One of the core problems in soil erosion research is the estimation of soil erosion. It is a feasible method and technical approach to estimate soil erosion in Loess Plateau region by using USLE model, GIS and RS technology and using DEM data, meteorological data and land-use type data. With the support of GIS and RS technology, the USLE factors and soil erosion in Loess Plateau region were estimated, and the soil erosion intensity was classified according to the Chinese soil erosion intensity classification standard. The results can provide reference for the development of soil erosion control measures in the Loess Plateau.

This study investigates the impact of extreme rainfall events on soil erosion in the downstream Parnaíba River Basin, located in the Brazilian Cerrado. The analysis focused on rainfall erosivity (R factor) and soil erodibility (K factor) as key indicators. The average erosivity in the region was 9051 MJ mm h⁻¹ha⁻¹year⁻¹, with a variation between 7943 and 10,081 MJ mm h⁻¹ha⁻¹year⁻¹, suggesting a high erosive potential, mainly in the rainiest months, from December to April. The soils of the studied area, mainly Ultisols and Chernosols, present high to very high erodibility, with K factor values ranging from 0.025 to 0.050 t h MJ⁻¹ mm⁻¹. Furthermore, fieldwork revealed areas, near highways, with apparently fragile soils, as well as rills and gullies, identified through photographs taken during fieldwork. These locations, due to the combination of high erosivity and susceptible soils, were considered prone to the occurrence of erosion processes, representing an additional risk to local infrastructure. The spatialization of R and K factors, along with field observations, showed that much of the area is at high risk of erosion and landslides, particularly in regions with greater topographic variability and proximity to water bodies. These results provide a basis for the development of mitigation strategies, being important for the effective prevention of landslides.

Soil erosion is characterized by the wearing away or loss of the uppermost layer of soil, driven by water, wind, and human activities. This process constitutes a significant environmental issue, with adverse effects on water quality, soil health, and the overall stability of ecosystems across the globe. This study focuses on the Anuppur district of Madhya Pradesh, India, employing the Revised Universal Soil Loss Equation (RUSLE) integrated with Geographic Information System (GIS) tools to estimate and spatially analyze soil erosion and fertility risk. The various factors of the model, like rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), conservation practices (P), and cover management factor (C), have been computed to measure annual soil loss in the district. Each factor was derived using geospatial datasets, including rainfall records, soil characteristics, a Digital Elevation Model (DEM), land use/land cover (LULC) data, and information on conservation practices. GIS methods are used to map the geographical variation of soil erosion, providing important information on the area’s most susceptible to erosion. The outcome of the study reveals that 3371.23 km², which constitutes 91% of the district’s total area, is identified as having mild soil erosion; in contrast, 154 km², or 4%, is classified as moderate soil erosion, while 92 km², representing 2.5%, falls under the high soil erosion category. Ad