Abstract: Pedotransfer functions (PTFs) are becoming a more common way to predict soil hydraulic properties from soil texture, bulk density, and organic matter content. Thus far, the calibration and validation of PTFs has been hampered by a lack of suitable databases. In this paper we employed three databases

Abstract: The application and validation of complex atmosphere-soil water transport models demands knowledge of the parameters that describe hydraulic properties over extensive areas. Such information is rarely available, but Pedo Transfer Functions (PTFs) provide a means of predicting these parameters from soil survey data. However, most PTFs have been derived and validated using information from soils of temperate regions and have not been tested for the soils of tropical areas, for which chemical, physical, and pedogenetic processes are different. The equations of Rawls and colleagues, for example, overestimate water content when applied to the soils of Brazilian Amazonia. In this paper, we have developed a PTF to predict Brooks-Corey parameters from texture using data from soils of Amazonia. Multiple linear regressions were fitted to estimate, from soil texture (% sand, silt, and clay), the bulk density and porosity and the water content at a range of matric potentials. Brooks-Corey parameters were then derived and correlated independently with soil texture, providing a straightforward method for deriving soil retention parameters from the percentage of clay and silt. The method was validated using an independent data set for which textural and water release data were available. The agreement between the observed and measured values was very significant, but the results showed that the differences between predictions and measurements also depended on bulk density. However, the Amazonian soil survey data, which may be used to extrapolate these results spatially, do not generally include bulk density, and for this reason they were not included in the regressions.

Abstract: Direct measurement of hydraulic properties is time consuming, costly, and sometimes unreliable because of soil heterogeneity and experimental errors. Instead, hydraulic properties can be estimated from surrogate data such as soil texture and bulk density with pedotransfer functions (PTFs). This paper describes neural network PTFs to predict soil water retention, saturated and unsaturated hydraulic properties from limited or more extended sets of soil properties. Accuracy of prediction generally increased if more input data are used but there was always a considerable difference between predictions and measurements. The neural networks were combined with the bootstrap method to generate uncertainty estimates of the predicted hydraulic properties.

Abstract: A conceptual model based on the assumption that soil structure evolves from a uniform random fragmentation process is proposed to define the water retention function. The fragmentation process determines the particle size distribution of the soil. The transformation of particles volumes into pore volumes via a power function and the adoption of the capillarity equation lead to an expression for the water retention curve. This expression presents two fitting parameters only. The proposed model is tested on water retention data sets of 12 soils representing a wide range of soil textures, from sand to clay. The agreement between the fitted curves and the measured data is very good. The performances of the model are also compared with those of the two-parameter models of van Genuchten [1980] and Russo [1988] for the water retention function. In general, the proposed model exhibits increased flexibility and improves the fit at both the high and the low water contents range.

Abstract: Physical and chemical soil properties were measured along a mountainous climatological gradient in the province of Alicante (Spain) The objective was to evaluate how the climate affects certain soil properties at different temporal and spatial scales These properties include infiltration, runoff and sediment concentrations resulting from rainfall simulation experiments performed in winter and in summer Chemical soil properties like carbonate content, organic matter content and CEC were analysed in reference soil profiles along the gradient Physical soil properties like soil moisture content, macroaggregation and waterstable microaggregation were measured at monthly intervals during a year The comparison of the results was done at different spatial (site, slope and patch) and temporal (monthly and seasonal) scales by means of some statistical tests It can be concluded that there are some soil properties positively related to the gradient, like organic matter, clay content and CEC which increase with the annual rainfall However, runoff coefficients and erosion are higher when the climatic annual rainfall However, runoff coefficients and erosion are higher when the climatic conditions become more arid Aggregation and infiltration capacity are higher on north-facing slopes and in vegetated patches than in south-facing slopes and in bare patches

Abstract: Soil water retention is an important hydraulic property in the study of water flow and solute transport in soils. However, soil water retention measurements are costly and time-consuming. In this study, a procedure was developed to estimate this function based on soil particle-size distribution

Abstract: The accuracy of pedotransfer functions can be improved using more flexible equations and additional input variables. Penetration resistance as a parameter related to soil structure can be a useful additional input to pedotransfer functions. Our objectives were to see whether using penetration resistance can improve the accuracy of estimating water retention from soil composition and bulk density. To develop pedotransfer functions, we applied group method of data handling (GMDH) resulting in hierarchical polynomial regression networks or abductive networks. The advantage of GMDH is that it automates finding essential input variables to be included in pedotransfer functions and, unlike the artificial neural networks (ANN), presents an explicit form of the equations. We developed pedotransfer functions from data on texture, bulk density, penetration resistance, and water content at 0, −5, −10, −20, −100 and −1500 kPa in 180 samples of soils in New Zealand. Abductive networks were used to estimate water content at particular matrix potentials. The water content at −1500 kPa and the penetration resistance were the essential variables to include in pedotransfer functions along with bulk density and texture. The pore volume fractal dimension could be reliably estimated from the water content at −1500 kPa and penetration resistance. The variation coefficient rather than average value of penetration resistance was found to be a good predictor in some cases.

Abstract: Soil hydraulic properties are required to fully understand and predict soil water distribution. Soil hydraulic properties include the soil water characteristic curve and hydraulic conductivity. We used an integral method to solve the problem of water absorption into a horizontal soil column. The integral solutions to the problem were used to estimate the parameters a and n in the van Genuchten model for soil water characteristic curves. The two parameters, a and n, in the characteristic curve model were estimated by the length of the wetted zone, sorptivity, and saturated hydraulic conductivity. This new integral method uses both Richards' equation and the closedform equations of soil hydraulic properties. Six soils ranging from sandy loam to clay loam were used to test the method. Soil water characteristic curves estimated by the infiltration method are in good agreement with measured characteristic curves. The integral method provides a transient water flow approach to estimate the soil water characteristic curve instead of the usual equilibrium method. This is a new and simple means to determine soil hydraulic properties. I NCREASING EVIDENCE shows that the quality of soil and water resources on the Earth is being adversely affected by the release of a variety of agricultural and industrial pollutants into the environment (van Genuchten, 1992). Water is the most important carrier of the pollutants into our soils. Rates of soil water movement in various soil water flow processes (e.g., infiltration, redistribution, root uptake, and drainage) are important for making practical soil management decisions to minimize potential groundwater contamination and degradation of soil quality from land-applied chemicals. Numerical solutions of the flow and transport problems in the vadose zone are the most important approaches to predict quantitatively the dynamic behavior of the system. Unsaturated flow and transport modeling usually requires accurate and complete information about the unsaturated hydraulic properties for the model to function properly. Soil hydraulic properties include a soil water characteristic curve (the relation between volumetric water content [6] and pressure head [h]) d(h), hydraulic conductivity (K), and water diffusivity (D). Because the three hydraulic properties are related by K = D dQIdh, only two of them are independent. Usually the hydraulic conductivity and the soil water characteristic curve are considered to be two of the most important hydraulic properties.

Abstract: A soil water and energy budget model coupled with a microwave emission model (MICRO-SWEAT) was used to predict the diurnal courses of soil surface water content and microwave brightness temperatures during a number of drying cycles on soils of contrasting texture that were either cropped or bare. The parameters describing the soil water retention and conductivity characteristics [saturated hydraulic conductivity, air entry potential, bulk density, and the exponent (b) describing the slope of the water release curve] had a strong influence on the modeled bare-soil microwave brightness temperatures. These parameters were varied until the error between the remotely sensed and modeled brightness temperatures was minimized, leading to their predicted values. These predictions agreed with the measured values to within the experimental error. The modeled brightness temperature for a soybean-covered soil was sensitive to some of the vegetation parameters (particularly to the optical depth), in addition to the soil hydraulic properties. Preliminary findings suggest that, given an independent estimate of the vegetation parameters, it may still be possible to estimate the soil hydraulic properties under a moderate vegetation canopy.

Abstract: This study examines the effect of soil water content on aggregate stability and determines the relationships between the variation in soil stability and soil physical properties (texture, organic carbon, bulk density, pore size distribution and saturated hydraulic conductivity) in a microcatchment located in a semi-arid area of southeast Spain. The aggregate stability of soils was determined at three soil water contents (close to saturation, field capacity and air-dry) using a laboratory rainfall simulator technique. The aggregate stability for wetter conditions was higher than for the air-dry conditions for 85% of the samples tested. Furthermore, considerable difference in air-dry aggregate stability values was observed for predominant erosional and depositional zones within the microcatchment. This variability in air-dry aggregates stability was closely related to hydraulic properties and organic carbon content of the soil. Test on aggregate stability of air-dried soils are particularly appropriate for soils from semi-arid environments, and provide a more sensitive indicator of differences in the soil stability within the microcatchment than wetter samples.

Abstract: Soil bulk density ( .b) is a physical property related to many phenomena, such as plant root development and solute transport in soils. In this study, a comprehensive data search of literature from 1980 to 1997 was made to examine .b as influenced by soil organic matter (OM), soil texture, primary tillage and secondary tillage practices and tillage depth. The literature data showed that .b is principally related to clay content and OM for no-till soils, while any soil textural variable and OM can be predictors of .b for tilled soil conditions, depending on primary tillage types and soil strata. Based on the literature data, regression models that incorporate tillage effects were proposed to estimate .b for nine tillage types, including no-tillage. The models predict .b for a given tillage condition by estimating the bulk density of soil for no-tillage ( .NT) and adding a change in density ( ..) induced by tillage which depends on tillage type used and the tillage depth. Model results for three common tillage types (moldboard plow, chisel, and no-tillage) were validated with field data from Quebec, Canada and good agreements in .b values between the field data and the model results were obtained. Model inputs are soil textural variables and OM. Thus, the model is widely applicable, and can be coupled into other studies, such as those of soil erosion, soil compaction, tillage evaluation, crop growth or soil water and solute transport.

Abstract: A function relating unsaturated soil hydraulic conductivity K and soil water pressure head h is most important for understanding water flow and chemical transport in the vadose zone. Furthermore, the K(h) function near saturation is critical for describing flow in macropores and other structural voids. The usefulness of similar media scaling and functional normalization to describe the near-saturated hydraulic conductivity function K(h) measured in situ at 296 spatial locations across a heterogeneous agricultural field was tested. Disc (ponded and tension) infiltrometers were used to measure K(h) at different field positions (corn row, no traffic interrow, and traffic interrow) cutting across different soil types (Nicollet and Clarion loam derived from glacial till material). The K(h) data ranged several orders of magnitude for different field positions and soil types and were found to be statistically different between different field positions. Using a Gardner type K(h) function, relative hydraulic conductivity values, and a hybrid of similar media scaling and functional normalization concepts, all disc infiltrometer data sets were coalesced to a single reference curve. Poor to moderately correlated K and h scale factors did not show any significant spatial structure across the field. A novel finding is that saturated hydraulic conductivities (Ksat) could be successfully used as the scale factor for the near-saturated K(h) functions (e.g., 0-15 cm soil water tension) under all field positions and soil types at the experimental field. Among others, Warrick et al. (1977) and Jarvis and Messing (1995) suggested that further research should be carried out with respect to both experimental technology and scaling con- cepts for an optimum coevolution of techniques addressing soil heterogeneity. More recently, in situ measurement of near- saturated hydraulic conductivlty (K(h)) using disc (ponded and tension) infiltrometers has opened up new avenues to assess spatial variability of hydraulic properties of field soils. These in situ K(h) measurements are better suited to repre- sent (near-saturated) flow and transport scenarios in the field than K(h) measurements obtained using detached soil cores in the laboratory (Mohanty et al., 1994a). Near-saturated K(h) measurements are important for understanding the influence of macropores and other structural voids in the soil water regime of field soils and useful for multidomain models for soil hydraulic properties. The effects of soil structure and macro- pores might be more reliably predicted, as shown by Mohanty et al. (1997). Spatial variability of these K(h) measurements using different geostatistical and/or scaling concepts need to be studied further for different soils, crops, tillage practices, traf- fic conditions, and other extrinsic/intrinsic field variables. Mo- hanty et al. (1994b, 1996) used geostatistical techniques to an- alyze disc infiltrometer K(h) data under different soil and traffic conditions. To date, only Jarvis and Messing (1995) used a similar media scaling technique to analyze disc infiltrometer K(h) data obtained by means of four to six disc infiltrometer experiments at each of six different soil types in Sweden. The objective of our study was to test the appropriateness of

Abstract: Multi-temporal microwave remotely-sensed soil moisture has been utilized for the estimation of profile soil property, viz. the soil hydraulic conductivity. Passive microwave remote sensing was employed to collect daily soil moisture data across the Little Washita watershed, Oklahoma, during 10-18 June 1992. The ESTAR (Electronically Steered Thin Array Radiometer) instrument operating at L -band was flown on a NASA C-130 aircraft. Brightness temperature (TB) data collected at a ground resolution of 200m were employed to derive spatial distribution of surface soil moisture. Analysis of spatial and temporal soil moisture information in conjunction with soils data revealed a direct relation between changes in soil moisture and soil texture. A geographical information system (GIS) based analysis suggested that 2-days initial drainage of soil, measured from remote sensing, was related to an important soil hydraulic property viz. the saturated hydraulic conductivity (Ksat). A hydrologic modelling methodology was...

Abstract: Although soil is of major importance in influencing river hydrology, there is often a lack of soil hydrological data available to quantify the ameliorating effects of soil on steam flow. The HOST classification (Hydrology of Soil Types) was developed using pedotransfer rules and functions to derive a set of semi-quantified soil attributes from existing soil morphological information as surrogates for the missing hydraulic data. The rules were applied to the soil horizon information and were scaled to the catchment level through the known relationships between soil horizons and soil taxonomic units and between soil taxonomic units and 1:250 000 scale soil map units. The resulting classification, however, is not scale-specific and is capable of predicting river flow indices at the catchment scale (r2 = 0.79) and of predicting the dominant pathways of water movement through individual soil profiles.

Abstract: Simple one-parameter models for predicting changes in unsaturated soil hydraulic properties with changing soil-water content are useful, considering the great uncertainty and variability in the hydraulic parameters, and the models are often used for stochastic simulations of water and solute transport under field conditions. Two general one-parameter models for predicting relative hydraulic conductivity between water saturation and −350 cm H2O of soil-water potential are presented. The two new hydraulic conductivity models were labeled the Double Log Conductivity (DLC) and the Single Log Conductivity (SLC) models and represent modifications of the Campbell and the Libardi et al. conductivity models, respectively. The DLC and SLC model constants were optimized based on conductivity and retention data from a broad texture group of 40 sieved soils, but they can be calibrated easily to specific series of soils. The main parameter in both models (the Campbell soil-water retention parameter, b) can be estimated readily from soil texture or water retention data. Both models gave improved predictions of relative hydraulic conductivity in sieved soils compared with traditionally used one-parameter models. DLC and SLC model predictions were further compared with conductivity data from 10 undisturbed soils. The results suggested that the new models are also useful for predicting both relative and absolute hydraulic conductivity in undisturbed soil, but in this case, a calibration of the model constants based on a larger undisturbed soil data set is recommended.

Abstract: An internal drainage experiment was conducted to examine soil water content variability in space and in time. It is shown that the flux-gradient model used to describe water flow in field soil profiles, based on the Darcy–Buckingham equation, yielded results of extreme variability and questionable validity. The problem lies in the representativeness of a site due to soil variability, horizontally and vertically in time, which added to the character of the hydraulic conductivity versus soil water content relation, which in many cases can be approximated by exponential functions, leads to coefficients of variation up to 170% in the estimation of soil hydraulic conductivity values.

Abstract: Soil and land quality indicators play an important role in the assessment and evaluation of soil and land quality. In contrast with the general definitions of soil and land quality, working with indicators demands a better awareness of at which scale level measurements were made, at which scale calculations and models were developed and validated, and at which scale answers are needed. We propose that soil and land quality indicators may be classified by three characteristics: 1) scale level, 2) complexity, and 3) transferability. Each characteristic is represented by an axis in the Soil and Land Quality Indicator Diagram. Indicators with a high complexity can not be measured directly, but need to be calculated with one or more models, eg. pedotransfer functions and hydrological simulation models. For the application of the indicator it is then important to know how the indicator value was obtained, i.e. which models were used. A specific sequence of models used for obtaining an indicator value is called a ‘research chain’ and is indicated in the Scale Hierarchy and Knowledge Type Diagram. The use of research chains allows the user to consider and evaluate alternative options for the assessment of a specific indicator. In this study values for three soil quality indicators were obtained through two alternative research chains. The research chains differed by the choice of used pedotransfer functions and soil hydrological models. The two research chains yielded for each of the three indicators two sets of thirty year averages for 166 locations in the study area. Per location the obtained indicator values were compared with a t-test. The research chains were found to yield significantly different values for all three indicators. The spatial and temporal variability of the data was analyzed for each step, i.e. per model, along both research chains. Alternative models yielded different spatial and temporal variability structures. Therefore, the choice of research chain not only affects the mean value of an indicator, but also the associated spatial and temporal variability structure. Knowledge of the spatial and temporal variability is important for upscaling purposes. Based on these results we conclude that the successful application of soil and land quality indicators depends on: 1) the definition of suitable indicators based on scale level, complexity, and transferability; 2) the careful selection and definition of research chains; and 3) the combined presentation of indicator values and used research chains.

Abstract: The quantitative evaluation of the thermodynamic status of moisture in the soil by the centrifuge method is discussed. The theoretical fundamentals of the method are described, and practical recommendations are given. A model of centrifugation kinetics was proposed for the determination of the equilibrium moisture content and moisture conductivity function of the soil from the measurements of the drainage rate in a soil sample. Experimental results obtained characterize the water-holding capacity of soils with different textures in the variation range of soil moisture potential from 0 to -650 J/kg.

Abstract: . The results from an application of MAGIC (Model of Acidification of Groundwater In Catchments) to 733 Scottish catchments are presented. The availability of representative, good quality soil data is frequently limiting factor for biogeochemical modelling, particularly those involving modelling at various spatial scales. This study tests the sensitivity of MAGIC to soil input data derived from two different methodologies; the "nearest neighbour method" considers the closest representative soil profile to a catchment, and the "spatial weighting method" of all soil types identified in a catchment, based on a soil physico-chemical classification of Scotland. Soil data (soil depth, density, cation exchange capacity and base saturation) calculated using the "nearest neighbour method" and the "spatial weighting method" were highly variable, although the range of upper and lower limits were greater for soil data produced using the nearest neighbour method. In contrast to the predominantly organic soil data calculated by the nearest neighbour method, the spatially weighted soil parameters included a greater proportion of mineral soils. With regard to simulated surface water Acid Neutralising Capacity (ANC) for 1851, 1997 and 2050, MAGIC predictions were similar irrespective of the methodology used to determine soil input parameters. However, soil input data derived from both methods resulted in variable base saturation predictions. It is concluded that the "nearest neighbour" methodology is most appropriate if the objective is to determine the predicted response of the most acid- sensitive sites within a region in line with the approach used in Critical Laod mapping. On the other hand, "spatial weighting" integrates catchment soils and represents a more robust methodology by which to determine changes in median soil and water response in a regional context. The anticipated reductions in S emissions associated with the Second S Protocol are predicted to have a marginal beneficial effect on the recovery of soils and surface waters of Scotland.

Abstract: A method for estimating hydraulic conductivity from in-situ measurements of soil’s hydraulic parameters from a point application of water was tested for three soil types. The method is based on Wooding’s (1968) and Warrick’s (1985) solutions of water flow from a shallow circular pond and point source, respectively. Measurements of the saturated radii and the associated flow rates are used to determine the saturated hydraulic conductivity and a for the assumed Gardner’s (1958) exponential relationship between hydraulic conductivity and soil matric head. Effects of flow rate on saturated and unsaturated surface wetted regimes were also observed. The surface wetted areas were found to be significantly affected by flow rate in all three soils. The results from the point application method were compared to those from ring infiltrometer measurements and gave consistent values for saturated hydraulic conductivity. The method’s simplicity, repeatability and the ability to make rapid in-situ measurement makes it practical and applicable to use under varying conditions.

Abstract: Soil saturated hydraulic conductivity (K,) is needed to simulate many water transport related processes in soil, such as water erosion, surface runoff, and water supply to plants. In this study, data reported in the literature relating ~ to tillage practices published during the past 25 years were compiled, pooled, and regressed to obtain relationships between ~ and soil variables. The data showed that soil bulk density (Pb) is a major factor influencing ~ for general tillage conditions. When specific tillage treatments are considered, K, is principally related to soil organic matter (OM) for no-till soil; ~ is also affected by the clay and silt contents for plowed soils. Based on data compiled from the literature, several equations that incorporate tillage practice and basic soil variables were proposed to estimate Ks• These equations were evaluated with field data from Quebec soils where the dominant textures were sandy. Large differences in K, values between the field data and the prediction values were found due to variable soil characteristics and tillage conditions. Evaluations of three previously-published models for K, prediction were also performed using the Quebec field data and none of them was in close agreement with the measurements. However, results from Campbell's model were significantly correlated to the field data, although the model under-predicted ~. This model was calibrated with the measured Quebec data used in this study for prediction of field Ks for sandy soils.

Abstract: It is known that field-scale variations in subsurface hydraulic characteristics are influenced, to a large extent, by soil properties. Limited information, however, exists on the sensitivity of hydraulic functions to field-scale variations in soil properties. The sensitivity of 4 soil water retention functions, t(h), to variations in soil properties and changes in bulk density (ρ) across and within soils along a 500-m transect has been assessed in this study. The t(h) functions compared are those of van Genuchten, Brooks and Corey, Campbell, and Gardner. Water retention characteristics for 7 soils, each packed to 2 relative ρ, were established for each function. The coefficient of determination, R 2 , for the best fit of water retention ranged from 0·79 to 0· 98 for the Gardner and Campbell functions, from 0· 92 to 0·99 for the Brooks and Corey function, and from 0·83 to 0·99 for the van Genuchten function. Simple linear regression analysis indicated the nonlinear slope parameters of the 4 functions were more strongly correlated with soil properties. However, only the van Genuchten slope parameters were sensitive to changes in ρ. No consistency existed between the sensitivity of the linear parameters of the 4 functions and soil properties, and none were sensitive to changes in ρ. Except for the a parameter in the van Genuchten function, all the parameters in this function can be predicted with satisfactory confidence from soil properties and ρ. The results indicate that, of the 4 functions assessed, the van Genuchten t(h) function is the most sensitive to field-scale variations in soil properties along a transect in a landscape unit and to changes in ρ.