This study employs a distributed eco-hydrological-landslide model, the tRIBS-VEGGIE-Landslide, to evaluate the influence of terrain resolution on the hydro-geomorphological processes involved in slope stability analysis. The model implements a Triangulated Irregular Network (TIN) to describe the topography starting from a grid-DEM. Five grid-DEM resolutions of the case study basin, i.e., 10, 20, 30 and 70 m, are used to derive the corresponding TINs. The results show that using irregular meshes reduces the loss of accuracy with coarser resolutions in the derived slope distribution in comparison to slope distributions estimated from the original grid-based DEM. From a hydrological perspective, the impact of resolution on soil moisture patterns and on slope stability is significant mostly when lateral water exchanges are allowed. The degrading of resolution leads to a reduction of the predicted unstable areas, with respect to the highest resolution case, from about 15% (20 m) to more than 40% (70 m).
Implications of terrain resolution on modeling rainfall-triggered landslides using a TIN- based model
Arnone E.
Primo
;
2021-01-01
Abstract
This study employs a distributed eco-hydrological-landslide model, the tRIBS-VEGGIE-Landslide, to evaluate the influence of terrain resolution on the hydro-geomorphological processes involved in slope stability analysis. The model implements a Triangulated Irregular Network (TIN) to describe the topography starting from a grid-DEM. Five grid-DEM resolutions of the case study basin, i.e., 10, 20, 30 and 70 m, are used to derive the corresponding TINs. The results show that using irregular meshes reduces the loss of accuracy with coarser resolutions in the derived slope distribution in comparison to slope distributions estimated from the original grid-based DEM. From a hydrological perspective, the impact of resolution on soil moisture patterns and on slope stability is significant mostly when lateral water exchanges are allowed. The degrading of resolution leads to a reduction of the predicted unstable areas, with respect to the highest resolution case, from about 15% (20 m) to more than 40% (70 m).File | Dimensione | Formato | |
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