Estimating the water retention curve from soil properties: comparison of linear, nonlinear and concomitant variable methods

The unsaturated soil hydraulic functions involving the soil–water retention curve (SWRC) and the hydraulic conductivity provide useful integrated indices of soil quality. Existing and newly devised methods were used to formulate pedotransfer functions (PTFs) that predict the SWRC from readily available soil data. The PTFs were calibrated using a large soils database from Hungary. The database contains measured soil–water retention data, the dry bulk density, sand, silt and clay percentages, and the organic matter content of 305 soil layers from some 80 soil profiles. A three-parameter van Genuchten type function was fitted to the measured retention data to obtain SWRC parameters for each soil sample in the database. Using a quasi-random procedure, the database was divided into “evaluation” (EVAL) and “test” (TEST) parts containing 225 and 80 soil samples, respectively. Linear PTFs for the SWRC parameters were calculated for the EVAL database. The PTFs used for this purpose particle-size percentages, dry bulk density, organic matter content, and the sand/silt ratio, as well as simple transforms (such as logarithms and products) of these independent variables. Of the various independent variables, the eight most significant were used to calculate the different PTFs. A nonlinear (NL) predictive method was obtained by substituting the linear PTFs directly into the SWRC equation, and subsequently adjusting the PTF parameters to all retention data of the EVAL database. The estimation error (SSQ) and efficiency (EE) were used to compare the effectiveness of the linear and nonlinearly adjusted PTFs. We found that EE of the EVAL and the TEST databases increased by 4 and 7%, respectively, using the second nonlinear optimization approach. To further increase EE, one measured retention data point was used as an additional (concomitant) variable in the PTFs. Using the 20 kPa water retention data point in the linear PTFs improved the EE by about 25% for the TEST data set. Nonlinear adjustment of the concomitant variable PTF using the 20 kPa retention data point as concomitant variable produced the best PTF. This PTF produced EE values of 93 and 88% for the EVAL and TEST soil data sets, respectively.     

基于土壤传递函数的土壤持水特性间接估计及其空间变异性研究

A total of 107 soil samples were taken from the city of Qingdao,Shandong Province,China.Soil water retention data at 2.5,6,10,33,100,300,and 1 500 kPa matric potentials were measured using a pressure membrane apparatus.Multiple linear regression (MLR) was used to develop pedotransfer functions (PTFs) for single point estimation and van Genuchten parameter estimation based on readily measurable soil properties,i.e.,MLR-based point (MLRP) PTF and MLR-based parametric (MLRV) PTF.The double cross-validation method was used to evaluate the accuracy of PTF estimates and the stability of the PTFs developed in this study.The performance of MLRP and MLRV PTFs in estimating water contents at matric potentials of 10,33,and 1 500 kPa was compared with that of two existing PTFs,the Rawls PTF and the Vereecken PTF.In addition,geostatistical analyses were conducted to assess the capabilities of these PTFs in describing the spatial variability of soil water retention characteristics.Results showed that among all PTFs only the Vereecken PTF failed to accurately estimate water retention characteristics.Although the MLRP PTF can be used to predict retention characteristics through traditional statistical analyses,it failed to describe the spatial variability of soil water retention characteristics.Although the MLRV and Rawls PTFs failed to describe the spatial variability of water contents at a matric potential of 10 kPa,they can be used to quantify the spatial variability of water contents at matric potentials of 33 and 1 500 kPa.     

基于单一和集合土壤转换函数模型对土壤含水量的模拟性能分析

土壤转换函数(Soil pedotransfer function,PTF)是一种高效获取土壤水力参数的方法。由于土壤具有很强的空间异质性,确定最优PTF模型成为模拟土壤含水量的关键。为此,以海河流域3个实验场地(密云站、大兴站、馆陶站)为研究区,采用7种常用的单一PTF模型预测土壤水力参数作为HYDRUS-1D的模型参数,求解Richards方程获得土壤含水量,并与实测土壤含水量进行比较,评价了常用单一PTF模型预测的土壤水力参数对土壤含水量的模拟性能。此外,采用3种方法构建集合PTF模型,评价了集合PTF模型对土壤含水量的模拟性能。结果表明：基于van Genuchten方程构建的单一PTF作为模型参数模拟土壤含水量的均方根误差最小;而其中Rosetta3模型表现更优。在集合PTF模型中,基于遗传算法加权法构建的模型表现最好。集合PTF模型预测土壤水力参数可以较好的捕捉多个单一PTF预测土壤水力参数的整体趋势,弥补单一PTF在某些情况下模拟误差较大的不足。     

Use of class pedotransfer functions based on texture and bulk density of clods to generate water retention curves

Abstract. Water retention properties of 219 horizons were measured in Cambisols, Luvisols and Fluvisols, mainly from the Paris basin. We derived class pedotransfer functions (class PTFs) based on texture alone and in a second stage class PTFs based on classes combining texture and clod bulk density. The performance of these two types of PTFs were discussed at −330 and −15000 hPa water potential on an independent set of 221 horizons. Results showed that PTFs based on sets grouped by texture and clod bulk density provide estimates with an accuracy that is (i) greater than with class PTFs based on texture alone, and (ii) similar to the estimation accuracy recorded with continuous PTFs. As a consequence, the lack of interest in class PTFs should be reconsidered to bridge the gap between the available basic soil data and hydraulic properties which are generally missing, particularly when pertinent soil characteristics can be derived from the data available in soil databases. The two types of class PTFs providing gravimetric water contents at seven water potentials ranging from −10 to −15 000 hPa were converted to volumetric water content using the soil bulk density. Finally, the parameters of van Genuchten's water retention curve model were computed for every class PTF.     

Soil hydraulic properties of two loess soils in China measured by various field-scale and laboratory methods

Knowledge of hydraulic properties is essential for understanding water movement in soil. However, very few data on these properties are available from the Loess Plateau of China. We determined the hydraulic properties of two silty loam soils on agricultural land at sites in Mizhi and Heyang in the region. Undisturbed soil cores were collected from seven layers to one meter depth to determine saturated hydraulic conductivity, soil water retention curves and unsaturated hydraulic conductivity (by the hot-air method). Additional field methods (internal drainage and Guelph permeameter) were applied at the Heyang site to compare differences between methods. Soil water retention curves were flatter at Mizhi than at Heyang. Water contents at saturation and wilting point (1500 kPa) were higher at Heyang than at Mizhi. However, unsaturated hydraulic conductivity was lower at Heyang than at Mizhi, with maximum differences of more than six orders of magnitude. Nevertheless, the two soils had similar saturated hydraulic conductivities of about 60 cm day^− 1. Comparison between the methods showed that soil water retention curves obtained in the laboratory generally agreed well with the field data. Field-saturated conductivities had similar values to those obtained using the soil core method. Unsaturated hydraulic conductivities predicted by the Brooks–Corey model were closer to field data than corresponding values predicted by the van Genuchten model.     

基于土壤质地数据估算土壤保水性能Van Genuchten参数

The van Genuchten (vG) function is often used to describe the soil water retention curve (SWRC) of unsaturated soils and fractured rock. The objective of this study was to develop a method to determine the vG model parameter m from the fractal dimension. We compared two approaches previously proposed by van Genuchten and Lenhard et al. for estimating m from the pore size distribution index of the Brooks and Corey (BC) model. In both approaches we used a relationship between the pore size distribution index of the BC model and the fractal dimension of the SWRC. A dataset containing 75 samples from the UNSODA unsaturated soil hydraulic database was used to evaluate the two approaches. The statistical parameters showed that the approach by Lenhard et al. provided better estimates of the parameter m. Another dataset containing 72 samples from the literature was used to validate Lenhard’s approach in which the SWRC fractal dimension was estimated from the clay content. The estimated SWRC of the second dataset was compared with those obtained with the Rosetta model using sand, silt, and clay contents. Root mean square error values of the proposed fractal approach and Rosetta were 0.081 and 0.136, respectively, indicating that the proposed fractal approach performed better than the Rosetta model.     

不同盆栽基质水分特征曲线的对比分析与模拟

现有关于盆栽控水模拟土壤干旱条件的试验中多采用含水率作为水分胁迫阈值,然而由于基质配比不同导致含水率相同的基质的水分状况也不尽相同,这导致各研究间结果难以对比和参考。为快速获取盆栽基质水分特征曲线,建立基质水分特征曲线预测模型。该研究以盆栽控水试验常用的泥炭土、蛭石和珍珠岩为基质材料,测定了不同配比基质的水分特征曲线,通过不同方法（多元回归模型、人工神经网络）建立了其预测模型。结果表明,人工神经网络模型对基质水分特征曲线的预测精度高于多元回归;相较于人工神经网络,多元回归模型的稳定性更高。综合考虑模型的精度和稳定性,多元回归模型是预测作物盆栽基质水分特征曲线的最佳模型。该模型为基质水分特征曲线快速获取以及相关作物干旱胁迫研究间的对比提供了方法和依据。     

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.     

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.     

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.     

非均匀土壤区域SVAT模型中土壤水动力学参数的整合研究

荷兰Cabauw地区一个 10km×10km区域内的四种主要土壤的水动力学参数用一种实验室直接测定法 (Wind氏蒸发法 )和两种间接方法 (“分段土壤推导函数”、“连续土壤推导函数”)确定 ,而该区域水动力学特性参数的整合则采用两组方案 (聚合土壤参数法和有效土壤参数法 )进行。一个SVAT模型的模拟输出结果———感热通量、潜热通量与实测数据的比较分析表明 :(1)对于用“分段土壤推导函数”确定的土壤水动力学参数的区域整合 ,以“逆模拟法”(有效土壤参数法 )较为可行 ,其模拟感热、潜热的精确性接近参比方案 (“模拟 平均法”) ;(2 )对于实验室直接测定的参数 ,则以几何平均vanGenuchten Mualem经验公式参数的方案 (聚合土壤参数法 )为佳 ;(3)对于“连续土壤推导函数”推导的水动力学参数 ,几何平均土壤组分方案 (聚合土壤参数法 )和“逆模拟法”方案 (有效土壤参数法 )二者均可得到优于参比方案 (“模拟 平均法”)的模拟结果 ,其中以前者最佳 ;(4 )所有区域化参数整合方案中 ,以水平几何平均区域内实验室直接测定的参数的方案最优 ;同时 ,“连续土壤推导函数”法的土壤组分几何平均方案的模型输出精确性接近该最优方案     

Alternative methods in the development of pedotransfer functions for soil hydraulic characteristics

Soil hydraulic properties are needed in the modeling of water flow and solute movement in the vadose zone. Pedotransfer functions (PTFs) have received the attention of many researchers for indirect determination of hydraulic properties from basic soil properties as an alternative to direct measurement. The objective of this study was to compare the performance of cascade forward network (CFN), multiple-linear regression (MLR), and seemingly unrelated regression (SUR) methods using prediction capabilities of point and parametric PTFs developed by these methods. The point PTFs estimated field capacity (FC), permanent wilting point (PWP), available water capacity (AWC), and saturated hydraulic conductivity (Ks) and the parametric PTFs estimated the van Genuchten retention parameters. A total of 180 soil samples was extracted from the UNSODA database and divided into two groups as 135 for the development and 45 for the validation of the PTFs. The model performances were evaluated with three statistical tools: the maximum error (ME), the model efficiency (EF), and the D index (D) using the observed and predicted values of a given parameter. Despite the fact that the differences among the three methods in prediction accuracies of the point and parametric PTFs were not statistically significant (p > 0.05) except θ_r and α (p < 0.05) based on the ANOVA test, overall MLR and SUR were somewhat better than CFN in prediction of the point PTFs, whereas CFN performed better than the other two methods in prediction of the parametric PTFs. The F.F values of FC and θ_r for CFN, MLR, and SUR methods were 0.705. 0.805, 0.795 and 0.356, −0.290, −0.290, respectively, which refer to the best and worst predictions. Properties (Ks, θ_r, α) having some difficulty in prediction were better predicted by CFN and SUR methods, where these methods predict all hydraulic properties from basic soil properties simultaneously rather than individually as in MLR. This suggests that multivariate analysis using such functional relationships between hydraulic properties and basic soil properties can be utilized in developing more accurate point and parametric PTFs with less time and effort.     

非均匀土壤区域SVAT模型中土壤水动力学参数的整合研究

荷兰Cabauw地区一个 10km10km区域内的四种主要土壤的水动力学参数用一种实验室直接测定法 (Wind氏蒸发法 )和两种间接方法 (分段土壤推导函数、连续土壤推导函数)确定 ,而该区域水动力学特性参数的整合则采用两组方案 (聚合土壤参数法和有效土壤参数法 )进行。一个SVAT模型的模拟输出结果感热通量、潜热通量与实测数据的比较分析表明 :(1)对于用分段土壤推导函数确定的土壤水动力学参数的区域整合 ,以逆模拟法(有效土壤参数法 )较为可行 ,其模拟感热、潜热的精确性接近参比方案 (模拟 平均法) ;(2 )对于实验室直接测定的参数 ,则以几何平均vanGenuchten Mualem经验公式参数的方案 (聚合土壤参数法 )为佳 ;(3)对于连续土壤推导函数推导的水动力学参数 ,几何平均土壤组分方案 (聚合土壤参数法 )和逆模拟法方案 (有效土壤参数法 )二者均可得到优于参比方案 (模拟 平均法)的模拟结果 ,其中以前者最佳 ;(4 )所有区域化参数整合方案中 ,以水平几何平均区域内实验室直接测定的参数的方案最优 ;同时 ,连续土壤推导函数法的土壤组分几何平均方案的模型输出精确性接近该最优方案     

Effects of agricultural practices on hydraulic properties and water movement in soils in Brittany (France)

The intensive agricultural use of soils in the Brittany region (western France) has increased the need for a better understanding of soil water dynamics. The aim of the present study is to compare quantitatively the differences produced by two agricultural practices on soil hydraulic properties (water retention curve and hydraulic conductivity) as well as the infiltration and drainage fluxes in the soils. This study was carried out on two experimental plots managed in the same way for 22 years. The two practices were continuous maize fertilized with mineral fertilizer, denoted as MX, and pasture within a ray-grass/maize rotation (3/1 year) with organic fertilization (pig slurry), denoted as PR. The study consisted of measuring soil physical properties in the laboratory and in the field, and estimating water infiltration in the soil of the two plots by recording water pressure heads after simulation of 2-h artificial rainfall with an intensity of 17 mm/h. We applied the van Genuchten model to describe the water retention and hydraulic conductivity curves (θ(h) and K(h)) for each soil horizon of the two plots. Hydrus-2D and ID softwares were used to construct a numerical model of water movement in the two soils. This model was used to quantify the infiltration rate, deep drainage and actual evaporation fluxes during the artificial rainfall experiment.The vertical influence of agricultural practices in both plots appears to be limited to the uppermost 35 cm. Deeper in the B horizon, there are only very slight differences in the hydraulic properties between the two plots. In the top soil horizons (H1–H5 and H6), the two soil properties mostly affected by practices are the hydraulic conductivity and the α parameter of the van Genuchten model. At the lowest pressure head studied here (−1.5 kPa), hydraulic conductivity in a given horizon differs by more than one order of magnitude between the two plots. The model reproduces quite satisfactorily the observed pressure heads in plot PR at all depths, in the rainy period as well as in the water redistribution period (efficiency >0.77). Results are less good for the MX plot, with efficiency ranging from 0.49 to 0.84 depending on the horizon. The different sources of simulation errors are identified and discussed. For the MX plot, the soil water movement model succeeds in reproducing the infiltration excess runoff observed in the field, allowing us to calculate that it accounts for 9% of the applied rainfall. No surface runoff or ponding appears in the PR plot during the artificial rainfall experiment. In the PR plot, the simulated deep drainage flux increases more rapidly than in the MX plot. The lower hydraulic conductivity in the top soil horizon of the MX plot compared with the PR plot appears to reduce the infiltration rate as well as the deep drainage flux. It also decreases the upward flow of water to the soil surface when the water content in the top soil layer is depleted by evaporation flux. The model simulation could be improved by a more precise representation of the soil structure, particularly the location, size and frequency of clods as well as the variability of hydraulic properties. However, we need to strike a balance between improving the quality of the simulation even further and the practical constraints and efforts involved in measuring the soil hydraulic properties.     

Soil structure and pedotransfer functions

Accurate estimates of soil hydraulic properties from other soil characteristics using pedotransfer functions (PTFs) are in demand in many applications, and soil structural characteristics are natural candidates for improving PTFs. Soil survey provides mostly categorical data about soil structure. Many available characteristics such as bulk density, aggregate distribution, and penetration resistance reflect not only structural but also other soil properties. Our objective here is to provoke a discussion of the value of structural information in modelling water transport in soils. Two case studies are presented. Data from the US National Pedon Characterization database are used to estimate soil water retention from categorical field‐determined structural and textural classes. Regression‐tree estimates have the same accuracy as those from textural class as determined in the laboratory. Grade of structure appears to be a strong predictor of water retention at ?33 kPa and ?1500 kPa. Data from the UNSODA database are used to compare field and laboratory soil water retention. The field‐measured retention is significantly less than that measured in the laboratory for soils with a sand content of less than 50%. This could be explained by Rieu and Sposito's theory of scaling in soil structure. Our results suggest a close relationship between structure observed at the soil horizon scale and structure at finer scales affecting water retention of soil clods. Finally we indicate research needs, including (i) quantitative characterization of the field soil structure, (ii) an across‐scale modelling of soil structure to use fine‐scale data for coarse‐scale PTFs, (iii) the need to understand the effects of soil structure on the performance of various methods available to measure soil hydraulic properties, and (iv) further studies of ways to use soil–landscape relationships to estimate variations of soil hydraulic properties across large areas of land.     

Performance of pedotransfer functions in predicting soil water characteristics of soils in Norway

Abstract

Pedotransfer functions (PTFs), predicting the soil water retention curve (SWRC) from basic soil physical properties, need to be validated on arable soils in Norway. In this study we compared the performance of PTFs developed by Riley (1996), Rawls and Brakensiek (1989), Vereecken et al. (1989), Wösten et al. (1999) and Schaap et al. (2001). We compared SWRCs calculated using textural composition, organic matter content (SOM) and bulk density as input to these PTFs to pairs of measured water content and matric potential. The measured SWRCs and PTF input data were from 540 soil horizons on agricultural land in Norway. We used various statistical indicators to evaluate the PTFs, including an integrated index by Donatelli et al. (2004). The Riley PTFs showed good overall performance. The soil specific version of Riley is preferred over the layer specific, as the latter may introduce a negative change in water content with increasing matric potential (h). Among the parameter PTFs, Wösten's continuous PTF showed the overall best performance, closely followed by Rawls&B and Vereecken. The ANN-based continuous PTF of Schaap showed poorer performance than its regression based counterparts. Systematic errors related to both particle size and SOM caused the class PTFs to perform poorly; these PTFs do not use SOM as input, and are therefore inappropriate for soils in Norway, being highly variable in SOM. The PTF performance showed little difference between soil groups. Water contents in the dry range of the SWRC were generally better predicted than water contents in the wet range. Pedotransfer functions that included both SOM and measured bulk density as input, i.e. Wösten, Vereecken and Rawls&B, performed best in the wet range.     

使用积分法估算原状土van Genuchten模型参数

The van Genuchten model is the most widely used soil water retention curve (SWRC) model. Two undisturbed soils (clay and loam) were used to evaluate the accuracy of the integral method to estimate van Genuchten model parameters and to determine SWRCs of undisturbed soils. SWRCs calculated by the integral method were compared with those measured by a high speed centrifuge technique. The accuracy of the calculated results was evaluated graphically, as well as by root mean square error (RMSE), normalized root mean square error (NRMSE) and Willmott’s index of agreement (l). The results obtained from the integral method were quite similar to those by the centrifuge technique. The RMSEs (4.61 × 10-5 for Eum-Orthic Anthrosol and 2.74 × 10-4 for Los-Orthic Entisol) and NRMSEs (1.56 × 10-4 for Eum-Orthic Anthrosol and 1.45 × 10-3 for Los-Orthic Entisol) were relatively small. The l values were 0.973 and 0.943 for Eum-Orthic Anthrosol and Los-Orthic Entisol, respectively, indicating a good agreement between the integral method values and the centrifuge values. Therefore, the integral method could be used to estimate SWRCs of undisturbed clay and loam soils.