干旱区生态环境知识资源中心(Arid): Soil Salinity Detection and Mapping in an Environment under Water Stress between 1984 and 2018 (Case of the Largest Oasis in Africa-Morocco)

Arid

DOI	10.3390/rs14071606
	Soil Salinity Detection and Mapping in an Environment under Water Stress between 1984 and 2018 (Case of the Largest Oasis in Africa-Morocco)
	Rafik, Abdellatif; Ibouh, Hassan; El Fels, Abdelhafid El Alaoui; Eddahby, Lhou; Mezzane, Daoud; Bousfoul, Mohamed; Amazirh, Abdelhakim; Ouhamdouch, Salah; Bahir, Mohammed; Gourfi, Abdelali; Dhiba, Driss; Chehbouni, Abdelghani
通讯作者	Rafik, A
来源期刊	REMOTE SENSING
EISSN	2072-4292
出版年	2022
卷号	14 期号:7
英文摘要	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 (R-2) 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 km(2), respectively, while a decrease of about 50% is observed during the periods of 1996-2000 and 2005-2018.
英文关键词	water stress Tafilalet oasis soil salinization Landsat Sentinel 2 drought Tafilalet Oasis
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000781411700001
WOS关键词	COEFFICIENT ; REGION
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/394130
推荐引用方式 GB/T 7714	Rafik, Abdellatif,Ibouh, Hassan,El Fels, Abdelhafid El Alaoui,et al. Soil Salinity Detection and Mapping in an Environment under Water Stress between 1984 and 2018 (Case of the Largest Oasis in Africa-Morocco)[J],2022,14(7).
APA	Rafik, Abdellatif.,Ibouh, Hassan.,El Fels, Abdelhafid El Alaoui.,Eddahby, Lhou.,Mezzane, Daoud.,...&Chehbouni, Abdelghani.(2022).Soil Salinity Detection and Mapping in an Environment under Water Stress between 1984 and 2018 (Case of the Largest Oasis in Africa-Morocco).REMOTE SENSING,14(7).
MLA	Rafik, Abdellatif,et al."Soil Salinity Detection and Mapping in an Environment under Water Stress between 1984 and 2018 (Case of the Largest Oasis in Africa-Morocco)".REMOTE SENSING 14.7(2022).