DOCSLIB.ORG

Estimating Available Water Capacity from Basic Soil Physical Properties -A Comparison of Common Pedotransfer Functions

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Estimating Available Water Capacity from Basic Soil Physical Properties -A Comparison of Common Pedotransfer Functions Estimating Available Water Capacity from basic Soil physical Properties -A comparison of common Pedotransfer Functions Kai Lipsius 22.07.2002 Studienarbeit, under supervision of Prof. Dr. W. Durner 1 Managed by Dr. Michael Sommer, Dipl. geoökol. Matthias Zipprich2 2 GSF-National research centre 1 Department of Geoecology for environment and health Braunschweig Technical University Studienarbeit Kai Lipsius 2002: Comparison of Pedotransfer Functions II Contents 1 Abstract ........................................................................................................................................... 1 2 Introduction ..................................................................................................................................... 2 2.1 The task ..................................................................................................................................2 2.2 Soil-water Storage..................................................................................................................2 2.3 Available water capacity ........................................................................................................3 2.4 Field capacity .........................................................................................................................3 2.5 Permanent wilting point .........................................................................................................3 2.6 Factors Affecting Moisture Storage .......................................................................................4 2.6.1 Soil Texture .............................................................................................................. 4 2.6.2 Soil structure............................................................................................................. 4 2.6.3 Clay content..............................................................................................................4 2.6.4 Organic matter content ............................................................................................. 5 2.6.5 Depth of wetting and antecedent moisture ............................................................... 5 2.6.6 The presence of impeding layers in the profile ........................................................ 5 2.6.7 Evapotranspiration.................................................................................................... 5 2.6.8 Bulk density.............................................................................................................. 5 2.6.9 Rock fragments......................................................................................................... 5 2.7 Newer Concepts of Soil Water Availability to Plants............................................................5 2.8 Water Retention Curve...........................................................................................................6 2.8.1 Parameterisation of the Water Retention Curve ....................................................... 6 2.8.2 Hysteresis ................................................................................................................. 6 2.9 Pedotransfer Functions...........................................................................................................7 2.9.1 PTF Group A -Direct Prediction of available water capacity................................... 7 2.9.2 PTF Group B -Prediction of water contents at specific points of the WRC............. 7 2.9.3 PTF Group C -Prediction of parameters of the soil water characteristic.................. 8 2.10 The effective AWC ................................................................................................................9 3 Materials and methods................................................................................................................... 10 3.1 Soils and sampling strategies ...............................................................................................10 3.1.1 Texture.................................................................................................................... 11 3.1.2 Organic Carbon content.......................................................................................... 11 3.1.3 Bulk density............................................................................................................ 11 3.1.4 Water Retention Curves (WRC)............................................................................. 12 3.2 Prediction of bulk density.....................................................................................................12 3.3 Prediction of organic carbon content....................................................................................15 3.4 Gravel Volume .....................................................................................................................15 3.5 Pedotransfer Functions.........................................................................................................16 3.5.1 Scheinost 1 (Sch1).................................................................................................. 16 3.5.2 Scheinost 2 (Sch2).................................................................................................. 16 3.5.3 Scheinost 3 (Sch3).................................................................................................. 17 3.5.4 Scheinost 4 (Sch4).................................................................................................. 17 3.5.5 Scheinost and Sinowski (S.S)................................................................................. 17 3.5.6 Sinowski (Sin) ........................................................................................................ 17 3.5.7 Rawls (Rawls) ........................................................................................................ 17 3.5.8 Vereecken 1 (V1) ................................................................................................... 17 3.6 Statistical Methods ...............................................................................................................17 4 Results and discussion................................................................................................................... 19 4.1 Available Water Capacity between –60 hPa and –15000 hPa..............................................19 4.2 Available Water Capacity between –100 hPa and –15000 hPa............................................22 4.3 Available Water Capacity between –300 hPa and –15000 hPa............................................25 5 Conclusions ................................................................................................................................... 29 6 Reference....................................................................................................................................... 30 7 Appendix ....................................................................................................................................... 31 7.1 FAM data base.......................................................................................................................... Studienarbeit Kai Lipsius 2002: Comparison of Pedotransfer Functions III 7.2 S-Plus Programs ...................................................................................................................31 7.2.1 Scheinost und Sinowski.......................................................................................... 31 7.2.2 Scheinost 1.............................................................................................................. 31 7.2.3 Scheinost 2.............................................................................................................. 32 7.2.4 Scheinost 3.............................................................................................................. 32 7.2.5 Scheinost 4.............................................................................................................. 33 7.2.6 Sinowski ................................................................................................................. 33 7.2.7 Rawls ...................................................................................................................... 33 7.2.8 Minasny .................................................................................................................. 34 7.2.9 Renger..................................................................................................................... 35 7.2.10 Vereecken 1............................................................................................................ 36 7.2.11 Vereecken 2............................................................................................................ 37 List of Tables Table 2.1: Soil property ranges of the calibration data sets used to develop the evaluated PTF. Arithmetic means are given in parentheses. .......................................................................... 7 Table 3.1: Parameters of the multiple linear regression for Equation 3.1 for all layers........................ 13 Table 3.2: Statistical results of the multiple linear regression to estimate bulk density........................ 15 Table 4.1: Summary of the performance of the different PTF to predict the AWC [cm3/cm3] between 60 and 15000 hPa ................................................................................................................19
Load more

Recommended publications
  • Deriving and Validating Pedotransfer Functions for Some Calcareous Soils ⇑ Habib Khodaverdiloo A, Mehdi Homaee B, , Martinus Th
    Journal of Hydrology 399 (2011) 93–99 Contents lists available at ScienceDirect Journal of Hydrology journal homepage: www.elsevier.com/locate/jhydrol Deriving and validating pedotransfer functions for some calcareous soils ⇑ Habib Khodaverdiloo a, Mehdi Homaee b, , Martinus Th. van Genuchten c, Shoja Ghorbani Dashtaki d a Department of Soil Science, Urmia University, Urmia, Iran b Department of Soil Science, Tarbiat Modares University, Tehran 14115-336, Iran c Department of Mechanical Engineering, COPPE/LTTC, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil d Department of Soil Science, Shahrekord University, Shahrekord 88186/34141, Iran article info summary Article history: The unsaturated soil hydraulic properties are needed for many different applications in soil hydrology. Received 12 January 2010 Pedotransfer functions (PTFs) have proven to be useful to indirectly estimate these parameters from more Received in revised form 14 December 2010 easily obtainable soil data. Until now no studies have been conducted to derive or verify PTFs for calcar- Accepted 28 December 2010 eous soils, which hydraulically may not behave the same as non-calcareous soils. The objectives of this Available online 6 January 2011 study were to assess the influence of soil CaCO3 on the soil water retention characteristics of some cal- This manuscript was handled by P. Baveye, careous soils, and to derive PTFs for these soils. Two data sets were used to derive and evaluate the estab- Editor-in-Chief lished PTFs. Data set 1 containing 220 samples was employed as a calibration set for multiple linear regression. An independent data set containing 55 soil samples from a different location served to verify Keywords: the derived PTFs.
    [Show full text]
  • Pedotransfer Functions for Estimating the Field Capacity and Permanent Wilting Point in the Critical Zone of the Loess Plateau, China
    Journal of Soils and Sediments https://doi.org/10.1007/s11368-018-2036-x SOILS, SEC 2 • GLOBAL CHANGE, ENVIRON RISK ASSESS, SUSTAINABLE LAND USE • RESEARCH ARTICLE Pedotransfer functions for estimating the field capacity and permanent wilting point in the critical zone of the Loess Plateau, China Jiangbo Qiao1 & Yuanjun Zhu2 & Xiaoxu Jia3 & Laiming Huang3 & Ming’an Shao2,3 Received: 26 February 2018 /Accepted: 18 May 2018 # Springer-Verlag GmbH Germany, part of Springer Nature 2018 Abstract Purpose Field capacity (FC) and permanent wilting point (PWP) are important physical properties for evaluating the available soil water storage, as well as being used as input variables for related agro-hydrological models. Direct measurements of FC and PWP are time consuming and expensive, and thus, it is necessary to develop related pedotransfer functions (PTFs). In this study, stepwise multiple linear regression (SMLR) and artificial neural network (ANN) methods were used to develop FC and PWP PTFs for the deep layer of the Loess Plateau based on the bulk density (BD),sand, silt, clay, and soil organic carbon (SOC) contents. Materials and methods Soil core drilling was used to obtain undisturbed soil cores from three typical sites on the Loess Plateau, which ranged from the top of the soil profile to the bedrock (0–200 m). The FC and PWP were measured using the centrifugation method at suctions of − 33 and − 1500 kPa, respectively. Results and discussion The results showed that FC and PWP exhibited moderate variation where the coefficients of variation were 11 and 23%, respectively. FC had significant correlations with sand, silt, clay, and SOC (P < 0.01), while there were also significant correlations between all of the variables and PWP.
    [Show full text]
  • Revisiting the S-Index for Soil Physical Quality and Its Use in Brazil 1
    REVISITING THE S-INDEX FOR SOIL PHYSICAL QUALITY AND ITS USE IN BRAZIL 1 REVISÃO DE LITERATURA REVISITING THE S-INDEX FOR SOIL PHYSICAL QUALITY AND ITS USE IN BRAZIL(1) Quirijn de Jong van Lier(2) SUMMARY The S-index was introduced in 2004 in a publication by A.R. Dexter. S was proposed as an indicator of soil physical quality. A critical value delimiting soils with rich and poor physical quality was proposed. At present, Brazil is world leader in citations of Dexter´s publication. In this publication the S-theory is mathematically revisited and extended. It is shown that S is mathematically correlated to bulk density and total porosity. As an absolute indicator, the value of S alone has proven to be incapable of predicting soil physical quality. The critical value does not always hold under boundary conditions described in the literature. This is to be expected because S is a static parameter, therefore implicitly unable to describe dynamic processes. As a relative indicator of soil physical quality, the S-index has no additional value over bulk density or total porosity. Therefore, in the opinion of the author, the fact that bulk density or total porosity are much more easily determined than the water retention curve for obtaining S disqualifies S as an advantageous indicator of relative soil physical quality. Among the several equations available for the fitting of water retention curves, the Groenevelt-Grant equation is preferable for use with S since one of its parameters and S are linearly correlated. Since efforts in soil physics research have the purpose of describing dynamic processes, it is the author´s opinion that these efforts should shift towards mechanistic soil physics as opposed to the search for empirical correlations like S which, at present, represents far more than its reasonable share of soil physics in Brazil.
    [Show full text]
  • Characterisation of the Least Limiting Water Range of a Texture-Contrast Soil
    q, È 'c)ç.\ CHARACTERISATION OF THE LEAST LIMITING WATER RANGE OF A TEXTURE- CONTRAST SOIL Thesis submitted for the degree of Master of Agricultural Science ln The UniversitY of Adelaide Faculty of Agricultural and Natural Resource Sciences by STANLEY RABASHI SEMETSA Department of Soil and Water January 2000 \Maite Agricuttural Research Institute Glen Osmond, South Australia Thisworkisdedicatedtomylateson,KITOSEANSEMETSA TABLE OF CONTENTS PAGE CHAPTER iv ABSTRACT..... viii STATEMENT... tx ACKNO\ryLEDGEMENTS. x LIST OF' F'IGURES... xlr LIST OF' TABLES... I CHAPTER1 : INTRODUCTION 1 3 I.2 Research Questions and Objectives 4 1.3 Structure of the Thesis CHAPTER2: LITERATURE REVIEIV' """"6 6 2.I Introduction .....'......" """"""""' temporal variability """"' 6 z.z Definition of soil structure incorporating spatial & 9 2.3 Soil structural quality indices for plant growth""' """" 9 2.3-l Aggregate Characteristics """"".' """"' t2 2.3.2 Bulk density and relative bulk density"""""""' 13 2.3.3 Macroporosity and pore continuity """""" 2.3.4 Plant available water capacity Relevance to Plant Growthl6 2.3.5 Least Limiting water Range (LLWR) and its z.3.sJUpper limit (Wet end)""""" """""'17 18 2.3.5.2lower limit .....'.'. """"" 18 2.3.5.3 Prediction of the LLWR"""' """""' (WRC) 20 2.3.5.4Estimation of the Water Retention Curve (SÃO 24 2.3.5.5 Estimation of the Soil Resistance Curve " the LLWR""""" 25 2.3.5.6 Pedotransfer functions and their use to characterise 26 2.4 Duplex soils and pedotransfer functions 2.4.1 Definition """"')6 soils 2.4.2 Origin, distribution and agricultural use of duplex """"' """"""""27 28 2.5 SummarY """""""" I CH^PTER3:ESTIMATIONoTLLWRFROMSOILPHYSICAL 30 PROPERTIES .........
    [Show full text]
  • Soil Resource Guide
    Soil Resource Guide Soil Resource Guide Everything you need to know about: Soil Soil monitoring Soil sensors1 CONTENTS Why is Soil Monitoring So Important? . 4 How Do Soil Sensors Work? . 4 SOIL Soil Geomorphology . 6 Soil Horizons . 6 Soil Orders and Taxonomy . 7 The 12 Orders of Soil Geomorphology . 7 Soil Textures . 9 Soil Properties . 9 Dielectric Permittivity . 10 Dielectric Theory . 11 How Temperature Affects Dielectric Permittivity . .. 13 Measuring Apparent vs . Imaginary Dielectric Permittivity . 13 Salinity / Electrical Conductivity (EC) . 14 Bulk EC Versus Pore Water EC . 14 Bulk EC and EC Pathways in Soil . 14 Application of Bulk EC Measurements . 15 Total Dissolved Solids (TDS) . 15 Soil Matric Potential . 16 Soil pH . 16 Soil Texture . 17 Soil Bulk Density . 17 Shrink/Swell Clays . 17 Ped Wetting . 17 Rock and Pebbles . 18 Bioturbation . 18 Soil Monitoring Applications . 19 Archeology . 19 Erosion Studies . 19 Agriculture . 19 Biofuel Studies . 19 Drought Forecasting Models . 20 Landslide Studies . 20 Mesonets and Weather Station Networks . 20 Dust Control . 20 Phytoremediation . 20 Soil Carbon Sequestration Studies . 21 Watershed Hydrology Studies . 21 Wetland Delineation Indicators . 21 Satellite Ground Truth Studies . 21 Reservoir Recharge from Snowpack . .. 21 Sports Turf . 21 Soil Moisture and Irrigation . 22 Soil Moisture Measurement Considerations for Irrigation . 22 Fill Point Irrigation Scheduling . .. 23 Mass Balance Irrigation Scheduling . 23 2 Soil Resource Guide SOIL SENSORS Volumetric Water Content Sensors . 26 Tensiometers (Soil Matric Potential Sensors) . 26 Single-Point Measurement . .. 27 Soil Profiling Probes . 28 Permanent and Semi-Permanent Installations . 29 Portable Soil Sensors . 29 Soil Sensor Technologies . 30 Capacitance (Charge) . 31 Frequency Domain Reflectometry (FDR) / Capacitance (Frequency) .
    [Show full text]
  • Field Determination of Permanent Wilting Point
    Field Determination of Permanent Wilting Point Item Type text; Article Authors Norton, E. R.; Silvertooth, J. C. Publisher College of Agriculture, University of Arizona (Tucson, AZ) Journal Cotton: A College of Agriculture Report Download date 30/09/2021 11:09:56 Link to Item http://hdl.handle.net/10150/210944 Field Determination of Permanent Wilting Point E.R. Norton and J.C. Silvertooth Abstract Water is a vital resource for cotton production in the desert Southwest.One method of managing irrigation water is through the use of a "checkbook" approach to irrigation scheduling.This involves irrigating based upon the percent depletion of plant available water (PAK9 from the soil profile. In order to effectively utilize this method of irrigation scheduling soil water content values at field capacity (FC) and permanent wilting point (PWP) must be defined. In this study the PWP values were characterized for Iwo different soil types, one at Maricopa, AZ and another at Marana, AZ. The possibility of having different values for PWP as a function of crop stage of growth was also investigated in this study. Results demonstrated differences in both FC and PWP values between the two locations. Differences were also observed as a function of crop growth stage in the pattern of soil water extraction. Introduction Irrigated agriculture in the desert Southwest is a very intensive, high input, high output production system. There are several important crop inputs that go into producing a successful crop of cotton. In order to attain maximum economic yield all inputs must be managed in an optimal fashion.The single most critical input in desert agriculture is water.If water is not managed in an optimum fashion, management of other inputs such as fertilizers, PGR's, insecticides, etc.
    [Show full text]
  • Pedotransfer Functions to Estimate Soil Water Content at Field Capacity
    J. Earth Syst. Sci. (2018) 127:35 c Indian Academy of Sciences https://doi.org/10.1007/s12040-018-0937-0 Pedotransfer functions to estimate soil water content at field capacity and permanent wilting point in hot Arid Western India Priyabrata Santra1,*, Mahesh Kumar1,RNKumawat1, D K Painuli1, KMHati2, G B M Heuvelink3 and NHBatjes3 1ICAR-Central Arid Zone Research Institute (CAZRI), Jodhpur 342 003, India. 2ICAR-Indian Institute of Soil Science (ISSS), Bhopal 462 001, India. 3ISRIC-World Soil Information, Wageningen, The Netherlands. *Corresponding author. e-mail: [email protected] MS received 17 August 2016; revised 10 August 2017; accepted 22 August 2017; published online 27 March 2018 Characterization of soil water retention, e.g., water content at field capacity (FC) and permanent wilting point (PWP) over a landscape plays a key role in efficient utilization of available scarce water resources in dry land agriculture; however, direct measurement thereof for multiple locations in the field is not always feasible. Therefore, pedotransfer functions (PTFs) were developed to estimate soil water retention at FC and PWP for dryland soils of India. A soil database available for Arid Western India (N=370) was used to develop PTFs. The developed PTFs were tested in two independent datasets from arid regions of India (N=36) and an arid region of USA (N=1789). While testing these PTFs using independent data from India, root mean square error (RMSE) was found to be 2.65 and 1.08 for FC and PWP, respectively, whereas for most of the tested ‘established’ PTFs, the RMSE was >3.41 and >1.15, respectively.
    [Show full text]
  • Pedotransfer Functions in Earth System Science
    PUBLICATIONS Reviews of Geophysics REVIEW ARTICLE Pedotransfer Functions in Earth System Science: 10.1002/2017RG000581 Challenges and Perspectives Key Points: Kris Van Looy1,2 , Johan Bouma3 , Michael Herbst1 , John Koestel4 , Budiman Minasny5, • Methods for development and 6 1 7 8 evaluation of pedotransfer functions Umakant Mishra , Carsten Montzka , Attila Nemes , Yakov A. Pachepsky , 5 9 10,11 12 1 are described, and perspectives in José Padarian , Marcel G. Schaap , Brigitta Tóth , Anne Verhoef , Jan Vanderborght , different Earth system science Martine J. van der Ploeg13, Lutz Weihermüller1, Steffen Zacharias14 , Yonggen Zhang9,15 , disciplines presented 1,16 • Novel applications are present for the and Harry Vereecken different fluxes of water, solutes, and 1 2 fi gas between soil and atmosphere, Institute of Bio- and Geosciences-3 Agrosphere, Forschungszentrum Jülich, Jülich, Germany, Scienti c Coordination 3 subject of the land surface models Office ISMC, International Soil Modeling Consortium, Jülich, Germany, Wageningen University and Research, Wageningen, • Methodological challenges are still Netherlands, 4Swedish University of Agricultural Sciences, Uppsala, Sweden, 5Department of Environmental Sciences, present for extrapolation and scaling, University of Sydney, Sydney, New South Wales, Australia, 6Environmental Science Division, Argonne National Laboratory, but integration and validation in 7 global-scale models is an Argonne, IL, USA, Division of Environment and Natural Resources, Norwegian Institute of Bioeconomy Research,
    [Show full text]
  • Pedotransfer Functions to Estimate Retention and Availability of Water In
    PEDOTRANSFER FUNCTIONS TO ESTIMATE RETENTION AND AVAILABILITY OF WATER IN... 889 PEDOTRANSFER FUNCTIONS TO ESTIMATE RETENTION AND AVAILABILITY OF WATER IN SOILS OF THE STATE OF SANTA CATARINA, BRAZIL(1) André da Costa(2), Jackson Adriano Albuquerque(3), Jaime Antônio de Almeida(3), Adriano da Costa(4) & Rodrigo Vieira Luciano(5) SUMMARY 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 pedotransfer functions (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.
    [Show full text]
  • Quantification of the Soil Physical Quality of a Tropical Oxisol Using the S Index
    56 Tormena et al. QUANTIFICATION OF THE SOIL PHYSICAL QUALITY OF A TROPICAL OXISOL USING THE S INDEX Cássio Antonio Tormena1*; Álvaro Pires da Silva2; Silvia Del Carmen Imhoff3; Anthony Roger Dexter4 1 UEM - Depto. de Agronomia, Av. Colombo, 5790 - 87020-900 - Maringá, PR - Brasil. 2 USP/ESALQ - Depto. de Ciência do Solo, C.P. 09 - 13418-900 - Piracicaba, SP - Brasil. 3 UNL - Cát. Diagnóstico y Tecnologia de Tierras, C.P. 3080 - Esperanza, SF - Argentina. 4 IUNG/PIB - ul. Czartoryskich 8, 24-100 - Pulawy, Poland. *Corresponding author <[email protected]> ABSTRACT: Soil physical quality is fundamental for the sustainability of agro ecosystems. Soil physical quality assessment must be developed using parameters that describe physical behavior. S, a new soil physical parameter has recently been introduced for assessing the soil physical quality. A good soil physical quality has been associated with values of S > 0.035 in soils from temperate climates. However, S has not been evaluated in tropical soils yet. Therefore we tested the hypothesis that S is a reliable soil physical quality indicator of a Typic Hapludox cropped with maize under no- tillage (NT) and conventional tillage (CT). Undisturbed samples were collected from each tillage system in the row and interrow positions. Soil bulk density was determined in the samples and the S parameter was calculated using a pedotransfer function from the same samples. The parameter S was able to differentiate tillage and position with SNT < SCT independent of the row and interrow sampling positions. Higher S values were verified in row position than in the interrow in both tillage systems.
    [Show full text]
  • Development and Comparative Analysis of Pedotransfer Functions for Predicting Soil Water Characteristic Content for Tunisian Soil
    Development and comparative analysis of pedotransfer functions for predicting soil water characteristic content for Tunisian soil Jabloun Mohamed and Sahli Ali* Abstract - An accurate determination of the soil Index Terms— Field capacity, Pedotransfer function, hydraulic characteristics is crucial for using soil Tunisian soils texture, Wilting point. water simulation models. However, these measurements are time consuming which makes it INTRODUCTION costly to characterise a soil. As an alternative, Knowledge of the soil hydraulic properties is pedotransfer functions (PTFs) often prove to be indispensable to solve many soil and water management good predictors for soil water contents. The problems related to agriculture, ecology, and purpose of this study is (i) to evaluate three well- environmental issues. These properties are needed to known and accepted parametric PTFs used to describe and predict water and solute transport, as well estimate soil water retention curves from available as to model heat and mass transport near the soil soil data [1]-[2]-[3], and (ii) to derive and validate, surface. One of the main soil hydraulic properties is the for Tunisian soils, a more accurate point PTFs; the water retention curve, as it expresses the relationship proposed PTFs were developed for four levels of between the matric potential and the water content of availability of basic soil data (particle fractions, dry the soil. It can be considered of great importance in bulk density and organic matter content) and present-day agricultural, ecological, and environmental provide estimation for water content at 0, 100 and soil research. Unfortunately, direct measurement of this 1500 kPa pressure. A total of 147 Tunisian soil property is labor intensive and impractical for most samples were divided into two groups; 109 for the applications in research and management, generally development of the new PTFs and 38 for cumbersome, expensive and time consuming, especially comparing the reliability of the tested PTFs for relatively large-scale problems.
    [Show full text]
  • Pedotransfer Functions Related to Spatial Variability of Water Retention
    PEDOTRANSFER FUNCTIONS RELATED TO SPATIAL VARIABILITY OF WATER RETENTION... 669 PEDOTRANSFER FUNCTIONS RELATED TO SPATIAL VARIABILITY OF WATER RETENTION ATTRIBUTES FOR LOWLAND SOILS(1) Álvaro Luiz Carvalho Nebel(2), Luís Carlos Timm(3), Wim Cornelis(4), Donald Gabriels(4), Klaus Reichardt(5), Leandro Sanzi Aquino(6), Eloy Antonio Pauletto(7) & Dalvan José Reinert(8) SUMMARY The estimation of non available soil variables through the knowledge of other related measured variables can be achieved through pedotransfer functions (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 Ug1,500 kPa. The PTFs were ranked according to their performance and also with respect to their potential in describing the structure of the spatial variability of the set of measured values. Although none of the PTFs have changed the distribution pattern of the data, all resulted in mean and variance statistically (1) Part of the PhD thesis of the first author presented to the Agronomy Degree Program, Federal University of Pelotas - UFPel. Received for publication in Juny 2009 and accepted in March 2010.
    [Show full text]