Natural Hazards Assessment in the Everest Region Natural Hazards - - PowerPoint PPT Presentation

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Natural Hazards Assessment in the Everest Region Natural Hazards - - PowerPoint PPT Presentation

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Natural Hazards Assessment in the Everest Region Natural Hazards Assessment in the Everest Region using Hydrodynamic and Geo-Spatial Tools using Hydrodynamic and Geo-Spatial Tools Birendra Bajracharya bbajracharya@icimod.org GIS Specialist

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Natural Hazards Assessment in the Everest Region using Hydrodynamic and Geo-Spatial Tools Natural Hazards Assessment in the Everest Region using Hydrodynamic and Geo-Spatial Tools

Birendra Bajracharya

bbajracharya@icimod.org GIS Specialist International Centre for Integrated Mountain Development (ICIMOD)

28 March 2006, Islamabad, Pakistan

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The Everest Region The Everest Region

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A DSS Framework for Ecosystem Management A DSS Framework for Ecosystem Management

Anthropic system Tourism system Subsistence economy Energy Waste Pastoral system Stone extraction Timber/ firewood extraction Agricultural system Natural system GLOF hazard Landslides Avalanche Infrastructure Agriculture land Forest land External driver class Internal driver class Pressure class Impact class Land system for ecosystem territorial management Land units Aquatic system Terrestrial system

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  • Modeling GLOF and simulation
  • Inventory and distribution of landslides
  • Hazard Mapping
  • Modeling GLOF and simulation
  • Inventory and distribution of landslides
  • Hazard Mapping

Mapping Natural Hazards for DSS Mapping Natural Hazards for DSS

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  • Fragile geological conditions
  • Great elevation differences
  • Steep sloping terrain
  • Fragile geological conditions
  • Great elevation differences
  • Steep sloping terrain

Why are the Mountains Hazardous? Why are the Mountains Hazardous?

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  • Sources of the headwaters of many great rivers
  • Glacial lakes are formed by accumulation of water from the

melting of snow and ice cover and by blockage of end moraines

  • Sudden break of a moraine may generate the discharge of

large volumes of water and debris causing floods (GLOFs) After the severe impact of the 1985 Dig Tsho GLOF, glacial lakes and the GLOF phenomenon in the Nepal Himalayas drew great attention

Glaciers and Glacial Lakes Glaciers and Glacial Lakes

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Birds-eye view showing the remnants of Dig Tsho Glacial Lake, Langmoche Glacier at the slope and the debris along the gully after the GLOF of 1985 (WECS 1991) Birds-eye view showing the remnants of Dig Tsho Glacial Lake, Langmoche Glacier at the slope and the debris along the gully after the GLOF of 1985 (WECS 1991) Dig Tsho (Langmoche) Glacial Lake burst on 4 August 1985, destroying the nearly completed Namche Hydropower Plant (estimated loss of US $1.5 million), 14 bridges, trails, cultivated land and loss of many lives. Dig Tsho (Langmoche) Glacial Lake burst on 4 August 1985, destroying the nearly completed Namche Hydropower Plant (estimated loss of US $1.5 million), 14 bridges, trails, cultivated land and loss of many lives.

Glacial Lake Outburst Flood (GLOF) Glacial Lake Outburst Flood (GLOF)

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Inventory of glaciers, glacial lakes and GLOF Inventory of glaciers, glacial lakes and GLOF

Dudh Koshi Basin 278 Glaciers (482.2 sq. Km) 473 Glacial lakes (13.07 sq. Km) 9 Potentially dangerous lakes

(Lumding Tsho, Dig Tsho, Chokarma Cho, Imja Tsho, Tam Pokhari, Hungu Lake, East Hungu 1, East Hungu 2, and West Chamjang)

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Potentially dangerous lakes Everest region Potentially dangerous lakes Everest region

Three potentially dangerous lakes identified in the Everest region – Dig Tsho, Imja and Lumding Tsho

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Growth of Imja and Digtsho Growth of Imja and Digtsho

Imja: Based on 2001 data (Yamada) Area = 0.83 Km2

  • Avg. depth = 41m
  • Max. depth = 90 m

Water volume = 35.8 million m3 Increase in area between 1991-2001 = 0.23 Km2 Dig Tsho: Area in 1962 = 0.2 Km2 in 1983 = 0.6 Km2 (before outburst) in 2001 = 0.35 km2

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15 December 1962 Corona 15 December 1962 Corona

Imja Glacier Imja Glacier

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02 December 1983 Space Shuttle 02 December 1983 Space Shuttle

Imja Glacier and Glacial Lake Imja Glacier and Glacial Lake

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19 March 2001 IRS 1D Pan 19 March 2001 IRS 1D Pan

Imja Glacier and Glacial Lake Imja Glacier and Glacial Lake

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29 November 2001 IKONOS Multispectral 29 November 2001 IKONOS Multispectral

Imja Glacier and Glacial Lake Imja Glacier and Glacial Lake

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IKONOS image draped over DEM IKONOS image draped over DEM

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Field Photo, April 2005 (Arun Shrestha) Field Photo, April 2005 (Arun Shrestha)

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Field Photo (Arun Shrestha) Field Photo (Arun Shrestha)

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Hydro-dynamic modeling of GLOF Hydro-dynamic modeling of GLOF

Topographic Information

  • Topographic Information (DEM)
  • Extraction of geometric and Hydraulic Information

(HEC GeoRAS)

  • Topographic Information (DEM)
  • Extraction of geometric and Hydraulic Information

(HEC GeoRAS)

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Bathymetry of Imja Bathymetry of Imja

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Input parameters Input parameters

Topographic Information

Cohesiveness 34 34 Internal Friction Angle (ø) 0.15 0.15 Manning's n of outer core 0.4 0.4 Porosity kg/m2 2000 2000 Unit Weight m 650 600 Dam length m 600 210 Dam width 1:6 1:1.7 Dam outside slope 1:8 1:0.47 Dam outside slope masl 4960 4360 Dam bottom elevation masl 5030 4395 Dam top elevation m 90 42.9 Lake maximum depth km2 0.86 0.4 Lake surface area Imja Dig Tsho Unit Values for GLOF Simulation Parameters/Input Data

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Modeling GLOF Modeling GLOF

Topographic Information

  • Dam Breach (NWS-BREACH)
  • Dam Breach (NWS-BREACH)
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Modeling GLOF Modeling GLOF

Topographic Information

  • Dam Breach model outputs
  • Dam Breach model outputs

30.5 231.0 m Final Width of the Top of the Breach 65.2 35.0 m Final Depth of the Breach 4982.3 4373.6 masl Final Water Level 5030.6 4395.0 masl Initial Water Level 3.2 2.0 hr Duration of the Outflow (Tout) 5463 5613 m3/s Maximum Outflow (Qmax) Imja Dig Tsho Unit Breach Output

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Modeling GLOF Modeling GLOF

Topographic Information

  • Flood Routing
  • Flood Routing

2 3 4 5 6 7 8 9 5 10 15 20 25 30 35 40 Distance from Lake (Km) Flood Depth (m) Dig Tsho 2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00 10.00 10 20 30 40 50 Distance from Lake (Km) Flood Depth (m) Imja

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Modeling GLOF Modeling GLOF

Topographic Information

  • Flood Routing
  • Flood Routing
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Modeling GLOF Modeling GLOF

Topographic Information

  • Comparison of model and observed values (Dig Tsho)
  • Comparison of model and observed values (Dig Tsho)
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If Imja Breaks… If Imja Breaks…

Topographic Information

Simulation of GLOF scenario from Imja Simulation of GLOF scenario from Imja

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If Imja Breaks… If Imja Breaks…

Topographic Information

Simulation of GLOF scenario from Imja Simulation of GLOF scenario from Imja

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Topographic Information

If Imja Breaks… If Imja Breaks…

GLOF vulnerability at Dinboche GLOF vulnerability at Dinboche

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Flood arrival time (Imja) Flood arrival time (Imja)

5.71 5275.00 33.60 Nakchung 8.13 5297.00 30.00 Ghat 8.01 5304.00 28.80 Sano Gumela 7.76 5310.00 27.60 Thulo Gumela 8.47 5315.00 26.40 Gumela 9.29 5316.00 25.20 Bengkar 8.68 5329.00 22.80 Confluence 6.76 5374.00 14.40 Panboche 5.77 5382.00 12.00 Orse 8.12 5387.00 10.80 Chure 5.81 5401.00 8.40 Dinboche 3.92 5419.00 6.00 Dhumsum 5458.00 0.00 Imja lake outlet Flood Depth(m) Discharge (m3/s) Time(min) Place

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Flood arrival time (Dig Tsho) Flood arrival time (Dig Tsho)

5.16 2145.00 60.60 Nakchung 5.49 2577.00 30.00 Confluence 4.97 2835.00 21.60 Pare 4.89 2888.00 21.60 Power House 5.42 2897.00 21.60 Thame 3.74 3100.00 17.40 Thyangmoche 4.58 3300.00 13.20 Hungmo 5.32 3592.00 9.00 Kamthuwa 4.19 4986.00 4.80 Langmucha 6.17 5610.00 0.0 Dig Tsho outlet Flood Depth(m) Discharge (cumec) Time(min) Place

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Landslide Hazard Zonation Landslide Hazard Zonation

  • Landslide Inventory
  • Landslide Distribution
  • Slope Stability Analysis
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Landslide Inventory and Distribution Landslide Inventory and Distribution

  • Topographic Maps (1:50000)
  • Satellite Images (IKONOS, 2001)
  • Aerial Photographs (Stereo Interpretation)
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Landslide Inventory and Distribution Landslide Inventory and Distribution

  • Satellite Images

(IKONOS, 2001)

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Landslide Inventory and Distribution Landslide Inventory and Distribution

  • Topographic Maps

(1:50000)

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Landslide Inventory and Distribution Landslide Inventory and Distribution

  • Aerial Photographs

(Stereo Interpretation)

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Landslide Inventory and Distribution Landslide Inventory and Distribution

Area 19 Average Width 18 Average Length 17 Longitude 16 Latitude 15 Weathering Condition 14 Slide Material Type (Lithology) 13 Slope Form & Aspect 12 Landslide Body 11 Landslide Depth 10 Contributing Factor 9 Slide Occur In 8 Hydro Condition 7 Estimated From 6 Slide Activity 5 Vegetation Condition 4 Type of Movement 3 Type of Material 2 LandslideID 1 Field Name Serial No

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Slope Instability Hazard Slope Instability Hazard

Black Gneisses Himalayan Gneisses Migmatic Ortho Gneisses Augen Gneisses Leuco-Granite Everest Meta Sediments < 20.8 < 42.5 < < 24.4 < 42.2 < < 21.8 <42 < < 18.5 < 33 < Bare soil Rocks Moraine Snow Water

Lithology Land cover Slope Criteria

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Lithology

Slope Instability Hazard Slope Instability Hazard

  • Compiled from literature

review and existing data sources

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Slope

Slope Instability Hazard Slope Instability Hazard

  • Derived from DEM
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Slope Instability Hazard Slope Instability Hazard

Legend Legend

Alpine grass and shrub Alpine grass and shrub Alpine meadow Alpine meadow Bare soil Bare soil Grass Grass Lower temperate broadleaf Lower temperate broadleaf Moraine Moraine Rock Rock Settlement/ agriculture Settlement/ agriculture Shrub Shrub Snow Snow Sub alpine mixed Sub alpine mixed Upper temperate conifer Upper temperate conifer Water Water

Land cover

  • Based on Landsat ETM+

(30 Oct 2000)

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Slope Instability Hazard Slope Instability Hazard

Instability

Stable Low Moderate High

  • Result from the criteria

based on lithology, slope and land cover

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Limitations Limitations

  • Topographical information derived from DEM generated from

contour maps – all intricacies can not be captured

  • Model parameters (geotechnical and hydraulic) either estimated or

taken from similar studies

  • Only single scenario considered for each GLOF simulation - a

systematic sensitivity analysis needed select most sensitive parameters

  • Detailed geological data of the area not available
  • Information on land use practices not available
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Conclusion Conclusion

  • Natural processes have significant impact on ecosystem health as

well as livelihood of local inhabitants

  • Modeling and simulation provides cost effective means to

understand the extent and impact of possible hazards due to these processes

  • Hazard maps incorporating socio-economic and bio-physical

information provide valuable information for decision making in developing management strategies, tourism plans and physical infrastructure

  • DSS based on Geo-Informatics and modeling tools can provide

effective support in planning and monitoring activities

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Acknowledgement Acknowledgement

  • Italian Partnership Initiative
  • Dr. Arun Bhakta Shrestha, Lokap Rajbhandari
  • Sagar Ratna Bajracharya, Samjwal Ratna Bajracharya
  • Dr. Lhakpa Norbu Sherpa