Assessing the value of electrical resistivity derived soil water content: Insights from a case study in the Critical Zone of the Chinese Loess Plateau
2020
Sun, Hui | Wang, Yunqiang | Zhao, Yali | Zhang, Pingping | Song, Yi | He, Meina | Zhang, Chencheng | Tong, Yongping | Zhou, Jingxiong | Qi, Lijun | Xu, Lan
Acquiring data for the soil water content (θ) is important for assessing vegetation growth, drought, and climate change. However, it is a time-consuming and labor-intensive task that is especially challenging in deep soils. Therefore, we introduce the noninvasive technique of electrical resistivity tomography (ERT) for indirectly determining θ through the development of prediction models for loessial regions under different site conditions (i.e., soil texture, land use, soil depth, and dry/wet conditions). We obtained 2769 pairs of electrical resistivity (ρ) and θ datasets using ERT (53 sites) and a neutron probe (69 access tubes) on the Chinese Loess Plateau. We built linear and nonlinear models correlating ρ and θ and selected the best model according to the coefficient of determination (R²) and root-mean-square error (RMSE). The uncertainty and sensitivity of ERT-derived θ were further evaluated and acceptable results were obtained. The new models correlating ρ and θ under different site conditions are the first set of models based on field data from a loessial region, and their acceptable performance makes them applicable for measuring different soil parameters in the Loess Plateau and possibly other loessial regions around the world.
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