Data/hora: 12/06/2024 06:30:14

Provedor de dados: 	64	
País: 	Brazil	
Título: 	Estimation of sediments produced in a subbasin using the Normalized Difference Vegetation Index	
Autores: 	Lense,Guilherme Henrique Expedito; Moreira,Rodrigo Santos; Bócoli,Fernanda Almeida; Avanzi,Junior Cesar; Teodoro,Alexandre Elias de Miranda; Mincato,Ronaldo Luiz.	
Data: 	2020-01-01	
Ano: 	2020	
Palavras-chave: 	Soil conservation; Water erosion; Modeling; RUSLE.	
Resumo: 	ABSTRACT Among the parameters considered by the Revised Universal Soil Loss Equation (RUSLE), the soil cover and management factor (C) is the main human influenced factor affecting the estimation of water erosion, and one of the most sensitive to spatiotemporal variations. Consequently, this study aims to compare the efficiency of C factor estimates obtained from the literature for each land-use class (Clit) and by calculation based on the Normalized Difference Vegetation Index (CNDVI). We test the hypothesis that soil loss estimates based on CNDVI approach are more accurate than those based on Clit. Water erosion was estimated based on soil morphological, physical, and chemical properties in addition to climate, relief, management practices, and land use and cover. The modeling steps were realized with the help of the Geographic Information System. The results were validated using the data of total sediment transported with water discharge and daily runoff. RUSLE underestimated soil losses by 0.64 Mg ha-1 year-1 using Clit and 0.45 Mg ha-1 year-1 with CNDVI, which corresponds to errors of 21.05% and 14.80%, respectively. Therefore, the CNDVI factor results are more accurate. Both methodologies identified areas with high erosion rates where the adoption of mitigation measures should be prioritized.	
Tipo: 	Info:eu-repo/semantics/article	
Idioma: 	Inglês	
Identificador: 	http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1413-70542020000100214	
Editor: 	Editora da Universidade Federal de Lavras	
Relação: 	10.1590/1413-7054202044031419	
Formato: 	text/html	
Fonte: 	Ciência e Agrotecnologia  v.44 2020	
Fonte: 	info:eu-repo/semantics/openAccess