首页|Can hydraulic-energy-indices be effectively used to describe the saturated hydraulic conductivity?
Can hydraulic-energy-indices be effectively used to describe the saturated hydraulic conductivity?
扫码查看
点击上方二维码区域,可以放大扫码查看
原文链接
NETL
NSTL
万方数据
The saturated hydraulic conductivity(Ks)and water retention curve(SWRC)parameters are important properties for simulating soil hydrological processes and characterizing soil conservation around the world.Therefore,Ks and SWRC are related with the soil physical quality(SPQ)and several SPQ indices can be derived from SWRC,such as the pore size distribution,relative field capacity,plant available water,drainable porosity,and soil hydraulic-energy indices(SHEI).It is well known that the soil structure can be assessed by using SHEI,but a possible physical relationship between Ks and SHEI was not examined yet.Therefore,the objective of this study was to investigate the behavior of Ks as function of SHEI for several soil textural classes.If this relationship be proved,then SHEI might be applied to improve the Ks prediction by PTF models.In this work,a data set of 395 measured SWRC's were fitted to the vG equation to obtain the SHEI to verify whether they are statistically correlated and physically dependent on Ks.The resulting parametric and non-parametric correlation results were split up according to six textural classes.The significant influence of Ks on at least one of the absolute SHEI(Aa or WRa)was verified on the numerical scale when all textures were grouped and on numerical and pF scales for clayey and silty textures.Ks showed significant impact on Aa and WRa indices in four textural classes.Furthermore,Ks had influence on the sum Aa+WRa denoted in pF scale for five of the six textural classes,with a significant linear correlation in the clayey texture when log(Aa+WRa)was applied.The significant and high cor-relation of Ks on the ratios WRa/AWC and Aa/φD was also observed in four of the six classes,and therefore the use of these indices is recommended for the development of PTFs for Ks prediction.
Soil structureSoil permeabilitySoil water retention curveSoil physical quality
Lucas Biasi Gastaldon、Sérgio Martins De Souza、Tatiana Cardoso e Bufalo、Robson André Armindo、Ole Wendroth
展开 >
Federal University of Lavras(UFLA),Institute of Natural Sciences(ICN),Department of Physics,Mailbox 3037,37200-900,Lavras(MG),Brazil
University of Kentucky(UK),Department of Plant and Soil Sciences,Ag.Sci.North N-122M,Lexington,KY 40546-0031,USA