Assessment of soil erosion by RUSLE in the Ecuadorian basins (2001−2020) based on GIS and high-resolution satellite data: Main drivers and changes on soil erosion

Abstract

Soil erosion is a significant environmental problem that can have devastating impacts on ecosystems and the sustainability of agricultural lands, including landscape degradation and biodiversity loss. Estimating erosion rates requires the installation of measurement devices such as sediment traps and runoff collectors or the use of erosion plots considering soil texture and vegetation cover. However, these procedures have significant spatial and temporal limitations, in addition to high implementation costs. The objective of this study was to analyze soil erosion in Ecuadorian basins using the Revised Universal Soil Loss Equation (RUSLE) based on Geographic Information System (GIS) and high-resolution satellite data from 2001 to 2020. The methodology involved delineating and evaluating the environmental characteristics of Ecuadorian basins, precipitation data, soil physical and chemical properties, identification of the Normalized Difference Vegetation Index (NDVI), land use, Digital Elevation Model (DEM) selection and assigning values based on slope raster. Basin delineation was obtained from regional literature; precipitation data from GPM-IMERG web servers; sand, clay, silt, and Soil Organic Carbon (SOC) content from SoilGrids web servers; DEM from SRTM database; spatial-temporal distribution of NDVI and land use from MODIS database; and P Factor value ranges based on slope from global literature. Recorded erosion rates ranged from 0.28 t/ha year to 2373.85 t/ha year, with the highest values identified in the Andes Mountains due to steep slopes. The main driver of soil erosion in Ecuadorian basins was the R-Factor, followed by LS and C. Land use variations indicated a loss of 9771 km² of forests and 80 km² of cultivated lands between 2001 and 2020, while semi-natural vegetation increased by 9851 km². These results provide relevant information to assist land managers in making decisions to address this natural phenomenon.