Prediction of gully erosion susceptibilities using detailed terrain analysis and maximum entropy modeling: A case study in the Mazayejan plain, southwest Iran

Gully erosion is one of the most severe environmental problems in large areas of Iran. Land degradation and accelerated desertification are the consequence in susceptible areas. Gully erosion normally takes place when surface runoff is concentrated and thus, detach and transfer soil particles down the slopes into the drainage network. In traditional soil erosion studies these processes often have been neglected. In this study we investigate the spatial distribution of gully erosion processes with a quantitative method since in many national assessment approaches just qualitative models were applied. For this study we utilized a detailed terrain analysis and a stochastic modeling approach using mechanical statistics. Moreover we predict the potential spatial distribution of gullies in the Mazayejan plain of Fars province in southwestern Iran where gully erosion is the main environmental threat. Our methodological approach consists in the following steps: i) mapping of gully erosion phenomena in a test area based on Google Earth images; ii) development of a digital elevation model (DEM) with 10 meter resolution, iii) detailed terrain analysis deriving more than 20 terrain indices, iv) application of the Maxent model for the test area using the gully erosion forms as dependent variable and topographic indices as predictor variable and finally v) prediction of the spatial distribution of gully erosion potential for the entire study area. Model performance was evaluated by the Receiver Operating Characteristic (ROC). The results obtained show that the Maxent model perform very well and thus, it is suitable for the prediction of the gully erosion potential in the area. Among the terrain indices utilized in the prediction the most important ones are: convergence index, plan curvature, and slope. The proposed methodology allows conducting a proper gully erosion assessment in order to identify the priority areas for soil conservation and land use management.