Quantitative Evaluation of Spatial and Temporal Variation of Soil Salinization Risk Using GIS-Based Geostatistical Method

Soil salinization is one of the environmental threats affecting the sustainable development of arid oases in the northwest of China. Thus, it is necessary to assess the risk of soil salinity and analyze spatial and temporal changes. The objective of this paper is to develop a temporal and spatial soil salinity risk assessment method based on an integrated scoring method by combining the advantages of remote sensing and GIS technology. Based on correlation coefficient analysis to determine the weights of risk evaluation factors, a comprehensive scoring system for the risk of salinity in the dry and wet seasons was constructed for the Ebinur Lake Wetland National Nature Reserve (ELWNNR), and the risk of spatial variation of soil salinity in the study area was analyzed in the dry and wet seasons. The results show the following: (1) The risk of soil salinity during the wet season is mainly influenced by the plant senescence reflectance index (PSRI), deep soil water content (D_wat), and the effect of shallow soil salinity (SH_sal). The risk of soil salinity during the dry season is mainly influenced by shallow soil salinity (SH_sal), land use and land cover change (LUCC), and deep soil moisture content (D_wat). (2) The wet season was found to have a high risk of salinization, which is mainly characterized by moderate, high, and very high risks. However, in the dry season, the risk of salinity is mainly characterized by low and moderate risk of salinity. (3) In the ELWNNR, as the wet season changes to dry season (from May to August), moderate-risk area in the wet season easily shifts to low risk and risk-free, and the area of high risk in the wet season easily shifts to moderate risk. In general, the overall change in salinity risk of the ELWNNR showed a significant relationship with changes in lake water volume, indicating that changes in water volume play an important role in the risk of soil salinity occurrence. Ideally, the quantitative analysis of salinity risk proposed in this study, which takes into account temporal and spatial variations, can help decision makers to propose more targeted soil management options.