SHIA_Landslide: a distributed conceptual and physically based model to forecast the temporal and spatial occurrence of shallow landslides triggered by rainfall in tropical and mountainous basins

Landslides are a main cause of human and economic losses worldwide. For this reason, landslide hazard assessment and the capacity to predict this phenomenon have been topics of great interest within the scientific community for the implementation of early warning systems. Although several models have been proposed to forecast shallow landslides triggered by rainfall, few models have incorporated geotechnical factors into a complete hydrological model of a basin that can simulate the storage and movement of rainwater through the soil profile. These basin and full hydrological models have adopted a physically based approach. This paper develops a conceptual and physically based model called open and distributed hydrological simulation and landslides—SHIA_Landslide (Simulación HIdrológica Abierta, or SHIA, in Spanish)—that is supported by geotechnical and hydrological features occurring on a basin-wide scale in tropical and mountainous terrains. SHIA_Landslide is an original and significant contribution that offers a new perspective with which to analyse shallow landslide processes by incorporating a comprehensive distributed hydrological tank model that includes water storage in the soil coupled with a classical analysis of infinite slope stability under saturated conditions. SHIA_Landslide can be distinguished by the following: (i) its capacity to capture surface topography and effects concerning the subsurface flow; (ii) its use of digital terrain model (DTM) to establish the relationships among cells, geomorphological parameters, slope angle, direction, etc.; (iii) its continuous simulation of rainfall data over long periods and event simulations of specific storms; (iv) its consideration of the effects of horizontal and vertical flow; and (vi) its inclusion of a hydrologically complete water process that allows for hydrological calibration. SHIA_Landslide can be combined with real-time rainfall data and implemented in early warning systems.