Evaluating land degradation by gully erosion through soil erosion indices and rainfall thresholds

Abstract

Among the land degradation processes, gully erosion is the one that poses more environmental and societal challenges in arid regions. Predicting spatiotemporal gully development in a region under changing conditions is important to adopt proper mitigation measures. Here we investigate the Ghapan-Olya watershed in Golestan province in Iran, which is affected by many erosional landforms, including gully phenomena. We apply the pixel-based distributed LANDPLANER model to predict where rainfall induced gullies will occur by exploiting input maps including UAV data, the region soil, and seasonal land use information. We compare our topographic thresholds and an erosion index with field observations through the application of quantitative metrics such as sensitivity, specificity, fallout, precision, and recall. Our study reveals that the spatial density of the gully’s location is more frequently predicted in the areas with an altitude of about 200–300 m, steep slope (between 15 and 30 degrees), and low average accumulation value (< 100) in the southeast facing slope. We obtain higher values of erosion index and topographic threshold for the minimum curve number where intense rainfalls are more frequent and where land use and cover conditions are more predisposing for gully occurrence. We obtain the largest values of soil erosion indices in the fall scenario when the daily rainfall is 80 mm (6.27), followed by the summer scenario with 80 mm daily rainfall (4.88), and spring again with 80 mm daily rainfall (2.99). In addition, topographic threshold maps illustrate the largest amount of soil erosion for the curve number scenario (without considering daily rainfall) in autumn. Our approach allows simulating gully erosion under changing conditions.