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Using pedotransfer functions to estimate soil hydraulic conductivity in the Loess Plateau of China
Zhao C. L.; Shao, M. A.; Jia, X. X.; Nasir, M.; Zhang, C. C.
Source PublicationCatena
2016
Volume143
Pages1-6
KeywordSaturated soil hydraulic conductivity Loess Plateau Artificial neural network Multiple linear regression Stability artificial neural-networks particle-size distribution physical-properties water conservation bulk-density prediction inference variables patterns systems
AbstractSoil hydraulic conductivity (K-s) is a crucial soil physical property that not only influences soil hydrological processes, but also the planning for vegetation recovery, irrigation practice and drainage design. However, K-s data are often lacking at large-scale soil database due to difficulties in direct measurement that is often labour intensive, time consuming and cost inefficient. The objective of this study was to compare the performance of different emerging methods [Multiple linear regression (MLR) and artificial neural network (ANN)] of K-s prediction. The pedotransfer function (PTF) is one such method that is based on selected factors closely correlated with K-s at regional scale. We collected disturbed and undisturbed soil samples in the 0-40 cm soil layer at 243 sites across the entire typical Loess Plateau of China (430,000 km(2)) and then measured K-s and the potentially related factors. The results showed that K-s was normally distributed with moderate a spatial variation (CV = 67%). Correlation analysis indicated that bulk density (BD), saturated soil water content (SSWC), clay content (Clay), silt content (Silt) and latitude were closely correlated (p < 0.05) with K-s. Although the accuracies of MLR and ANN were equal in terms of estimating K-s, the stability of PTF developed via ANN was not as good as that of MLR. Thus PTF developed via MLR, which included BD, Silt and Clay, was considered as the best model for estimating K-s. There is a need to closely monitor the stability and repeatability of PTF during comparison and determination of PTF. (C) 2016 Elsevier B.V. All rights reserved.
Indexed BySCI
Language英语
ISSN0341-8162
DOI10.1016/j.catena.2016.03.037
Citation statistics
Document TypeSCI/SSCI论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/43430
Collection历年回溯文献
Recommended Citation
GB/T 7714
Zhao C. L.,Shao, M. A.,Jia, X. X.,et al. Using pedotransfer functions to estimate soil hydraulic conductivity in the Loess Plateau of China. 2016.
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