Prediction of the van Genuchten model soil hydraulic parameters for the 5-m soil profile in China's Loess Plateau
文献类型：期刊论文
| 作者 | Bai, Xiao1; Shao, Ming'an1,2,3; Jia, Xiaoxu2,3; Zhao, Chunlei2,3 |
| 刊名 | CATENA
 |
| 出版日期 | 2022-03-01 |
| 卷号 | 210页码:11 |
| 关键词 | Soil hydraulic parameter Van Genuchten model Pedotransfer function China 's Loess Plateau Region |
| ISSN号 | 0341-8162 |
| DOI | 10.1016/j.catena.2021.105889 |
| 通讯作者 | Shao, Ming'an(shaoma@igsnrr.ac.cn) |
| 英文摘要 | Soil hydraulic parameters (SHPs) represent a crucial input for modelling of water flow, biogeochemical pro-cesses, 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. |
| WOS关键词 | PEDOTRANSFER FUNCTIONS |
| 资助项目 | Strategic Priority Research Program of the Chinese Academy of Sciences[XDB40020000] ; National Natural Science Foundation of China[41877016] ; National Natural Science Foundation of China[42022048] ; Youth Innovation Promotion Association of Chinese Academy of Sciences[2017076] |
| WOS研究方向 | Geology ; Agriculture ; Water Resources |
| 语种 | 英语 |
| WOS记录号 | WOS:000790437800003 |
| 出版者 | ELSEVIER |
| 资助机构 | Strategic Priority Research Program of the Chinese Academy of Sciences ; National Natural Science Foundation of China ; Youth Innovation Promotion Association of Chinese Academy of Sciences |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/175889]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Shao, Ming'an |
| 作者单位 | 1.Northwest A&F Univ, Coll Nat Resources & Environm, 3 Taicheng Rd, Yangling 712100, Shaanxi, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modelling, Beijing 100101, Peoples R China 3.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Bai, Xiao,Shao, Ming'an,Jia, Xiaoxu,et al. Prediction of the van Genuchten model soil hydraulic parameters for the 5-m soil profile in China's Loess Plateau[J]. CATENA,2022,210:11. |
| APA | Bai, Xiao,Shao, Ming'an,Jia, Xiaoxu,&Zhao, Chunlei.(2022).Prediction of the van Genuchten model soil hydraulic parameters for the 5-m soil profile in China's Loess Plateau.CATENA,210,11. |
| MLA | Bai, Xiao,et al."Prediction of the van Genuchten model soil hydraulic parameters for the 5-m soil profile in China's Loess Plateau".CATENA 210(2022):11. |
入库方式： OAI收割
来源：地理科学与资源研究所
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