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| Titre: | Soil Salinity Detection and Mapping in an Environment under Water Stress between 1984 and 2018 (Case of the Largest Oasis in Africa-Morocco) |
| Auteur(s): | Abdellatif Rafik
Hassan Ibouh
Abdelhafid El Alaoui El Fels
Lhou Eddahby
Daoud Mezzane
Mohamed Bousfoul
Abdelhakim Amazirh
Salah Ouhamdouch
Mohammed Bahir |
| Date de publication: | 2022 |
| Référence bibliographique: | Remote Sensing, p. 1-17 |
| Résumé: | Water stress is one of the factors controlling agricultural land salinization and is also a major
problem worldwide. According to FAO and the most recent estimates, it already affects more than
400 million hectares. The Tafilalet plain in Southeastern Morocco suffers from soil salinization. In this
regard, the GIS tools and remote sensing were used in the processing of 19 satellite images acquired
from Landsat 4–5, (Landsat 7), (Landsat 8), and (Sentinel 2) sensors. The most used indices in the
literature were (16 indices) tested and correlated with the results obtained from 25 samples taken
from the first soil horizon at a constant depth of 0.20 m from the 2018 campaign. The linear model,
at first, allows the selection of five better indices of the soil salinity discrimination (SI-Khan, VSSI, BI,
S3, and SI-Dehni). These last indices were the subject of the application of a logarithmic model and
polynomial models of degree two and four to increase the prediction of saline soil.. After studies and
analysis, we concluded that the second-degree polynomial model of the salinity index (SI-KHAN) is
the most efficient one for detecting and mapping soil salinity in the Tafilalet oasis, with a coefficient
of determination (R2) and the Nash–Sutcliffe efficiency (NSE) equal to 0.93 and 0.86, respectively.
Percent bias (PBIAS) calculated for this model equal was 1.868% < 10%, and the low value of the
root mean square error (RMSE) confirms its very good performance. The drought cyclicity led to the
intensification of the soil salinization process and accelerated soil degradation. The standardized
precipitation anomaly index (SPAI) is strongly correlated to soil salinity. The hydroclimate condition is
the factor that further controls this phenomenon. An increase in salinized surfaces is observed during
the periods of 1984–1996 and 2000–2005, which cover a surface of 11.50 and 24.20 km2, respectively,
while a decrease of about 50% is observed during the periods of 1996–2000 and 2005–2018 |
| Licence: | http://andzoa.ma/fr |
| URI/URL: | http://localhost:8080/dspace/handle/0/3772 |
| ISSN: | 1104-3792 |
| Collection(s) : | Fonds Documentaire
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