Simple Method for Shallow Landslide Prediction Based on Wide-Area Terrain Analysis Incorporated with Surface and Subsurface Flows

During intense rainfall, shallow landslides often occur on natural slopes due to the rising groundwater level. This study proposed a simple model for rainfall-induced shallow landslide prediction in broad areas based on an infinite homogeneous slope assumption and a simplified hydrological process. For this purpose, a numerical model, TAG_FLOW, was developed in Fortran 90. Its structure was divided into four modules: (1) a surface infiltration module based on the Green-Ampt model, (2) a groundwater-level simulation based on a previously developed simple one-dimensional vertical prediction method combined with horizontal groundwater distribution, (3) a surface water control module based on two-dimensional shallow water equations and a depression removal process, and (4) slope stability estimated using the assumption of an infinite homogeneous slope. The simplified hydrological process for the surface and subsurface flows was validated using a tilted V-catchment model and tested with the Abdul and Gillham system. For the performance evaluation of TAG_FLOW, we applied the model to analyze rainfall-induced landslides for an area in North Kyushu during the historically large torrential rainfall event in July 2017. The landslide prediction capacity of the TAG_FLOW model was evaluated by the TRIGRS model and the actual landslide map. The results confirmed that both groundwater and surface water contributed to the occurrence of landslides in the study area. The prediction performance of the TAG_FLOW model was slightly better than that of the TRIGRS model, but both models overpredicted landslides in the study area.