Estimation of Water Erosion and the Transportation of Sediments in the Upper Basin of Cuxtepeques River, Chiapas, Mexico

Changes in land use and increased intensity of rainfall are factors of greater influence that accelerate the soil erosion process. The application of basin scale sedimentological models integrated to Geographic Information Systems (GIS), is a tool that allows the definition of critical zones, and of...

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Autores:
Gutierrez Lopez, Ricardo
Muciño Porras, Juan José
Arellano Monterrosas, Jose Luis
Guichard Romero, Delva del Rocío
Aguilar Suárez, Miguel Ángel
Tipo de recurso:
Article of journal
Fecha de publicación:
2020
Institución:
Universidad EIA .
Repositorio:
Repositorio EIA .
Idioma:
eng
OAI Identifier:
oai:repository.eia.edu.co:11190/5125
Acceso en línea:
https://repository.eia.edu.co/handle/11190/5125
https://doi.org/10.24050/reia.v18i35.1445
Palabra clave:
Land use
Water Erosion
Basin
GIS
Sediments
USLE
Extreme Events
Plant Cover
Statistic Homogeneity
Correlation
Land use
Water Erosion
Basin
GIS
Sediments
USLE
Extreme Events
Plant Cover
Statistic Homogeneity
Correlation
Rights
openAccess
License
Revista EIA - 2020
Description
Summary:Changes in land use and increased intensity of rainfall are factors of greater influence that accelerate the soil erosion process. The application of basin scale sedimentological models integrated to Geographic Information Systems (GIS), is a tool that allows the definition of critical zones, and of this the establishment of measures of control of processes of production and transport of sediments. This study evaluates the water erosion using the Universal Soil Loss Equation (USLE), five scenarios were studied: corresponding to the start of operations of the El Portillo II (1980) dam, and the before and after the two extreme events in the basin (September 1998 and October 2005). The transport of sediments was evaluated by regression, using full annually records (eight years) of flows of two gauging stations in the basin. Overall, variations in erosion rates were observed with changes in the vegetal coverage and statistical homogeneity in the gauging data, which allowed adjust them to a regression model, with correlation coefficient upper to 88%.