Characterizing soil salinity at multiple depth using electromagnetic induction and remote sensing data with random forests: A case study in Tarim River Basin of southern Xinjiang, China

Fei Wang; Shengtian Yang; Yang Wei; Qian Shi; Jianli Ding

doi:10.1016/j.scitotenv.2020.142030

Characterizing soil salinity at multiple depth using electromagnetic induction and remote sensing data with random forests: A case study in Tarim River Basin of southern Xinjiang, China

Sci Total Environ. 2021 Feb 1:754:142030. doi: 10.1016/j.scitotenv.2020.142030. Epub 2020 Aug 29.

Authors

Fei Wang¹, Shengtian Yang², Yang Wei¹, Qian Shi³, Jianli Ding⁴

Affiliations

¹ Xinjiang Common University Key Lab of Smart City and Environmental Stimulation, College of Resource and Environmental Sciences, Xinjiang University, Urumqi 830046, China.
² Xinjiang Common University Key Lab of Smart City and Environmental Stimulation, College of Resource and Environmental Sciences, Xinjiang University, Urumqi 830046, China; College of Water Sciences, Beijing Normal University, Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology, Beijing 100875, China.
³ School of Geography and Planning, Sun Yat-Sen University, West Xingang Road, Guangzhou 510275, China; Guangdong Key Laboratory for Urbanization and Geo-simulation, Sun Yat-Sen University, West Xingang Road, Guangzhou 510275, China.
⁴ Xinjiang Common University Key Lab of Smart City and Environmental Stimulation, College of Resource and Environmental Sciences, Xinjiang University, Urumqi 830046, China. Electronic address: warid@xju.edu.cn.

PMID: 32911147
DOI: 10.1016/j.scitotenv.2020.142030

Abstract

Tarim River Basin is experiencing heavy soil degeneration in a long term because of the extreme natural conditions, added with improper human activities such as reclamation and rejected field repeatedly, which hindered the soil health. One of the mainly form is soil salinization. Spatial distribution and variation of soil salinity is essential both for agricultural resource management and local economic development. However, knowledge of the spatial distribution of soil salinization in this region has not been updated since 1980s while land use and climate have undergone major changed. Electromagnetic induction (EMI) has been successfully used to directly measurement the spatial distribution of targeting soil property at field- scale, and apparent electrical conductivity (ECa, mS m^-1) has become a surrogate of soil salinity (EC, dS m^-1) studied by many researchers at local scale. However, the effectiveness of this equipment has not been verified in the typical soil salinization areas in southern Xinjiang, especially on a large scale. This study was aimed to test the performance of ECa jointed with Random Forest (RF) for soil salinity regional-scale mapping at a typical arid area, taking Tarim River Basin as an example. The result showed that ECa together with environmental derivative variables and with RF were suited for regional-scale soil salinity mapping. Predicted accuracy of EC was higher at surface (0-20 cm, R² = 0.65, RMSE = 5.59) and deeper soil depth (60-80 cm, R² = 0.63, RMSE = 2.00, and 80-100 cm, R² = 0.61, RMSE = 1.73), lower at transitional zone (20-40 cm, R² = 0.55, RMSE = 2.66, and 40-60 cm, R² = 0.51, RMSE = 2.49). When ECa is involved in modeling, the prediction accuracy of multiple depths of EC is improved by 13.33%-61.54%, of which the most obvious depths are 60-80 cm and 0-20 cm. The results of variable importance show that SoilGrids were also favored the power EC model. Hence, we strongly recommended to joint EMI reads with remote sensing imagery for soil salinity monitoring at large scale in southern Xinjiang. These EC and ECa map can provide a data source for environmental modeling, a benchmark against which to evaluate and monitor water and salt dynamics, and a guide for the design of future soil surveys.

Keywords: Digital soil mapping; Electromagnetic induction (EMI); Harmonized World Soil Database; Random forest; Soil salinity; Tarim River Basin.