Identification of Saline Soils Using Soil Geochemical Data: A Case Study in Soda-Salinization Areas, NE China

Tian Lan, Jilong Lu, Libo Hao, Rongjie Bai, Xiaohan Sun, Xinyun Zhao () and Yongzhi Wang ()
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Tian Lan: College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China
Jilong Lu: College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China
Libo Hao: College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China
Rongjie Bai: Geological Survey of Jilin Province, Changchun 130102, China
Xiaohan Sun: College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China
Xinyun Zhao: College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China
Yongzhi Wang: College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China

Sustainability, 2023, vol. 15, issue 12, 1-13

Abstract: Identifying saline soils is of great importance for protecting land resources and for the sustainable development of agriculture. Total soil salinity (TSS) is the most commonly used indicator for determining soil salinization, but the application of soil geochemical data is rarely reported. In general, there is a significant relationship between TSS and the content of soil-soluble Na, which can be estimated by the difference between the bulk-soil Na 2 O content and its background value. In this study, the partial least squares regression (PLSR) method was employed to calculate the Na 2 O background value via a regression model between Na 2 O and SiO 2 , Al 2 O 3 , TFe 2 O 3 , Cr, Nb, and P in a 1:250,000 scale regional geochemical data set of soils in Jilin Province, NE China. We defined δNa as the difference between the bulk-soil Na 2 O value and the regression background value, which can be used as a geochemical indicator to identify saline soils. One hundred and five samples with known TSS contents in the study area were selected to test the capability of the indicator δNa. The result shows that the identification accuracy can be up to 75%, indicating that the indicator can provide a new means for saline soil identification.

Keywords: saline soil; soil geochemical data; soda-salinization areas; NE China (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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