Traditional dry soil layer index method overestimates soil desiccation severity following conversion of cropland into forest and grassland on China’s Loess Plateau

Due to severe soil erosion and low crop yield, sloping croplands have been converted into forests and grasslands during the past decades on China’s Loess Plateau (CLP). The introduced exotic high-water consumption plants cause soil water deficit that leads to the formation of dry soil layer (DSL). The traditional index method used to determine the existence of DSL considers only soil hydraulic property of “stable field capacity” and fails to fully reflect the interactions between soil water and vegetation. A new index method that considers physiological response of vegetation to drought is needed for DSL research. Here, we proposed a new method to identify and quantify the severity of DSL and compared the proposed method with the traditional method using field data for the 5 m soil depth in typical tree (R. pseudoacacia, n = 85) and grass (M. sativa, n = 20) plantations on CLP. The number of sites detected with DSL through the new method was less than the traditional method for both species. Based on the traditional method, the level of DSL was even more severe; with mean DSL thickness of 3.2 for R. pseudoacacia and 3.9 m for M. sativa. Then for the new index method, it was only 2.4 m for both plantations. DSL formation depth was much deeper under the new method than the traditional method. Also mean plant available soil water (PASW) stored in the identified DSL by the traditional method was ∼44.1 and 37.8 mm; accounting for 37.2 and 88.9% of total PASW in the 1–5 m soil profile under R. pseudoacacia and M. sativa, respectively. Thus, the traditional DSL index method overestimated DSL severity as it fails to account for plant soil water availability, especially in areas with coarser soil texture. The proposed new index method that is based on soil water potential is more suitable for characterization of DSL conditions under different soil types. This is critical for application in reclamation of DSLs and optimization of vegetation cover in the study area and beyond.