Issue |
E3S Web Conf.
Volume 37, 2018
The Sixth International Congress “Water, Waste and Environment” (EDE6-2017)
|
|
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Article Number | 04002 | |
Number of page(s) | 9 | |
Section | Watershed Management | |
DOI | https://doi.org/10.1051/e3sconf/20183704002 | |
Published online | 25 May 2018 |
Modelling soil salinity in Oued El Abid watershed, Morocco
1
Sultan MoulaySlimane University, Department of Geology, Beni Mellal, Morocco
2
Sultan MoulaySlimane University, Department of Geology, Beni Mellal, Morocco
3
Sultan MoulaySlimane University, Department of Geology, Beni Mellal, Morocco
4
Sultan MoulaySlimane University, Department of Geology, Beni Mellal, Morocco
5
Agence de bassinhydraulique Oum Er Rbia|, Beni Mellal, Morocco
6
Agence de bassinhydraulique Oum Er Rbia, Beni Mellal, Morocco
* Corresponding author: e.sabri@usms.ma.
Soil salinisation is a phenomenon considered to be a real threat to natural resources in semi-arid climates. The phenomenon is controlled by soil (texture, depth, slope etc.), anthropogenic factors (drainage system, irrigation, crops types, etc.), and climate factors. This study was conducted in the watershed of Oued El Abid in the region of Beni Mellal-Khenifra, aimed at localising saline soil using remote sensing and a regression model. The spectral indices were extracted from Landsat imagery (30 m resolution). A linear correlation of electrical conductivity, which was calculated based on soil samples (ECs), and the values extracted based on spectral bands showed a high accuracy with an R2 (Root square) of 0.80. This study proposes a new spectral salinity index using Landsat bands B1 and B4. This hydro-chemical and statistical study, based on a yearlong survey, showed a moderate amount of salinity, which threatens dam water quality. The results present an improved ability to use remote sensing and regression model integration to detect soil salinity with high accuracy and low cost, and permit intervention at an early stage of salinisation.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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