Prediction of the van Genuchten model soil hydraulic parameters for the 5-m soil profile in China’s Loess Plateau

• Published in: Catena (Giessen) 2022-03, Vol.210, p.105889, Article 105889
• Main Authors: Bai, Xiao, Shao, Ming'an, Jia, Xiaoxu, Zhao, Chunlei
• Format: Article
• Language: English
• Subjects: China’s Loess Plateau Region; Pedotransfer function; Soil hydraulic parameter; Van Genuchten model
• ISSN: 0341-8162; 1872-6887
• DOI: 10.1016/j.catena.2021.105889

Flowchart of PTF development, PTF validation and SHP estimation in the study area. [Display omitted] •Soil hydraulic parameters measured for the 0–8 m profiles in China’s Loess Plateau.•Soil hydraulic parameters estimated for the 5-m soil profile at 243 sites.•Soil hydraulic parameter data developed at 1 km resolution for the study area. Soil hydraulic parameters (SHPs) represent a crucial input for modelling of water flow, biogeochemical processes, and plant growth. This modelling depends on an accurate description of the water balance in a critical soil zone. To this end, pedotransfer functions (PTFs) are required to translate basic soil data into SHPs as it is challenging to measure them. This challenge is peculiarly acute for deep soil layers in thick loess deposits, such as in the China’s Loess Plateau Region (CLPR). In this study, we analysed which factors are strongly correlated with SHPs, and developed PTFs for the SHPs. To this end, undisturbed and disturbed soil samples were collected up to 8 m depth at seven sampling sites in the CLPR to measure the soil water retention curve, saturated hydraulic conductivity (Ks), and associated soil and environmental factors. Furthermore, soil core samples in the 5 m soil profile were collected at 243 sites, and the corresponding environmental factors were calculated to estimate the spatial distribution of SHPs across the CLPR using the established PTFs. Redundancy analysis of the collected data in the 0–8-m soil profile revealed that soil texture, soil depth, mean annual precipitation, slope gradient, slope aspect, and elevation were strongly correlated with SHPs. The most correlated variables were used to develop PTFs for SHPs by using stepwise multiple linear regression. The accuracy of the established regional PTFs was significantly higher compared to state-of-the-art in this domain. The spatial distribution of SHPs in the CLPR study area exhibited significant spatial clustering. Generally, SHPs transitioned from the southeast to the northwest, with significant differences between the south and north. Our results provide empirical basis for further quantification of the response of soil hydrological processes to vegetation restoration and land-use change not only in the CLPR, but also in other similar regions.