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  5. Flow routing algorithms and landslide modelling

Flow routing algorithms and landslide modelling

Author(s)
Rulli, Maria Cristina
Nardi, Fernando
Santini, Monia
Petroselli, Andrea  
Grimaldi, Salvatore
Date Issued
2007
Type
Other
Abstract
The physical processes governing shallow landslide triggering can be ascribed to hydrological and geomechanic forcings. Modelling shallow landslide triggering via hydrogeomorphic spatially distributed model requires to extract for any location in the river basin the geomorphic and hydrologic attributes. The Digital Elevation Models allow an easy quantification of several morphologic and hydrologic landscape properties e.g.primary attributes such as slope, aspect, plan and profile curvature, flow path lengths and secondary attributes such as topographic index and drainage area per unit contour length. Although all of these attributes are used when assessing the hydrological forcings to shallow landslide triggering, it has to be stressed that the flow direction and accumulation algorithm plays a significant role in the accurate physical representation of those waterdriven slope instability phenomena. In this study three flow direction algorithm (D8, D8- LTD and D ) are applied in conjunction with two DEM correction techniques for the treatment of pits and flat areas (ArcInfo standard approach and PEM4PIT), in order to determine the terrain attributes needed as input for the hydrogeomorphic model Shalstab. Quantitative results corresponding to the implementation of the different hydrogeomorphic terrain analysis algorithms on different case studies provide an objective framework for testing the accuracy and performance of the different schemes in relation to the DEM-based hydrogeomorphic prediction of shallow landslides.
Citation
Rulli, M.C. et al. 2007. Flow routing algorithms and landslide modelling. AGU Fall Conference (San Francisco, CA, 10-14 December 2007)
Handle
http://hdl.handle.net/2067/1416
File(s)
Thumbnail Image
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AGU_2007_Flow Routing_Landslide.pdf

Size

2.22 MB

Format

Adobe PDF

Checksum (MD5)

1b625b39231fa6013c30a8d9693df0f7

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