期刊
ENVIRONMENTAL EARTH SCIENCES
卷 82, 期 12, 页码 -出版社
SPRINGER
DOI: 10.1007/s12665-023-10944-w
关键词
Soil erosion; RUSLE; Soil erodibility; Erodibility factor; K-Factor
Soil erodibility (K-Factor) is an important parameter for estimating rainfall erosion through mathematical models. Analyzing soil erodibility at different depths can identify its susceptibility to erosion. However, the lack of a comprehensive field database is a major limitation in applying this method.
Soil erodibility (K-Factor) is one of the fundamental parameters to estimate its rainfall erosion through mathematical models such as RUSLE. Carrying out an erodibility analysis at different pedological depths allows identifying what would be its susceptibility to erosion processes. Soil unit parcel data obtained by long-term field measurements are required, ensuring that the analyzed sections remain uncovered throughout observation period, investing large amounts of time and money. However, the lack of a good and extensive field database is the main limitation to apply this methodology. The objective of this work was to analyze the spatial distribution of soil erodibility in different pedological profiles, through the implementation of satellite data of soil characteristics. The methodology consisted in delimiting and analyzing the environmental characteristics of the Ecuadorian basins, obtaining the clay, silt, sand SOC contents of the analyzed depths, determining the K-Factor values and comparing them with environmental layers. Basins delimitation and environmental characteristics were extracted from regional literature; soil layer contents were obtained from SoilGrids; K-Factor calculation was made from soil characteristics using Software R and QGIS; results comparison against the elevation and land cover parameters were carried out using QGIS. The results allowed to identify very small variations between pedological profiles; determine that clay and silt are the most incident elements of K-Factor; identify that Crop and Grass are coverages that concentrate on the highest values of K-Factor as well as the highest areas. This allows the administrators of the territory to generate measures to reduce soil loss.
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