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

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 Na2O content and its background value. In this study, the partial least squares regression (PLSR) method was employed to calculate the Na2O background value via a regression model between Na2O and SiO2, Al2O3, TFe2O3, 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 Na2O 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.