

63. Calculation of Soil Stability Value For each polygon of the study area, the Soil Stability Value (SSV) is calculated as 8 SSV= ΣWi i=1 i=1Where W1 = stability weight of the soil based on the depth of the soil W1 = stability weight of the soil based on the depth of the soil W2= stability weight of the soil based on the texture of the soil W2= stability weight of the soil based on the texture of the soil W3= stability weight of the soil based on the surface texture of the soil W4= stability weight of the soil based on the erosion of the soil W5= stability weight of the soil based on the stoniness of the soil W6= stability weight of the soil based on the slope of the soil W7= stability weight of the soil based on the drain of the soil W8= stability weight of the soil based on the hydraulic conductivity of the soil

64. Zonation on SSV Sl. No No of Polygons Area in Square KM. Soil Stability Value (SSV) Stability Zone 162UnknownStable/Unknown 24819.8415-16Unstable 3175.9217-19Vulnerable 4141120-22 Most Vulnerable Total8538.76100

65. Calculation of Multi-criteria Stability Value (LSIV) 5LSIV=SSV+ΣWp P=1 P=1Where W1 is the stability weights based on the rock type and the geological factor W1 is the stability weights based on the rock type and the geological factor W2 is the stability weights based on the land use type W2 is the stability weights based on the land use type W3 is the stability weights based on slope of the area W4 is the stability weights based on availability of roads within a buffer distance of 40 meters W5 is the stability weights based on availability of unprotected drainage within a buffer distance of 30 meters

66. Zonation on Landslide Information Value (LSIV) Sl. No No of Polygons Area in Square KM. Landslide Information Value (LSIV) Stability Zone 111141.98UnknownStable/Unknown 2349911.984-14Unstable 3622614.9025-28Vulnerable 436459.929-36 Most Vulnerable Total1448438.76100

67. Zonation Maps based on SSV & LSIV

68. Agreement Between SSV & LSIV based Vulnerability Zones Sl.No. Stability Zones Area (Sq.Km) based on SSV Area (Sq.Km) based on LSIV Percentage of Agreement 1Unknown21.98 2 Less Vulnerable 19.8411.9860% 3 Moderately Vulnerable 5.9214.9839% 4 Most Vulnerable 119.990% Sum38.7638.7672%

69. Future Plans Preparation of Zonation maps based on Information Value theory, Regression Model, Fuzzy Logic, ANN, Monte-Carlo Simulation etc. Preparation of Zonation maps based on Information Value theory, Regression Model, Fuzzy Logic, ANN, Monte-Carlo Simulation etc. Development of Software Model (SDSS) for zonation, management & mitigation of landslide hazard. Development of Software Model (SDSS) for zonation, management & mitigation of landslide hazard.