Pedo-transfer functions for estimating the hydraulic properties of paddy soils in subtropical central China

Pedo-transfer functions (PTFs) have been widely used to estimate soil hydraulic properties in the simulation of catchment eco-hydrological processes. However, the accuracy of existing PTFs is usually inadequate for use. To develop PTFs for local use, soil columns were collected from a double rice-cropped agricultural catchment in subtropical central China. The PTFs for saturated soil hydraulic conductivity (K_s) and parameters (θ_s, α, and n) of the van Genuchten model for the soil water retention curve (SWRC) were obtained based on soil’s basic properties, and compared with models developed by Li et al. in 2007 and Wösten et al. in 1999, respectively. Our results indicated that K_s in the range of 0.04–1087 cm d^?1 and θ_s in the range of 0.34–0.51 cm³ cm^?3 were both well estimated with the R²_adj of 0.72 and 0.87, respectively, but α (0.04–0.65 cm^?1) and n (1.05–1.21) were relatively poorly predicted with the respective R²_adj of 0.38 and 0.55, despite the use of more input parameters. Our local derived PTFs outperformed the other two existing models. However, if the local PTFs for paddy soils are not available, the Wösten et al. 1999 model can be proposed as a useful alternative. Therefore, this study can improve our understanding of the development and application of PTFs for predicting paddy soil hydraulic properties in China.     

利用土壤传递函数估算土壤水力学特性研究进展

Characterization of soil hydraulic properties is important to environment management; however, it is well recognized that it is laborious, time-consuming and expensive to directly measure soil hydraulic properties. This paper reviews the development of pedotransfer functions (PTFs) used as an alternative tool to estimate soil hydraulic properties during the last two decades. Modern soil survey techniques like satellite imagery/remote sensing has been used in developing PTFs. Compared to mechanistic approaches, empirical relationships between physical properties and hydraulic properties have received wide preference for predicting soil hydraulic properties. Many PTFs based on different parametric functions can be found in the literature. A number of researchers have pursued a universal function that can describe water retention characteristics of all types of soils, but no single function can be termed generic though van Genuchten (VG) function has been the most widely adopted. Most of the reported parametric PTFs focus on estimation of VG parameters to obtain water retention curve (WRC). A number of physical, morphological and chemical properties have been used as predictor variables in PTFs. Conventionally, regression algorithms/techniques (statistical/neural regression) have been used for calibrating PTFs. However, there are reports of utilizing data mining techniques, e.g., pattern recognition and genetic algorithm. It is inferred that it is critical to refine the data used for calibration to improve the accuracy and reliability of the PTFs. Many statistical indices, including root mean square error (RMSE), index of agreement (d), maximum absolute error (ME), mean absolute error (MAE), coefficient of determination (r²) and correlation coefficient (r), have been used by different researchers to evaluate and validate PTFs. It is argued that being location specific, research interest in PTFs will continue till generic PTFs are developed and validated. In future studies, improved methods will be required to extract information from the existing database.     

A relatively simple scaling method for describing the unsaturated hydraulic functions of stony soils

Few if any methods exist to estimate the effects of stone content (stoniness) on the unsaturated soil hydraulic properties. A relatively simple scaling method is presented to estimate the hydraulic conductivity of unsaturated stony soils having different stone contents. A key assumption of the method is that van Genuchten's water retention parameters α and n of the fine soil fraction are the same as those of the stony soil. The method further assumes a linearly decreasing relationship between the saturated hydraulic conductivity and the stone content, based on previous numerical simulations. Using the proposed method, it is possible to calculate the hydraulic conductivity of unsaturated stony soils, knowing the saturated hydraulic conductivity of the fine soil fraction, the retention curve of the fine soil fraction, and the particular stoniness of the soil.     

Pedotransfer functions for solute transport parameters of Portuguese soils

The purpose of this study is to quantify solute transport parameters of fine‐textured soils in an irrigation district in southern Portugal and to investigate their prediction from basic soil properties and unsaturated hydraulic parameters. Solute displacement experiments were carried out on 24 undisturbed soil samples by applying a 0.05 m KCl pulse during steady flow. The chloride breakthrough curves (BTCs) were asymmetric, with early breakthrough and considerable tailing characteristic of non‐equilibrium transport. The retardation factor (R), dispersion coefficient (D), partitioning coefficient (β), and mass transfer coefficient (ω) were estimated by optimizing the solution of the non‐equilibrium convection–dispersion equation (CDE) to the breakthrough data. The solution could adequately describe the observed data as proved by a median of 0.972 for the coefficient of determination (r²) and a median for the mean squared error (MSE) of 5.1 × 10^?6. The median value for R of 0.587 suggests that Cl^– was excluded from a substantial part of the liquid phase. The value for β was typically less than 0.5, but the non‐equilibrium effects were mitigated by a large mass transfer coefficient (ω > 1). Pedotransfer functions (PTFs) were developed with regression and neural network analyses to predict R, D, β and ω from basic soil properties and unsaturated hydraulic parameters. Fairly accurate predictions could be obtained for logD (r² ≈ 0.9) and β (r² ≈ 0.8). Prediction for R and logω were relatively poor (r² ≈ 0.5). The artificial neural networks were all somewhat more accurate than the regression equations. The networks are also more suitable for predicting transport parameters because they require only three input variables, whereas the regression equations contain many predictor variables.     

Evaluation of pedotransfer functions predicting hydraulic properties of soils and deeper sediments

Eight pedotransfer functions (PTF) originally calibrated to soil data are used for evaluation of hydraulic properties of soils and deeper sediments. Only PTFs are considered which had shown good results in previous investigations. Two data sets were used for this purpose: a data set of measured pressure heads vs. water contents of 347 soil horizons (802 measured pairs) from Bavaria (Southern Germany) and a data set of 39 undisturbed samples of tertiary sediments from deeper ground (down to 100 m depth) in the molasse basin north of the Alps, containing 840 measured water contents vs. pressure head and unsaturated hydraulic conductivity. A statistical analysis of the PTFs shows that their performance is quite similar with respect to predicting soil water contents. Less satisfactory results were obtained when the PTFs were applied to prediction of water content of sediments from deeper ground. The predicted unsaturated hydraulic conductivities show about the same uncertainty as for soils in a previous study. Systematic deviations of predicted values indicate that an adaptation of the PTFs to the specific conditions of deeper ground should be possible in order to improve predictions.     

Pedotransfer functions for estimating soil water retention curve of Sicilian soils

Pedotransfer functions (PTFs) make use of routinely surveyed soil data to estimate soil properties but their application to soils different from those used for their development can yield inaccurate estimates. This investigation aimed at evaluating the water retention prediction accuracy of eight existing PTFs using a database of 217 Sicilian soils exploring 11 USDA textural classes. PTFs performance was assessed by root mean square differences (RMSD) and average differences (AD) between estimated and measured data. Extended Nonlinear Regression (ENR) technique was adopted to recalibrate or develop four new PTFs and Wind’s evaporation method was applied to validate the effectiveness of the relationships proposed. PTFs evaluation resulted in RMSD and AD values in the range 0.0630–0.0972 and 0.0021–0.0618 cm³ cm^–3, respectively. Best and worst performances were obtained respectively by PTF-MI and PTF-ZW. ENR allowed to recalibrate PTF-MI and PTF-ZW with improvements of RMSD (0.0594 and 0.0508 cm³ cm^–3) and to develop two relationships that improved RMSD by 75–78% as compared to PTF-MI. The results confirmed the potential of ENR technique in calibrating existing PTFs or developing new ones. Validation conducted with an independent dataset suggested that recalibrated/developed PTFs represent a viable alternative for water retention estimation of Sicilian soils.     

Influence of water content and soil properties on unsaturated hydraulic conductivity of some red and black soils

The unsaturated hydraulic conductivity was determined in the laboratory for some red and black soils, following water movement into a horizontal column of homogenous soil of uniform packing. A highly significant positive relationship was found between moisture content and hydraulic conductivity values in all the soils studied. Correlation coefficients calculated for the relationships between soil constituents/properties and the change in hydraulic conductivity per unit change in moisture content (regression coefficient between hydraulic conductivity and moisture content) have shown positive relationship to sand and negative relationships to silt, silt + clay, clay, carbonates, aggregates > 0.25 mm and saturated hydraulic conductivity. It is concluded that the unsaturated hydraulic conductivity decreases rapidly with decrease in moisture content and this decrease depends on the soil constituents/properties and differences between soil types are clear.     

Simplified method for quantifying the hydraulic properties of shrinking soils

In general, soils and their pore size systems are assumed to be rigid during the loss of water on drying. In reality, it is not the case for most soils, especially for soils with high quantities of clay or organic matter. As a result of shrinking, there are changes in the bulk density, the porosity, the pore size distribution, and the hydraulic properties of these soils. Currently, only a few methods enable the shrinkage behavior of soil samples to be determined while simultaneously quantifying the corresponding soil hydraulic properties. Either the methods need proprietary software for data processing, the equipment used is expensive or the calculation of the hydraulic properties is executed by inverse modelling. The aim of this study was to develop an alternative, simplified method for the simultaneous and automatic determination of the soil hydraulic properties, taking shrinkage into account. The HYPROP® evaporative device was combined with a circumference meter. A preliminary investigation found that the diameter of the cylindrical samples used for the HYPROP decreased linearly during evaporation from the bottom to the top. To sum up, recording the perimeter change in the middle position of the sample during drying‐out, together with the corresponding tension and water content, was sufficient to determine the hydraulic functions taking shrinkage into account. Measurements are presented for 6 samples which are different in texture and geological origin. The maximum shrinkage (19.5% by vol. between saturation and 5,000 hPa) was measured in the peat samples. The minimum shrinkage was quantified at 0.68% by vol. for the silty loam samples from Chile. The advantages of the method presented are: (1) the water retention curve and the hydraulic conductivity function can be determined simultaneously in the range between saturation and close to the wilting point, at a high resolution and taking into consideration shrinkage; (2) the method and device are simple and robust to use; (3) little time is required for measurement, between 3 and at most 10 d; (4) the functions are described over the whole tension range, using more than 100 user‐defined data points; (5) the evaluation of the volumetric soil water content measurement in shrinking soils is improved; and (6) common data models can be fitted to the hydraulic data as well as to the shrinkage data.     

Pedotransfer functions for estimating plant available water and bulk density in Swedish agricultural soils

Abstract

Pedotransfer functions (PTFs) to estimate plant available water were developed from a database of arable soils in Sweden. The PTFs were developed to fulfil the minimum requirements of any agro-hydrological application, i.e., soil water content at wilting point (θ _wp ) and field capacity (θ _fc ), from information that frequently is available from soil surveys such as texture and soil organic carbon content (SOC). From the same variables we also estimated bulk density (ρ) and porosity (ε), which seldom are included in surveys, but are needed for calculating element mass balances. The seven particle-size classes given in the data set were aggregated in different ways to match information commonly gained from surveys. Analysis of covariance and stepwise multiple linear regression were used for quantifying the influence of depth, particle size class, textural class and soil organic carbon on the characteristic variables. PTFs developed from other data sets were also tested and their goodness-of-fit and bias was evaluated. These functions and those developed for the Swedish database were also tested on an independent data set and finally ranked according to their goodness of fit. Among single independent variables, clay was the best predictor for θ _wp , sand (or the sum of clay and silt) for θ _fc and SOC for ρ and ε. A large fraction of the variation in θ _wp and θ _fc is explained by soil texture and SOC (up to 90%) and root mean square errors (RMSEs) were as small as 0.03 m³ water m^?3 soil in the best models. For the prediction of ρ and ε in the test data set, the best PTF could only explain 40–43% of the total variance with corresponding RMSEs of 0.14 g cm^?3 and 5.3% by volume, respectively. Recently presented PTFs derived from a North American database performed very well for estimating θ _wp (low error and bias) and could be recommended for Swedish soils if measurements of clay, sand and SOC were available. Although somewhat less accurately, also θ _fc could be estimated satisfactorily. This indicates that the determination of plant available water by texture and SOC is rather independent of soil genesis and that certain PTFs are transferable between continents.     

Relationship between hydraulic and basic properties for irrigated soils in southeast Australia

This paper examines the potential of soil maps and spatial information on basic soil properties for predicting soil hydraulic properties in the Shepparton irrigation region (SE Australia). For this purpose, the relationship between locally measured soil hydraulic properties and basic soil properties, and soil categories was analyzed. Pedotransfer functions developed for Australian soil were tested. Furthermore, association of field‐scale final infiltration rates with basic soil properties was investigated. Water‐retention properties, and in particular subsoil water‐retention properties, were significantly correlated with readily available basic soil properties. Spearman's rank correlation coefficients were particularly high for clay content, bulk density, and the sum of exchangeable cations Ca²⁺, Mg²⁺, Na⁺, and K⁺. Water‐retention properties were adequately predicted using Australian pedotransfer functions. Water‐transmission properties such the saturated conductivity and the final infiltration rate were overall poorly correlated with basic physical and chemical properties. Generally, median water‐transmission properties did not significantly change with soil groups and “within‐paddock variability” accounted for over half of the “within‐soil‐type variability” for many soil types. We concluded that it is feasible to regionalize water‐retention properties for the Shepparton irrigation region using basic physical and chemical soil properties, whereas the information on basic soil properties and from soil maps was insufficient to reliably estimate water‐transmission properties. It is demonstrated why field‐scale estimates of final infiltration rates, obtained by fitting a model for surface irrigation to field measurements of advance, depletion, and recession, may be better correlated with basic soil properties.     

Predicting unsaturated hydraulic conductivity of soil based on some basic soil properties

Soil hydraulic conductivity is a crucial parameter in modeling flow process in soils and deciding water management. In this study, by combining the non-similar media concept (NSMC) to the one-parameter model of Brooks and Corey, a new NSMC-based model for estimating unsaturated hydraulic conductivity of various soils was presented. The main inputs are soil bulk density, particle-size distribution, soil water retention characteristic and saturated hydraulic conductivity of soil. The results indicated that the NSMC-based model could generally more accurately predict unsaturated hydraulic conductivity of soils, as compared to four one-parameter models and van Genuchten–Mualem model. This study, by introducing NSMC, provided a new way to incorporate soil physical heterogeneity into soil hydraulic simulation, and hence NSMC-based approach is expected to improve efficiency of the existing models in the simulation of soil water flow.     

用于估算伊朗盐土和盐碱土土壤水分特征曲线的土壤传递函数(PTFs)研究

Soil water retention data are essential for irrigation scheduling and determination of irrigation frequency.However,direct measurement of this characteristic is time consuming and expensive and furthermore its spatial and temporal variabilities in field scales increase the number of measurements.Different pedotransfer functions,such as Saxton et al.,Campbell,Vereecken et al.,Rawls and Brakensiek,Wo¨sten et al.,Rajkai et al.,Ghorbani Dashtaki and Homaee,Zacharias and Wessolek,and Rosetta,were evaluated to estimate soil water retention of saline and saline-alkali soils collected from south of Tehran,Iran.The saturation-extract conductivity of all the 68 samples and exchangeable sodium percentage of more than half of them were measured to be greater than 4 dS m-1 and 15%,respectively.The calculated Akaike’s information criterion values showed that Saxton et al.and Campbell models were the best in estimation of soil water retention curve and total available water,respectively.     

Applicability of cavity-throat connecting model for estimating the hydraulic conductivity of fine-grained soils: a geometrical and mathematical approach

Purpose

Determining the hydraulic conductivity of low permeable fine-grained soils is difficult and time-consuming. This work develops a new method with an eye to the pore morphology to correlate hydraulic conductivity with pore-size distribution (PSD) parameters obtained from mercury porosimeter data. In order to realize this method, calculating percolation loss along the flow paths in pore channels and quantifying the spatial morphology of pore channels by proposing a cavity-throat connecting model is necessary.

Materials and methods

In order to establish the standard process of the new method, a kind of sedimentary mucky clay with regular dual-structural PSD has been collected. The samples are divided into three series: (a) vibrated with variable frequencies; (b) frozen at variable temperatures and unfrozen, making the freezing-thawing effect as the variable; and (c) remolded with different water contents. The PSD of freeze-dried samples at the end of each process is obtained by mercury intrusion porosimetry. After that, the method is demonstrated with application to 12 series of fine-grained soils.

Results and discussion

Deduced from mercury porosimeter data, the volume-based PSD curves of fine-grained soils are bimodal, due to the presence of inter-aggregate and intra-aggregate pores. Two important hypotheses have been proposed: (i) one is that in the smaller pore scales, the experimental extrusion curve controlled by the hysteresis loop has a really approximate part compared to the theoretical overall retraction curve, making the experimental extrusion curve characterize the pore cavity size approximately, and (ii) the pore system consists of a series of multistage cavity-throat connections. Accumulating the effects of single connection on the percolation can be used to measure the overall effects of pore system on the percolation. Based on fluid-driven path analysis of percolation, the pore system is quantified by a series of cavity-throat connections and the percolation loss has been derived to estimate the hydraulic conductivity.

Conclusions

The permeable parameter (κ) representing the overall effects of pore connections on the hydraulic conductivity (K) is suited to correlate the microstructure and hydraulic conductivity by the linear relationship with the fixed slope in semilogarithmic coordinate for the fine-grained soils. It is the destruction and recombination of cavity-throat connections that are dominant during the treatments like freezing, remolding, and reinforcing.

     

根据土壤水平一维入渗推求紫色土水动力学参数

选择3种不同质地的紫色土,通过室内土壤水平一维入渗试验,探讨简单入渗法和入渗特性法推求水动力学参数对于紫色土的适用性。结果显示,简单入渗法和入渗特性法推求的水动力学参数中,水分特征曲线准确性较高,水分扩散率和非饱和导水率准确性较差。简单入渗法推求的水分扩散率和非饱和导水率均低于实测值1～2个数量级,但推求值与实测值曲线趋势较为一致。入渗特性法推求的水分扩散率和非饱和导水率在高含水量小于实测值,在低含水量大于实测值,推求值随含水量变化趋势响应缓慢。     

Determination of unsaturated soil hydraulic properties at different applied tensions and water qualities

Irrigation with low-quality water may change soil hydraulic properties due to excessive electrical conductivity (EC_w) and sodium adsorption ratio (SAR_w). Field experiments were conducted to determine the effects of water quality (EC_w of 0.5–20 dS m^?1 and SAR_w of 0.5–40 mol^0.5 l^?0.5) on the hydraulic properties of a sandy clay loam soil (containing ～421 g gravel kg^?1 soil) at applied tensions of 0–0.2 m. The mean unsaturated hydraulic conductivity [K(ψ)], sorptive number (α) and sorptivity coefficient (S) varied with change in EC_w and SAR_w as quadratic or power equations, whereas macroscopic capillary length, λ, varied as quadratic or logarithmic equations. The maximum value of K(ψ) was obtained with a EC_w/SAR_w of 10 dS m^?1/20 mol^0.5 l^?0.5 at tensions of 0.2 and 0.15 m, and with 10 dS m^?1/10 mol^0.5 l^?0.5 at other tensions. Changes in K(ψ) due to the application of EC_w and SAR_w decreased as applied tension increased. Analysis indicated that 13.7 and 86.3% of water flow corresponded to soil pore diameters <1.5 and >1.5 μm, respectively, confirming that macropores are dominant in the studied soil. The findings indicated that use of saline waters with an EC of <10 dS m^?1 can improve soil hydraulic properties in such soils. Irrigation waters with SAR_w < 20 mol^0.5 l^?0.5 may not adversely affect hydraulic attributes at early time; although higher SAR_w may negatively affect them.     

预测天然文岩渠流域土壤饱和导水率的土壤转换函数方法比较研究

在天然文岩渠流域大量实测土壤剖面数据的基础上,评价了12种根据基本土壤性质预测不同层次土壤饱和水力传导率的土壤转换函数方法的效果,同时还探讨了多元回归和BP人工神经网络两种构建方法的适用性。结果表明：基于BP神经网络方法的土壤转换函数预测精度均显著优于根据多元回归建立的土壤转换函数,其中基于BP-ANN的Wosten1999函数对于表层和底层土壤预测精度最高,而Li2007方法对第二层土壤预测效果最好;不考虑分层因素时,基于BP-ANN的Wosten1999函数预测效果最好。此外还利用GIS空间插值,对天然文岩渠流域不同深度的土壤饱和导水率进行可视化表达,为模拟该地区的土壤水分运动提供参数支持。     

Development and use of a database of hydraulic properties of European soils

Many environmental studies on the protection of European soil and water resources make use of soil water simulation models. A major obstacle to the wider application of these models is the lack of easily accessible and representative soil hydraulic properties. In order to overcome this apparent lack of data, a project was initiated to bring together the available hydraulic data which resided within different institutions in Europe into one central database. This information was then used to derive a set of pedotransfer functions applicable to studies at a European scale. These pedotransfer functions predict the hydraulic properties from parameters collected during soil surveys and can be a good alternative for costly and time-consuming direct measurement of these properties. A total of 20 institutions from 12 European countries collaborated in establishing the database of draulic operties of uropean oils (HYPRES). This database has a flexible relational structure capable of holding a wide diversity of both soil pedological and hydraulic data. As these data were contributed by 20 different institutions it was necessary to standardise both the particle-size and the hydraulic data. A novel similarity interpolation procedure was successfully used to achieve standardization of particle-sizes according to the FAO clay, silt and sand particle-size ranges. Standardization of hydraulic data was achieved by fitting the Mualem-van Genuchten model parameters to the individual θ(h) and K(h) hydraulic properties stored in HYPRES. The HYPRES database contains information on a total of 5521 soil horizons (including replicates). Of these, 4030 horizons had sufficient data to be used in the derivation of pedotransfer functions. Information on both water retention and hydraulic conductivity was available for 1136 horizons whereas 2894 horizons had only information on water retention. Each soil horizon was allocated to one of 11 possible soil textural/pedological classes derived from the six FAO texture classes (five mineral and one organic) and the two pedological classes (topsoil and subsoil) recognised within the 1:1 000 000 scale Soil Geographical Data Base of Europe. Next, both class and continuous pedotransfer functions were developed. By using the class pedotransfer functions in combination with the 1:1 000 000 scale Soil Map of Europe, the spatial distribution of soil water availability within Europe was derived.