The evaporation method: Extending the measurement range of soil hydraulic properties using the air‐entry pressure of the ceramic cup

Knowledge of hydraulic functions is required for various hydrological and plant‐physiological studies. The evaporation method is frequently used for the simultaneous determination of hydraulic functions of unsaturated soil samples, i.e., the water‐retention curve and hydraulic‐conductivity function. All methodic variants of the evaporation method suffer from the limitation that the hydraulic functions can only be determined to a mean tension of ≈ 60 kPa. This is caused by the limited measurement range of the tensiometers of typically 80 kPa on the dry end. We present a new, cost‐ and time‐saving approach which overcomes this restriction. Using the air‐entry pressure of the tensiometer's porous ceramic cup as additional defined tension value allows the quantification of hydraulic functions up to close to the wilting point. The procedure is described, uncertainties are discussed, and measured as well as simulated test results are presented for soil samples of various origins, different textures (sand, loam, silt, clay, and peat) and variable dry bulk density. The experimental setup followed the system HYPROP which is a commercial device with vertically aligned tensiometers that is optimized to perform evaporation measurements. During the experiment leaked water from the tensiometer interior wets the surrounding soil of the tensiometer cup and can lead to a tension retardation as shown by simulation results. This effect is negligible when the tensiometers are embedded vertically. For coarsely textured soils and horizontal tensiometer alignment, however, the retardation must be considered for data evaluation.     

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.     

Applicability of site-specific pedotransfer functions and rosetta model for the estimation of dynamic soil hydraulic properties under different vegetation covers

Background, Aims, and Scope  During the last decades, different methods have been developed to determine soil hydraulic properties in the field and laboratory. These methodologies are frequently time-consuming and/or expensive. An indirect method, named Pedotransfer Functions (PTFs), was developed to predict soil hydraulic properties using other easily measurable soil (physical and chemical) parameters. This work evaluates the use of the PTFs included in the Rosetta model (Schaap et al. 2001) and compares them with PTFs obtained specifically for soils under two different vegetation covers. Methods  Rosetta software includes two basic types of pedotransfer functions (Class PTF and Continuous PTF), allowing the estimation of van Genuchten water retention parameters using limited (textural classes only) or more extensive (texture, bulk density and one or two water retention measurements) input data. We obtained water retention curves from undisturbed samples using the ‘sand box’ method for potentials between saturation and 20 kPa, and the pressure membrane method for potentials between 100 and 1500 kPa. Physical properties of sampled soils were used as input variables for the Rosetta model and to determine site-specific PTFs. Results  The Rosetta model accurately predicts water content at field capacity, but clearly underestimates it at saturation. Poor agreement between observed and estimated values in terms of root mean square error were obtained for the Rosetta model in comparison with specific PTFs. Discrepancies between both methods are comparable to results obtained by other authors. Conclusions  Site-specific PTFs predicted the van Genuchten parameters better than Rosetta model. Pedotransfers functions have been a useful tool to solve the water retention capacity for soils located in the southern Pyrenees, where the fine particle size and organic matter content are higher. The Rosetta model showed good predictions for the curve parameters, even though the uncertainty of the data predicted was higher than for the site-specific PTFs. Recommendations and Perspectives  The Rosetta model accurately predicts the retention curve parameters when the use is related with wide soil types; nevertheless, if we want to obtain good predictors using a homogenous soil database, specific PTFs are required. ESS-Submission Editor: Prof. Zhihong Xu, PhD (zhihong.xu@griffith.edu.au)     

关中平原农田土壤水力参数空间分异与模拟

土壤水力参数是土壤水分和污染物迁移等陆面过程数值模拟的重要基础参数。为探明关中平原农田土壤水力参数空间分异特征,建立空间分布预测模型,在关中平原网格布设124个样点,采集根层0-20 cm原状和扰动土壤样品,利用van Genuchten模型拟合获取土壤水分特征曲线,获得残余含水量(θr)、饱和含水量(θs)以及系数α和n等土壤水力参数。采用经典统计学、地统计学和结构方程方法分析了θr、θs、α和n的空间变异特征及影响因子,建立了水力参数传递函数预测模型。结果表明:θr和α为强变异,θs为中等变异,n为弱变异。θr、θs、α和n半方差函数最佳拟合模型分别为球状模型、指数模型、指数模型和球状模型。θs和n具有强烈的空间依赖性,变程分别为32.7,54.3 km;θr和α具有中等程度空间依赖性,变程均为52.8 km。土壤质地、容重、pH、有机质和海拔是影响土壤水力参数空间分布的主要因子。基于土壤理化性质和海拔建立的水力参数传递函数模型具有较好的模拟效果,可用于关中地区大尺度农田生态系统土壤水力参数的模拟预测。     

Applications of S‐theory in the study of soil physical degradation and its consequences

The S‐theory for soil physical quality is introduced. It is shown how values of S can be determined from the water retention characteristic curve. It is also explained how, when experimental data are not available, pedotransfer functions can be used to obtain estimates of S. Although S was first introduced as an index of soil physical quality, it is being increasingly found that it is a useful numerical quantity that can be used in equations for prediction of a range of soil physical properties. Its use is illustrated with examples for hydraulic conductivity, friability, tillage, compaction, penetrometer resistance, plant‐available water, root growth and readily dispersible clay. The main merit of S derives from the fact that given values of S have the same meaning and consequences in different soils. It is described how S can be used to identify areas of land where physical degradation or amelioration are taking place, and to evaluate management practices that will give sustainable land use. Copyright © 2007 John Wiley & Sons, Ltd.     

Grazing‐induced alterations of soil hydraulic properties and functions in Inner Mongolia,PR China

Increasing grazing intensities of sheep and goats can lead to an increasing degradation of grasslands. We investigated four plots of different grazing intensities (heavily grazed, winter‐grazed, ungrazed since 1999, and ungrazed since 1979) in Inner Mongolia, PR China, in order to study the effects of trampling‐induced mechanical stresses on soil hydraulic properties. Soil water transport and effective evapotranspiration under “heavily grazed” and “ungrazed since 1979” were modeled using the HYDRUS‐1D model. Model calibration was conducted using data collected from field studies. The field data indicate that grazing decreases soil C content and hydrophobicity. Pore volume is reduced, and water‐retention characteristics are modified, the saturated hydraulic conductivity decreases, and its anisotropy (vertical vs. horizontal conductivity) is influenced. Modeling results revealed higher evapotranspiration on the ungrazed site (ungrazed since 1979) compared to the grazed site (heavily grazed) due to wetter soil conditions, more dense vegetation, litter cover, and decreased runoff and drainage, respectively. Grazing modified the partitioning of evapotranspiration with lower transpiration and higher evaporation at the grazed site owing to reduced root water uptake due to reduced evaporation and a patchy soil cover.     

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.     

Integrating biophysical and socio‐economic aspects of soil conservation on the Loess Plateau,China. Part II. Productivity impact and economic costs of erosion

Using the simulation model described in Part I, this paper examines the impact of erosion on soil productivity, how the impact varies according to initial soil conditions and organic matter management and the economic cost of erosion measured as net present value. The reference crop is winter wheat grown in Chunhua in the southern Loess Plateau. Biomass yield is plotted over 100 years for four erosion scenarios represented by 0, 9, 27 and 47 per cent slopes, three initial soil conditions indicated by 0·5, 1 and 2 per cent organic matter, and two management levels determined by high or low levels of reincorporation of organic residues. Calculations of soil productive half‐life (time to half initial yield) and whole‐life (to equilibrial yield) are presented. The principal findings are that decline in soil productivity is caused by both erosion and insufficient return of organic matter. By increasing organic matter input, erosion damage is offset and soil productive life prolonged, but this is a costly strategy. If yield decline caused by erosion is isolated, erosion control is more important on a high organic matter input system. A maximum soil productive half‐life of 600 years is achieved with no erosion, high initial organic matter and return of organic residues; minimum half‐life of 10 years is with high erosion, low initial organic matter and little return of residues. In between, there are complicated interactions that significantly affect the economic cost of erosion and hence the decisions farmers make in investing in conservation practices. Copyright © 2000 John Wiley & Sons, Ltd.     

Integrating biophysical and socio‐economic aspects of soil conservation on the Loess Plateau,China. Part I. Design and calibration of a model

A principal challenge in erosion control is the integration of the many technical and non‐technical issues that affect the acceptance of soil conservation measures by land users. This first paper in a three‐part series considers the main criteria at farm level: biophysical efficiency; productivity and sustainability; and socio‐economic acceptability. A model is developed to integrate these various components into a decision‐making framework for soil conservation at the farm level. With the particular conditions of the Loess Plateau in China, land degradation comprises a number of key biophysical and socio‐economic variables. The model components therefore include available water storage capacity of the soil as an index of productivity, the organic matter and mineral soil balance to reflect the major changes to the soil when eroded, and cost‐benefit analysis to determine the economic wisdom of devoting household resources to land improvement. The model is calibrated using data from the Nihegou Catchment near Chunhua in the southern part of the Loess Plateau. Through simulation runs, this model enables a better understanding of erosion–productivity–time relationships. Although relatively simple, the model successfully encompasses the processes of greatest significance to agricultural development in this part of China. Copyright © 2000 John Wiley & Sons, Ltd.     

Relation between soil P test values and mobilization of dissolved and particulate P from the plough layer of typical Danish soils from a long‐term field experiment with applied P fertilizers

Accumulation of phosphorus (P) in agricultural topsoils can contribute to leaching of P which may cause eutrophication of surface waters. An understanding of P mobilization processes in the plough layer is needed to improve agricultural management strategies. We compare leaching of total dissolved and particulate P through the plough layer of a typical Danish sandy loam soil subjected to three different P fertilizer regimes in a long‐term field experiment established in 1975. The leaching experiment used intact soil columns (20 cm diameter, 20 cm high) during unsaturated conditions. The three soils had small to moderate labile P contents, expressed by water‐extractable P (3.6–10.7 mg/kg), Olsen P (11–28 mg/kg) and degree of P saturation (DPS) (25–34%). Mobilization of total dissolved P (TDP) increased significantly (P < 0.05) from the intact soil columns with increasing labile P, whereas the increase in particulate P (PP) with increasing labile P content was modest and statistically insignificant. We found concentrations up to 1.5 mg TP/L for the plough layer of this typical Danish sandy loam soil. This highlights that even a moderate labile P content can be a potential source of TDP from the plough layer, and that a lower concentration margin of optimum agronomic P levels should be considered.