Water Retention Parameters Research Articles

Characterizing Scale‐ and Location‐Dependent Correlation of Water Retention Parameters with Soil Physical Properties Using Wavelet Techniques

Understanding the correlation between soil hydraulic parameters and soil physical properties is a prerequisite for the prediction of soil hydraulic properties from soil physical properties. The objective of this study was to examine the scale- and location-dependent correlation between two water retention parameters (alpha and n) in the van Genuchten (1980) function and soil physical properties (sand content, bulk density [Bd], and organic carbon content) using wavelet techniques. Soil samples were collected from a transect from Fuxin, China. Soil water retention curves were measured, and the van Genuchten parameters were obtained through curve fitting. Wavelet coherency analysis was used to elucidate the location- and scale-dependent relationships between these parameters and soil physical properties. Results showed that the wavelet coherence between alpha and sand content was significantly different from red noise at small scales (8-20 m) and from a distance of 30 to 470 m. Their wavelet phase spectrum was predominantly out of phase, indicating negative correlation between these two variables. The strong negative correlation between alpha and Bd existed mainly at medium scales (30-80 m). However, parameter n had a strong positive correlation only with Bd at scales between 20 and 80 m. Neither of the two retention parameters had significant wavelet coherency with organic carbon content. These results suggested that location-dependent scale analyses are necessary to improve the performance for soil water retention characteristic predictions.

Evaluation of Three Models that Describe Soil Water Retention Curves from Saturation to Oven Dryness

Measuring a soil water retention curve (SWRC) with the pressure plate device is generally limited to matric suctions ≤1500 kPa. A few models have been proposed to describe the SWRC from saturation to oven dryness using measurements in the pressure plate matric suction range. The development and validation of these models were mostly based on a limited set of published measurements, and in general, the models have not been validated by independent data from additional soils. In this study, we tested the hypothesis that these models were able to predict the complete SWRC from a limited range of water retention data or by using water retention parameters available from the literature. Soil water retention measurements from saturation to oven dryness were conducted on disturbed, repacked soil samples of various textures using the pressure plate method and the dew point potential technique. When the model parameters were obtained from water retention data in the 0 to 1500 kPa range, the RMSE of water content was approximately 0.01. The RMSE of the Fayer–Simmons model was slightly larger than that of the Webb model and Khlosi model. In addition, the Fayer–Simmons model was sensitive to the data point near the matric suction of 1500 kPa. The Khlosi model produced acceptable results if data sets from 0 to 500 kPa were used for model establishment; larger errors were observed on some soils if the measured data were limited to the 0‐ to 100‐kPa range. All three models could provide reliable results across the entire range of soil water content if measurements in the 0‐ to 1500‐kPa range were available.

Interpretation of water retention field measurements in relation to hysteresis phenomena

Knowledge of the soil water retention function is fundamental to quantifying the flow of water and dissolved contaminants in the vadose zone. This function is usually determined by fitting a particular model (see, for example, van Genuchten (1980) or Brooks‐Corey (1964)) to observed retention points. Independent of the model chosen, interpretation and identification of the water retention parameters are subjective and prone to error, particularly as it is common that the hysteresis history in measured data points is unknown. Experimental data sets from three different field soils are used to clearly demonstrate how the lack of hysteresis knowledge can lead to an inconsistent and incorrect interpretation of the retention data, and therefore to the incorrect estimation of soil hydraulic parameters. By using a hysteresis model to interpret this same data set, it is easily shown that consistent and reliable estimates of soil retention parameters can be obtained. This is true for any physically based hysteresis model. The difficulty in reading water retention measurements may be evident when both drying and wetting data are measured. However, in practice, users are rarely aware of this problem since generally only one set of drying data is measured, making comparison impossible. Such erratic interpretation of water retention field data in the literature will be probably far more common than expected.

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

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. 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. 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. 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. 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.

Estimating soil water retention in a selected range of soil pores using tension disc infiltrometer data

The hydraulic properties of soil, such as soil moisture characteristic and pore size distribution, are very important for the interpretation of the physical characteristics of soil and the management of agricultural practices. The current standard methods employing pressure chamber, however, are often time-consuming and difficult to carry out. In this study, we proposed a simple approach to estimate the soil moisture retention and soil pore size, with sufficient accuracy, using steady-state infiltration data. First, the tension disc infiltration data was interpreted using Wooding's analytical solution to obtain the K( h) function, from which K s (saturated hydraulic conductivity) was optimized. The K s value was then used as an initial input data for the Brooks–Corey model fit to obtain the water retention parameters α BC and b, and the soil water retention characteristics within a selected range of soil pores of 9–450 μm were predicted. The proposed approach was tested for three differently textured soils in laboratory test and one undisturbed field soils. The measurement was replicated for three to five times for each soil. The validity of this method was confirmed by showing good linear regression relationship with data sets obtained by standard pressure chamber method, yielding slopes being close to unity and r 2 values being >0.86. This observation strongly suggests that the proposed method can be applied for the in situ measurement of water retention and pore size in field soils. The results of this work will enable us to easily determine the temporal changes of hydrodynamic nature of soil using tension disc infiltrometer technique.

Pedotransfer functions estimating soil hydraulic properties using different soil parameters

AbstractEstimates of soil hydraulic properties using pedotransfer functions (PTF) are useful in many studies such as hydrochemical modelling and soil mapping. The objective of this study was to calibrate and test parametric PTFs that predict soil water retention and unsaturated hydraulic conductivity parameters. The PTFs are based on neural networks and the Bootstrap method using different sets of predictors and predict the van Genuchten/Mualem parameters. A Danish soil data set (152 horizons) dominated by sandy and sandy loamy soils was used in the development of PTFs to predict the Mualem hydraulic conductivity parameters. A larger data set (1618 horizons) with a broader textural range was used in the development of PTFs to predict the van Genuchten parameters. The PTFs using either three or seven textural classes combined with soil organic mater and bulk density gave the most reliable predictions of the hydraulic properties of the studied soils. We found that introducing measured water content as a predictor generally gave lower errors for water retention predictions and higher errors for conductivity predictions. The best of the developed PTFs for predicting hydraulic conductivity was tested against PTFs from the literature using a subdata set of the data used in the calibration. The test showed that the developed PTFs gave better predictions (lower errors) than the PTFs from the literature. This is not surprising since the developed PTFs are based mainly on hydraulic conductivity data near saturation and sandier soils than the PTFs from the literature. Copyright © 2007 John Wiley & Sons, Ltd.

Modeling the effects of throughfall reduction on soil water content in a Brazilian Oxisol under a moist tropical forest

Access to water reserves in deep soil during drought periods determines whether or not the tropical moist forests of Amazonia will be buffered from the deleterious effects of water deficits. Changing climatic conditions are predicted to increase periods of drought in Amazonian forests and may lead to increased tree mortality, changes in forest composition, or greater susceptibility to fire. A throughfall reduction experiment has been established in the Tapajós National Forest of east‐central Amazonia (Brazil) to test the potential effects of severe water stress during prolonged droughts. Using time domain reflectometry observations of water contents from this experiment, we have developed a dynamic, one‐dimensional, vertical flow model to enhance our understanding of hydrologic processes within these tall‐stature forests on well‐drained, upland, deep Oxisols and to simulate changes in the distribution of soil water. Simulations using 960 days of data accurately captured mild soil water depletion near the surface after the first treatment year and decreasing soil moisture at depth during the second treatment year. The model is sensitive to the water retention and unsaturated flow equation parameters, specifically the van Genuchten parameters θs, θr, and n, but less sensitive to Ks and α. The low root‐mean‐square error between observed and predicted volumetric soil water content suggests that this vertical flow model captures the most important hydrologic processes in the upper landscape position of this study site. The model indicates that present rates of evapotranspiration within the exclusion plot have been sustained at the expense of soil water storage.

Wavelet‐based multifractal analysis of field scale variability in soil water retention

Better understanding of spatial variability of soil hydraulic parameters and their relationships to other soil properties is essential to scale‐up measured hydraulic parameters and to improve the predictive capacity of pedotransfer functions. The objective of this study was to characterize scaling properties and the persistency of water retention parameters and soil physical properties. Soil texture, bulk density, organic carbon content, and the parameters of the van Genuchten water retention function were determined on 128 soil cores from a 384‐m transect with a sandy loam soil, located at Smeaton, SK, Canada. The wavelet transform modulus maxima, or WTMM, technique was used in the multifractal analysis. Results indicate that the fitted water retention parameters had higher small‐scale variability and lower persistency than the measured soil physical properties. Of the three distinct scaling ranges identified, the middle region (8–128 m) had a multifractal‐type scaling. The generalized Hurst exponent indicated that the measured soil properties were more persistent than the fitted soil hydraulic parameters. The relationships observed here imply that soil physical properties are better predictors of water retention values at larger spatial scales than at smaller scales.

SOLUTE DIFFUSION ANALOGY MODEL FOR PREDICTING UNSATURATED HYDRAULIC CONDUCTIVITY IN REPACKED SOIL

Solute diffusion in soil has been shown to cease below a certain threshold water content. In this study, the threshold water content (θ th ) for unsaturated hydraulic conductivity (K) was investigated, with the purpose of establishing a relationship between θ th and the Campbell soil water retention parameter, b. A model for predicting K in sieved, repacked soil from the soil water retention curve using an approach similar to a newly developed model for solute diffusion in soil was developed using K data for a set of 39 sieved, repacked soils representing a wide range of textures. The new solute diffusivity analogy model for predicting K was tested against a set of independent conductivity data from six additional repacked soils and predicted the measured hydraulic conductivity values well. The comparison between the threshold water contents for solute diffusivity and hydraulic conductivity implied that the transport of water can still occur at low water contents where solute (ion) diffusion is restricted or nonexistent. This effect was found most prominent in fine textured soils such as clayey and silty soils.

Drospirenone and its antialdosterone properties

Drospirenone is a unique progestogen derived from 17α-spirolactone, with a pharmacologic profile very similar to that of endogenous progesterone. In contrast with other available progestins, drospirenone is a progestogen with aldosterone receptor antagonism (PARA) through its affinity for the mineralocorticoid receptor. It is thus able to act on the renin–angiotensin–aldosterone system (RAAS), which prevents excessive sodium loss and regulates blood pressure. Estrogen acts on the RAAS to stimulate the synthesis of angiotensinogen, which increases aldosterone levels and promotes sodium and water retention. When these effects are unopposed, for example during estrogen replacement therapy, they can lead to increases in weight and blood pressure. The antialdosterone properties exhibited by drospirenone promote sodium excretion and prevent water retention, conferring potential blood pressure benefits. In addition to its effects on the kidney, aldosterone has effects on the vasculature, myocardium and central nervous system, which may elicit a variety of pathophysiologic processes associated with cardiovascular disease. The antialdosterone properties of drospirenone may therefore confer additional cardiovascular benefits beyond the RAAS system. The combined actions of drospirenone on sodium and water retention and cardiovascular parameters make it a more attractive therapeutic option as a component of hormone replacement therapy than other synthetic progestins.

Modeling manure-borne bromide and fecal coliform transport with runoff and infiltration at a hillslope

Hillslope vegetated buffers are recommended to prevent water pollution from agricultural runoff. However, models to predict the efficacy of different grass buffer designs are lacking. The objective of this work was to develop and test a mechanistic model of coupled surface and subsurface flow and transport of bacteria and a conservative tracer on hillslopes. The testing should indicate what level of complexity and observation density might be needed to capture essential processes in the model. We combined the three-dimensional FEMWATER model of saturated–unsaturated subsurface flow with the Saint-Venant model for runoff. The model was tested with data on rainfall-induced fecal coliforms (FC) and bromide (Br) transport from manure applied at vegetated and bare 6-m long plots. The calibration of water retention parameters was unnecessary, and the same manure release parameters could be used both for simulations of Br and FC. Surface straining rates were similar for Br and bacteria. Simulations of Br and FC concentrations were least successful for the funnels closest to the source. This could be related to the finger-like flow of the manure from the strip along the bare slopes, to the transport of Br and FC with manure colloids that became strained at the grass slope, and to the presence of micro-ponds at the grassed slope. The two-dimensional model abstraction of the actual 3D transport worked well for flux-averaged concentrations. The model developed in this work is suitable to simulate surface and subsurface transport of agricultural contaminants on hillslopes and to evaluate efficiency of grass strip buffers, especially when lateral subsurface flow is important.

LINKING THE GARDNER AND CAMPBELL MODELS FOR WATER RETENTION AND HYDRAULIC CONDUCTIVITY IN NEAR-SATURATED SOIL

Linking the classical Gardner and Campbell models for soil hydraulic properties yields a combined Gardner-Campbell (GC) relationship for predicting unsaturated hydraulic conductivity (K) from soil-water retention. The new GC water retention and hydraulic conductivity relationships are described by simple linearized expressions based on Campbell-b-scaled values of volumetric soil-water content (θ). The GC hydraulic properties models include four parameters, the pore connectivity parameter x (typically between 1 and 2), the Campbell pore size distribution parameter b, the Gardner macroscopic capillary length λ, and the air-entry soil-water matric potential (ψ e ). In the GC model for K(θ), these parameters are merged into a single dimensionless parameter, A. The GC models are applied to seven different undisturbed soils within a soil-water matric potential ψ with a range of 0 to -60 cm H 2 O. Results show that the simple GC ψ(θ) model adequately describes water retention data close to saturation, and that the GC K(θ) model performs well for predicting near-saturated hydraulic conductivity. The GC water retention and hydraulic conductivity parameters were incorporated into Wooding's equation for steady-state infiltration rate to examine the effects of variability in physical characteristics on infiltration. The steady-state infiltration rate was less sensitive to the GC water retention and hydraulic conductivity parameters than the saturated hydraulic conductivity. The GC models, which combine advantages of the Gardner model for linearization of the Richards' equation and the simple Campbell model for soil-water retention, seem useful for describing or predicting near-saturated soil hydraulic properties and for stochastic simulations of field-scale water infiltration.

Regional Salinity Modeling for Conjunctive Water Use Planning in Kheri Command

A one-dimensional water and solute transport UNSATCHEM model is calibrated and validated with a saline water use experiment for wheat and cotton crops. The model is further employed for regional scale salinity modeling with distributed data on soil, irrigation water supply, and its quality from six representative locations from the Kheri command of the Bhakra irrigation system. The wheat-cotton crop rotation, the main rotation in the command, is considered during long-term simulations. The CROPWAT model is used to determine the evapotranspiration requirements of different wheat and cotton crops, while soil water retention parameters are estimated by the RETC model. Atmospheric water and solute boundary conditions are assumed at the top boundary, while free drainage is considered for the lower boundary, as the watertable in the command is sufficiently deep. Simulated salinity and yield values are compared with observed values for regional validation of the model. Critical areas in the command are identified using regional scale modeling results, and applying irrigation water availability and root zone salinity criteria. Guidelines for sustainable conjunctive water use planning are for the Kheri command to get optimum agricultural production despite the use of saline water for irrigation under prevailing scenarios of water availability and its quality.

Estimation of areal specific yield in sands using the central limit theorem

A new approach is demonstrated that permits a reliable estimate of specific yield using published values of the van Genuchten water retention parameters and effective grain sizes and the measured effective grain sizes of soil samples. The specific yield distribution of the soil texture was computed using the published values of the van Genuchten parameters. The specific yield values and the published values of effective grain sizes were then used to construct a specific yield–effective grain size curve, which estimates the ‘point’ specific yield of the soil samples. Applying the central limit theorem, the point specific yields could be transformed into an ‘areal’ specific yield for a study area. Compared with other commonly used approaches, the present procedure requires relatively low computational efforts and readily obtainable data. It is cost effective and does not depend on soil texture classification. More importantly, it incorporates the depth to water table and the variations in grain sizes inherent in natural soil conditions in the estimation. The approach developed was applied for estimating the specific yield of an unconfined sandy aquifer created by land reclamation in the equatorial region. The values obtained were compared with field measurements and the typical ranges of specific yield from the literature. Instead of a single estimate of the specific yield, the method yields a confidence interval with a high confidence level of 95% and with a narrower range than the typical ranges from the literature. In addition, the estimated values are close to the field measurements; hence, the procedure provides a cost-effective alternative to field measurement. The applicability of the present approach could be extended to sites with heterogeneity in the horizontal direction. Nevertheless, the applicability of the present approach for layered soil profiles requires further evaluations. Copyright © 2006 John Wiley & Sons, Ltd.

Two‐dimensional steady unsaturated flow through embedded elliptical layers

New analytic element solutions are presented for unsaturated, two‐dimensional steady flow in vertical planes that include nonoverlapping impermeable elliptical layers and elliptical inhomogeneities. The hydraulic conductivity, which is represented by an exponential function of the pressure head, differs between the inside and outside of an elliptical inhomogeneity; both the saturated hydraulic conductivity and water retention parameters are allowed to differ between the inside and outside. The Richards equation is transformed, through the Kirchhoff transformation and a second standard transformation, into the modified Helmholtz equation. Analytic element solutions are obtained through separation of variables in elliptical coordinates. The resulting equations for the Kirchhoff potential consist of infinite sums of products of exponentials and modified Mathieu functions. In practical applications the series are truncated but still fulfill the differential equation exactly; boundary conditions are met approximately but up to machine accuracy, provided that enough terms are used. The pressure head, saturation, and flow may be computed analytically at any point in the vadose zone. Examples are given of the shadowing effect of an impermeable elliptical layer in a uniform flow field and funnel‐type flow between two elliptical inhomogeneities. The presented solutions may be applied to study transport processes in vadose zones containing many impermeable elliptical layers or elliptical inhomogeneities.

Comparison of Models for Indirect Estimation of Water Retention and Available Water in Surface Soils

Quantitative knowledge of the unsaturated soil hydraulic properties is required in most studies involving water flow and solute transport in the vadose zone. Unfortunately, direct measurement of such properties is often difficult, expensive and time‐consuming. Pedotransfer functions (PTFs) offer a means to estimate soil hydraulic properties based on predictors like texture, bulk density, and other soil variables. In this study, we focus on PTFs for water retention and show that systematic errors in five existing PTFs can be reduced by using water content–based objective functions, instead of parameter value–based objective functions. The alternative analysis was accomplished by establishing offset and slope coefficients for each estimated hydraulic parameter. Subsequently we evaluated these and six other PTFs for estimating water retention parameters using the NRCS soils database. A total of 47435 records containing 113970 observed water contents were used to test the PTFs for mean errors and root mean square errors. No overall superior model was found. Models with many calibration parameters or more input variables were not necessarily better than more simple models. All models underestimated water contents, with values ranging from −0.0086 to −0.0279 cm3 cm−3 Average root mean square errors ranged from 0.0687 cm3 cm−3 for a PTF that provided textural class average parameters to 0.0315 cm3 cm−3 for a model that also used two water retention points as predictors. Available soil water content for vegetation was estimated with errors ranging from 0.058 to 0.080 cm3 cm−3, depending on the model and the definition of available water.

Comparison of Models for Indirect Estimation of Water Retention and Available Water in Surface Soils

Quantitative knowledge of the unsaturated soil hydraulic properties is required in most studies involving water flow and solute transport in the vadose zone. Unfortunately, direct measurement of such properties is often difficult, expensive and time-consuming. Pedotransfer functions (PTFs) offer a means to estimate soil hydraulic properties based on predictors like texture, bulk density, and other soil variables. In this study, we focus on PTFs for water retention and show that systematic errors in five existing PTFs can be reduced by using water content–based objective functions, instead of parameter value–based objective functions. The alternative analysis was accomplished by establishing offset and slope coefficients for each estimated hydraulic parameter. Subsequently we evaluated these and six other PTFs for estimating water retention parameters using the NRCS soils database. A total of 47435 records containing 113970 observed water contents were used to test the PTFs for mean errors and root mean square errors. No overall superior model was found. Models with many calibration parameters or more input variables were not necessarily better than more simple models. All models underestimated water contents, with values ranging from −0.0086 to −0.0279 cm3 cm−3 Average root mean square errors ranged from 0.0687 cm3 cm−3 for a PTF that provided textural class average parameters to 0.0315 cm3 cm−3 for a model that also used two water retention points as predictors. Available soil water content for vegetation was estimated with errors ranging from 0.058 to 0.080 cm3 cm−3, depending on the model and the definition of available water.

A statistical approach to estimating runoff in center pivot irrigation with crust conditions

There have been several proposals to evaluate potential runoff in center pivot irrigation, through the integration of time varying infiltration–precipitation rate curves, involving complex iterative procedures. Some methods use empirical infiltration functions, such as the Kostiakov equation. Others use physically based infiltration functions, such as the Green–Ampt equation. Another option is to use the Richards equation, describing the one-dimensional vertical infiltration of water into the soil for a specified irrigation event. This equation is generally accepted to provide a basis for comparison between other runoff estimation methods. [P.B. Luz, J.C. Martins, M.C. Gonçalves, Reliable estimate of runoff in center pivot irrigation: statistical approach, in: Proceedings of the 16 Congress Mondial de Science du Sol, Poster 2-658, ISSS, Montpellier, France, August 19–25, 1998, pp. 577–593], developed a conceptual method of statistical nature, to estimate potential runoff in center pivot irrigation, comprising regression equations built with runoff results from a simulation computer model using the Richards equation. The procedure to simulate runoff involved a wide set of data related to water retention parameters and soil texture [W.J. Rawls, D.L. Brakensiek, Estimation of soil water retention and hydraulic properties, in: H.J. Morel-Seytoux (Ed.), Unsaturated Flow in Hydrologic Modeling, Theory and Practice, Kluwer Academic Publishers, Dordrecht, 1989, pp. 275–300], and water application. Such regression equations present a dependent variable, defined as an index of four parameters, related to the center pivot irrigation and to the soil-water system evaluation. The method had unacceptable results when a crust developed on the soil surface. Therefore, the objective of this study was to redefine the index, establishing new parameter coefficients with a trial and error approach. The model efficiency (similar to the coefficient of determination, r 2) ranged from 90 to 98%, showing the results are in good agreement to those computed by Richards equation, exhibiting a strong predictive value.

Development of pedotransfer functions using a group method of data handling for the soil of the Pianura Padano–Veneta region of North Italy: water retention properties

Pedotransfer functions (PTFs) with quantified uncertainty for estimating water retention from soil structure and texture, organic carbon content, bulk density and derived variables are presented for the soils of the Pianura Padano–Veneta region of North Italy. A data set of 153 soil horizons from 59 soil profiles was used for calibration of parametric PTFs using a group method of data handling (GMDH); the proposed PTFs provide estimations for the Brooks and Corey water retention parameters and for water content at −5, −10, −33 and −1500 kPa matric potentials. Soil structure descriptors were retained as essential input variables to be included in the PTFs for the estimation of the Brooks and Corey water retention parameters. Calibrated PTFs were validated against two independent data sets: a local one of 122 soil horizons and a data set of 78 soil horizons selected from the UNSODA data set. Point and parametric neural network PTFs were also trained and validated on the same data sets in order to evaluate which of the two methods is more accurate. In the case of point PTFs, GMDH PTFs performed better with the exception of water content at −1500 kPa; in the case of parametric PTFs, given an a posteriori correction of the parameters estimates outside calibration ranges, neural network provided slightly better validation results, but were less accurate in the case of the training data set. Results show that the proposed GMDH PTFs provide good results for the local validation data set and that for input data within the PTFs calibration range, the estimation holds the same degree of accuracy also for the UNSODA data set. Results suggest that whenever PTFs calibrated on a local data set are available, their use should be recommended, provided an a priori control of input variable ranges. Bootstrap results and Monte Carlo analysis highlighted the need for extending the calibration data set to include poorly represented coarse textured soils in order to reduce estimation variance and improve PTFs accuracy.

Estimating water retention curves of forest soils from soil texture and bulk density

AbstractForest soils differ significantly from the arable land in their distribution of the soil bulk density and humus content, but the water retention parameters are primarily derived from the data of agricultural soils. Thus, there is a need to relate physical parameters of forest soils with their water retention characteristics and compare them with those of agricultural soils. Using 1850 water retention curves from forest soils, we related the following soil physical parameters to soil texture, bulk density, and C content: air capacity (AC), available water capacity (AWC), and the permanent wilting point (PWP). The ACs of forest soils were significantly higher than those of agricultural soils which were related to the low bulk densities of the forest soils, whereas differences in AWCs were small. Therefore, for a proper evaluation of the water retention curves (WRCs) and the parameters derived from them, further subdivisions of the lowest (< 1.45 g cm‐3) of the three bulk density classes was undertaken to the wide range of low soil densities in forest soils (giving a total of 5 bulk density classes). In Germany, 31 soil texture classes are used for the estimation of soil physical parameters. Such a detailed classification is not required because of insignificant differences in WRCs for a large number of these classes. Based on cluster analysis of AC, AWC, and PWP parameters, 10 texture collectives were obtained. Using 5 classes of bulk densities, we further calculated the ACs, AWCs, and the PWPs for these 10 classes. Furthermore, “van Genuchten parameters” (θ r, θ s, α, and n) were derived which described the average WRC for each designated class. In a second approach using multiple regression analysis, regression functions for AC, AWC, and PWP and for the van Genuchten parameter were calculated.