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

Jones Anschau Xavier de Oliveira, Frederico Terra de Almeida (), Adilson Pacheco de Souza, Rhavel Salviano Dias Paulista, Cornélio Alberto Zolin and Aaron Kinyu Hoshide
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Jones Anschau Xavier de Oliveira: Environmental Sciences, Federal University of Mato Grosso, Sinop 78550-728, MT, Brazil
Frederico Terra de Almeida: Institute of Agrarian and Environmental Sciences, Federal University of Mato Grosso, Sinop 78550-728, MT, Brazil
Adilson Pacheco de Souza: Institute of Agrarian and Environmental Sciences, Federal University of Mato Grosso, Sinop 78550-728, MT, Brazil
Rhavel Salviano Dias Paulista: Postgraduate Program in Environmental Physics, Institute of Physics, Federal University of Mato Grosso, 2367, Av. Fernando Corrêa da Costa, Cuiabá 78060-900, MT, Brazil
Cornélio Alberto Zolin: EMBRAPA Agrossilvipastoril, Brazilian Agricultural Research Corporation, Sinop 78550-970, MT, Brazil
Aaron Kinyu Hoshide: College of Earth, Life, and Health Sciences, The University of Maine, Orono, ME 04469, USA

Land, 2024, vol. 13, issue 9, 1-17

Abstract: 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.

Keywords: analytical methods; erodibility; soil erosion; rainfall simulator; Universal Soil Loss Equation (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
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