Evolution of the Contemporary Landscape: Relevance of Land Use Management Over Environmental Drivers of Soil Erosion

Water erosion is the main soil degradation process in landscapes under human pressure. The assessment of soil losses according to biophysical factors is the key to understanding erosion processes. This study aimed to assess the biophysical and anthropological factors controlling the change in water soil erosion rates under different morphological units as an indicator of geological evolution, topographic variety, and land use. The revised Universal Soil Loss Equation model was employed to estimate the soil erosion rates and evaluate soil loss. The geographic information system was used to present the spatial distribution of soil erosion and its change induced by geological and morphological factors. Nonparametric multidimensional scaling ordinations were applied to evaluate similarities in soil erosion parameters between six geomorphological units. The analysis showed a clear clustering between morphological units, both in terms of absolute soil loss (stress value: 0.15, ANOSIM: R = 0.61, p = 0.001) and in the distribution pattern of erosion rates (stress value: 0.17, ANOSIM: R = 0.74, p = 0.001). Significant differences were observed in erosion rates, which range between 2.5 up to 65.9 t ha⁻¹ yr⁻¹, although 82% of the La Primavera present rates below 15 t ha⁻¹ yr⁻¹. The most eroded unit produces 351 thousand t yr⁻¹, displaying a rate of 23.3 t ha⁻¹ yr⁻¹, while the least eroded unit produces 10 thousand t yr⁻¹, displaying a rate of 2.5 t ha⁻¹ yr⁻¹. This study shows that integrating landscape evolution and morphology into soil erosion research enhances understanding of erosion processes, strengthening the LS Factor. Forest land use is often linked to preventing water erosion, but this study shows it depends on vegetation type; secondary vegetation can have higher erosion rates than conservation agriculture. Soil loss patterns show that each unit combines unique biophysical and human factors, requiring discrete units for systematic erosion analysis.