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Identifying landslide triggers and estimating inundation zones in the Monte Sano Nature Preserve Applications of Spatial Analysis tools and ArcInfo Workstation.

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Presentation on theme: "Identifying landslide triggers and estimating inundation zones in the Monte Sano Nature Preserve Applications of Spatial Analysis tools and ArcInfo Workstation."— Presentation transcript:

1 Identifying landslide triggers and estimating inundation zones in the Monte Sano Nature Preserve
Applications of Spatial Analysis tools and ArcInfo Workstation software ATS 515 – Advanced Topics in GIS Robert Griffin, Instructor 28 February 2012 Eric R. Anderson University of Alabama in Huntsville Department of Atmospheric Science

2 Lesson Outline Overall goals and specific objectives
Context and important concepts Pinpoint landslide triggers Simulate rock avalanche inundation zones Visualize results (time permitting) Discuss the methods and results

3 Overall goals and specific objectives
Pinpoint locations most prone to slope failure Delineate rock fall inundation hazard zones Perform basic surface and hydrology analyses of high resolution digital terrain model (DTM) Predict the locations of unstable conditions as a function of slope and upslope contributing area Simulate rock avalanches to estimate inundation hazard areas (time permitting) Visualize results in ArcScene.

4 Context and important concepts
Annual losses attributed to landslides are greater than any other natural disaster except hurricanes (Lee 2009) $3 billion + annually in the US (USGS 2006) $10 billion + annually worldwide (Lee 2009) Where they happen Types of landslides

5 Landslide potential in the U.S.
Red – very high Yellow – high green – moderate (Abbott 2012)

6 Classification of Mass Movements
Speed and water content (Abbott 2012) Insert Table 15.2

7 Classification of Mass Movements
Downward – falling or subsiding Downward and outward – sliding and flowing (Abbott 2012)

8 Falls Elevated rock mass separates along joint, bedding or weakness and falls downward through air in free fall until hitting the ground, bouncing and rolling Yosemite National Park, California, 1996 162,000 ton granite mass slid and launched into air, fell 500 m before hitting valley floor Blast knocked down 1,000 trees 50 acres covered with inch-thick layer of dust One person killed by tree (Abbott 2012)

9 Flows La Conchita, CA, Slump, Debris Flows, 1995, 2005
Cliff behind La Conchita is ancient landslide 1995: two slow landslides destroyed 14 houses, no deaths 2005: 15% of 1995 slide mass remobilized into highly fluid debris flow, at 10 m/sec, went over retaining wall, destroyed 13 houses, damaged 23 others, killed 10 people (Abbott 2012) 1995 2005

10 Landslide Susceptibility in Alabama
(extract of Madison County) Moderate to Very High susceptibility throughout Monte Sano State Park and the Land Trust By: Sandy M. Ebersole, Steven Driskell and Anthony M. Tavis. Geologic Mapping and Hazards Section, Geological Survey of Alabama, December 2011.

11 Landslide triggers Converging upslope contributing areas
Failure slope threshold Regions of continuous steep slopes (Montgomery and Dietrich 1994; Dietrich et al 1998; in Griswold 2012)

12 Inundation hazard zones
LAHARZ software For a given volume, V, Objectively delineates hazard zones based on elevation Cross-sectional inundation area, A Planimetric inundation area, B Iverson et al 1998

13 Inundation hazard zones
(Iverson, USGS)

14 Exercises Part I – identify trigger cells in ArcGIS Desktop
Part II – delineate hazard zones using LAHARZ in Arc Workstation

15 Field observations Environment of trigger points
Evidence of past landslides Evidence of slumping

16 Possible slumping

17 Channel erosion / deposition

18 Visualize the results

19 Visualize the results Open the following in ArcScene:
Original DEM Hillshade Triggers shapefile LAHARZ outputs For all layers, set Base Heights to DEM Right click on layer/Properties/Base Heights/ Floating on Custom Surface

20

21 Discussion What were our inputs for a) trigger and b) inundation estimates? What are the assumptions? What are the uncertainties, and how do we deal with these? How can we improve these models? a) DTM and user-defined thresholds for slope, flow accumulation, and upslope contributing area b) DTM, volumes 2. Basing inundation zone measurement on an average of observed cases; LAHARZ does not account for snowball effect (increasing volume); assuming that these things begin in stream or channel (rather than a far-off slope) – this can be remedied - to start wherever you want, just include more “stream” cells from the flow accumulation definition 3. Vertical and horizontal error in DTM – greater uncertainty in flow path once debris reaches flat terrain (fewer contours / unit area in flat than steep terrain—LiDar greatly improves this). Volumes we use are just estimates. 4. Include other factors like geology, precipitation, seismic activity; consider the timing of these events rather than just the “where”

22 Acknowledgements Julia Griswold, Steve Schilling, Jon Major, USGS
Sundar Christopher, Robert Griffin, Tom Sever, Kevin Knupp, Stephanie Mullins, Africa Flores, UAHuntsville Daniel Irwin, Jason Kessler, Gwen Artis, Ashutosh Limaye, Francisco Delgado, Burgess Howell, Karthik Srinivasan, NASA/SERVIR Carrie Stokes, Michelle Jennings, Orlando Altamirano, Ruben Aleman, USAID Emilio Sempris, Emil Cherrington, Antonio Clemente, Alejandro del Castillo, CATHALAC Manuel Diaz, Giovanni Tobar, Karla Marroquín, Luis Mixco, SNET/MARN (El Salvador)


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