Assessing Soil Water Retention Characteristics and Their Spatial Variability Using Pedotransfer Functions

Liao, Kaihua; Su, Xu; Wu, Jichun; Ji, Shuhua; Qing, Lin

doi:10.1016/s1002-0160(11)60143-4

Cited by 33 publications

(21 citation statements)

References 25 publications

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“…Analyzing the empirical 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 Table 2, it can be concluded that in the case of the forest soils occurring in the pine and spruce ecosystems the bulk density (ρ b ), specific density (ρ p ), organic matter content (C org ), sand fraction from 1 to 0.1 mm (S a ), silt fraction from 0.1 to 0.02 mm (S i ), and content of particles smaller than 0.02 mm (S pl ) had essential impact on soil water retention characteristics. The obtained results in the forms of empirical equations generally are in agreement with data presented in the literature [5,15,29]. However, it should be stressed that forecasting of the field capacity, commonly assumed at pF=2, which is a very important soil moisture status [6,32], the S pl fraction content was required.…”

Section: Resultssupporting

confidence: 85%

“…The X i values represent explanatory variables regarding physical properties, particle soil distribution, and soil organic matter content. The set of independent variables describing moisture contents were determined with the use of the backward stepwise elimination method [29]. Finally, the regression coefficients (β i ) were obtained by solving a set of simultaneous linear equations.…”

Section: Methodsmentioning

confidence: 99%

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Analysis of Water Retention Capacity for Select Forest Soils in Poland

Hewelke¹,

Gratowski²,

Hewelke³

et al. 2015

Pol. J. Environ. Stud.

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Section: Resultssupporting

confidence: 85%

Section: Methodsmentioning

confidence: 99%

Analysis of Water Retention Capacity for Select Forest Soils in Poland

Hewelke¹,

Gratowski²,

Hewelke³

et al. 2015

Pol. J. Environ. Stud.

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“…>100 000 km 2 ), a series of predictive methods such as pedotransfer functions (PTFs) have been used to overcome the challenge of collecting a large number of soil samples and of determining the corresponding SWRCs [11,[14][15][16]. However, in practice these methods have not generated accurate results when the PTFs were applied to soils outside of the region for which they were originally developed [17].…”

Section: Introductionmentioning

confidence: 99%

Spatial Variability of Soil Parameters of the van Genuchten Model at a Regional Scale

Wang

Shao

Han

et al. 2014

CLEAN Soil Air Water

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Spatial heterogeneity of soil water retention curves (SWRC) plays an important role in modelling the movement of water and solutes in soils. To characterize the spatial variability of SWRC parameters fitted by the van Genuchten (VG) equation, and then identify factors that closely correlated with the VG parameters, we collected undisturbed and disturbed soil samples from the upper 0-5 cm soil layer at 382 sampling sites across the entire Loess Plateau of China ($620 000 km 2 ). We determined the SWRC and six other soil properties as well as nine environmental factors for each site. Results showed that the saturated water content (u s ) and a curve-shape parameter that is related to soil pore size distribution (n) were weakly spatially variable (coefficient of variation (CV) ¼ 15%), and that the residual soil water content (u r ) and a scaling parameter that is related to the inverse of the air entry pressure (a) were moderately (CV ¼ 96%) and strongly variable (CV ¼ 136%), respectively. Semivariograms of ffiffiffiffi u r p and log(a) were best-fitted by an isotropic exponential model, while those of u s and log(n) were fitted by an isotropic spherical model. Fractal analysis indicated that log(a) demonstrated the most short-range variation, while log(n) reflected the importance of long-range variation. Bulk density and the contents of clay, silt, sand and soil organic carbon contributed greatly to the variations in the VG parameters (except a). However, the vegetation, topographic and climatic elements as well as land use also usually explained some of the variation. The VG parameters, at the regional scale, demonstrated different characteristics of spatial variation, which comprehensively reflected the combined effects of processes involving the soil, vegetation, topography and climate as well as effects of land use, which is often determined by human activity.

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“…Liao et al (2011) evaluated the performance of a PTF developed by Rawls et al (1982), which also assumes Eq. [1], for similar soils of this study to predict the SV of soil water retention.…”

Section: Resultsmentioning

confidence: 99%

An Assessment of Pedotransfer Function Performance for the Estimation of Spatial Variability of Key Soil Hydraulic Properties

Silva

Armindo

Brito

et al. 2017

Vadose Zone Journal

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Core Ideas PTFs have been widely applied in environmental and hydrological watershed studies. PTFs can simulate the spatial variability of hydraulic functions. The simulation of hydraulic maps using PTF data should be performed with care. The reliable applications of soil water dynamics and its spatial variability are very important in hydrological and environmental studies. However, determination of some hydraulic properties requires time and sometimes high costs. Pedotransfer functions (PTFs) have been applied as an alternative for the prediction of soil hydraulic properties by working with some easily measurable physical properties. This study examined the performance of the Splintex and Rosetta PTFs for estimating the spatial variability of some soil hydraulic properties such as available water capacity (AWC), field capacity (θfc), permanent wilting point (θpwp), specific water capacity [C(θ)], conductivity [K(θ)], and diffusivity [D(θ)] in a sandy soil from southeastern Brazil. Based on the log‐likelihood, Akaike, and Bayesian information criteria, semivariogram models were fitted and used to krige the assessed variable maps. The results showed the feasibility of using these PTFs to estimate the spatial variability in soil hydraulic properties and functions, which would greatly benefit vadose zone flow and transport modeling. Geostatistical analyses presented similarities in kriged maps of both observed K(θ) and C(θ) data with kriged maps by Rosetta estimates, as well as the kriged map of the observed AWC data with the kriged map by Splintex estimates sometimes revealing the same semivariogram data pattern. Predicted maps of θfc, θpwp, and D(θ) were, however, different from kriged maps of the observed data, showing that this approach should be used carefully. The use of the range parameter from the semivariogram models was efficient to determine the optimal sample density for the studied area.

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Assessing Soil Water Retention Characteristics and Their Spatial Variability Using Pedotransfer Functions

Cited by 33 publications

References 25 publications

Analysis of Water Retention Capacity for Select Forest Soils in Poland

Analysis of Water Retention Capacity for Select Forest Soils in Poland

Spatial Variability of Soil Parameters of the van Genuchten Model at a Regional Scale

An Assessment of Pedotransfer Function Performance for the Estimation of Spatial Variability of Key Soil Hydraulic Properties

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