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Spatial Estimation of Soil Erosion Risk by Land‐cover Change in the Andes OF Southern Ecuador
Author(s) -
OchoaCueva Pablo,
Fries Andreas,
Montesinos Pilar,
RodríguezDíaz Juan A.,
Boll Jan
Publication year - 2015
Publication title -
land degradation and development
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.403
H-Index - 81
eISSN - 1099-145X
pISSN - 1085-3278
DOI - 10.1002/ldr.2219
Subject(s) - deforestation (computer science) , environmental science , erosion , land cover , watershed , land use , universal soil loss equation , pasture , hydrology (agriculture) , vegetation (pathology) , agricultural land , geography , physical geography , forestry , ecology , geology , soil loss , medicine , paleontology , geotechnical engineering , pathology , machine learning , computer science , biology , programming language
Ecuador has the highest deforestation rate in South America, causing large‐scale soil erosion. Inter‐Andean watersheds are especially affected by a rapid increase of the population leading to the conversion of large areas of montane forest into pasture and cropland. In this study, we estimate soil erosion risk in a small mixed land‐use watershed in the southern Andes of Ecuador. Soil loss was estimated at a spatial resolution of 30 m, using the Revised Universal Soil Loss Equation (RUSLE) where the RUSLE factors were estimated on the basis of limited public available data. Land‐cover maps for 1976, 2008 and 2040 were created assuming increasing deforestation rates over the ensuing decades. Greater erosion rates are estimated for succession areas with agricultural cropland and pasture with maximum values of 936 Mg ha −1 y −1 , where slopes and precipitation amounts are the greatest. Under natural forest vegetation, the estimated soil erosion rates are negligible (1·5 to 40 Mg ha −1 y −1 ) even at steep slopes and higher elevations where rainfall amounts and intensities are generally higher. When the entire watershed has undergone substantial deforestation in 2040, erosion values may reach 2,021 Mg ha −1 y −1 . Vegetation cover is the most important factor for potential soil erosion. Secondary factors are related to rainfall ( R ‐factor) and topography ( LS factors). Although the spatial predictions of potential soil erosion have only limited meaning for erosion risk, this method provides an important screening tool for land management and assessment of land‐cover change. Copyright © 2013 John Wiley & Sons, Ltd.