Abstract form

Mapping the risk of soil salinization: application of electromagnetic
induction and non-parametric geostatistics
Houria DAKAK* 12 , Brahim SOUDI 3 , Ahmed DOUAIK 1 , Aicha BENMOHAMMADI 2 ,
Mohamed BADRAOUI 1 , Fatima-Zohra CHERKAOUI 4
1: National Institute of Agricultural Research (INRA), Avenue de la Victoire, BP 415,
Rabat, Morocco ;
2: UFR ST 11/DOC/K, Department of Earth Sciences, Ibn Tofail University, Kenitra,
Morocco ;
3: Department of Soil Science, Hassan II Institute of Agricultural Sciences and
Veterinary Medicine, Rabat, Morocco.
4: Regional Office of Agricultural Development of Tadla (ORMVAT), Fqih Ben Saleh,
Morocco.
For a better management of salt-affected soils, the knowledge of the magnitude, the
spatial extent and the evolution with time of soil salinity is required. Soil salinity is
determined, conventionally, by measuring the electrical conductivity of a saturated past
extract (ECe). However, given the spatio-temporal variability of the salinity, numerous
samples are necessary, which makes the conventional procedure laborious and
expensive. As an alternative, the apparent electrical conductivity of soil (ECa) can be
measured in the field by the use of the electromagnetic induction (EMI). This procedure
is fast and allows making an extensive sampling in space and monitoring in time. The
study area covers 2060 ha in the irrigation district of Tadla, central Morocco. Twelve
samples were taken for the determination of ECe while about hundred ECa
measurements were realized with the EM38 instrument of Geonics. The pairs of ECe-
ECa values allowed establishing the calibration equation permitting to convert the ECa
into ECe values. This equation was used to convert the other ECa values for which there
was no measure of ECe. Then, geostatistics was used for the establishment of the maps
of the risk of soil salinization. First of all, a threshold for risk of soil salinization was
determined and indicators were built. Then, the spatial variability of these indicators
was described and modeled using the variogram. Finally, the maps were generated
based on a non-parametric method of geostatistical interpolation, i.e., indicator kriging.
The results showed that the study area presents various degrees of soil salinization risk.
In the centre of this area, the risk is low; the major part of the study area has a moderate
risk while the south and northwestern parts have a high risk. In conclusion, the
combined use of the electrical conductivity, electromagnetic induction and geostatistics
allowed establishing a reliable soil salinization risk map. This information could serve
as a basis for any rehabilitation effort of salt-affected soils, in the future, according to
their actual risk of salinization and not by considering the average risk of the whole
study area.
Keywords. Electrical conductivity, indicator kriging, salinization risk, variogram.
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