中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Pedotransfer functions for estimating the field capacity and permanent wilting point in the critical zone of the Loess Plateau, China

文献类型:期刊论文

作者Qiao, Jiangbo1; Zhu, Yuanjun2; Jia, Xiaoxu3; Huang, Laiming3; Shao, Ming'an2,3
刊名JOURNAL OF SOILS AND SEDIMENTS
出版日期2019
卷号19期号:1页码:140-147
关键词Earth's critical zone Field capacity Pedotransfer function Permanent wilting point
ISSN号1439-0108
DOI10.1007/s11368-018-2036-x
通讯作者Zhu, Yuanjun(zhuyuanjun@foxmail.com)
英文摘要PurposeField capacity (FC) and permanent wilting point (PWP) are important physical properties for evaluating the available soil water storage, as well as being used as input variables for related agro-hydrological models. Direct measurements of FC and PWP are time consuming and expensive, and thus, it is necessary to develop related pedotransfer functions (PTFs). In this study, stepwise multiple linear regression (SMLR) and artificial neural network (ANN) methods were used to develop FC and PWP PTFs for the deep layer of the Loess Plateau based on the bulk density (BD),sand, silt, clay, and soil organic carbon (SOC) contents.Materials and methodsSoil core drilling was used to obtain undisturbed soil cores from three typical sites on the Loess Plateau, which ranged from the top of the soil profile to the bedrock (0-200m). The FC and PWP were measured using the centrifugation method at suctions of -33 and -1500kPa, respectively.Results and discussionThe results showed that FC and PWP exhibited moderate variation where the coefficients of variation were 11 and 23%, respectively. FC had significant correlations with sand, silt, clay, and SOC (P<0.01), while there were also significant correlations between all of the variables and PWP. In addition, sand was an important input variable for predicting FC, and clay and BD for predicting PWP. The performance of the SMLR and ANN approaches was similar.ConclusionsIn this study, we developed new PTFs for FC and PWP as the first set of PTFs based on data obtained from deep profiles in the Loess Plateau. These PTFs are important for evaluating the soil water conditions in the deep profile in this region.
WOS关键词SOIL HYDRAULIC-PROPERTIES ; WATER RETENTION ; BULK-DENSITY ; PREDICTION ; REGRESSION ; TEXTURE
资助项目National Natural Science Foundation of China for a major international cooperation program between China and England[41571130081] ; National Natural Science Foundation of China[41371242] ; National Natural Science Foundation of China[41530854] ; National Key Research and Development Program of China[2016YFC0501706-03]
WOS研究方向Environmental Sciences & Ecology ; Agriculture
语种英语
WOS记录号WOS:000456207800014
出版者SPRINGER HEIDELBERG
资助机构National Natural Science Foundation of China for a major international cooperation program between China and England ; National Natural Science Foundation of China ; National Key Research and Development Program of China
源URL[http://ir.igsnrr.ac.cn/handle/311030/50527]  
专题中国科学院地理科学与资源研究所
通讯作者Zhu, Yuanjun
作者单位1.Northwest A&F Univ, Coll Resources & Environm, Yangling 712100, Shaanxi, Peoples R China
2.Northwest A&F Univ, State Key Lab Soil Eros & Dryland Agr Loess Plate, Yangling 712100, Shaanxi, Peoples R China
3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China
推荐引用方式
GB/T 7714
Qiao, Jiangbo,Zhu, Yuanjun,Jia, Xiaoxu,et al. Pedotransfer functions for estimating the field capacity and permanent wilting point in the critical zone of the Loess Plateau, China[J]. JOURNAL OF SOILS AND SEDIMENTS,2019,19(1):140-147.
APA Qiao, Jiangbo,Zhu, Yuanjun,Jia, Xiaoxu,Huang, Laiming,&Shao, Ming'an.(2019).Pedotransfer functions for estimating the field capacity and permanent wilting point in the critical zone of the Loess Plateau, China.JOURNAL OF SOILS AND SEDIMENTS,19(1),140-147.
MLA Qiao, Jiangbo,et al."Pedotransfer functions for estimating the field capacity and permanent wilting point in the critical zone of the Loess Plateau, China".JOURNAL OF SOILS AND SEDIMENTS 19.1(2019):140-147.

入库方式: OAI收割

来源:地理科学与资源研究所

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