Predicting gully erosion susceptibility in South Africa by integrating literature directives with regional spatial data

Gully erosion has been identified as a severe land degradation process with environmental and socio-economic consequences. Identifying areas susceptible to gully will aid in developing strategies inhibit future degradation. Various approaches have implemented predict map susceptibility but are mostly restricted small geographical extents because of limitations. Here, we introduce novel method that predicts on regional/national scale (1.22 million km2) by synthesising literature directives statistical approach. Findings from review were used extract physiographic properties associated was conditioned characterise using the Frequency Ratio model. The aggregated weighted overlay procedure an aggregation controlling factors derived weighting system. index (GSI) model validated against published inventory (n = 163 019) randomly generated 1-km2 tessellation zones which primary validation data derived. Although uncertainties within modelling exist (e.g., site distribution, spatial resolution input determination points), shows GSI is generally robust, identifying contrasting susceptibilities. Furthermore, findings converge other metrics, different methodologies. Because empirical research conducted worldwide, this could be applied regional-scale assessments (as solitary or combined data) parts world. Additionally, can adopted change scenarios.