Landslide susceptibility modelling in Nyahode and Buzi sub-catchments of Zimbabwe

Abstract

Abstract Landslides are natural hazards that have different susceptibility across landsurface terrains and are mostly triggered by high rainfall intensity. Cyclone Idai, which affected the Eastern Highlands of Zimbabwe in 2019, resulted in at least 634 deaths, and over 300 missing people due to landslides and floods, necessitating investigations to understand hydrometeorological hazards in the area. This study aimed at modelling landslide susceptibility using field and remote sensing data in Nyahode and Buzi sub-catchments. The mapped landslide inventory was used in the building and validation of the landslide susceptibility model. A geostatistical approach was used for landslide susceptibility model building with 11 landslide conditioning factors: slope degree, slope aspect, altitude, lithology, land use/land cover, distance from the river, Normalized Difference Vegetation Index, topographic wetness Index, and soil clay content, soil sand content, and soil silt content. The landslide susceptibility map was categorized into four classes, namely low, moderate, high, and very high. The Receiver Operating Characteristic curve used to validate obtained landslide susceptibility. Results show a frequency success rate of 0.85 and a frequency predictive rate of 0.82 indicating a very good accuracy in the identification of landslide susceptibility areas. The utilized method provides affordable, faster, practical, and more reliable results useful in land use planning, water resources, and disaster risk management as well as catchment protection actions to reduce the impact of landslide hazards.