Spatial scaling effects of gully erosion in response to driving factors in southern China

Gully erosion, an integrated result of various social and environmental factors, is a severe problem for sustainable development and ecology security in southern China. Currently, the dominant driving forces on gully distribution are shown to vary at different spatial scales. However, few systematic studies have been performed on spatial scaling effects in identifying driving forces for gully erosion. In this study, we quantitatively identified the determinants of gully distribution and their relative importance at four different spatial scales (southern China, Jiangxi province, Ganxian county, and Tiancun township, respectively) based on the Boruta algorithm. The optimal performance of gully susceptibility mapping was investigated by comparing the performance of the multinomial logistic regression (MLR), logistic model tree (LMT), and random forest (RF). Across the four spatial scales, the total contributions of gully determinants were classified as lithology and soil (32.65%) > topography (22.40%) > human activities (22.31%) > climate (11.32%) > vegetation (11.31%). Among these factors, precipitation (7.82%), land use and land cover (6.16%), rainfall erosivity (10.15%), and elevation (11.59%) were shown to be the predominant factors for gully erosion at the individual scale of southern China, province, county, and township, respectively. In addition, contrary to climatic factors, the relative importance of soil properties and vegetation increased with the decrease of spatial scale. Moreover, the RF model outperformed MLR and LMT at all the investigated spatial scales. This study provided a reference for factor selection in gully susceptibility modeling and facilitated the development of gully erosion management strategies suitable for different spatial scales.