Water Erosion Prediction Using the Revised Universal Soil Loss Equation (RUSLE) in a GIS Framework, Central Chile

Soil erosion is a growing problem in Central Chile, particularly in coastal dry lands, where it can significantly decrease the productivity of rainfed agriculture and forestry. In this study, the Revised Universal Soil Loss Equation (RUSLE) was integrated into a Geographic Information System (GIS),...

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Autores principales:	Bonilla,Carlos A, Reyes,José L, Magri,Antoni
Lenguaje:	English
Publicado:	Instituto de Investigaciones Agropecuarias, INIA 2010
Materias:	RUSLE water erosion soil conservation forestry changes in land use/land cover Central Chile
Acceso en línea:	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-58392010000100017
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spelling	oai:scielo:S0718-583920100001000172018-10-01Water Erosion Prediction Using the Revised Universal Soil Loss Equation (RUSLE) in a GIS Framework, Central ChileBonilla,Carlos AReyes,José LMagri,Antoni RUSLE water erosion soil conservation forestry changes in land use/land cover Central Chile Soil erosion is a growing problem in Central Chile, particularly in coastal dry lands, where it can significantly decrease the productivity of rainfed agriculture and forestry. In this study, the Revised Universal Soil Loss Equation (RUSLE) was integrated into a Geographic Information System (GIS), and used to evaluate the effects of different combinations of vegetative cover on soil erosion rates for Santo Domingo County in Central Chile. Implementing RUSLE in the GIS required a complete description of the county’s soils, climate, topography and current land use/land cover. This information was compiled in rasters of 25 x 25 m cells. RUSLE parameter values were assigned to each cell and annual soil loss estimates were generated on a cell by cell basis. Soil losses were estimated for the current and for three alternate scenarios of vegetative cover. Under current conditions, 39.7% of the county is predicted to have low erosion rates (< 0.1 t ha-1 yr-1), 39.8% has intermediate rates (0.1-1.0 t ha-1 yr-1), and 10.4% has high erosion rates (> 1.1 t ha-1 yr-1). The remainder of the surface (10.2%) is not subject to erosion. Under the recommended alternate scenario, 89.3% of the county is predicted to have low erosion rates, and no areas are affected by high soil loss, reducing soil erosion to a level that will not affect long term productivity. This paper describes how RUSLE was implemented in the GIS, and the methodology and equations used to evaluate the effects of the land use/land cover changes.info:eu-repo/semantics/openAccessInstituto de Investigaciones Agropecuarias, INIAChilean journal of agricultural research v.70 n.1 20102010-03-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-58392010000100017en10.4067/S0718-58392010000100017
institution	Scielo Chile
collection	Scielo Chile
language	English
topic	RUSLE water erosion soil conservation forestry changes in land use/land cover Central Chile
spellingShingle	RUSLE water erosion soil conservation forestry changes in land use/land cover Central Chile Bonilla,Carlos A Reyes,José L Magri,Antoni Water Erosion Prediction Using the Revised Universal Soil Loss Equation (RUSLE) in a GIS Framework, Central Chile
description	Soil erosion is a growing problem in Central Chile, particularly in coastal dry lands, where it can significantly decrease the productivity of rainfed agriculture and forestry. In this study, the Revised Universal Soil Loss Equation (RUSLE) was integrated into a Geographic Information System (GIS), and used to evaluate the effects of different combinations of vegetative cover on soil erosion rates for Santo Domingo County in Central Chile. Implementing RUSLE in the GIS required a complete description of the county’s soils, climate, topography and current land use/land cover. This information was compiled in rasters of 25 x 25 m cells. RUSLE parameter values were assigned to each cell and annual soil loss estimates were generated on a cell by cell basis. Soil losses were estimated for the current and for three alternate scenarios of vegetative cover. Under current conditions, 39.7% of the county is predicted to have low erosion rates (< 0.1 t ha-1 yr-1), 39.8% has intermediate rates (0.1-1.0 t ha-1 yr-1), and 10.4% has high erosion rates (> 1.1 t ha-1 yr-1). The remainder of the surface (10.2%) is not subject to erosion. Under the recommended alternate scenario, 89.3% of the county is predicted to have low erosion rates, and no areas are affected by high soil loss, reducing soil erosion to a level that will not affect long term productivity. This paper describes how RUSLE was implemented in the GIS, and the methodology and equations used to evaluate the effects of the land use/land cover changes.
author	Bonilla,Carlos A Reyes,José L Magri,Antoni
author_facet	Bonilla,Carlos A Reyes,José L Magri,Antoni
author_sort	Bonilla,Carlos A
title	Water Erosion Prediction Using the Revised Universal Soil Loss Equation (RUSLE) in a GIS Framework, Central Chile
title_short	Water Erosion Prediction Using the Revised Universal Soil Loss Equation (RUSLE) in a GIS Framework, Central Chile
title_full	Water Erosion Prediction Using the Revised Universal Soil Loss Equation (RUSLE) in a GIS Framework, Central Chile
title_fullStr	Water Erosion Prediction Using the Revised Universal Soil Loss Equation (RUSLE) in a GIS Framework, Central Chile
title_full_unstemmed	Water Erosion Prediction Using the Revised Universal Soil Loss Equation (RUSLE) in a GIS Framework, Central Chile
title_sort	water erosion prediction using the revised universal soil loss equation (rusle) in a gis framework, central chile
publisher	Instituto de Investigaciones Agropecuarias, INIA
publishDate	2010
url	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-58392010000100017
work_keys_str_mv	AT bonillacarlosa watererosionpredictionusingthereviseduniversalsoillossequationrusleinagisframeworkcentralchile AT reyesjosel watererosionpredictionusingthereviseduniversalsoillossequationrusleinagisframeworkcentralchile AT magriantoni watererosionpredictionusingthereviseduniversalsoillossequationrusleinagisframeworkcentralchile
_version_	1714205280606093312

Water Erosion Prediction Using the Revised Universal Soil Loss Equation (RUSLE) in a GIS Framework, Central Chile

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