such as the Rio Doce basin in southeastern Brazil, is indirect estimation from less costly covari- ates using pedotransferfunctions (PTF). This study primarily aims to develop region-specific PTFs for ρ b using multiple linear regressions (MLR) and random forests (RF). Secondly, it assessed the accuracy of PTFs for data grouped into soil horizons and soil classes. For that purpose, we compared the performance of PTFs compiled from the literature with those developed here. Two groups of data were evaluated as covariates: 1) readily available soil properties and 2) maps derived from a digital elevation model and MODIS satellite imagery, jointly with lithological and pedological maps. The MLR model was applied step-wise to select significant predictors and its accuracy assessed by means of cross-validation. The PTFs developed using all data estimated ρ b from soil properties by MLR and RF, with R
van den BERG, M.; KLAMT, E.; van REEUWIJK, L.P. & SOMBROEK, W.G. Pedotransferfunctions for the estimation of moisture retention characteristics of Ferralsols and related soils. Geoderma, 78:161-180, 1997. van GENUCHTEN, M.Th.; LEIJ, F.J. & YATES, S.R. The RETC code for quantifying the hydraulic functions of unsaturated soils. EPA/600/2-91/065. Washington, U.S Environmental Protection Agency, 1991. 85p. van GENUCHTEN, M.Th. A closed-form equation for
Pedotransferfunctions (PTFs) are equations used to estimate soil characteristics difficult to determine from other easily obtained ones. Water retention in soil is used in several agronomic and environmental applications, but its direct determination is time consuming and onerous, therefore PTFs are alternatives to obtaining this information more quickly and economically. The aims of this study were to generate a database and develop PTFs for water retention at potentials of -33 kPa (field capacity) and -1500 kPa (permanent wilting point) for Yellow Argisol and Yellow Latosol from the Brazilian Coastal Plains region. The Coastal Plains soils are mostly developed from Barreiras formation (pre-weathered sediments) and their main uses are sugarcane, livestock, forestry and fruticulture. The database to generate the PTFs was composed from the selection of information derived from scientific works and soil survey reports of the region. Specific PTFs were generated for each soil class, in their respective A and B horizons and for solum, through multiple regression by stepwise package of R language programming. Due to the small pedological variability (small number of soil classes containing great geographical expression) and mineralogical uniformity, usually observed in this environment, non-stratification of soil classes to create general PTFs presented similar or superior results compared to equations for each soil class. The adjustment of data demonstrated that water retention values at -33 kPa and -1500 kPa potentials can be estimated with adequate accuracy for the main soils of the Brazilian Coastal Plains through PTFs mainly from particle size distribution and secondarily from organic matter data.
Water retention in soil is used in many agronomic and environmental applications, but its direct measurement is time- consuming and expensive. Therefore, pedotransferfunctions (PTFs) are alternatives to obtain this information faster and more economically. The objectives of this study were to generate and validate PTFs to estimate the water content at potentials of -33 kPa (field capacity) and -1500 kPa (permanent wilting point) for different soil classes from the central-south portion of Rio Grande do Sul State. The physical and chemical analyses database from soil surveys of the Celulose Riograndense Corp were used. The database is composed of particle size distribution (coarse and fine sand, silt and clay), soil organic matter, and water content data at the above mentioned potentials, besides other information concerning the behavior of the soil classes at field conditions. Firstly, the data were stratified by soil classes and depths, and then 70% of the data were separated for PTF generation and 30% for validation. PTFs were generated for each specific soil class and also general PTFs which were not stratified by soil class, by means of stepwise multiple regression. In most situations, PTFs for a specific soil class showed a better fit than the general PTFs. Proper adjustment of the data showed that the water retention values at potentials of -33 kPa and -1500 kPa can be estimated for the soils from the central-south portion of Rio Grande do Sul State that do not have such analyses through the use of PTFs.
Taking into account the nature of the hydrological processes involved in in situ measurement of Field Capacity (FC), this study proposes a variation of the definition of FC aiming not only at minimizing the inadequacies of its determination, but also at maintaining its original, practical meaning. Analysis of FC data for 22 Brazilian soils and additional FC data from the literature, all measured according to the proposed definition, which is based on a 48-h drainage time after infiltration by shallow ponding, indicates a weak dependency on the amount of infiltrated water, antecedent moisture level, soil morphology, and the level of the groundwater table, but a strong dependency on basic soil properties. The dependence on basic soil properties allowed determination of FC of the 22 soil profiles by pedotransferfunctions (PTFs) using the input variables usually adopted in prediction of soil water retention. Among the input variables, soil moisture content θ θ θ θ (6 kPa) had the θ greatest impact. Indeed, a linear PTF based only on it resulted in an FC with a root mean squared residue less than 0.04 m 3 m -3 for most soils individually. Such a PTF
Pedotransferfunctions (PTFs) are predictive mod- els of certain soil properties using data from soil surveys (Bouma, 1989). These functions fill the gap between the available soil data and the properties that are more use- ful or required for a particular model or quality assess- ment. In this work, PTFs are used as physical-mathe- matical models that allow the estimation of D b from soil data, which are needed to convert carbon contents from percentage of dry weight to carbon mass per unit of area (Howard et al., 1995; Benites et al., 2007).
Pedotransferfunctions (PTFs) (Bouma, 1989) have been widely used for estimating ρb using soil properties which are easier to measure and are available in most da- tabases. These PTFs have been developed from specific datasets using OC and texture data as input parameters (Curtis and Post, 1964; Alexander, 1980; Federer, 1983; Grigal et al., 1989; Huntington et al., 1989; Manrique and Jones, 1991; Bernoux et al., 1998; Tomasella and Hodnett, 1998; Kaur et al., 2002; Prévost, 2004; De Vos et al., 2005; Périé and Ouimet, 2008; Han et al., 2012; Al-Qinna and Jaber, 2013; Hong et al., 2013; Nanko et al., 2014). Benites et al. (2007) also used the sum of basic cations (SB) as an input parameter.
However, bulk density has been found to vary with depth (Leonaviˇciut˙e, 2000) and soil type (Manrique and Jones, 1991), while the use of generic pedotransferfunctions can result in large errors in the calculation of SOC stocks. In say- ing this, De Vos indicates there is a need for specific PTF to be calibrated and validated on a regional basis (De Vos et al., 2005). Others take this further and report that PTF should be developed for particular horizon types or designations (Su- uster et al., 2011). Correlation with international data sets can be employed to generate PTF where local information is lacking. There is information available from large interna- tional soil survey databases (Hollis et al., 2006; Batjes, 2005, 2009), but in many cases bulk density is poorly documented. In these instances the use of splines or models of bulk density are then used with their own inherent variances, which can be problematic without large validation data sets (Lettens et al., 2005).
tion procedures – referred to here as “parameter estimation algorithms” – are generally called “pedotransferfunctions” (PTFs) when they concern soil properties. The survey data used to obtain agro-environmental conditions are derived from measured point data, or remotely sensed spatial data, and are therefore only estimations of their “true” spatio-temporal variations. So estimating pesticide leaching risks over large areas nec-
The estimation of non available soil variables through the knowledge of other related measured variables can be achieved through pedotransferfunctions (PTF) mainly saving time and reducing cost. Great differences among soils, however, can yield non desirable results when applying this method. This study discusses the application of developed PTFs by several authors using a variety of soils of different characteristics, to evaluate soil water contents of two Brazilian lowland soils. Comparisons are made between PTF evaluated data and field measured data, using statistical and geostatistical tools, like mean error, root mean square error, semivariogram, cross-validation, and regression coefficient. The eight tested PTFs to evaluate gravimetric soil water contents (Ug) at the tensions of 33 kPa and 1,500 kPa presented a tendency to overestimate Ug 33 kPa and underestimate
Abstract. The quartz fraction in soils is a key parameter of soil thermal conductivity models. Because it is dif- ficult to measure the quartz fraction in soils, this information is usually unavailable. This source of uncertainty impacts the simulation of sensible heat flux, evapotranspiration and land surface temperature in numerical simu- lations of the Earth system. Improving the estimation of soil quartz fraction is needed for practical applications in meteorology, hydrology and climate modeling. This paper investigates the use of long time series of routine ground observations made in weather stations to retrieve the soil quartz fraction. Profile soil temperature and water content were monitored at 21 weather stations in southern France. Soil thermal diffusivity was derived from the temperature profiles. Using observations of bulk density, soil texture, and fractions of gravel and soil organic matter, soil heat capacity and thermal conductivity were estimated. The quartz fraction was inversely estimated using an empirical geometric mean thermal conductivity model. Several pedotransferfunctions for estimating quartz content from gravimetric or volumetric fractions of soil particles (e.g., sand) were analyzed. The soil volumetric fraction of quartz (f q ) was systematically better correlated with soil characteristics than the
Studies on water retention and availability are scarce for subtropical or humid temperate climate regions of the southern hemisphere. The aims of this study were to evaluate the relations of the soil physical, chemical, and mineralogical properties with water retention and availability for the generation and validation of continuous point pedotransferfunctions (PTFs) for soils of the State of Santa Catarina (SC) in the South of Brazil. Horizons of 44 profiles were sampled in areas under different cover crops and regions of SC, to determine: field capacity (FC, 10 kPa), permanent wilting point (PWP, 1,500 kPa), available water content (AW, by difference), saturated hydraulic conductivity, bulk density, aggregate stability, particle size distribution (seven classes), organic matter content, and particle density. Chemical and mineralogical properties were obtained from the literature. Spearman’s rank correlation analysis and path analysis were used in the statistical analyses. The point PTFs for estimation of FC, PWP and AW were generated for the soil surface and subsurface through multiple regression analysis, followed by robust regression analysis, using two sets of predictive variables. Soils with finer texture and/or greater organic matter content retain more moisture, and organic matter is the property that mainly controls the water availability to plants in soil surface horizons. Path analysis was useful in understanding the relationships between soil properties for FC, PWP and AW. The predictive power of the generated PTFs to estimate FC and PWP was good for all horizons, while AW was best
Soil hydraulic properties, e.g., water retention, are cumbersome, time-consuming, and costly to measure, and they also change over time. Therefore, soil scientists and hydrologists have searched alternative methods for fast and accurate prediction of difficult- to-measure soil properties. Over the past three decades, estimation methods, called pedotransferfunctions (PTFs) have been widely used by soil scientists in temperate regions in response to the lack of measured soil property information. Bouma (1989) described the term pedotransfer function as “translating data we have into what we need”. Pedotransferfunctions are predictive functions that relate more easily measurable soil data, such as soil texture (sand, silt, and clay content), bulk density (BD), organic matter (OM) or organic carbon (OC) content, and/or other data routinely measured or registered in soil surveys, to hydraulic parameters, such as the soil water retention curve, SWRC (Bouma & van Lanen, 1987; Bouma, 1989; van den Berg et al., 1997). The most readily available data come from soil survey reports and soil databases.
van den BERG, M.; KLAMT, E.; van REEUWIJK, L.P. & SOMBROEK, W.G. Pedotransferfunctions for the estimation of moisture retention characteristics of Ferralsols and related soils. Geoderma, 78:161-180, 1997. van DIEPEN, C.; van KEULEN.; WOLK, J. & BERKHOUT, J. Land evaluation: From intuition to quantification. Adv. Soil Sci., 15:139-204, 1991.
One big challenge for soil science is to translate existing data into data that is needed. Pedotransferfunctions have been proposed for this purpose and they can be point or parametric when estimating the water retention characteristics. Many indicators of soil physical quality have been proposed, including the S-Index proposed by Dexter. The objective of this study was to assess the use of pedotransferfunctions for soil water retention to estimate the S-index under field conditions in the diversity of soils of the Paraná state. Soil samples were collected from 36 sites with textures ranging from sandy to heavy clay in the layers of 0-0.10 and 0.10-0.20 m and under two conditions (native forest and cultivated soil). Water content at six matric potentials, bulk density and contents of clay, sand and silt were determined. Soil-water retention curve was fitted by the van Genuchten-Mualem model and the S-index was calculated. S-index was estimated from water retention curves obtained by the pedotransfer function of Tomasella (point and parametric). Although the coefficient of determination varied from 0.759 to 0.895, modeling efficiency was negative and the regression coefficient between observed and predicted data was different from 1 in all comparisons. Under field conditions in the soil diversity of the Paraná state, restrictions were found in S-index estimation using the evaluated pedotransferfunctions.
K-values from soils and saprolites can be measured by direct ield methods or by indirect methods that estimate iniltration potential through other parameters. Most of the studies developed in the region used direct methods such as the double ring and open-end-hole. Field direct meth- ods are time-consuming and expensive. As an alternative, pedotransferfunctions (PTFs) are often used to estimate K-values indirectly, based on soil attributes such as texture, morphological structure, organic matter content and density (Bouma & Van Lanen 1987). hese methods were developed for soils from temperate regions. herefore, adequation for tropical soils, mainly Oxisols (the most extensive soil type from tropics), is necessary.
The soil water available to crops is defined by specific values of water potential limits. Underlying the estimation of hydro-physical limits, identified as permanent wilting point (PWP) and field capacity (FC), is the selection of a suitable method based on a multi-criteria analysis that is not always clear and defined. In this kind of analysis, the time required for measurements must be taken into consideration as well as other external measurement factors, e.g., the reliability and suitability of the study area, measurement uncertainty, cost, effort and labour invested. In this paper, the efficiency of different methods for determining hydro-physical limits is evaluated by using indices that allow for the calculation of efficiency in terms of effort and cost. The analysis evaluates both direct determination methods (pressure plate - PP and water activity meter - WAM) and indirect estimation methods (pedotransferfunctions - PTFs). The PTFs must be validated for the area of interest before use, but the time and cost associated with this validation are not included in the cost of analysis. Compared to the other methods, the combined use of PP and WAM to determine hydro-physical limits differs significantly in time and cost required and quality of information. For direct methods, increasing sample size significantly reduces cost and time. This paper assesses the effectiveness of combining a general analysis based on efficiency indices and more specific analyses based on the different influencing factors, which were considered separately so as not to mask potential benefits or drawbacks that are not evidenced in efficiency estimation.
Due to the existence of soil variables in the RS soil database with direct and indirect relationships to water retention, it was possible to estimate water retention by pedotransferfunctions (Table 4), as shown in figure 2. The independent variables included in the equations were the same as the model presented by Gupta & Larson (1979) and Rawls et al. (1982), and the coefficient associated with bulk density also had a negative signal, as in the cited study, which is due to the fact that sandier soils, with low water retention, are denser. In the model of van den Berg et al. (1997),
An alternative method that overcomes these shortcomings is the use of pedotransferfunctions (PTFs) to predict θ for different Ψm values according to other physical attributes, such as the bulk density (BD), total porosity (TP), macroporosity (Ma), microporosity (Mi), and textural classes (Machado et al., 2008; Michelon et al., 2010). The idea behind the PTFs is the evaluation of more laborious physical attributes using other less laborious ones for reference (Botula et al., 2014).