Determination of Soil Erodibility by Different Methodologies in the Renato and Caiabi River Sub-Basins in Brazil

• Published in: Land (Basel) 2024-09, Vol.13 (9), p.1442
• Main Authors: Oliveira, Jones Anschau Xavier de, Almeida, Frederico Terra de, Souza, Adilson Pacheco de, Paulista, Rhavel Salviano Dias, Zolin, Cornélio Alberto, Hoshide, Aaron Kinyu
• Format: Article
• Language: English
• Subjects: Agriculture; Aluminum; Analysis; analytical methods; Basins; Commodities; Corn; Crops; Environmental protection; erodibility; Farming systems; k factors; Methods; Parameters; Prediction models; Rain and rainfall; Rainfall; rainfall simulator; Rainfall simulators; River basins; Rivers; Runoff; Simulation; Simulators; Soil analysis; Soil conservation; Soil erosion; Soybeans; Universal Soil Loss Equation; Watersheds
• ISSN: 2073-445X; 2073-445X
• DOI: 10.3390/land13091442

Mitigating soil erosion‘s effects have been prioritized since the early 20th century. Rainfall simulators and analytical prediction models are used to determine soil erosion susceptibility. This study used different methodologies to measure soil erodibility in two hydrographic sub-basins, the Renato and Caiabi, in the Middle and Upper Teles Pires River in Mato Grosso state, Brazil. The rainfall simulator showed a higher range of K-factor values for the Renato sub-basin of 0.0009 to 0.0086 Mg × h × (MJ × mm)−1 and a lower range of K-factor values for the Caiabi sub-basin of 0.0014 to 0.0031 Mg × h × (MJ × mm)−1. Soil loss equations similarly estimated a higher range of K-factor values for the Renato of 0.0008 to 0.0990 Mg × h × (MJ × mm)−1 and a lower range of K-factor values for the Caiabi of 0.0014 to 0.0846 Mg × h × (MJ × mm)−1. There was no significant difference at the 5% level for the K factor determined by the rainfall simulator for both sub-basins. Equations specified in Bouyoucos (1935) and Lombardi Neto and Bertoni (1975) showed significant correlation (5%) for farming systems in the Caiabi sub-basin. Indirect methodologies that performed well for correlation were equations 2 and 3 from Roloff and Denardin (1994), which use iron and aluminum as parameters. Soil erosion was most influenced by physical texture parameters of the region’s soil.