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Electrical resistivity and spatial variation in agriculture terraces: statistical correlation between ert and flow direction algorithms

J. Fernandes / C. Bateira / A. Costa / B. Fonseca / R. Moura
Published Online: 2017-06-30 | DOI: https://doi.org/10.1515/opag-2017-0037


The construction of earthen embankment terraces in the Douro Region raises a set of problems related to hydrological processes. The main objective of this study is the evaluation of the spatial variation of electrical resistivity in agriculture terraces at Douro valley (Portugal). To achieve this objective, two variables are analysed, the soil electrical resistivity and the flow direction algorithm. In a field survey we recorded 13 electrical resistivity profiles. The contributing area was calculated with the algorithms D∞ (Deterministic Infinity Flow) and MFD (Multiple Flow Direction) and the results are the base of the internal runoff modelling, both supported by the digital elevation model with a spatial resolution of 1m2. A correlation between the spatial variation of the soil electrical resistivity represented by the standard deviation of the electrical resistivity for each profile and the average value of the contributing area coincident with each profile was established. The electrical resistivity standard deviation seems to be moderately well correlated according to the D∞ algorithm at about 1m of depth, and it has a good correlation at 1,5m to 2m of depth with the MFD algorithm. Taken together, the results show a significant positive statistical correlation between the electrical resistivity standard deviation and the contributing areas (MFD and D∞) depending on the soil depth.

Keywords : electrical resistivity tomography; multiple flow direction; D-infinity; electrical resistivity spatial variation; agricultural terraces


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About the article

Received: 2017-01-31

Accepted: 2017-05-30

Published Online: 2017-06-30

Published in Print: 2017-02-23

Citation Information: Open Agriculture, Volume 2, Issue 1, Pages 329–340, ISSN (Online) 2391-9531, DOI: https://doi.org/10.1515/opag-2017-0037.

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© 2017. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. BY-NC-ND 4.0

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