SHIA_Landslide: developing a physically based model to predict shallow landslides triggered by rainfall in tropical environments
Trabajo de grado - Doctorado
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SummaryAbstract: Landslides are one of the main causes of human and economic losses worldwide. Therefore, landslide hazard assessment and the capacity to predict these phenomenon has been a topic of great interest within scientific community for implementation of early warning systems. Although, several models has been proposed to forecast shallow landslides triggered by rainfall, no model has yet incorporated geotechnical factors into a complete hydrologic model, one that simulates the storage and movement of rainwater through soil profile, providing multiple components that can be calibrated along with measurements of surface discharge and perched water table fluctuation. The present paper develops a conceptual and physically based model, named SHIA_Landslide, for shallow landslide prediction triggered by rainfall in tropical environments and complex terrains supported by geotechnical and hydrological aspects occurring over a basin wide scale. SHIA_Landslide is an original and significant contribution that offers a new perspective to analyses shallow landslide processes, incorporating a full and comprehensive distributed hydrological tank model that includes water storage in the soil, coupled with a geotechnical and classical analysis of infinite-slope stability under saturated conditions. SHIA_Landslide can be distinguished by: (i) the capacity to capture the surface topography and its effects concerning the overland flow and the concentration cells of subsurface flow; (ii) it uses DTM to establish the relationships among cells, geomorphologic parameters, slope angle, direction, etc., needed for the model; (iii) rainfall dataset can be incorporated with the spatial and temporal resolution preferred and available; (iv) continuous simulation for long periods of rainfall data (years) or event simulations for specific storms; (v) consider the effect of horizontal and vertical flow; (vi) is at a basin scale; (vii) includes a hydrologically complete water process that permits perched water table calibration. All these conditions of SHIA_Landslide make the model as an interesting tool to be implemented in early warning system, combined with realtime rainfall monitoring and dissemination of alerts and communication.
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