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科研机构
地理科学与资源研究所 [4]
内容类型
SCI/SSCI论文 [4]
发表日期
2016 [2]
2013 [2]
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Using pedotransfer functions to estimate soil hydraulic conductivity in the Loess Plateau of China
SCI/SSCI论文
2016
作者:
Zhao C. L.
;
Shao, M. A.
;
Jia, X. X.
;
Nasir, M.
;
Zhang, C. C.
收藏
  |  
浏览/下载:56/0
  |  
提交时间:2016/12/16
Saturated 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
Predicting available water of soil from particle-size distribution and bulk density in an oasis-desert transect in northwestern China
SCI/SSCI论文
2016
作者:
Li D. F.
;
Gao, G. Y.
;
Shao, M. A.
;
Fu, B. J.
收藏
  |  
浏览/下载:19/0
  |  
提交时间:2017/11/09
Soil water characteristic curve
Soil available water
Pedotransfer
functions
Oasis-desert transect
hydraulic-properties
pedotransfer functions
retention properties
liquid retention
neural-networks
porous-media
model
pore
conductivity
capacity
Multiscale Influences of Soil Properties on Soil Water Content Distribution in a Watershed on the Chinese Loess Plateau
SCI/SSCI论文
2013
作者:
She, Dongli
;
Liu, Dongdong
;
Peng, Shizhang
;
Shao, Ming'an
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  |  
浏览/下载:1/0
  |  
提交时间:2014/12/24
Spatial Variability
Soil Water Content
Scale
Multivariate Empirical Mode Decomposition
Comparison of three methods to develop pedotransfer functions for the saturated water content and field water capacity in permafrost region
SCI/SSCI论文
2013
Yi X. S.
;
Li G. S.
;
Yin Y. Y.
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  |  
浏览/下载:26/0
  |  
提交时间:2014/12/24
Pedotransfer functions
Multiple-linear regression
Artificial neural
network
Rosetta method
soil hydraulic conductivity
particle-size distribution
pedo-transfer
functions
neural-network models
retention characteristics
bulk-density
physical-properties
alluvial soils
prediction
parameters
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