Reconstruction of historical soil surfaces and estimation of soil erosion rates with mound measurements and UAV photogrammetry in Mediterranean olive groves
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Description: Articulo principal
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Elsevier
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Abstract
Olive groves on hillsides. Governments and public agencies recognize the need to control this process in order to
improve soil conservation, especially in vulnerable areas. In the present study, a simple, inexpensive method
using Structure-from-motion (SfM) and Unmanned Aerial Vehicle (UAV) technology was applied to quantify the
soil loss rates provoked by water erosion and tillage in mountain olive groves, according to a reconstruction of
their historical surface features. Specifically, the main study aims were: i) to quantify the historical soil loss in
olive groves, by analysing residual tree mounds; ii) to consider how soil relief and management can influence the
erosion process; iii) to determine the degree to which the proposed method achieves the above aims.
Analysis revealed a mean erosion rate in the study area of 127.69 t ha 1 years 1, with a linear relationship
between soil truncation and slope (R2 = 0.64, p < 0.001). The highest soil loss rates (-1.67 ± 0.48 m) occurred in
areas where the slopes were steepest (22.36 ± 4.46 %) and the longitudinal profile rectilinear. Erosion rates are
determined not only by the slope, but also by its position and distance from the tree mound. This study highlights
the need for differential management based on slope-feature considerations, in order to limit soil losses. Overall,
the tool presented to support decision making provides an effective method for calculating erosion rates.
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Francisco Lima, Rafael Blanco-Sepúlveda, Mikel Calle, Dionisio Andújar, Reconstruction of historical soil surfaces and estimation of soil erosion rates with mound measurements and UAV photogrammetry in Mediterranean olive groves, Geoderma, Volume 440, 2023, 116708, ISSN 0016-7061, https://doi.org/10.1016/j.geoderma.2023.116708. (https://www.sciencedirect.com/science/article/pii/S0016706123003853)










