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.     

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 the pool size of slowly mineralizable organic N in sandy arable soils

The major aim of this study was to evaluate how the pool size of slowly mineralizable, ‘old’ soil organic N can be derived from more easily accessible soil and site information via pedotransfer functions (PTF). Besides modeling, this pool size might be of great importance for the identification of soils with high mineralization potential in drinking‐water catchments. From long‐term laboratory incubations (ca. 200 days) at 35 °C, the pool sizes of easily mineralizable organic N (N_fast), mainly in fresh residues, and slowly mineralizable, ‘old’ soil organic N (N_slow) as well as their first‐order rate coefficients were obtained. 90 sandy arable soils from NW Germany served to derive PTFs for N_slow that were evaluated using another 20 soils from the same region. Information on former land‐use and soil type was obtained from topographical, historical, and soil maps (partly from 1780). Pool size N_slow very strongly depends on soil type and former land‐use. Mean pool sizes of N_slow were much lower in old arable lowland (105 mg N kg^–1) than upland soils (175 mg N kg^–1) possibly due to lower clay contents. Within lowlands, mean pool sizes in former grassland soils (245 mg N kg^–1) were 2 to 3 times larger than in old arable soils due to accumulation of mineralizable N. In contrast, mean pool sizes of N_slow were lowest in recently cleared, former heath‐ and woodland (31 mg N kg^–1) as a result of the input of hardly decomposable organic matter. Neither N nor C in the light fraction (density < 1.8 g cm^–3) was adequate to derive pool size N_slow in the studied soils (r² < 0.03). Instead, N_slow can be accurately (r² = 0.55 – 0.83) derived from one or two basic soil characteristics (e.g. organic C, total N, C : N, mineral fraction < 20 μm), provided that sites were grouped by former land‐use. Field mineralization from N_slow during winter (independent data set) can be predicted as well on the basis of N_slow‐values calculated from PTFs that were derived after grouping the soils by former land‐use (r² = 0.51***). In contrast, using the PTF without soil grouping strongly reduced the reliability (r² = 0.16).     

多因素作用下浑水入渗对土壤导水特性的影响

浑水土壤入渗具有复杂的上边界变化过程,其上边界导水能力的变化规律是研究浑水土壤入渗特性的重要基础。为研究浑水入渗形成致密层过程中导水率的变化情况,该研究进行了17组（9组正交试验处理,8组用于模型验证）浑水饱和土柱入渗试验,通过对试验结果进行多元回归构建多因素（浑水含沙率、黏粒含量及入渗时间）影响下砂土导水率动态模型;并结合浑水饱和土柱入渗特性进行合理假设,分别建立浑水砂壤土和粉壤土饱和土柱导水率动态模型并进行验证。结果表明：浑水含沙率、黏粒含量及入渗时间对砂土导水率影响极显著（P<0.01）,入渗时间为砂土影响导水率变化的主要因素,其次为含沙率和黏粒含量;建立的砂土导水率动态模型决定系数为0.853,均方根误差为0.004 cm/min,表明该模型可客观反映各因素与导水率之间的关系;模型验证试验结果中均方根误差小于0.01 cm/min,相对误差绝对值均值小于7%,说明该导水率动态模型可靠性较高;砂壤土和粉壤土导水率动态模型决定系数分别为0.912和0.930,均方根误差分别为2×10^-3和5×10^-5 cm/min;模型验证中均方根误差小于0.01 cm/min,相对误差绝对值小于17%,表明模型计算值与实测值的一致性较好。研究结果有助于揭示浑水土壤入渗规律,为进一步探明浑水入渗过程及致密层阻渗机理提供理论依据。     

基于ANN的复垦土壤水分特征曲线的预测研究

为能较容易且更准确地获取复垦土壤水分特征曲线,将易测定的土壤特性如土壤质地、容重和饱和含水量作为输入变量,采用基于bagging算法的神经网络法建立了用于预测土壤水分特征曲线的土壤转换函数法(PTFs)模型,并对徐州矿区复垦土壤的水分特征曲线进行了预测,同时与普通BP算法预测精度进行了比较.研究结果表明所建立的PTFs参数模型具有较高的估计精度,bagging算法均方根预测误差比普通BP算法减少了7.5%～27.0%,说明该模型的建立与求解为复垦土壤水分特征曲线的预测研究提供了一条新途径.     

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.     

Comparison of seven water retention functions used for modelling soil hydraulic conductivity due to film flow

The unsaturated soil hydraulic conductivity accounting for film flow is important for understanding soil hydrological and biological processes, especially in arid and semi‐arid regions. Recently, a theoretically based hydraulic conductivity model was developed to describe the hydraulic conductivity as a function of water content. We have used this model to compare seven soil water retention functions commonly used for predicting soil hydraulic conductivity due to film flow. A total of 30 soils, varying in basic properties, were selected from the Unsaturated Soil Hydraulic Database to evaluate the seven functions. The Webb method was applied to identify the critical soil matric potential (h _c) below which thin film flow controls water movement. Soil hydraulic conductivity measurements at matric potential below h _c were then used for curve fitting according to the seven functions. Slight differences were observed among the functions in predicting soil hydraulic conductivity due to film flow. Six of the seven functions in combination with the hydraulic conductivity model described the hydraulic conductivity due to film flow well, according to the terms of the coefficient of efficiency. The relatively poor performance of the one exception was due to the fact that the linear shape of the function made it less flexible at low matric potentials. In addition, the effect of textural class on its performance was substantial, showing a poorer fit for the sand soil compared with the loam and clay soils. These findings have important applications related to soil and water resources conservation especially in arid and semi‐arid regions.     

Particle arrangement and internal porosity of coarse fragments affect water retention in stony soils

Information about water retention in stony soils lags behind due to methodological difficulties. We applied a new strategy to measure the water retention in soils with coarse fragments (CFs) and to get insights into the effect of CFs porosity on water retention. Water retention at zero, 10, and 150 m suction, bulk density, and the mass fraction of six particle size classes were measured in undisturbed blocks from soils with variable CFs contents, originating from three parent materials. The results showed that some soils contain porous CFs (2–250 mm) with a water holding capacity as high as the fine fraction (<2 mm). The water held in the suction range of 1–150 m in a soil with porous CFs was twice as high as in soils with non-porous CFs. Multilinear regressions revealed that both the water retention capacity at 1 m suction and in the range 1–150 m were more dependent on bulk density than on the fraction of CFs and fine particles. In the soil with porous CFs, there was no correlation between their fraction and soil water retention. These results show that the bulk water retention capacity of soils with CFs is underestimated when not considering the internal porosity of the CFs. A better understanding of the effect of the porosity of CFs on bulk soil porosity and water retention is important to propose suitable pedotransfer functions and refine physically-based hydraulic functions for stony soils.     

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.     

冻土水力传导系数的理论模型研究

冻土水力传导系数多采用经验公式来描述,其结果缺少理论依据。该文从冰水界面水膜热力学理论出发,对克拉贝隆方程进行修正,得到孔隙水冻结温度与孔隙半径的关系式。基于此,结合毛细管束理论和土壤冻结特征曲线(SFCC),给出预测冻土水力传导系数的理论模型,并与前人的实测值和经验公式进行对比分析。结果表明:孔隙冻结温度随着孔隙半径的减小而下降,且温度下降速率也随之逐渐增大;考虑未冻孔隙水和未冻水膜作为水分的迁移通道,该模型计算值与试验结果具有很好吻合度,且优于经验公式,验证该模型的合理性;最后指出SFCC的拟合效果会影响该模型的预测结果。     

Transferability of continuous‐ and class‐pedotransfer functions to predict water retention properties of semiarid Syrian soils

Hydraulic properties of soils, particularly water retention, are key for appropriate management of semiarid soils. Very few pedotransfer functions (PTF s) have been developed to predict these properties for soils of Mediterranean regions, where data are particularly scarce. We investigated the transferability of PTF s to semiarid soils. The quality of the prediction was compared to that for soils originating from temperate regions for which most PTF s were developed. We used two soil data sets: one from the Paris basin (French data set, n  = 30) and a Syrian data set (n  = 30). Soil samples were collected in winter when the water content was near field capacity. Composition and water content of the samples were determined at seven water potentials. Continuous‐ and class‐PTF s developed using different predictors were tested using the two data sets and their performance compared to those developed using artificial neural networks (ANN ). The best performance and transferability of the PTF s for both data sets used soil water content at field capacity as predictor after stratification by texture. The quality of prediction was similar to that for ANN ‐PTF s. Continuous‐ and class‐PTF s may be transferable to other countries with performances that vary according to their ability to account for variation in soil composition and structure. Taking into account predictors of composition (particle size distribution, texture, organic carbon content) and structure (bulk density, porosity, field capacity) did not lead to a better performance or the best transferability potential.     

Pedotransfer function to predict density of forest soils in Switzerland

Soil density is an important soil property, but respective measurements are usually scarce. With data from 559 mineral soil horizons (134 sites) we developed a linear regression pedotransfer function (PTF) for the density of forest soils (sieved to ≤ 2 mm). The field estimate of density was the most important covariate. RMSE of 0.205 Mg m^?3 and R² of 0.67, calculated on independent data (131 horizons), were better than the statistics obtained by published, recalibrated PTF (RMSE 0.271–0.324 Mg m^?3; R² 0.28–0.42).     

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.     

Effect of zeolite and saline water application on saturated hydraulic conductivity and infiltration in different soil textures

The effects of zeolite application (0, 4, 8 and16 g kg^?1) and saline water (0.5, 1.5, 3.0 and 5.0 dS m^?1) on saturated hydraulic conductivity (K _s) and sorptivity (S) in different soils were evaluated under laboratory conditions. Results showed that K _s was increased at salinity levels of 0.5‐1.5 dS m^?1 in clay loam and loam with 8 and 4 g zeolite kg^?1 soil, respectively, and at salinity levels of 3.0–5.0 dS m^?1 with 16 g zeolite kg^?1 soil. K _s was decreased by using low and high salinity levels in sandy loam with application of 8 and 16 g zeolite kg^?1, respectively. In clay loam, salinity levels of 0.5–3.0 dS m^?1 with application of 16 g kg^?1 zeolite and 5.0 dS m^?1 with application of 8 g zeolite kg^?1 soil resulted in the lowest values of S. In loam, all salinity levels with application of 16 g zeolite kg^?1 soil increased S compared with other zeolite application rates. In sandy loam, only a salinity level of 0.5 dS m^?1 with application of 4 g zeolite kg^?1 soil increased S. Other zeolite applications decreased S, whereas increasing the zeolite application to 16 g kg^?1 soil resulted in the lowest value of S.     

华北地区微咸水应用对土壤水力传导性能的影响

由于淡水资源短缺,中国华北地区微咸地下水灌溉面积逐年增多。该文通过室内土柱淋洗试验,研究了灌溉水盐分浓度和钠吸附比(SAR)对华北地区非碱土(可交换钠百分比ESP0)和碱土(ESP30)饱和水力传导性能的影响。灌溉水盐浓度分别为2.5、10和25mmolc/L,SAR分别为0、10和30(mmolc/L)0.5。去离子(盐浓度0)作为对照处理。试验包括2个土壤碱度、9个灌溉水质组合和1个去离子水处理,共20个试验处理。试验结果显示,非碱土和碱土对微咸水应用的反应机理以及反应程度不同。当黏粒弥散程度较弱时,上部土壤的饱和水力传导度显著大于下层土壤;反之,则各层土壤的水力传导度均较小。在试验水质条件下,非碱土的平均饱和水力传导度的变化范围为0.75～13.25cm/h,而碱土的变化范围为0.06～6.50cm/h。碱土的稳定饱和水力传导度随着灌溉水盐浓度的增加或/和SAR的减小而增大,但在非碱土中稳定饱和水力传导度的变化规律与此基本相反。试验结果对合理应用微咸水灌溉非碱土和碱土具有指导意义。     

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泥炭土-蛭石复配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,预测精度R2≥0.950,平均误差接近0。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。     

Prediction of hydraulic conductivity and sorptivity in soils at steady-state infiltration

The purpose of this study was (1) to find a matching factor (u) between infiltration rate and hydraulic conductivity during steady-state infiltration, and (2) to propose equations based on infiltration and soil moisture-retention functions for prediction of the hydraulic conductivity K(θ) within the rapidly (non-capillary) drainable pores (RDP) and capillary-matrix pores of soils. The K(θ) of capillary pores was divided into K(θ)_SDP, K(θ)_WHP and K(θ)_FCP within slowly drainable pores (SDP), water-holding pores (WHP) and fine capillary pores (FCP), respectively. Five soil profiles of calcareous sandy loam, alluvial saline and non-saline clay, located at the Nile Delta, were used to apply the proposed equations. The highest and the lowest values of K(θ)_RDP were observed in calcareous and saline clay soil profiles, respectively. Values of K(θ)_RDP remained higher than those for capillary pores in the studied soils. The predicted values of K(θ) in capillary and non-capillary pores classes were in the expected range for unsaturated hydraulic conductivity. Water sorptivity (S) was determined at initial unsaturated soil water conditions and calculated at steady-state infiltration (S _w) using a derived equation. There was a decrease in S with an increase in soil water content; i.e. at steady-state infiltration, S decreased by 35–40% in calcareous soils and by 45–60% in alluvial clay soils. The parameter values of u and S _w tended to be uniform in calcareous soils, but nonuniform in saline and non-saline clay soils.