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  4. Global predictions of primary soil salinization under changing climate in the 21st century
 
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Global predictions of primary soil salinization under changing climate in the 21st century

Citation Link: https://doi.org/10.15480/882.4026
Publikationstyp
Journal Article
Date Issued
2021-11-18
Sprache
English
Author(s)
Hassani, Amirhossein  
Azapagic, Adisa  
Shokri, Nima  
Institut
Geohydroinformatik B-9  
TORE-DOI
10.15480/882.4026
TORE-URI
http://hdl.handle.net/11420/11258
Journal
Nature communications  
Volume
12
Issue
1
Article Number
6663
Citation
Nature Communications 12 (1): 6663 (2021-12-01)
Publisher DOI
10.1038/s41467-021-26907-3
Scopus ID
2-s2.0-85119451230
Publisher
Nature Publishing Group UK
Soil salinization has become one of the major environmental and socioeconomic issues globally and this is expected to be exacerbated further with projected climatic change. Determining how climate change influences the dynamics of naturally-occurring soil salinization has scarcely been addressed due to highly complex processes influencing salinization. This paper sets out to address this long-standing challenge by developing data-driven models capable of predicting primary (naturally-occurring) soil salinity and its variations in the world’s drylands up to the year 2100 under changing climate. Analysis of the future predictions made here identifies the dryland areas of South America, southern and western Australia, Mexico, southwest United States, and South Africa as the salinization hotspots. Conversely, we project a decrease in the soil salinity of the drylands in the northwest United States, the Horn of Africa, Eastern Europe, Turkmenistan, and west Kazakhstan in response to climate change over the same period.
Subjects
MLE@TUHH
DDC Class
004: Informatik
550: Geowissenschaften
600: Technik
More Funding Information
We gratefully acknowledge the funding by the Presidential Doctoral Scholarship Award at The University of Manchester, UK Research Councils (grant no. EP/K011820/1) and the Institute of Geo-Hydroinformatics at Hamburg University of Technology. Open Access funding enabled and organized by Projekt DEAL.
Publication version
publishedVersion
Lizenz
https://creativecommons.org/licenses/by/4.0/
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