Marcel G Schaap
 Professor, Environmental Physics
 Associate Professor, Hydrology / Atmospheric Sciences
Contact
 (520) 6264532
 Shantz, Rm. 429
 Tucson, AZ 85721
 mschaap@cals.arizona.edu
Degrees
 Ph.D. Environmental Science
 University of Amsterdam, Amsterdam, Netherlands
 The Role of Organic Matter in Forest Hydrology
Work Experience
 University of Arizona, Tucson, Arizona (2006  2020)
 UCRiverside (2000  2006)
 George E. Brown, Jr. Salinity Laboratory (USDAARS) (1996  2006)
 UCRiverside (1996  2000)
Awards
 2011 Award for Excellence, presented to Marcel G. Schaap of University of Arizona and member of the Technical Committee W2188
 Awarded on July 13, 2011 by Western Association of Agricultural Experiment Station Directors., Spring 2011
Interests
Research
Soil, Aquifer and Vadose zone flow and transport, porescale fluid dynamics
Teaching
Environmental Physics, Fluids in porous media
Courses
202021 Courses

Environmental Physics
ENVS 420 (Fall 2020) 
Environmental Physics
ENVS 520 (Fall 2020) 
Independent Study
ENVS 499 (Fall 2020) 
Master's Report
ENVS 909 (Fall 2020)
201920 Courses

Environmental Physics
ENVS 420 (Spring 2020) 
Environmental Physics
ENVS 520 (Spring 2020) 
Graduate Workshop
ENVS 697 (Spring 2020) 
Independent Study
ENVS 599 (Spring 2020) 
Environmental Physics
ENVS 420 (Fall 2019) 
Environmental Physics
ENVS 520 (Fall 2019)
201819 Courses

Colloquium
ENVS 595 (Spring 2019) 
Environmental Physics
ENVS 420 (Spring 2019) 
Environmental Physics
ENVS 520 (Spring 2019) 
Graduate Workshop
ENVS 697 (Spring 2019) 
Internship
ENVS 393 (Spring 2019) 
Colloquium
ENVS 595 (Fall 2018) 
Dissertation
ENVS 920 (Fall 2018) 
Environmental Physics
ENVS 420 (Fall 2018) 
Environmental Physics
ENVS 520 (Fall 2018)
201718 Courses

Colloquium
ENVS 595 (Spring 2018) 
Dissertation
ENVS 920 (Spring 2018) 
Environmental Physics
ENVS 420 (Spring 2018) 
Environmental Physics
ENVS 520 (Spring 2018) 
Graduate Workshop
ENVS 697 (Spring 2018) 
Colloquium
ENVS 595 (Fall 2017) 
Dissertation
ENVS 920 (Fall 2017) 
Environmental Physics
ENVS 420 (Fall 2017) 
Environmental Physics
ENVS 520 (Fall 2017) 
Independent Study
ENVS 499 (Fall 2017)
201617 Courses

Colloquium
ENVS 595 (Spring 2017) 
Dissertation
ENVS 920 (Spring 2017) 
Environmental Physics
ENVS 420 (Spring 2017) 
Environmental Physics
ENVS 520 (Spring 2017) 
Independent Study
ENVS 699 (Spring 2017) 
Research
ENVS 900 (Spring 2017) 
Soils, Water + Envir Sci
ENVS 696A (Spring 2017) 
Colloquium
ENVS 595 (Fall 2016) 
Dissertation
ENVS 920 (Fall 2016) 
Environmental Physics
ENVS 420 (Fall 2016) 
Environmental Physics
ENVS 520 (Fall 2016)
201516 Courses

Dissertation
ENVS 920 (Spring 2016) 
Environmental Physics
ENVS 420 (Spring 2016) 
Environmental Physics
ENVS 520 (Spring 2016) 
Soils, Water + Envir Sci
ENVS 696A (Spring 2016)
Scholarly Contributions
Chapters
 Volkmann, T. H., Sengupta, A., Pangle, L. A., Dontsova, K. M., BarronGafford, G. A., Harman, C. J., Niu, G., Meredith, L., Abramson, N., Alves Meira Neto, A., Wang, Y., Adams, J. R., Breshears, D. D., Bugaj, A., Chorover, J. D., Cueva, A., DeLong, S. B., Durcik, M., Ferre, P. A., , Huxman, T. E., et al. (2018). Controlled Experiments of Hillslope Coevolution at the Biosphere 2 Landscape Evolution Observatory: Toward Prediction of Coupled Hydrological, Biogeochemical, and Ecological Changes. In Hydrology of Artificial and Controlled Experiments. Rijeka, Croatia: IN TECH d.o.o.
 Guadagnini, A., Neumann, S. P., Schaap, M. G., & Riva, M. (2015). 2. Alternative to Multifractal Analysis of Scalable Random Variables Applied to Measured and Estimated Soil Properties at an Arizona Field Site. In SIMULATION AND MODELING METHODOLOGIES, TECHNOLOGIES AND APPLICATIONS (SIMULTECH) Book Series: Advances in Intelligent Systems and Computing(pp 133134).
 Schaap, M. G. (2013). Description, Analysis, and Interpretation of an Infiltration Experiment in a Semiarid Deep Vadose Zone. In Advances in Hydrogeology(p. 26). New York: Springer Science+Business Media.
Journals/Publications
 , Y. Z., , M. G., & , Z. W. (2020). Hierarchical Multimodel Ensemble Estimates of Soil Water Retention with Global Coverage.More infoA correct quantification of mass and energy exchange processes among landsurface and atmosphere requires an accurate description of unsaturated soilhydraulic properties. Soil pedotransfer functions (PTFs) have been widely usedto predict soil hydraulic parameters. Here, 13 PTFs were grouped according toinput data requirements and evaluated against a welldocumented soil databasewith global coverage. Weighted ensembles (calibrated by four groups and thefull 13member set of PTFs) were shown to have improved performance overindividual PTFs in terms of root mean square error and other model selectioncriteria. Global maps of soil water retention data from the ensemble models aswell as their uncertainty were provided. These maps demonstrate that five PTFensembles tend to have different estimates, especially in middle and highlatitudes in the Northern Hemisphere. Our full 13member ensemble modelprovides more accurate estimates than PTFs that are currently being used inearth system models.[Journal_ref: ]
 Zhang, Y., & Schaap, M. G. (2019). Estimation of saturated hydraulic conductivity with pedotransfer functions: A review. JOURNAL OF HYDROLOGY, 575, 10111030.
 Zhang, Y., Schaap, M. G., & Zhangwang, W. (2019). Hierarchical Multimodel Ensemble Estimates of Soil Water Retention with Global Coverage. arXiv:1906.03182. doi:arXiv:1906.03182
 Ottoni, M. V., Ottoni, F., Schaap, M. G., LopesAssad, M., & Rotunno, F. (2018). Hydrophysical Database for Brazilian Soils (HYBRAS) and Pedotransfer Functions for Water Retention. VADOSE ZONE JOURNAL, 17(1).
 Shepard, C., Pelletier, J. D., Schaap, M. G., & Rasmussen, C. (2018). Signatures of Obliquity and Eccentricity in Soil Chronosequences. GEOPHYSICAL RESEARCH LETTERS, 45(20), 1114711153.
 Shepard, C., Schaap, M. G., Chorover, J., & Rasmussen, C. (2018). Understanding Critical Zone Evolution through Predicting the ThreeDimensional Soil Chemical Properties of a Small Forested Catchment. SOIL SCIENCE SOCIETY OF AMERICA JOURNAL, 82(6), 15381550.
 Zhang, Y., Schaap, M. G., & Zha, Y. (2018). A HighResolution Global Map of Soil Hydraulic Properties Produced by a Hierarchical Parameterization of a Physically Based Water Retention Model. WATER RESOURCES RESEARCH, 54(12), 97749790.
 Shepard, C., Schaap, M. G., Pelletier, J. D., & Rasmussen, C. (2017). A probabilistic approach to quantifying soil physical properties via timeintegrated energy and mass input. SOIL, 3(1), 6782.
 Van, L. K., Bouma, J., Herbst, M., Koestel, J., Minasny, B., Mishra, U., Montzka, C., Nemes, A., Pachepsky, Y. A., Padarian, J., Schaap, M. G., Toth, B., Verhoef, A., Vanderborght, J., van, d., Weihermueller, L., Zacharias, S., Zhang, Y., & Vereecken, H. (2017). Pedotransfer Functions in Earth System Science: Challenges and Perspectives. REVIEWS OF GEOPHYSICS, 55(4), 11991256.
 Xu, C., Zeng, W., Zhang, H., Huang, J., Zhang, Y., Wu, J., & Schaap, M. G. (2017). Inversion of Root Zone Soil Hydraulic Parameters with Limited Calibration Data. SOIL SCIENCE SOCIETY OF AMERICA JOURNAL, 81(4), 734746.
 Zhang, Y., & Schaap, M. G. (2017). Weighted recalibration of the Rosetta pedotransfer model with improved estimates of hydraulic parameter distributions and summary statistics (Rosetta3). JOURNAL OF HYDROLOGY, 547, 3953.
 da, S., Armindo, R. A., Brito, A., & Schaap, M. G. (2017). An Assessment of Pedotransfer Function Performance for the Estimation of Spatial Variability of Key soil Hydraulic Properties. VADOSE ZONE JOURNAL, 16(9).
 da, S., Armindo, R. A., Brito, A., & Schaap, M. G. (2017). SPLINTEX: A physicallybased pedotransfer function for modeling soil hydraulic functions. SOIL & TILLAGE RESEARCH, 174, 261272.
 Naveed, M., Moldrup, P., Schaap, M. G., Tuller, M., Kulkarni, R., Vogel, H., & de Jonge, L. W. (2016). Prediction of biopore and matrixdominated flow from Xray CTderived macropore network characteristics. Hydrol. Earth Syst. Sci., 20, 40174030. doi:10.5194/hess2040172016
 Naveed, M., Moldrup, P., Schaap, M. G., Tuller, M., Kulkarni, R., Vogel, H., & de, J. (2016). Prediction of biopore and matrixdominated flow from Xray CTderived macropore network characteristics. HYDROLOGY AND EARTH SYSTEM SCIENCES, 20(10), 40174030.
 Zhang, Y., Schaap, M. G., Guadagnini, A., & Neuman, S. P. (2016). Inverse modeling of unsaturated flow using clusters of soil texture and pedotransfer functions. WATER RESOURCES RESEARCH, 52(10), 76317644.
 Guadagnini, A., Neuman, S. P., Schaap, M. G., & Riva, M. (2015). Alternative to Multifractal Analysis of Scalable Random Variables Applied to Measured and Estimated Soil Properties at an Arizona Field Site. SIMULATION AND MODELING METHODOLOGIES, TECHNOLOGIES AND APPLICATIONS (SIMULTECH), 319, 133143.
 Levi, M. R., Schaap, M. G., & Rasmussen, C. (2015). Application of Spatial Pedotransfer Functions to Understand Soil Modulation of Vegetation Response to Climate. VADOSE ZONE JOURNAL, 14(9).
 Levi, M. R., Schaap, M. G., & Rasmussen, C. (2015). Application of Spatial Pedotransfer Functions to Understand Soil Modulation of Vegetation Response to Climate. Vadose Zone Journal, 14(9).
 Pangle, L. A., DeLong, S. B., Abramson, N., Adams, J., BarronGafford, G. A., Breshears, D. D., Brooks, P. D., Chorover, J., Dietrich, W. E., Dontsova, K., Durcik, M., Espeleta, J., Ferre, T., Ferriere, R., Henderson, W., Hunt, E. A., Huxman, T. E., Millar, D., Murphy, B., , Niu, G., et al. (2015). The Landscape Evolution Observatory: A largescale controllable infrastructure to study coupled Earthsurface processes. GEOMORPHOLOGY, 244, 190203.
 Pangle, L. A., Pangle, L. A., Delong, S. B., Delong, S. B., Abramson, N., Abramson, N., Adams, J., Adams, J., BarronGafford, G. A., BarronGafford, G. A., Breshears, D. D., Breshears, D. D., Brooks, P. D., Brooks, P. D., Chorover, J. D., Chorover, J. D., Dietrich, W. E., Dietrich, W. E., Dontsova, K. M., , Dontsova, K. M., et al. (2015). The Landscape Evolution Observatory: A largescale controllable infrastructure to study Earthsurface processes.. Geomorphology, 244, 190203.
 Pangle, L., DeLong, S., Abramson, N., Adams, J., BarronGafford, G. A., Breshears, D. D., Brooks, P. D., Chorover, J. D., Dietrich, W. E., Dontsova, K. M., Durcik, M., Espeleta, J., Ferre, P. A., Ferriere, R. H., Henderson, W., Hunt, E., Huxman, T. E., Millar, D., Murphy, B., , Niu, Y., et al. (2015). The Landscape Evolution Observatory: A largescale controllable infrastructure to study coupled Earthsurface processes. Geomorphology.
 VazquezOrtega, A., Perdrial, J., Harpold, A., ZapataRios, X., Rasmussen, C., McIntosh, J., Schaap, M. G., Pelletier, J. D., Brooks, P. D., Amistadi, M. K., & Chorover, J. D. (2015). Rare earth elements as reactive tracers of biogeochemical weathering in forested rhyolitic terrain. Chem. Geol., 391, 1932.
 VazquezOrtega, A., Perdrial, J., Harpold, A., ZapataRios, X., Rasmussen, C., McIntosh, J., Schaap, M., Pelletier, J. D., Brooks, P. D., Amistadi, M. K., & Chorover, J. (2015). Rare earth elements as reactive tracers of biogeochemical weathering in forested rhyolitic terrain. CHEMICAL GEOLOGY, 391, 1932.
 Chorover, J. D., VazquezOrtega, A., Perdrial, J., Harpold, A., ZapataRios, X., McIntosh, J., Rasmussen, C., Schaap, M. G., Pelletier, J. D., Brooks, P. D., & Amistadi, M. K. (2014). Rare earth elements as reactive tracers of biogeochemical weathering in forested rhyolitic terrain. Chem. Geol., 391, 1932.
 Guadagnini, A., Neuman, S. P., Schaap, M. G., & Riva, M. (2014). Frequency Distributions and Scaling of Soil Texture and Hydraulic Properties in a Stratified Deep Vadose Zone Near Maricopa, Arizona. MATHEMATICS OF PLANET EARTH, 189192.
 Pelletier, J. D., Pelletier, J. D., Pelletier, J. D., Breshears, D. D., Breshears, D. D., Breshears, D. D., BarronGafford, G. A., BarronGafford, G. A., BarronGafford, G. A., Brooks, P. D., Brooks, P. D., Brooks, P. D., Chorover, J. D., Chorover, J., Chorover, J. D., Durick, M., Durick, M., Durick, M., Harman, C. J., , Harman, C. J., et al. (2013). Coevolution of nonlinear trends in vegetation, soils, and topography with elevation and slope aspect: A case study in the sky islands of southern Arizona. Journal of Geophysical Research  Earth Surface, 118(2), 118.More infoFeedbacks among vegetation dynamics, pedogenesis, and topographic development affect the “critical zone”—the living filter for Earth's hydrologic, biogeochemical, and rock/sediment cycles. Assessing the importance of such feedbacks, which may be particularly pronounced in waterlimited systems, remains a fundamental interdisciplinary challenge. The sky islands of southern Arizona offer an unusually welldefined natural experiment involving such feedbacks because mean annual precipitation varies by a factor of five over distances of approximately 10 km in areas of similar rock type (granite) and tectonic history. Here we compile highresolution, spatially distributed data for Effective Energy and Mass Transfer (EEMT: the energy available to drive bedrock weathering), aboveground biomass, soil thickness, hillslopescale topographic relief, and drainage density in two such mountain ranges (Santa Catalina: SCM; Pinaleño: PM). Strong correlations exist among vegetationsoiltopography variables, which vary nonlinearly with elevation, such that warm, dry, lowelevation portions of these ranges are characterized by relatively low aboveground biomass, thin soils, minimal soil organic matter, steep slopes, and high drainage densities; conversely, cooler, wetter, higher elevations have systematically higher biomass, thicker organicrich soils, gentler slopes, and lower drainage densities. To test if ecopedogeomorphic feedbacks drive this pattern, we developed a landscape evolution model that couples pedogenesis and topographic development over geologic time scales, with rates explicitly dependent on vegetation density. The model selforganizes into states similar to those observed in SCM and PM. Our results highlight the potential importance of ecopedogeomorphic feedbacks, mediated by soil thickness, in waterlimited systems.
 Schaap, M. G., Guadagnini, A., Neuman, S. P., & Riva, M. (2013). Anisotropic statistical scaling of vadose zone hydraulic property estimates near Maricopa, Arizona.. Water Resources Research, 49(12), 84638479.
 Chorover, J., Troch, P. A., Rasmussen, C., Brooks, P. D., Pelletier, J. D., Breshears, D. D., Huxman, T. E., Kurc, S. A., Lohse, K. A., McIntosh, J. C., Meixner, T., Schaap, M. G., Litvak, M. E., Perdrial, J., Harpold, A., & Durcik, M. (2011). How Water, Carbon, and Energy Drive Critical Zone Evolution: The JemezSanta Catalina Critical Zone Observatory. VADOSE ZONE JOURNAL, 10(3), 884899.
 Chorover, J., Troch, P. A., Rasmussen, C., Brooks, P. D., Pelletier, J. D., Breshears, D. D., Huxman, T. E., Kurc, S. A., Lohse, K., Mcintosh, J. C., Meixner, T., Schaap, M. G., Litvak, M., Perdrial, J., Harpold, A., & Durcik, M. (2011). How water, carbon, and energy drive critical zone evolution: the JemezSanta Catalina Critical Zone Observatory. Vadose Zone Journal, 10, 884899.
 Jacobsen, S. M., Schaap, M., Walker, J., Weber, R., & Willey, P. (2011). Soil data preparation for determination of drainage lateral effect using rosetta software. American Society of Agricultural and Biological Engineers Annual International Meeting 2011, 6, 50585068.More infoAbstract: Analysis of surface and subsurface drainage lateral effects is performed for a number of purposes, including compliance with the 1985 Farm Bill and analysis of wetland restoration alternatives. Lateral effects analysis conducted by NRCS is used in cases where wetland hydrology is maintained by high water tables, and potentially removed by installation of buried drains or surface ditches. The analysis assumes that water content can be determined by soil moisture characteristics computed by van Genuchten Equations, and the rate of water movement is determined by soil saturated hydraulic conductivity. With these parameters, standard lateral effect equations can be used to determine horizontal distance of lateral effect of a drainage system installation or modification. The direct measurement of necessary parameters is difficult and expensive. However, the Rosetta computer software utilizes a large number of test results for drainable porosity and saturated hydraulic conductivity that have been correlated with readily available parameters in the NRCS soils database, including texture, bulk density, moisture content, and organic matter content at 33 and 1500 kPa of plant tension. Soil data available from the NRCS Soil Data Access website is downloaded, formatted, and processed through the Rosetta program, which produces a file suitable for use in lateral effects software.
 Schaap, M. G., Chorover, J. ., & TrochP, . (2011). How Water, Carbon, and Energy Drive Critical Zone Evolution: The JemezSanta Catalina Critical Zone Observatory. VADOSE ZONE JOURNAL, 10(3), 884899.More infoDOI: 10.2136/vzj2010.0132
 Guadagnini, A., Neuman, S. P., Schaap, M. G., & Riva, M. (2010). Anisotropic statistical scaling of vadose zone hydraulic property estimates near Maricopa, Arizona. WATER RESOURCES RESEARCH, 49(12), 84638479.More infoFluid flow and mass transport in the vadose zone are strongly influenced by spatial variability in soil hydraulic properties. It has become common to characterize spatial variability geostatistically and to solve corresponding flow and/or transport problems stochastically. The typical (though not only) approach is to treat log saturated hydraulic conductivity, Y=log(10)K(s), and perhaps other medium properties as statistically homogeneous, isotropic, or anisotropic multivariateGaussian random fields with unique variance and autocorrelation scale. A growing body of literature suggests that Y as well as many other variables may possess heavytailed, nonGaussian distributions, and/or scaledependent statistical parameters representing a multiscale, hierarchical structure. Elsewhere, we have demonstrated that these important phenomena are difficult to detect, and are not fully tractable, with standard geostatistical methods. They are however detectable and tractable with a novel geostatistical method of analysis which treats such variables as samples from subGaussian random fields subordinated to truncated fractional Brownian motion (tfBm) or truncated fractional Gaussian noise (tfGn). Each such field is a mixture of Gaussian components having random variances. The purpose of this paper is to explore the extent to which hydraulic parameters of unsaturated soils exhibit heavytailed distributions and statistical scaling of the above type. As a test bed we have selected an experimental site near Maricopa, Arizona, at which soil texture data have been collected in boreholes and trenches to a depth of 15 m over an area of 3600 m(2). Since hydraulic parameters are difficult to measure to such depths we estimate them using a neural network pedotransfer model. Input data include percent sand, silt, and clay. Outputs include estimates of saturated and residual volumetric water content, saturated hydraulic conductivity, and (due to their wide applicability) parameters of the van GenuchtenMualem constitutive model of unsaturated soil property variations with capillary pressure head. We find indeed that vertical and horizontal increments of our hydraulic parameter estimates exhibit heavytailed frequency distributions and statistical scaling which conform closely to our novel geostatistical framework. Its generality and applicability to the Maricopa site has far reaching implications visavis the geostatistical characterization of vadose zone properties and the stochastic modeling of flow and transport in unsaturated media at other sites.
 K., N., Šimůnek, J., & Schaap, M. G. (2010). Can texturebased classification optimally classify soils with respect to soil hydraulics?. Water Resources Research, 46(1).More infoAbstract: In the past, texturebased classification of soils has been used for grouping soils in variably saturated water flow and solute transport studies. Classification of soils becomes especially important for largescale studies where the spatial and temporal variability in the hydraulic properties of soils exceeds the field sampling capabilities. Although soiltexturebased classification has been widely used, questions remain about the validity of its use from a hydraulic perspective. In this study, we attempt to answer the following questions: (1) what is the optimal number of (soil hydraulic) classes that can adequately classify the soils from a hydraulic standpoint, and (2) how does such a classification compare to the soil texture classification currently used? To investigate these questions, the commonly used κmeans clustering algorithm was integrated with the ROSETTA pedotransfer functions to predict the socalled soil hydraulic classes. The optimal soil hydraulic classifications and the associated uncertainty were estimated for numbers of soil hydraulic classes varying from 2 to 30. It was concluded that the optimal number of soil hydraulic classes is 12. The optimal soil hydraulic classes were represented in a ternary diagram called the soil hydraulic triangle. While there exist some surprising similarities in classification between the soil texture triangle and the soil hydraulic triangle for soils with high sand percentages (sand >60%), the opposite is true for soils with low sand contents. From a hydraulic standpoint, the texturebased classification does not classify soils well when there is a considerable impact of capillary forces. The soil texture and hydraulic classes were analyzed for accuracy using two databases. Compared to the soil texture classes, it was found that the soil hydraulic classes marginally improve the accuracy of classification. Even though the improvement is only marginal, it was observed that the optimality of soil texture triangle for hydraulic studies cannot be assured because of the nonuniform distribution of data across various textural possibilities in the two databases. As an extension of this research, we have also estimated the average soil hydraulic parameters for the different optimal soil hydraulic classes. Copyright 2010 by the American Geophysical Union.
 Schaap, M. G., & Tuller, M. (2010). Quantitative PoreScale Investigations of Multiphase Bio/Geo/Chemical Processes. VADOSE ZONE JOURNAL, 9(3), 573575.
 Schaap, M. G., & Tuller, M. (2010). Quantitative porescale investigations of multiphase Bio/Geo/Chemical processes. Vadose Zone Journal, 9(3), 573575.
 Vereecken, H., Javaux, M., Weynants, M., Pachepsky, Y., Schaap, M. G., & Genuchten, V. (2010). Using pedotransfer functions to estimate the van genuchten mualem soil hydraulic properties: A review. Vadose Zone Journal, 9(4), 795820.More infoAbstract: We reviewed the use of the van GenuchtenMualem (VGM) model to parameterize soil hydraulic properties and for developing pedotransfer functions (PTFs). Analysis of literature data showed that the moisture retention characteristic (MRC) parameterization by setting shape parameters m = 1 ; 1/n produced the largest deviations between fitted and measured water contents for pressure head values between 330 (log 10 pressure head [pF] 2.5) and 2500 cm (pF 3.4). The Schaapvan Genuchten model performed best in describing the unsaturated hydraulic conductivity, K. The classical VGM model using fixed parameters produced increasingly higher root mean squared residual, RMSR, values when the soil became drier. The most accurate PTFs for estimating the MRC were obtained when using textural properties, bulk density, soil organic matter, and soil moisture content. The RMSR values for these PTFs approached those of the direct fit, thus suggesting a need to improve both PTFs and the MRC parameterization. Inclusion of the soil water content in the PTFs for K only marginally improved their prediction compared with the PTFs that used only textural properties and bulk density. Including soil organic matter to predict K had more effect on the prediction than including soil moisture. To advance the development of PTFs, we advocate the establishment of databases of soil hydraulic properties that (i) are derived from standardized and harmonized measurement procedures, (ii) contain new predictors such as soil structural properties, and (iii) allow the development of timedependent PTFs. Successful use of structural properties in PTFs will require parameterizations that account for the effect of structural properties on the soil hydraulic functions. © Soil Science Society of America.
 Deng, H., Ming, Y. e., Schaap, M. G., & Khaleel, R. (2009). Quantification of uncertainty in pedotransfer functionbased parameter estimation for unsaturated flow modeling. Water Resources Research, 45(4).More infoAbstract: While pedotransfer functions (PTFs) have long been applied to estimate soil hydraulic parameters for unsaturated flow and solute transport modeling, the uncertainty associated with the estimates is often ignored. The objective of this study is to evaluate uncertainty of the PTFestimated soil hydraulic parameters and its effect on numerical simulation of moisture flow. Contributing to the parameter estimation uncertainty are (1) the PTF intrinsic uncertainty caused by limited data used for PTF training and (2) the PTF input uncertainty in pedotransfer variables (i.e., PTF inputs). The PTF intrinsic uncertainty is assessed using the bootstrap method by generating multiple bootstrap realizations of the soil hydraulic parameters; the realizations follow normal or lognormal distributions. The PTF input variables (i.e., bulk density and soil texture) are obtained using the cokriging technique. The PTF input uncertainty is quantified by assuming that the cokriging estimates follow a normal distribution. Our results show that the PTF input uncertainty dominates over the PTF intrinsic uncertainty and determines the spatial distribution of the PTF parameter estimation uncertainty. When the parameter estimation uncertainty is included, the spatial variability of the measured soil hydraulic parameters is better captured. This is also the case for the observed moisture contents, whose spatial variability is well bracketed by the prediction intervals. However, this is only possible after the PTF input uncertainty is considered. These results suggest that additional sample acquisition for the PTF input variables would have a more favorable impact on reduction of the parameter estimation uncertainty than collecting additional soil hydraulic parameter measurements for PTF development. Copyright 2009 by the American Geophysical Union.
 Deng, H., Ye, M., Schaap, M. G., & Khaleel, R. (2009). Quantification of uncertainty in pedotransfer functionbased parameter estimation for unsaturated flow modeling. WATER RESOURCES RESEARCH, 45.
 Kelleners, T. J., FerrePikal, E., Schaap, M. G., & Paige, G. B. (2009). Calibration of hydra impedance probes using electric circuit theory. Soil Science Society of America Journal, 73(2), 453465.More infoAbstract: Impedance probes are an attractive electromagnetic technique to measure water content and bulk electrical conductivity (EC) in the same volume of soil. In this study, we developed an electric circuit model for Hydra probes that explains how the output voltages can be related to the soil real and imaginary permittivity. Internal probe transmission line sections were modeled using either a distributed approach or a lumped approach. The distributed approach resulted in seven circuit model parameters, while the lumped approach resulted in six parameters. Optimization of all the parameters using probe readings in air, ethanol, methanol, deionized water, and saline water solutions did not result in physically realistic parameter values. In contrast, fixing four parameters (distributed approach) and two parameters (lumped approach), while optimizing others, did yield realistic parameter values. Both the parameter optimization method and the default probe algorithm performed well during model verification. The parameter optimization method resulted in improved real permittivity measurements when nonsaline fluids at different temperatures were used in the optimization process. © Soil Science Society of America.
 Porter, M. L., Schaap, M. G., & Wildenschild, D. (2009). LatticeBoltzmann simulations of the capillary pressuresaturationinterfacial area relationship for porous media. ADVANCES IN WATER RESOURCES, 32(11), 16321640.
 Porter, M. L., Schaap, M. G., & Wildenschild, D. (2009). LatticeBoltzmann simulations of the capillary pressuresaturationinterfacial area relationship for porous media. Advances in Water Resources, 32(11), 16321640.More infoAbstract: Hysteresis in the relationship between capillary pressure (Pc), wetting phase saturation (Sw) and nonwettingwetting interfacial area per volume (anw) is investigated using multiphase latticeBoltzmann simulations of drainage and imbibition in a glass bead porous system. In order to validate the simulations, the Pc s() Sw and anw s() Sw main hysteresis loops were compared to experimental data reported by Culligan et al. [Culligan KA, Wildenschild D, Christensen BS, Gray WG, Rivers ML, Tompson AB. Interfacial area measurements for unsaturated flow through porous media. Water Resour Res 2004;40:W12413]. In general, the comparison shows that the simulations are reliable and capture the important physical processes in the experimental system. Pc s() Sw curves, anw s() Sw curves and phase distributions (within the pores) show good agreement during drainage, but less satisfactory agreement during imbibition. Drainage and imbibition scanning curves were simulated in order to construct Pc s() Sw s() anw surfaces. The root mean squared error (RMSE) and mean absolute error (MAE) between drainage and imbibition surfaces was 0.10 mm1 and 0.03 mm1, respectively. This small difference indicates that hysteresis is virtually nonexistent in the Pc s() Sw s() anw relationship for the multiphase system studied here. Additionally, a surface was fit to the main loop (excluding scanning curves) of the drainage and imbibition Pc s() Sw s() anw data and compared to the surface fit to all of the data. The differences between these two surfaces were small (RMSE = 0.05 mm1 and MAE = 0.01 mm1) indicating that the Pc s() Sw s() anw surface is adequately represented without the need for the scanning curve data, which greatly reduces the amount of data required to construct the nonhysteretic Pc s() Sw s() anw surface for this data. © 2009 Elsevier Ltd. All rights reserved.
 Twarakavi, N. K., Šimůnek, J., & Schaap, M. G. (2009). Development of pedotransfer functions for estimation of soil hydraulic parameters using support vector machines. Soil Science Society of America Journal, 73(5), 14431452.More infoAbstract: A number of hydrological models used to simulate situations ranging from fieldscale water flow to global climate change rely on numerical techniques that simulate heat, water, and solute fluxes in the vadose zone. The use of flow models for variably saturated conditions requires accurate estimates of the hydraulic characteristics that govern water retention and water flow in soils (Wosten et al., 2001). The hydraulic characteristics of soils vary spatially from one location to another, and are also scaledependent (Hopmans et al., 2002). The temporal variability can also occur as a result of various biological and human activities, such as rootgrowth, soil management and agricultural practices, or Modeling flow in variably saturated porous media requires reliable estimates of the hydraulic parameters describing the soil water retention and hydraulic conductivity. These soil hydraulic properties can be measured using a wide variety of laboratory and field methods. Frequently, this proves to be an arduous task because of the high spatial and temporal variability of soil properties. In the last decade, researchers have shown a keen interest in developing a class of indirect approaches, called pedotransfer functions (PTFs), to overcome this problem. Pedotransfer functions predict soil hydraulic parameters using easily obtainable soil properties such as textural information, bulk density and/or few retention points. In this paper, we use a new methodology called Support Vector Machines (SVMs) to derive a new set of PTFs. Support vector machines represent a pattern recognition approach where the overall prediction error and complexity of the SVM structure are minimized simultaneously. We used the same database that was utilized to develop ROSETTA to generate the SVMbased PTFs. The performance of the SVMbased PTFs was analyzed using the coefficient of determination, root mean square error (RMSE) and mean error (ME). All soil hydraulic parameters estimated using the SVMbased PTFs showed improved confidence in the estimates when compared with the ROSETTA PTF program. Estimates of water contents and saturated hydraulic conductivities using the hydraulic parameters predicted by the SVMbased PTFs mostly improved compared with those obtained using the artificial neural network (ANN)based ROSETTA. The RMSE for water contents decreased from 0.062 to 0.034 as more predictors were used, while the RMSE for the saturated hydraulic conductivity decreased from 0.716 to 0.552 (dimensionless logĻ0 units). Similarly, the bias in the water contents estimated using the SVMbased PTF was reduced significantly compared with ROSETTA. © Soil Science Society of America.
 Wang, T., Zlotnik, V. A., Simunek, J., & Schaap, M. G. (2009). Using pedotransfer functions in vadose zone models for estimating groundwater recharge in semiarid regions. WATER RESOURCES RESEARCH, 45.
 Wang, T., Zlotnik, V. A., Šimunek, J., & Schaap, M. G. (2009). Using pedotransfer functions in vadose zone models for estimating groundwater recharge in semiarid regions. Water Resources Research, 45(4).More infoAbstract: Processbased vadose zone models are becoming common tools for evaluating spatial distributions of groundwater recharge (GR), but their applications are restricted by complicated parameterizations, especially because of the need for highly nonlinear and spatially variable soil hydraulic characteristics (SHCs). In an attempt to address the scarcity of field SHC data, pedotransfer functions (PTF) were introduced in earlier attempts to estimate SHCs. However, the accuracy of this method is rarely questioned in spite of significant uncertainties of PTFestimated SHCs. In this study, we investigated the applicability of coupling vadose zone models and PTFs for evaluating GR in sand and loamy sand soils in a semiarid region and also their sensitivity to lower boundary conditions. First, a data set containing measured SHCs was used in the simulations. A second data set contained correlated SHCs drawn from the covariance matrix of the first data set. The third SHC data set used was derived from a widely used PTF. Although standard deviations for individual parameters were known for this PTF, no covariance matrix was available. Hence, we assumed that the parameters of this PTF were uncorrelated, thereby potentially overestimating the volume of the parameter space. Results were summarized using histograms of GR for various sets of input parameters. Under the unit gradient flow lower boundary condition, the distributions of GR for sand and loamy sand significantly overlap. Values of GR based on mean SHCs (or GR*) generally lie off the mode of the GR distribution. This indicates that the routinely used method of taking GR* as a regional representation may not be viable. More importantly, the computed GR largely depends in a nonlinear fashion on the shape factor n in the van Genuchten model. Under the same meteorological conditions, a coarser soil with a larger n generally produces a higher GR. Therefore, the uncertainty in computed GR is largely determined by the uncertainty in estimated n by PTFs (e.g., mean and standard deviation). Under the constant head lower boundary condition, upward soil moisture flux may exist from the lower boundary. Especially for regions with shallow water tables where upward flux exists, choosing an appropriate lower boundary condition is more important than selecting SHC values for calculating GR. The results show that the distribution of GR is less scattered and GR is more intense if the constant head lower boundary is located at deeper depths. Copyright 2009 by the American Geophysical Union.
 Borgesen, C. D., Iversen, B. V., Jacobsen, O. H., & Schaap, M. G. (2008). Pedotransfer functions estimating soil hydraulic properties using different soil parameters. HYDROLOGICAL PROCESSES, 22(11), 16301639.
 Børgesen, C. D., Iversen, B. V., Jacobsen, O. H., & Schaap, M. G. (2008). Pedotransfer functions estimating soil hydraulic properties using different soil parameters. Hydrological Processes, 22(11), 16301639.More infoAbstract: Estimates 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.
 Toth, T., Schaap, M. G., & Molnar, Z. (2008). UTILIZATION OF SOILPLANT INTERRELATIONS THROUGH THE USE OF MULTIPLE REGRESSION AND ARTIFICIAL NEURAL NETWORK IN ORDER TO PREDICT SOIL PROPERTIES IN HUNGARIAN SOLONETZIC GRASSLANDS. CEREAL RESEARCH COMMUNICATIONS, 36, 14471450.
 Tóth, T., Schaap, M. G., & Molnár, Z. (2008). Utilization of soilplant interrelations through the use of multiple regression and artificial neural network in order to predict soil properties in Hungarian solonetzic grasslands. Cereal Research Communications, 36(SUPPL. 5), 14471450.More infoAbstract: Soil and plant interrelations are strong enough in seminatural solonetzic grasslands to permit the use of plant cover as predictor variable for soil salinity, sodicity and alkalinity. Four data sets were analysed which covered 47 plant association types, with sample sizes ranging from 20 to 120 and quadrat sizes 0.16 to 20 m2; and correlation coefficients (R) of the multiple regression equations established between plant cover (independent or predictor variables) and soil (dependent or predicted variables) usually ranged from 0.65 to 0.80. Utilization of neural networks improved the prediction further and provided typically R values of 0.8. Plant cover observations consequently can be used to improve the precision of numerical maps of soil properties on solonetz soils and to delineate risk areas more precisely faster at a lower cost.
 Huang, H., Thorne Jr., D. T., Schaap, M. G., & Sukop, M. C. (2007). Proposed approximation for contact angles in ShanandChentype multicomponent multiphase lattice Boltzmann models. PHYSICAL REVIEW E, 76(6).
 Huang, H., Thorne, D. T., Schaap, M. G., & Sukop, M. C. (2007). Proposed approximation for contact angles in ShanandChentype multicomponent multiphase lattice Boltzmann models. Physical Review E  Statistical, Nonlinear, and Soft Matter Physics, 76(6).More infoAbstract: We propose a method for approximating the adhesion parameters in the Shan and Chen multicomponent, multiphase lattice Boltzmann model that leads to the desired fluidsolid contact angle. The method is a straightforward application of Young's equation with substitution of the Shan and Chen cohesion parameter and a density factor for the fluidfluid interfacial tension, and the adhesion parameters for the corresponding fluidsolid interfacial tensions. © 2007 The American Physical Society.
 Ming, Y. e., Khaleel, R., Schaap, M. G., & Zhu, J. (2007). Simulation of field injection experiments in heterogeneous unsaturated media using cokriging and artificial neural network. Water Resources Research, 43(7).More infoAbstract: Simulations of moisture flow in heterogeneous soils are often hampered by lack of measurements of soil hydraulic parameters, making it necessary to rely on other sources of information. In this paper, we develop a methodology to integrate data that can be easily obtained (for example, initial moisture content, θi, bulk density, and soil texture) with data on soil hydraulic properties via cokriging and Artificial Neural Network (ANN)based pedotransfer functions. The method is applied to generate heterogeneous soil hydraulic parameters at a field injection site in southeastern Washington State. Stratigraphy at the site consists of imperfectly stratified layers with irregular layer boundaries. Cokriging is first used to generate threedimensional heterogeneous fields of bulk density and soil texture using an extensive data set of fieldmeasured θi, which carry signature about site heterogeneity and stratigraphy. Soil texture and bulk density are subsequently input into an ANNbased sitespecific pedotransfer function to generate threedimensional heterogeneous soil hydraulic parameter fields. The stratigraphy at the site is well represented by the estimated pedotransfer variables and soil hydraulic parameters. The parameter estimates are then used to simulate a field injection experiment at the site. A relatively good agreement is obtained between the simulated and observed moisture contents. The spatial distribution pattern of observed moisture content as well as the southeastward moisture movement is captured well in the simulations. In contrast to earlier work using an effective parameter approach (Yeh et al., 2005), we are able to reproduce the observed splitting of the moisture plume in a coarse sand unit that is sandwiched between two finetextured units. The simple method of combining cokriging and ANN for site characterization provides unbiased prediction of the observed moisture plume and is flexible so that additional measurements of various types can be included as they become available. Copyright 2007 by the American Geophysical Union.
 Schaap, M. G., Porter, M. L., Christensen, B., & Wildenschild, D. (2007). Comparison of pressuresaturation characteristics derived from computed tomography and lattice Boltzmann simulations. WATER RESOURCES RESEARCH, 43(12).
 Schaap, M. G., Porter, M. L., S., B., & Wildenschild, D. (2007). Comparison of pressuresaturation characteristics derived from computed tomography and lattice Boltzmann simulations. Water Resources Research, 43(12).More infoAbstract: A ShanChentype multiphase lattice Boltzmann (LB) model was applied to observed computed microtomography data from waterair and waterSoltrol displacement experiments in a glass bead porous medium. Analysis of the Bond, Reynolds, and Capillary numbers for these systems showed that capillary forces were dominant removing the need to model viscous, gravitational, and density effects. A numerical parameterization of the LB model yielded lattice surface tension and contact angle, and appropriate pressure boundary conditions. Two scaling relations provided a link between lattice pressure and physical pressure and lattice time and physical time. Results showed that there was a good match between measured and simulated pressuresaturation data for the waterair system, but that there were large differences between the simulations and observations for the waterSoltrol system. The discrepancies for the waterSoltrol system were probably due to inconsistencies between experimental conditions and simulated conditions such as nonzero contact angle in the experiments. Analysis of saturation profiles indicated increasing saturation near the wetting boundary and decreasing saturations near the nonwetting boundary. We attribute these saturation transitions to poreneck and percolation effects. While computationally intensive, results of this study were very encouraging for the application of LB simulations to microscale interfacial phenomena. Future studies will carry out a further validation in terms of interfacial areas, contact lines, and fluid distributions. Copyright 2007 by the American Geophysical Union.
 Ye, M., Khaleel, R., Schaap, M. G., & Zhu, J. (2007). Simulation of field injection experiments in heterogeneous unsaturated media using cokriging and artificial neural network. WATER RESOURCES RESEARCH, 43(7).
 Borgesen, C. D., Jacobsen, O. H., Hansen, S., & Schaap, M. G. (2006). Soil hydraulic properties near saturation, an improved conductivity model. JOURNAL OF HYDROLOGY, 324(14), 4050.
 Buehler, M. G., Bostic, H., Chin, K. B., McCann, T., Keymeulen, D., Anderson, R. C., Seshadri, S., & Schaap, M. G. (2006). Electrical Properties Cup (EPC) for characterizing water content of martian and lunar soils. IEEE Aerospace Conference Proceedings, 2006.More infoAbstract: In this effort we used electrical impedance spectroscopy and a fourprobe apparatus, the Electrical Properties Cup (EPC), to measure the properties of various lunar and martian soil simulants. The impedance values are characterized by a resistancecapacitor network that is used to determine the soil conductivity and dielectric constant. In this effort we measured the impedance of different types of martian soil simulants (Silica sand, Atacama Desert sand, and Moses Lake basalt) and lunar simulants. The results show that the soil impedance measurements are strongly dependent on water content and soil type and to a lesser extent particle size and electrolyte concentration. This presentation describes the experimental fourprobe apparatus, procedures used to prepare the samples including soil washing and loading, and soil impedance measurements. © 2006 IEEE.
 Børgesen, C. D., Jacobsen, O. H., Hansen, S., & Schaap, M. G. (2006). Soil hydraulic properties near saturation, an improved conductivity model. Journal of Hydrology, 324(14), 4050.More infoAbstract: The hydraulic properties near saturation can change dramatically due to the presence of macropores that are usually difficult to handle in traditional pore size models. The purpose of this study is to establish a data set on hydraulic conductivity near saturation, test the predictive capability of commonly used hydraulic conductivity models and give suggestions for improved models. Water retention and near saturated and saturated hydraulic conductivity were measured for a variety of 81 top and subsoils. The hydraulic conductivity models by van Genuchten [van Genuchten, 1980. A closedform equation for predicting the hydraulic conductivity of unsaturated soils. Soil Sci. Soc. Am. J. 44, 892898.] (vGM) and Brooks and Corey, modified by Jarvis [Jarvis, 1991. MACROA Model of Water Movement and Solute Transport in Macroporous Soils. Swedish University of Agricultural Sciences. Department of Soil Sciences. Reports and Dissertations 9.] were optimised to describe the unsaturated hydraulic conductivity in the range measured. Different optimisation procedures were tested. Using the measured saturated hydraulic conductivity in the vGM model tends to overestimate the unsaturated hydraulic conductivity. Optimising a matching factor (k0) improved the fit considerably whereas optimising the lparameter in the vGM model improved the fit only slightly. The vGM was improved with an empirical scaling function to account for the rapid increase in conductivity near saturation. Using the improved models, it was possible to describe both the saturated and the unsaturated hydraulic conductivity better than a previously published model by Jarvis. The pore size boundary of the macropores was found at a capillary pressure of 4 hPa corresponding to a circular pore diameter of 750 μm. © 2005 Elsevier B.V. All rights reserved.
 Faust, A. E., Ferre, T., Schaap, M. G., & Hinnell, A. C. (2006). Can basinscale recharge be estimated reasonably with waterbalance models?. VADOSE ZONE JOURNAL, 5(3), 850855.
 Schaap, M. G., & Th., M. (2006). A modified Mualemvan Genuchten formulation for improved description of the hydraulic conductivity near saturation. Vadose Zone Journal, 5(1), 2734.More infoAbstract: The unsaturated soil hydraulic properties are often described using Mualemvan Genuchten (MVG) type analytical functions. Recent studies suggest several shortcomings of these functions near saturation, notably the lack of secondorder continuity of the soil water retention function at saturation and the inability of the hydraulic conductivity function to account for macroporosity. We present a modified MVG formulation that improves the description of the hydraulic conductivity near saturation. The modified model introduces a small but constant airentry pressure (hs) into the water retention curve. Analysis of the UNSODA soil hydraulic database revealed an optimal value of 4 cm for hs, more or less independent of soil texture. The modified model uses a pressure dependent piecewise linear correction to ensure that deviations between measured and fitted conductivities between pressure heads of 0 and 40 cm were eliminated. A small correction was found necessary between 4 and 40 cm, and a much larger correction was needed between 0 and 4 cm. An average RMSE in logK of only 0.26 remained for a data set of 235 samples. The resulting modified MVG model was found to have small systematic errors across the entire pressure range. The modified model appears well suited for largescale vadose zone flow and transport simulations, including inverse modeling studies. © Soil Science Society of America.
 Schaap, M. G., & van Genuchten, M. T. (2006). A modified Mualemvan Genuchten formulation for improved description of the hydraulic conductivity near saturation. VADOSE ZONE JOURNAL, 5(1), 2734.
 Twarakavi, N. K., Simunek, J., & Schaap, M. G. (2006). Development of Pedotransfer Functions for Estimation of Soil Hydraulic Parameters using Support Vector Machines. SOIL SCIENCE SOCIETY OF AMERICA JOURNAL, 73(5), 14431452.More infoModeling flow in variably saturated porous media requires reliable estimates of the hydraulic parameters describing the soil water retention and hydraulic conductivity. These soil hydraulic properties can be measured using a wide variety of laboratory and field methods. Frequently, this proves to be an arduous task because of the high spatial and temporal variability of soil properties. In the last decade, researchers have shown a keen interest in developing a class of indirect approaches, called pedotransfer functions (PTFs), to overcome this problem. Pedotransfer functions predict soil hydraulic parameters using easily obtainable soil properties such as textural information, bulk density and/or few retention points. In this paper, we use a new methodology called Support Vector Machines (SVMs) to derive a new set of PTFs. Support vector machines represent a pattern recognition approach where the overall prediction error and complexity of the SVM structure are minimized simultaneously. We used the same database that was utilized to develop ROSETTA to generate the SVMbased PTFs. The performance of the SVMbased PTFs was analyzed using the coefficient of determination, root mean square error (RMSE) and mean error (ME). All soil hydraulic parameters estimated using the SVMbased PTFs showed improved confidence in the estimates when compared with the ROSETTA PTF program. Estimates of water contents and saturated hydraulic conductivities using the hydraulic parameters predicted by the SVMbased PTFs mostly improved compared with those obtained using the artificial neural network (ANN)based ROSETTA. The RMSE for water contents decreased from 0.062 to 0.034 as more predictors were used, while the RMSE for the saturated hydraulic conductivity decreased from 0.716 to 0.552 (dimensionless log(10) units). Similarly, the bias in the water contents estimated using the SVMbased PTF was reduced significantly compared with ROSETTA.
 Borgesen, C. D., & Schaap, M. G. (2005). Point and parameter pedotransfer functions for water retention predictions for Danish soils. GEODERMA, 127(12), 154167.
 Buehler, M. G., Anderson, R. C., Seshadri, S., & Schaap, M. G. (2005). Prospecting for in situ resources on the moon and mars using wheelbased sensors. IEEE Aerospace Conference Proceedings, 2005.More infoAbstract: 12The Apollo and Russian missions during 1970's were reviewed to rediscover the type and distribution of minerals on the Moon. This study revealed that the Moon has a restricted set of minerals when compared with the Earth. Results from lunar minerals brought back to Earth, indicate that the Moon lacks water, hydroxyl ions, and carbon based minerals. This mineral set is probably incomplete and so is the motivation for prospecting for other minerals using wheelbase sensors. Our approach to prospecting utilizes a vehicle with sensors embedded in a wheel that allow measurements while the vehicle is in motion. Once a change in soil composition is detected, decision making software stops the vehicle and analytical instruments perform a more quantitative soil analysis. This paper discusses instrumentation and data derived from wheelbased sensors. © 2005 IEEE.
 Buehler, M. G., Sant, T. A., Brizendine, E., Keymeulen, D., Kuhlman, G. M., Schaap, M. G., Seshadri, S., & Anderson, R. C. (2005). Measuring water content of martian soil simulants using planar fourprobes. IEEE Aerospace Conference Proceedings, 2005.More infoAbstract: A miniature fourpoint probe instrument has been developed and applied to the characterization of the moisture content of the Martian soil simulants using fine and coarse silica sand and Moses Lake basalt. The results indicate that the soil resistivity varies over four orders of magnitude as the moisture content varied from 0.1% to over 10%. In addition it was found that forcing too much current through the sand sample resulted in a curious breakdown in the currentvoltage characteristic. © 2005 IEEE.
 Børgesen, C. D., & Schaap, M. G. (2005). Point and parameter pedotransfer functions for water retention predictions for Danish soils. Geoderma, 127(12), 154167.More infoAbstract: Estimates of soil water retention characteristics using pedotransfer functions (PTFs) are useful in many studies, such as hydrological modelling and soil mapping. The objective of this study was to calibrate and validate point and parametric PTF models based on neural networks and the Bootstrap method using different sets of predictors. The point PTF models estimated retention points at 1, 10, 100, and 1500 kPa pressure and the parametric PTF models estimated the van Genuchten retention parameters. A Danish soil data set (3226 horizons) dominated by sandy and sandy loamy soils was used in the analysis. The data were split up into a calibration data set (N=1618 horizons) and a testing data set (N=1608). The data were evaluated with the root mean square residuals (RMSR) and the Akaike Information Criterion (AIC), both obtained from measured and predicted water contents at the four retention points. The results for the point PTF models show similar predictions using detailed soil textural classification (seven textural classes) compared to a simplified textural classification (sand, silt, and clay). In general, we found that adding bulk density (BD) and soil organic matter (SOM) as predictors increased the prediction capability. The RMSR values varied between 0.037 and 0.051 cm 3 cm3 and the lowest RMSR values were found for the models that used the most detailed data. The AIC followed the change in RMSR closely. The RMSR values for the parametric PTF models were generally 0.011 cm3 cm3 higher than the point PTF models using the same predictors. This was mainly due to an imperfect fit of the van Genuchten retention model to the retention data at 1500 kPa. Adding measured soil water content at 10 kPa in the parametric PTF models reduced the RMSR by 0.006 cm3 cm3. Adding additional soil water contents measured at 1 kPa, 100 kPa, and 1500 kPa improved the predictions only to a minor degree. The uncertainty in the prediction of water content using both the point and parametric PTF increased with increasing clay content. Another finding was that the absolute uncertainty in point PTF predictions of water content at 10 kPa was generally higher than the uncertainty found at 1, 100, and 1500 kPa. © 2005 Elsevier B.V. All rights reserved.
 Kelleners, T. J., FerrePikal, E. S., Schaap, M. G., & Paige, G. B. (2005). Calibration of Hydra Impedance Probes using Electric Circuit Theory. SOIL SCIENCE SOCIETY OF AMERICA JOURNAL, 73(2), 453465.More infoImpedance probes are an attractive electromagnetic technique to measure water content and bulk electrical conductivity (EC) in the same volume of soil. In this study, we developed an electric circuit model for Hydra probes that explains how the output voltages call be related to the soil real and imaginary permittivity. Internal probe transmission line sections were modeled using either a distributed approach or a Jumped approach. The distributed approach resulted in seven circuit model parameters, while the lumped approach resulted in six parameters. Optimization of all the parameters using probe readings in air, ethanol, methanol, deionized water, and saline water solutions did not result in physically realistic parameter values. In contrast, fixing four parameters (distributed approach) and two parameters (lumped approach), while optimizing others, did yield realistic parameter values. Both the parameter optimization method and the default probe algorithm performed well during model verification. The parameter optimization method resulted in improved real permittivity measurements when nonsaline fluids at different temperatures were used in the optimization process.
 Robinson, D. A., Schaap, M. G., Or, D., & Jones, S. B. (2005). On the effective measurement frequency of time domain reflectometry in dispersive and nonconductive dielectric materials. Water Resources Research, 41(2), 19.More infoAbstract: Time domain reflectometry (TDR) is one of the most commonly used techniques for water content determination in the subsurface. The measurement results in a single bulk permittivity value that corresponds to a particular, but unknown, "effective" frequency (feff). Estimating feff using TDR is important, as it allows comparisons with other techniques, such as impedance or capacitance probes, or microwave remote sensing devices. Soils, especially those with high clay and organic matter content, show appreciable dielectric dispersion, i.e., the real permittivity changes as a function of frequency. Consequently, comparison of results obtained with different sensor types must account for measurement frequency in assessing sensor accuracy and performance. In this article we use a transmission line model to examine the impact of dielectric dispersion on the TDR signal, considering lossless materials (negligible electrical conductivity). Permittivity is inferred from the standard tangent line fitting procedure (KaTAN) and by a method of using the apex of the derivative of the TDR waveform (KaDER). The permittivity determined using the tangent line method is considered to correspond to a velocity associated with a maximum passable frequency; whereas we consider the permittivity determined from the derivative method to correspond with the frequency associated with the signal group velocity. The effective frequency was determined from the 1090% risetime of the reflected signal. On the basis of this definition, feff was found to correspond with the permittivity determined from KaDER and not from KaTAN in dispersive dielectrics. The modeling is corroborated by measurements in bentonite, ethanol and 1propanol/water mixtures, which demonstrate the same result. Interestingly, for most nonconductive TDR measurements, frequencies are expected to lie in a range from 0.7 to 1 GHz, while in dispersive media, f eff is expected to fall below 0.6 GHz. Copyright 2005 by the American Geophysical Union.
 Schaap, M. G., & Hendrickx, J. M. (2005). Dielectric relaxation effects on permittivity of surface soils. Proceedings of SPIE  The International Society for Optical Engineering, 5794(PART I), 135143.More infoAbstract: The detectability of buried nonconductive objects with high frequency dielectric methods depends strongly on the contrast between the dielectric properties of the object and the surrounding soil. In this study we report on effects of dielectric relaxation phenomena on the dielectric "constant" of five texturally different soils. We found that fine textured soils (loam, silt and clay) exhibit significant decreases in permittivity between 100 and 1000 MHz. It was also found that the strength of the decrease depends linearly on the soil water content and that the highfrequency permittivity of the soils follow the Toppcurve. The changes in permittivity, however, do not significantly increase the detectability of buried nonconductive lowpermittivity objects in soil.
 Kelleners, T. J., Soppe, R. W., Robinson, D. A., Schaap, M. G., Ayars, J. E., & Skaggs, T. H. (2004). Calibration of capacitance probe sensors using electric circuit theory. Soil Science Society of America Journal, 68(2), 430439.More infoAbstract: Capacitance probe sensors are an attractive electromagnetic technique for estimating soil water content. There is concern, however, about the influence of soil salinity and soil temperature on the sensors. We present an electric circuit model that relates the sensor frequency to the permittivity of the medium and that is able to correct for dielectric losses due to ionic conductivity and relaxation. The circuit inductance L is optimized using sensor readings in a modified setup where ceramic capacitors replace the sensor's capacitance plates. The three other parameters in the model are optimized using sensor readings in a range of nonconductive media with different permittivities. The geometric factor for the plastic access tube gp is higher than the geometric factor for the medium gm, indicating that most of the electromagnetic field does not go beyond the access tube. The effect of ionic conductivity on the sensor readings is assessed by mixing salts in three of the media. The influence is profound. The sensor frequency decreases with increasing conductivity. The effect is most pronounced for the medium with the lowest permittivity. The circuit model is able to correct for the conductivity effect on the sensors. However, as the dielectric losses increase, the frequency becomes relatively insensitive to permittivity and small inaccuracies in the measured frequency or in the sensor constants result in large errors in the calculated permittivity. Calibration of the capacitance sensors can be simplified by fixing two of the constants and calculating the other two using sensor readings in air and water.
 Kelleners, T. J., Soppe, R., Robinson, D. A., Schaap, M. G., Ayars, J. E., & Skaggs, T. H. (2004). Calibration of capacitance probe sensors using electric circuit theory. SOIL SCIENCE SOCIETY OF AMERICA JOURNAL, 68(2), 430439.
 Leij, F. J., Romano, N., Palladino, M., Schaap, M. G., & Coppola, A. (2004). Topographical attributes to predict soil hydraulic properties along a hillslope transect. WATER RESOURCES RESEARCH, 40(2).
 Leij, F. J., Romano, N., Palladino, M., Schaap, M. G., & Coppola, A. (2004). Topographical attributes to predict soil hydraulic properties along a hillslope transect. Water Resources Research, 40(2), W024071W02407115.More infoAbstract: Basic soil properties have long been used to predict unsaturated soil hydraulic properties with pedotransfer function (PTFs). Implementation of such PTFs is usually not feasible for catchmentscale studies because of the experimental effort that would be required. On the other hand, topographical attributes are often readily available. This study therefore examines how well PTFs perform that use both basic soil properties and topographical attributes for a hillslope in Basilicata, Italy. Basic soil properties and hydraulic data were determined on soil samples taken at 50m intervals along a 5km hillslope transect. Topographical attributes were determined from a digital elevation model. Spearman coefficients showed that elevation (z) was positively correlated with organic carbon (OC) and silt contents (0.62 and 0.59, respectively) and negatively with bulk density (ρb) and sand fraction (0.34 and 0.37). Retention parameters were somewhat correlated with topographical attributes z, slope (β), aspect (cosφ), and potential solar radiation. Water contents were correlated most strongly with elevation (coefficient between 0.38 and 0.48) and aspect during "wet" conditions. Artificial neural networks (ANNs) were developed for 21 different sets of predictors to estimate retention parameters, saturated hydraulic conductivity (KS), and water contents at capillary heads h = 50 cm and 12 bar (103 cm). The prediction of retention parameters could be improved with 10% by including topography (RMSE = 0.0327 cm3 cm 3) using textural fractions, ρb, OC, z, and β as predictors. Furthermore, OC became a better predictor when the PTF also used z as predictor. The water content at h = 50 cm could be predicted 26% more accurately (RMSE = 0.0231 cm3 cm3) using texture, ρb, OC, z, β, and potential solar radiation as input. Predictions of ANNs with and without topographical attributes were most accurate in the wet range (0 < h < 250 cm). Semivariograms of the hydraulic parameters and their residuals showed that the ANNs could explain part of the (spatial) variability. The results of this study confirm the utility of topographical attributes such as z, β, cosφ, and potential solar radiation as predictors for PTFs when basic soil properties are available. A next step would be the use of topographical attributes when no or limited other predictors are available.
 Pachepsky, Y., & Schaap, M. G. (2004). Data mining and exploration techniques. Developments in Soil Science, 30(C), 2132.
 Schaap, M. G. (2004). Accuracy and uncertainty in PTF predictions. Developments in Soil Science, 30(C), 3343.
 Schaap, M. G. (2004). Graphic user interfaces for pedotransfer functions. Developments in Soil Science, 30(C), 349356.
 Schaap, M. G., & Lebron, I. (2004). An evaluation of permeability of statistically reconstructed threedimensional pore structures with lattice boltzmann simulations. Developments in Water Science, 55(PART 1), 1522.More infoAbstract: Water flow and related processes at the pore scale essentially occur in three dimensions (3D). Unfortunately, it is often difficult and expensive to obtain reliable "images" of the 3D pore structure. Several techniques are available to statistically generate 3D pore structures from spatial information derived from 2D microscope images of thin sections of rock and soil. The question remains, however, whether the reconstructed media are functionally identical to the 3D originals. In this study we try to answer this question by reconstructing pore structures of idealized media. Lattice Bolzmann simulations are carried out to compare the permeabilities of the original and reconstructed 3D media. © 2004 Elsevier B.V.
 Schaap, M. G., Nemes, A., & Th, M. (2004). Comparison of models for indirect estimation of water retention and available water in surface soils. Vadose Zone Journal, 3(4), 14551463.More infoAbstract: 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 timeconsuming. Pedotransfer functions(PTFs) offer a meansto estimate soilhydraulic 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 contentbased objective functions, instead of parameter valuebased 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 47 435 records containing 113 970 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 cm 3 cm 3. Average root mean square errors ranged from 0.0687 cm 3 cm 3 for a PTF that provided textural class average parameters to 0.0315 cm 3 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 cm 3 cm 3, depending on the model and the definition of available water. © Soil Science Society of America.
 L., R., H., E., Schaap, M. G., Broekema, L. H., & Schlager, W. (2003). Radar reflections from sedimentary structures in the vadose zone. Geological Society Special Publication, 211, 257273.More infoAbstract: Ground penetrating radar (GPR) is a suitable technique for imaging sedimentary structures in the vadose zone because small texturerelated capillarypressure variations lead to changes in water content and electromagnetic properties. To study exactly how GPR reflections are generated by sedimentary structures, GPR profiles of an aeolian sedimentary succession are combined with measurements of textural, electromagnetic and waterretention characteristics from a trench. Time domain reflectometry indicates that small variations in texture in the highangle dune sediment are associated with changes in water content. Synthetic modelling shows that these changes cause clear GPR reflections. In an experimental approach to estimate the radar response of structures below the wave resolution, i.e. features smaller than λ/4, variations in grainsize distribution and porosity in a thin section were used to reconstruct waterretention curves and impedance models of the thinly layered sediment. Synthetic radar records calculated from the impedance models show that reflections from the studied subcentimetrescale structures are composites of interfering signals. Although these lowamplitude interfering signals will commonly be overprinted by more prominent reflections, they may cause reflection patterns that change with frequency and do not represent primary bedding.
 Nemes, A., Schaap, M. G., & Wosten, J. (2003). Functional evaluation of pedotransfer functions derived from different scales of data collection. SOIL SCIENCE SOCIETY OF AMERICA JOURNAL, 67(4), 10931102.
 Nemes, A., Schaap, M. G., & Wösten, J. (2003). Functional evaluation of pedotransfer functions derived from different scales of data collection. Soil Science Society of America Journal, 67(4), 10931102.More infoAbstract: Estimation of soil hydraulic properties by pedotransfer functions (PTFs) can be an alternative to troublesome and expensive measurements. New approaches to develop PTFs are continuously being introduced, however, PTF applicability in locations other than those of data collection has been rarely reported. We used three databases were used to develop PTFs using artificial neural networks (NNs). Data from Hungary were used to derive national scale soil hydraulic PTFs. The HYPRES database was used to develop continental scale PTFs. Finally, a database containing mostly American and European data was used to develop intercontinental scale PTFs. For each database, 11 PTFs were developed that differed in detail of input data. Accuracy of the estimations was tested using independent Hungarian data. First, soil water retention at nine values of matric potential were estimated. Root mean squared residuals (RMSRs) using different inputs ranged from 0.02 to 0.06 m3 m3 for national scale PTFs, while international scale PTFs had RMSRs from 0.025 to 0.088 m3 m3. Estimated water retention curves (WRCs) were then used to simulate soil moisture time series of seven Hungarian soils. Root mean squared residuals during a growing season ranged from 0.065 to 0.07 m3 m3, using different PTF estimates. Simulations using laboratorymeasured WRCs had RMSR of 0.061 m3 m3. Such small differences in the accuracy of simulations make international PTFs an alternative to national PTFs and measurements. However, testing of the international PTFs with a specific model for specific soil and land use remains desirable because of uncertainty in soil representation in such databases.
 Robinson, D. A., Schaap, M., Jones, S. B., Friedman, S. P., & Gardner, C. M. (2003). Considerations for improving the accuracy of permittivity measurement using time domain reflectometry: Airwater calibration, effects of cable length. Soil Science Society of America Journal, 67(1), 6270.More infoAbstract: In a paper presented by Heimovaara (1993) a method of calibrating TDR sensors was presented using air and water. Time has moved on but time domain reflectometry (TDR) sensors are still calibrated in a number of different ways. In this article we present a rigorous investigation of the method proposed by Heimovaara and demonstrate its accuracy. We demonstrate that the placement of a starting point in any place other than the one determined using Heimovaara's method results in erroneous permittivity measurement. This will be most significant at low values of permittivity. We propose that Heimovaara's method be adopted as a standard method for calibrating TDR sensors for measuring permittivity. The discussion centers on the placement of the first time marker used to measure the signal travel time from which permittivity is measured. Our modeling results suggest that this point is slightly forward of the apex of the bump on the waveform which corresponds to the impedance increase as the wave travels from the cable into the TDR sensor head. We also demonstrate that using the apex of this bump as a starting point reference can lead to erroneous measurements of travel time in layered dielectric media. Finally we examine the use of long cables to connect sensors to the TDR. We demonstrate that the travel time in the cable changes as a function of temperature and that fixed travel time markers based on cable length cause error in the measurement of travel time. For a 2.6m cable the error was 1.6% at 50°C, and 4.7% for a 10.3m cable, relative to calibration at 25°C. Software that tracks the sensor head either through the impedance mismatch caused by the head or using an electrical marker eliminates this source of error.
 Schaap, M. G., Robinson, D. A., Friedman, S. P., & Lazar, A. (2003). Measurement and modeling of the TDR signal propagation through layered dielectric media. SOIL SCIENCE SOCIETY OF AMERICA JOURNAL, 67(4), 11131121.
 Schaap, M. G., Robinson, D. A., Friedman, S. P., & Lazar, A. (2003). Measurement and modeling of the TDR signal propagation through layered dielectric media. Soil Science Society of America Journal, 67(4), 11131121.More infoAbstract: Layered dielectric materials are often encountered in the natural environment due to differences in water content caused either by a wetting or drying front. This is especially true for coarsegrained materials such as sandy soils, sediments, and some rocks that have very distinctive layers of water content. This paper examines the issue of how the permittivity along a time domain reflectometry (TDR) probe is averaged as a function of layer thickness and probe orientation. Measurements of apparent permittivity using TDR are presented for two, three, and multilayer materials. Time domain reflectometry waveforms are modeled for multiple layers of varying thickness and show a change in the averaging of the apparent permittivity from refractive index to arithmetic when more thin layers are present. Analysis of the modeled results shows that the averaging regime is frequencydependent. However, broadband techniques applied to materials with a few layers will generally produce refractive averaging. A transition to arithmetic averaging is found for systems having many (>4 layers). Narrowband methods may be very sensitive to layering and may perform in a highly nonrefractive way when layering with a strong permittivity contrast is present.
 Lebron, I., Suarez, D. L., & Schaap, M. G. (2002). Soil pore size and geometry as a result of aggregatesize distribution and chemical composition. Soil Science, 167(3), 165172.More infoAbstract: Soil pore size and pore geometry are important propernes affecting soil hydraulic properties. Using scanning electron micrographs and image analysis, we quantified the actual poresize distribution and pore shape in undisturbed soil cores. Aggregatesize distribution was also quantified for the same micrographs. For soils with similar texture, we observed a decrease both in the median aggregate size and in the aggregatesize distribution when the sodium content in the soil increased. We hypothesize that the decrease in the aggregate stability is caused by the weakening of the binding capacity of the cementing agents bonding the domains that form the aggregates. An equivalent decrease in the poresize distribution was found with increasing sodium and pH. There was a significant correlation between median aggregate size and median pore size, but there was not a significant correlation between median pore diameter and soil texture.
 Raat, K. J., Draaijers, G. P., Schaap, M. G., Tietema, A., & Verstraten, J. M. (2002). Spatial variability of throughfall water and chemistry and forest floor water content in a Douglas fir forest stand. Hydrology and Earth System Sciences, 6(3), 363374.More infoAbstract: This study focuses on spatial variability of throughfall water and chemistry and forest floor water content within a Douglas fir (Pseudotsuga menziesii, Franco L.) forest plot. Spatial patterns of water and chemistry (NH4, NO3, SO42, Cl, Mg2+, Ca2+, Na+ and K+) were compared and tested for stability over time. The spatial coefficient of variation (CV) was between 18 and 26% for amounts of throughfall water and ions, and 17% for forest floor water content. Concentrations and amounts of all ions were correlated significantly. Ion concentrations were negatively correlated with throughfall water amounts, but, except for NH4+, there was no such relation between throughfall water and ion amounts. Spatial patterns of throughfall water fluxes and forest floor water contents were consistent over time; patterns of ion fluxes were somewhat less stable. Because of the spatial variability of forest floor thickness and drainage, it was not possible to relate patterns in throughfall water directly to patterns in water content. The spatial variability of throughfall nitrogen and forest floor water contents can cause significant variability in NO3 production within the plot studied.
 Raat, K. J., Draaijers, G., Schaap, M. G., Tietema, A., & Verstraten, J. M. (2002). Spatial variability of throughfall water and chemistry and forest floor water content in a Douglas fir forest stand. HYDROLOGY AND EARTH SYSTEM SCIENCES, 6(3), 363374.
 Dekker, S. C., Bouten, W., & Schaap, M. G. (2001). Analysing forest transpiration model errors with artificial neural networks. Journal of Hydrology, 246(14), 197208.More infoAbstract: A Single Big Leaf (SBL) forest transpiration model was calibrated on halfhourly eddy correlation measurements. The SBL model is based on the PenmanMonteith equation with a canopy conductance controlled by environmental variables. The model has eight calibration parameters, which determine the shape of the response functions. After calibration, residuals between measurements and model results exhibit complex patterns and contain random and systematic errors. Artificial Neural Networks (ANNs) were used to analyse these residuals for any systematic relations with environmental variables that may improve the SBL model. Different subsets of data were used to calibrate and validate the ANNs. Both wind direction and wind speed turned out to improve the model results. ANNs were able to find the source area of the fluxes of the Douglas fir stand within a larger heterogeneous forest without using a priori knowledge of the forest structure. With ANNs, improvements were also found in the shape and parameterisation of the response functions. Systematic errors in the original SBL model, caused by interdependencies between environmental variables, were not found anymore with the new parameterisation. After the ANNs analyses, about 80% of the residuals can be attributed to random errors of eddy correlation measurements. It is finally concluded that ANNs are able to find systematic trends even in very noisy residuals if applied properly. © 2001 Elsevier Science B.V.
 Goncalves, M. C., Leij, F. J., & Schaap, M. G. (2001). Pedotransfer functions for solute transport parameters of Portuguese soils. European Journal of Soil Science, 52(4), 563574.More infoAbstract: The purpose of this study is to quantify solute transport parameters of finetextured soils in an irrigation district in southern Portugal and to investigate their prediction from basic soil properties and unsaturated hydraulic parameters. Solute displacement experiments were carried out on 24 undisturbed soil samples by applying a 0.05 M KC1 pulse during steady flow. The chloride breakthrough curves (BTCs) were asymmetric, with early breakthrough and considerable tailing characteristic of nonequilibrium transport. The retardation factor (R), dispersion coefficient (D), partitioning coefficient (β), and mass transfer coefficient (ω) were estimated by optimizing the solution of the nonequilibrium convectiondispersion equation (CDE) to the breakthrough data. The solution could adequately describe the observed data as proved by a median of 0.972 for the coefficient of determination (r2) and a median for the mean squared error (MSE) of 5.1 × 106. The median value for R of 0.587 suggests that Cl was excluded from a substantial part of the liquid phase. The value for β was typically less than 0.5, but the nonequilibrium effects were mitigated by a large mass transfer coefficient (ω > 1). Pedotransfer functions (PTFs) were developed with regression and neural network analyses to predict R, D, β and ω from basic soil properties and unsaturated hydraulic parameters. Fairly accurate predictions could be obtained for logD (r2 ≈ 0.9) and β (r2 ≈ 0.8). Prediction for R and logω were relatively poor (r2 ≈ 0.5). The artificial neural networks were all somewhat more accurate than the regression equations. The networks are also more suitable for predicting transport parameters because they require only three input variables, whereas the regression equations contain many predictor variables.
 Johnson, C. A., Schaap, M. G., & Abbaspour, K. C. (2001). Model comparison of flow through a municipal solid waste incinerator ash landfill. Journal of Hydrology, 243(12), 5572.More infoAbstract: The drainage discharge of a municipal solid waste incinerator (MSWI) bottom ash landfill was simulated using various modelling approaches. Two functional models including a neural networks approach and a hydrological linear storage model, and two mechanistic models requiring physical/hydrodynamic properties of the waste material, HYDRUS5 and MACRO (Version 4.0) were used. The models were calibrated using an 8month data set from 1996 and validated on a 3month data set from winter 1994/1995. The data sets comprised hourly values of rainfall, evaporation (estimated from the PenmanMonteith relationship), drainage discharge and electrical conductivity. Predicted and measured discharges were compared. The discharge predicted by the functional models more exactly followed the discharge patterns of the measured data but, particularly the linear storage model, could not cope with the nonlinearity of the system that was caused by seasonal changes in water content of the MSWI bottom ash. The fit of the neural networks model to the data improved with increasing prior information but was less smooth than the measured data. The mechanistic model that included preferential discharge, MACRO, better modelled the discharge characteristics when inversely applied, indicating that preferential flow does occur in this system. However, even the inverse application of HYDRUS5 could not describe the system discharge as well as the linear storage model. All model approaches would have benefited from a more exact knowledge of initial water content. © 2001 Elsevier Science B.V.
 Nemes, A., Schaap, M. G., Leij, F. J., & Wosten, J. (2001). Description of the unsaturated soil hydraulic database UNSODA version 2.0. JOURNAL OF HYDROLOGY, 251(34), 151162.
 Nemes, A., Schaap, M. G., Leij, F. J., & Wösten, J. (2001). Description of the unsaturated soil hydraulic database UNSODA version 2.0. Journal of Hydrology, 251(34), 151162.More infoAbstract: Quantifying water flow and chemical transport in the vadose zone typically requires knowledge of the unsaturated soil hydraulic properties. The UNsaturated SOil hydraulic DAtabase (UNSODA) was developed to provide a source of unsaturated hydraulic data and some other soil properties for practitioners and researchers. The current database contains measured soil water retention, hydraulic conductivity and water diffusivity data as well as pedological information of some 790soil samples from around the world. A first MSDOS version of the database was released in 1996. It has been applied in numerous studies. In this paper, we describe the second version (UNSODA V2.0) for use with Microsoft Access97®1. The format and structure of the new database have been modified to provide additional and more convenient options for data searches, to provide compatibility with other programs for easy loading and downloading of data, and to allow users to customise the contents and look of graphical output. This paper reviews the structure and contents of the database as well as the operations that can be performed on the different data types in UNSODA V2.0. The use and application of the new database are illustrated with two examples. The retrieval of data is briefly illustrated, followed by a more detailed example regarding the interpolation of soil particlesize distribution data obtained according to different national definitions of particlesize classes. The interpolation procedure, which is based on finding similar particlesize distribution curves from a large European data set, also performed well for soils that originate from other geographical areas. © 2001 Elsevier Science B.V. All rights reserved.
 Schaap, M. G., & Lebron, I. (2001). Using microscope observations of thin sections to estimate soil permeability with the KozenyCarman equation. Journal of Hydrology, 251(34), 186201.More infoAbstract: In this study we used the KozenyCarman (KC) equation as a semiphysical model for estimating the soil permeability using data derived from microscope observations. Specific surface areas and porosities were obtained from twopoint correlation functions derived from scanning electron microscope images of thin sections using a magnification of 50 and a resolution of 1.88 μm pixel1.Permeabilities were predicted using two published ('Ahuja' and 'Berryman') and one generalized variant of the KC equation. The latter model was similar to the Berryman variant, but used a free parameter C rather than a porosity dependent formation factor. All KC model variants were optimized on measured permeabilities. The Ahuja and Berryman KC models performed relatively poorly with R2 values of 0.36 and 0.57, respectively, while the generalized model attained R2 values of 0.91. The parameter C was strongly related to texture and, to a lesser extent, particle density. The general model still required measured surface area and porosity. However, we showed that it was possible to estimate these parameters from texture resulting in an R2 of 0.87. A fully empirical model that did not assume KC concepts performed slightly worse (R2 = 0.84). The results indicate that after developing the model using microscope information, only macroscopic data are necessary to predict permeability of soils in a semiphysical manner with the KC equation. © 2001 Elsevier Science B.V. All rights reserved.
 Schaap, M. G., Leij, F. J., & Th., M. (2001). Rosetta: A computer program for estimating soil hydraulic parameters with hierarchical pedotransfer functions. Journal of Hydrology, 251(34), 163176.More infoAbstract: Soil hydraulic properties are necessary for many studies of water and solute transport but often cannot be measured because of practical and/or financial constraints. We describe a computer program, ROSETTA, which implements five hierarchical pedotransfer functions (PTFs) for the estimation of water retention, and the saturated and unsaturated hydraulic conductivity. The hierarchy in PTFs allows the estimation of van Genuchten water retention parameters and the saturated hydraulic conductivity using limited (textural classes only) to more extended (texture, bulk density, and one or two water retention points) input data. ROSETTA is based on neural network analyses combined with the bootstrap method, thus allowing the program to provide uncertainty estimates of the predicted hydraulic parameters. The general performance of ROSETTA was characterized with coefficients of determination, and root mean square errors (RMSEs). The RMSE values decreased from 0.078 to 0.044 cm3 cm3 for water retention when more predictors were used. The RMSE for the saturated conductivity similarly decreased from 0.739 to 0.647 (dimensionless log10 units). The RMSE values for unsaturated conductivity ranged between 0.79 and 1.06, depending on whether measured or estimated retention parameters were used as predictors. Calculated mean errors showed that the PTFs underestimated water retention and the unsaturated hydraulic conductivity at relatively high suctions. ROSETTA'S uncertainty estimates can be used as an indication of model reliability when no hydraulic data are available. The ROSETTA program comes with a graphical user interface that allows userfriendly access to the PTFs, and can be downloaded from the US Salinity Laboratory website: http://www.ussl.ars.usda.gov/. © 2001 Elsevier Science B.V. All rights reserved.
 Schaap, M., Leij, F., & van Genuchten, M. (2001). ROSETTA: a computer program for estimating soil hydraulic parameters with hierarchical pedotransfer functions. JOURNAL OF HYDROLOGY, 251(34), 163176.
 Leij, F. J., Priesack, E., & Schaap, M. G. (2000). Solute transport modeled with Green's functions with application to persistent solute sources. JOURNAL OF CONTAMINANT HYDROLOGY, 41(12), 155173.
 Leij, F. J., Priesack, E., & Schaap, M. G. (2000). Solute transport modeled with Green's functions with application to persistent solute sources. Journal of Contaminant Hydrology, 41(12), 155173.More infoAbstract: Analytical models can be valuable tools to investigate solute transport in porous media. The application of analytical solutions is limited by the perception that they are too cumbersome to derive while their implementation rests on assumptions that are too restrictive. The Green's function method (GFM) was applied to facilitate analytical solution of the advection dispersion equation (ADE) for solute transport in uniform porous media with steady one or twodimensional flow. The GFM conveniently handles different boundary and initial conditions as well as multidimensional problems. Concise expressions are possible for the solute concentration with the GFM. This paper provides a general framework to efficiently formulate analytical solutions for many transport problems. Expressions for the longitudinal and transversal Green's function are presented that can be inserted in the general expression to solve a wide variety of transport problems in infinite, semiinfinite, and finite media. These solutions can be used to elucidate transport phenomena, estimate transport parameters, evaluate numerical solution procedures and simulate the movement and fate of solutes. An illustration of the GFM is provided by the analytical modeling of transport from a planar source of persistent, longlasting contamination. Such a source may be used to represent dissolution from a pool of a nonaqueous phase liquid (NAPL). Analytical solutions are obtained for a first, second, and thirdtype condition in case of a planar source; the thirdtype condition is due to downward flow or ratelimited dissolution. Several examples are presented to show the effect of source conditions, the sensitivity of NAPL dissolution to transport parameters included in the Damkohler and Peclet numbers, and upstream dispersion.
 Schaap, M. G., & Leij, F. J. (2000). Improved prediction of unsaturated hydraulic conductivity with the Mualemvan Genuchten model. Soil Science Society of America Journal, 64(3), 843851.More infoAbstract: In many vadose zone hydrological studies, it is imperative that the soil's unsaturated hydraulic conductivity is known. Frequently, the Mualemvan Genuchten model (MVG) is used for this purpose because it allows prediction of unsaturated hydraulic conductivity from water retention parameters. For this and similar equations, it is often assumed that a measured saturated hydraulic conductivity (K(s)) can be used as a matching point (K(o)) while a factor S(c)/(L) is used to account for pore connectivity and tortuosity (where S(e) is the relative saturation and L = 0.5). We used a data set of 235 soil samples with retention and unsaturated hydraulic conductivity data to test and improve predictions with the MVG equation. The standard practice of using K(o) = K(s) and L = 0.5 resulted in a root mean square error for log(K) (RMSE(K)) of 1.31. Optimization of the matching point (K(o)) and L to the hydraulic conductivity data yielded a RMSE(K) of 0.41. The fitted K(o) were, on average, about one order of magnitude smaller than measured K(s). Furthermore, L was predominantly negative, casting doubt that the MVG can be interpreted in a physical way. Spearman rank correlations showed that both K(o) and L were related to van Genuchten water retention parameters and neural network analyses confirmed that K(o) and L could indeed be predicted in this way. The corresponding RMSE(K) was 0.84, which was half an order of magnitude better than the traditional MVG model. Bulk density and textural parameters were poor predictors while addition of K(s) improved the RMSE(K) only marginally. Bootstrap analysis showed that the uncertainty in predicted unsaturated hydraulic conductivity was about one order of magnitude near saturation and larger at lower water contents.
 Lebron, I., Schaap, M. G., & Suarez, D. L. (1999). Saturated hydraulic conductivity prediction from microscopic pore geometry measurements and neural network analysis. Water Resources Research, 35(10), 31493158.More infoAbstract: Traditional models to describe hydraulic properties in soils are constrained by the assumption of cylindrical capillarity to account for the geometry of the pore space. This study was conducted to develop a new methodology to directly measure the porosity and its microscopic characteristics. The methodology is based on the analysis of binary images collected with a backscattered electron detector from thin sections of soils. Pore surface area, perimeter, roughness, circularity, and maximum and average diameter were quantified in 36 thin sections prepared from undisturbed soils. Saturated hydraulic conductivity K(sat), particle size distribution, particle density, bulk density, and chemical properties were determined on the same cores. We used the KozenyCarman equation and neural network and bootstrap analysis to predict a formation factor from microscopic, macroscopic, and chemical data. The predicted K(sat) was in excellent agreement with the measured K(sat) (R2 = 0.91) when a hydraulic radius r(H) defined as pore area divided by pore perimeter and the formation factor were included in the KozenyCarman equation.
 Schaap, M. G., & Leij, F. J. (1998). Databaserelated accuracy and uncertainty of pedotransfer functions. Soil Science, 163(10), 765779.More infoAbstract: 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 (RAWLS, AHUJA, and UNSODA) to evaluate the accuracy and uncertainty of neural networkbased PTFs. Sand, slit, and clay percentages and bulk density were used as input for the PTFs, which subsequently provided retention parameters and saturated hydraulic conductivity, K(s) as output. Calibration and validation of PTFs were carried out on independent samples from the same database through combination with the bootstrap method. This method also yielded the possibility of calculating uncertainty estimates of predicted hydraulic parameters. Calibration and validation results showed that water retention could be predicted with a root mean square residual (RMSR) between 0.06 and 0.10 cm3 cm3; the RMSR of log(K(s)) was between 0.4 and 0.7 log (cm day1). Crossvalidation was used to test how well PTFs that were calibrated for one database could predict the hydraulic properties of the other two databases. The results showed that systematically different predictions were made when the RMSR values increased to between 0.08 and 0.13 cm3 cm3 for water retention and to between 0.6 and 0.9 log(cm day1) for log(K(s)). The uncertainty in predicted K was onehalf to one order of magnitude, whereas predicted water retention points had an uncertainty of about 0.04 to 0.10 cm3 cm3. Uncertainties became somewhat smaller if the PTFs were calibrated on all available data. We conclude that the performance of PTFs may depend strongly on the data that were used for calibration and evaluation.
 Schaap, M. G., & Leij, F. J. (1998). Using neural networks to predict soil water retention and soil hydraulic conductivity. SOIL & TILLAGE RESEARCH, 47(12), 3742.
 Schaap, M. G., & Leij, F. J. (1998). Using neural networks to predict soil water retention and soil hydraulic conductivity. Soil and Tillage Research, 47(12), 3742.More infoAbstract: 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.
 Schaap, M. G., Leij, F. J., & Th., M. (1998). Neural network analysis for hierarchical prediction of soil hydraulic properties. Soil Science Society of America Journal, 62(4), 847855.More infoAbstract: The solution of many fieldscale flow and transport problems requires estimates of unsaturated soil hydraulic properties. The objective of this study was to calibrate neural network models for prediction of water retention parameters and saturated hydraulic conductivity, K(s), from basic soil properties. Twelve neural network models were developed to predict water retention parameters using a data set of 1209 samples containing sand, silt, and clay contents, bulk density, porosity, gravel content, and soil horizon as well as water retention data. A subset of 620 samples was used to develop 19 neural network models to predict K(s). Prediction of water retention parameters and K(s) generally improved if more input data were used. In a more detailed investigation, four models with the following levels of input data were selected: (i) soil textural class, (ii) sand, silt, and clay contents, (iii) sand, silt, and clay contents and bulk density, and (iv) the previous variables and water content at a pressure head of 33 kPa. For water retention, the root mean square residuals decreased from 0.107 for the first to 0.060 m3 m3 for the fourth model while the root mean square residual K(s) decreased from 0.627 to 0.451 log(cm d1). The neural network models performed better on our data set than four published pedotransfer functions for water retention (by ≃0.010.05 m3 m3) and better than six published functions for K(s) (by ≃0.10.9 order of magnitude). Use of the developed hierarchical neural network models is attractive because of improved accuracy and because it permits a considerable degree of flexibility toward available input data.
 Schaap, M., & Leij, F. (1998). Databaserelated accuracy and uncertainty of pedotransfer functions. SOIL SCIENCE, 163(10), 765779.
 Schaap, M., Leij, F., & van Genuchten, M. (1998). Neural network analysis for hierarchical prediction of soil hydraulic properties. SOIL SCIENCE SOCIETY OF AMERICA JOURNAL, 62(4), 847855.
 Simunek, J., AnguloJaramillo, R., Schaap, M. G., Vandervaere, J. P., & van Genuchten, M. T. (1998). Using an inverse method to estimate the hydraulic properties of crusted soils from tensiondisc infiltrometer data. GEODERMA, 86(12), 6181.
 Šimůnek, J., AnguloJaramillo, R., Schaap, M. G., Vandervaere, J., & Th., M. (1998). Using an inverse method to estimate the hydraulic properties of crusted soils from tensiondisc infiltrometer data. Geoderma, 86(12), 6181.More infoAbstract: An inverse procedure was used to estimate the soil hydraulic characteristics of a twolayered soil system  soil surface crust and subsoil  from data obtained during a tensiondisc infiltration experiment. The inverse procedure combined the LevenbergMarquardt nonlinear parameter optimization method with a numerical solution of the axisymmetric variablysaturated flow equation. The objective function was defined in terms of the cumulative infiltration curve and the final water content measured directly below the tensiondisc infiltrometer at the end of the experiment; this final water content was assumed to correspond to the final supply pressure head. We analyzed two infiltration experiments carried out with a 25cm diameter tensiondisc infiltrometer. One experiment was carried out on a twolayered system, and a second after removal of the surface crust covering the sandy subsoil. Both experiments were performed with six consecutive supply tensions. We first analyzed the infiltration experiment for the subsoil only, thus yielding its hydraulic characteristics. Subsequent analysis of the infiltration experiment for the twolayered system with known hydraulic properties of the subsoil provided estimates of the hydraulic properties of the surface crust. We further compared the estimated hydraulic parameters of the subsoil with those obtained using Wooding's analytical method [Wooding, R.A., 1968. Steady infiltration from a shallow circular pond. Water Resour. Res. 4, 12591273] and predictions based on a neural network model requiring textural input information. All three methods generated roughly the same results. The numerical inversion technique proved to be a convenient tool for estimating the soil hydraulic properties of both the surface crust and the subsoil.
 Schaap, M. G., & Bouten, W. (1997). Forest floor evaporation in a dense Douglas fir stand. JOURNAL OF HYDROLOGY, 193(14), 97113.
 Schaap, M. G., & Bouten, W. (1997). Forest floor evaporation in a dense Douglas fir stand. Journal of Hydrology, 193(14), 97113.More infoAbstract: Forest floor evaporation was measured with an accurate weighing lysimeter during 44 clays in early spring and summer. The PenmanMonteith approach was used to model the evaporation rates as well as the temperature difference between forest floor surface and air at 1 m height. Values of resistance parameters were slightly different when the PenmanMonteith model was optimized for measured evaporation rates or for measured temperature differences. These discrepancies were partly due to field variability in forest floor water contents but also because our approach considered the forest floor to be isothermal. With the appropriate parameter sets, the model was able to predict measured hourly forest floor evaporation rates and surface temperature dynamics satisfactorily. We show that in the forest discussed in this paper the PenmanMonteith ventilation term dominates over the available energy term. As a result the evaporation flux is matched by an almost equal, sensible heat flux but in opposite direction. Forest floor water content dynamics have a strong control over the evaporation flux. Spatial variability in forest floor water contents cause the 44day average forest floor evaporation to range from 0.19 mm d1 in a dry part of the forest to 0.3 mmd1 in a wet pan with 0.23 mmd1 as a site representative value.
 Schaap, M. G., Beuten, W., & Verstraten, J. M. (1997). Forest floor water content dynamics in a Douglas fir stand. Journal of Hydrology, 201(14), 367383.More infoAbstract: This paper considers the hydrology of the forest floor within a homogeneous Douglas fir forest. Time domain reflectometry measurements show that forest floor water contents have considerable spatial variabilities but similar temporal dynamics. Simple linear relations can be used to translate forest floor water content dynamics from one site in a forest to another. Forest floor evaporation rates were calculated using a previously developed forest floor evaporation model and a year of soil water and micrometeorological data. For a relatively wet site within the stand the calculated evaporation rate was 137 mm year1, for a more representative site 112 mm year1 and for a dry site 76 mm year1. These amounts range between 7 and 13% of the total yearly forest evapotranspiration. Together with throughfall rates and transpiration rates, these forest floor evaporation rates served as boundary conditions to a soil water model with which we simulated forest floor and mineral soil water content dynamics. The simulations showed that throughfall and drainage dynamics determine the forest floor water content dynamics in wet conditions. In dry periods, forest floor evaporation and, to a lesser extent, root water uptake determine forest floor water content dynamics. The same simulations showed that 25% of the forest floor evaporation is replenished by capillary rise from the mineral soil.
 Schaap, M. G., Bouten, W., & Verstraten, J. M. (1997). Forest floor water content dynamics in a Douglas fir stand. JOURNAL OF HYDROLOGY, 201(14), 367383.
 Schaap, M. G., Lange, L. D., & Heimovaara, T. J. (1997). TDR calibration of organic forest floor media. Soil Technology, 11(2), 205217.More infoAbstract: We carried out a time domain reflectometry (TDR) calibration for 25 forest floor samples of five different forest stands. Linear regression was used to estimate the volumetric water content from the refraction index. Due to the presence of bound water, it was impossible to predict the calibration line parameters from theoretical values with a refractive mixing model. However, when the apparent dielectric constant of the water was considered, it was possible to predict the offset parameter because the low forest floor bulk density caused the calibration line slope and offset to be almost reversely proportional. Calibration parameters for different forest floor materials are presented. Allowing a somewhat higher margin of error we could also establish general calibration curves which were in close agreement with a published calibration curve (Malicki et al., 1994). An error analysis showed that decomposition of organic matter, residual water and temperature effects have negligible effects on the calibration parameters. Shrinkage of the organic material significantly influenced both the volumetric water content and the TDR reflection times. If not corrected, both effects yielded systematic errors of approximately 0.02 cm3 cm3 for a strongly shrinking H horizon.
 Bouten, W., Schaap, M. G., Aerts, J., & Vermetten, A. W. (1996). Monitoring and modelling canopy water storage amounts in support of atmospheric deposition studies. Journal of Hydrology, 181(14), 305321.More infoAbstract: Canopy water storage amounts were measured with a newly developed measuring system based on the attenuation of a 10.26 GHz microwave signal. Every 5 min, vertical scans were made, over a period of nine months. A physically based multilayer interception model with empirical parameters was calibrated using an onlinear optimization technique. Calibrated model appeared to be capable of explaining up to 92% of the measured variance of water storage amounts for an independent validation period when using onsite measurements of meteorological variables.
 Schaap, M. G., & Bouten, W. (1996). Modeling water retention curves of sandy soils using neural networks. Water Resources Research, 32(10), 30333040.More infoAbstract: We used neural networks (NNs) to model the drying water retention curve (WRC) of 204 sandy soil samples from particlesize distribution (PSD), soil organic matter content (SOM), and bulk density (BD). Neural networks can relate multiple model input data to multiple model output data without the need of an a priori model concept. In this way a high performance blackbox model is created, which is very useful in a data exploration effort to assess the maximum obtainable prediction accuracy. We used a series of NN models with an increasing parametrization of input and output variables to get a better interpretability of model results. In the first two models we used the nine PSD fractions, BD, and SOM as input, while we predicted the nine points of the water retention curve. These NNs had 12 input and 9 output variables, predicting WRCs with an average rootmeansquare residual (RMSR) water content of 0.020 cm3 cm3. After a few intermediary models with increasing parametrization of PSD and WRC using (adapted) van Genuchten [1980] equations we arrived at a final NN model that used six input variables to predict three van Genuchten [1980] parameters resulting in a RMSR of 0.024 cm3 cm3. We found saturated and residual water contents to be unrelated to the PSD, BD, or SOM, therefore the saturated water content was considered to be an independent input variable, while the residual water content was set to zero. Sensitivity analyses showed that the PSD had a major influence on the shape of the WRC, while BD and SOM were less important. On the basis of these sensitivity analyses we established more explicit equations that demonstrated similarity relations between PSD and WRC and incorporated effects of SOM and BD in an empirical way. Despite the fact that we considered a large number of linear and nonlinear variants these equations had a weaker performance (RMSR: 0.029 cm3 cm3) than the NN models, proving the modeling power of that technique.
 Schaap, M. G., & Bouten, W. (1996). Modeling water retention curves of sanely soils using neural networks. WATER RESOURCES RESEARCH, 32(10), 30333040.
 Schaap, M. G., Bouten, W., & Kuiper, L. C. (1995). The role of organic soil profiles on water availability in forests: Sensitivity analyses. Studies in Environmental Science, 65(PART B), 729734.More infoAbstract: This research concerns the soil organic matter linked availability of water in forests on dry, sandy soils. Results show that changes in soil organic matter (SOM) storage influences soil water retention, especially at low SOM contents. Further the organic forest floor allows a significant evaporation flux from the forest floor (yearly max. 30% of the evapotranspiration). Sensitivity analyses show that forest transpiration is only indirectly affected by SOM. A change in water retention does hardly change the transpiration but can alter the strategies of water uptake by roots. Global changes can thus indirectly affect the vitality of forests although the effects may vary with soil type. © 1995 Elsevier B.V.
 Bouten, W., Schaap, M. G., Bakker, D. J., & Verstraten, J. M. (1992). Modelling soil water dynamics in a forested ecosystem. I: a site specific evaluation. Hydrological Processes, 6(4), 435444.More infoAbstract: On the basis of model results, the hydrological behaviour of the forest system is discussed, with special attention to transpiration and to the vertical and temporal dynamics of soil water contents, root water uptake and soil water fluxes. As water uptake by oaks and beeches is restricted to the unsaturated soil zone, high groundwater tables in the rather poorly drained duplex soil appear to have a large impact on the soil water dynamics. Suggestions are made on the implications of the hydrology for soil acidification. This discussion shows that a thorough knowledge of the hydrological behaviour of the system can greatly contribute to the understanding of biogeochemical processes and soil acidification. from Authors
Proceedings Publications
 Schaap, M. G. (2013, Summer). Statistical and scaling analyses of neural network soil property inputs/outputs at an Arizona field site.. In SIMUTECH 2013, Proceedings of the 3rd International Conference on Simulation & Modeling Methodologies, Technologies & Applications , 5.
 Shepard, C., Rasmussen, C. ., Crimmins, M. A., & Schaap, M. G. (2013, Fall). Soil modulation of ecosystem response to climate forcing across the Desert Southwest. In American Geophysical Union Fall Meetings.
 Buehler, M. G., Anderson, R. C., Seshadri, S., Schaap, M. G., & , . (2009). Prospecting for in situ resources on the Moon and Mars using wheelbased sensors. In 2005 IEEE Aerospace Conference, Vols 14, 607616.More info(12)The Apollo and Russian missions during 1970's were reviewed to rediscover the type and distribution of minerals on the Moon. This study revealed that the Moon has a restricted set of minerals when compared with the Earth. Results from lunar minerals brought back to Earth, indicate that the Moon lacks water, hydroxyl ions, and carbon based minerals. This mineral set is probably incomplete and so is the motivation for prospecting for other minerals using wheelbase sensors. Our approach to prospecting utilizes a vehicle with sensors embedded in a wheel that allow measurements while the vehicle is in motion. Once a change in soil composition is detected, decision making software stops the vehicle and analytical instruments perform a more quantitative soil analysis. This paper discusses instrumentation and data derived from wheelbased sensors.
 Buehler, M. G., Bostic, H., Chin, K. B., McCann, T., Keymeulen, D., Anderson, R. C., Seshadri, S., Schaap, M. G., & , . (2009). Electrical Properties Cup (EPC) for characterizing water content of martian and lunar soils. In 2006 IEEE Aerospace Conference, Vols 19, 363380.More infoIn this effort we used electrical impedance spectroscopy and a fourprobe apparatus, the Electrical Properties Cup (EPC), to measure the properties of various lunar and martian soil simulants. The impedance values are characterized by a resistancecapacitor network that is used to determine the soil conductivity and dielectric constant. In this effort we measured the impedance of different types of martian soil simulants (Silica sand, Atacama Desert sand, and Moses Lake basalt) and lunar simulants. The results show that the soil impedance measurements are strongly dependent on water content and soil type and to a lesser extent particle size and electrolyte concentration. This presentation describes the experimental fourprobe apparatus, procedures used to prepare the samples including soil washing and loading, and soil impedance measurements.
 Buehler, M. G., Sant, T. A., Brizendine, E., Keymeulen, D., Kuhlman, G. M., Schaap, M. G., Seshadri, S., Anderson, R. C., & , . (2005). Measuring water content of Martian soil simulants using planar fourprobes. In 2005 IEEE Aerospace Conference, Vols 14, 648659.More info(1,2) A miniature fourpoint probe instrument has been developed and applied to the characterization of the moisture content of the Martian soil simulants using fine and coarse silica sand and Moses Lake basalt. The results indicate that the soil resistivity varies over four orders of magnitude as the moisture content varied from 0.1% to over 10%. In addition it was found that forcing too much current through the sand sample resulted in a curious breakdown in the currentvoltage characteristic.
Presentations
 Schaap, M. G., & Zhang, Y. (2019, March 1). What do we Know About the Global Distribution of Soil Hydraulic Properties?. Departmental Seminar (Environmental Science), UCRiverside. Department of Environmental Science UCRiverside, California: UC Riverside.
 Rasmussen, C., Schaap, M. G., McKellar, T., & Crimmins, M. A. (2018, January). Tracking drought across the SW in a changing climate. Climate Assessment for the Southwest Seminar Series. Tucson, AZ: CLIMAS.
 Crimmins, M. A., McKellar, T., Rasmussen, C., Schaap, M. G., & Ferguson, D. B. (2017, September). Evaluating Existing and Developing New Drought Indices Using Modeled Soil Moisture Time Series. Climate Assessment for the Southwest  New Project Showcase. Tucson, AZ: Climate Assessment for the Southwest.
 Ferguson, D. B., Rasmussen, C., Schaap, M. G., McKellar, T., & Crimmins, M. A. (2017, March). Evaluating drought indices using modeled soil moisture time series. Climate Assessment for the Southwest Spring Meeting. Tucson, AZ: Climate Assessment for the Southwest.
 Volkmann, T. H., Sengupta, A., Pangle, L. A., Abramson, N., BarronGafford, G. A., Breshears, D. D., Bugaj, A., Chorover, J. D., Dontsova, K. M., Durcik, M., Ferre, P. A., Harman, C. J., Hunt, E. A., Kim, M., Maier, R. M., Matos, K. A., Alves Meira Neto, A., Meredith, L., Monson, R. K., , Niu, G., et al. (2017, December). Controlled Experiments of Hillslope Coevolution at the Biosphere 2 Landscape Evolution Observatory: Toward Prediction of Coupled Hydrological, Biogeochemical, and Ecological change. AGU International Annual Meeting. New Orleans, LA: American Geophysical Union (AGU).
 Zhang, Y., & Schaap, M. G. (2017, December). An improved Rosetta pedotransfer function and evaluation in earth system models. AGU Fall meeting. New Orleans.More infoSoil hydraulic parameters are often difficult and expensive to measure, leading to the pedotransfer functions (PTFs) an alternative to predict those parameters. Rosetta (Schaap et al., 2001, denoted as Rosetta1) are widely used PTFs, which is based on artificial neural network (ANN) analysis coupled with the bootstrap resampling method, allowing the estimation of van Genuchten water retention parameters (van Genuchten, 1980, abbreviated here as VG), saturated hydraulic conductivity (Ks), as well as their uncertainties. We present an improved hierarchical pedotransfer functions (Rosetta3) that unify the VG water retention and Ks submodels into one, thus allowing the estimation of univariate and bivariate probability distributions of estimated parameters. Results show that the estimation bias of moisture content was reduced significantly. Rosetta1 and Posetta3 were implemented in the python programming language, and the source code are available online. Based on different soil water retention equations, there are diverse PTFs used in different disciplines of earth system modelings. PTFs based on Campbell [1974] or Clapp and Hornberger [1978] are frequently used in land surface models and general circulation models, while van Genuchten [1980] based PTFs are more widely used in hydrology and soil sciences. We use an independent global scale soil database to evaluate the performance of diverse PTFs used in different disciplines of earth system modelings. PTFs are evaluated based on different soil characteristics and environmental characteristics, such as soil textural data, soil organic carbon, soil pH, as well as precipitation and soil temperature. This analysis provides more quantitative estimation error information for PTF predictions in different disciplines of earth system modelings.
 Schaap, M. G. (2015, 11/18). Lattice Boltzmann Simulations of Multiphase Behavior at the PoreScale. OSU. Oregon State University: Oregon State University.More infoAs part of a trip to OSU during my sabbatical, I have an hourlong presentation about past and current research on porescale modeling.
 Schaap, M. G., Levi, M. R., Zhang, Y., Xu, C., Rasmussen, C., & Larsen, J. (2015, May). Pedotransfer FunctionsAssisted Inversion of Vadose Zone Flow Models.. BSPM Curitiba, Brazil. Curitiba, Brazil: several federal, state organizations in Brazil.
 Shepard, C., Schaap, M. G., & Rasmussen, C. (2015, Nov.). Using Probability Distributions to Quantify Soil Development Variability with Time.. 2015 Soil Science Society of America Annual Meeting. Minneapolis, MN: Soil Science Society of America.More infoChris won the best oral presentation award for the Pedology division.
 Chorover, J. D., Pelletier, J. D., Breshears, D. D., Mcintosh, J. C., Rasmussen, C., Brooks, P. D., BarronGafford, G. A., Gallery, R. E., Ferre, P. A., Meixner, T., Niu, Y., Papuga, S. A., Schaap, M. G., & Troch, P. A. (2014, September). The CatalinaJemez CZO: Transformative Behavior of Energy, Water and Carbon in the Critical Zone II. Interactions between Long and Short Term Processes that Control Delivery of Critical Zone Services.. National Critical Zone Observatory AllHands Meeting.
 Naveed, M., Moldrup, P., Schaap, M. G., Tuller, M., Kulkarni, R., Vogel, H., & de Jonge, L. W. (2014, November). Prediction of Macropore Water and Air Flow at the Field Scale: Empirical Models v/s Lattice Boltzmann Simulations. ASACSSASSSA International Annual Meetings. Long Beach, CA: Soil Science Society of America.
 Guadagnini, A., Neuman, S. P., Schaap, M. G., & Riva, M. (2013, July). Statistical and Scaling Analyses of Neural Network Soil Property Inputs/Outputs at an Arizona Field Site. SIMUTECH 2013. Reykjavik, Iceland: SIMULTECH.
 Guadagnini, A., Neuman, S. P., Schaap, M. G., & Riva, M. (2013, September). Frequency Distributions and Scaling of Soil Texture and Hydraulic Properties in a Stratified Deep Vadose Zone near Maricopa, Arizona. IAMG. Madrid, Sapin: IAMG (presentation DOECRESP III).
 Schaap, M. G. (2013, October). Evaluation of Equations of State and Mixing Models for Simulating the BrineCO2 System with a Lattice Boltzmann Model Under Reservoir Conditions. Pore Scale Conference (UA). UA Marshall: UAHWR.
 Schaap, M. G., Tuller, M. ., Kulkarni, R., & Guber, A. (2013, December). Comparison of competing segmentation standards for Xray computed topographic imaging using Lattice Boltzmann techniques.. AGU Fall meeting 2013. San Fancisco: AGU (presentation: DOEBES).
 Schaap, M. G., Tuller, M., Kulkarni, R., & Guber, A. (2013, December). Comparison of competing segmentation standards for Xray computed topographic imaging using Lattice Boltzmann techniques.. AGU International Annual Meeting. San Fancisco: American Physical Union.
Poster Presentations
 McKellar, T., Crimmins, M. A., Schaap, M. G., Rasmussen, C., & Ferre, P. A. (2019, December). Using HYDRUS Soil Moisture Modeling to Improve Drought Index Usage on Arizona’s Rangelands. American Geophysical Union Annual Meeting. San Francisco, CA: American Geophysical Union.
 Shepard, C., Pelletier, J. D., Schaap, M. G., & Rasmussen, C. (2018, December). Signatures of obliquity and eccentricity in soil chronosequences. American Geophysical Union Annual Meetings.
 Shepard, C., Pelletier, J. D., Schaap, M. G., & Rasmussen, C. (2018, November). OBLIQUITY AND ECCENTRICITY SIGNALS FOUND IN A METAANALYSIS OF SOIL CHRONOSEQUENCES. Geological Society of America Annual Meetings.
 Troch, P. A., Zeng, X., Wang, Y., Van Haren, J. L., Tuller, M., Sibayan, M., Schaap, M. G., Saleska, S. R., Ruiz, J., Rasmussen, C., Pelletier, J. D., Niu, G., Monson, R. K., Meredith, L., Alves Meira Neto, A., Matos, K. A., Maier, R. M., Kim, M., Hunt, E. A., , Harman, C. J., et al. (2017, December). Controlled Experiments of Hillslope Coevolution at the Biosphere 2 Landscape Evolution Observatory: Toward Prediction of Coupled Hydrological, Biogeochemical, and Ecological change. 2017 AGU Fall Meeting, Abstract B43A2105. New Orleans, LA: American Geophysical Union (AGU).More infoUnderstanding the process interactions and feedbacks among water, microbes, plants, and porous geological media is crucial for improving predictions of the response of Earth’s critical zone to future climatic conditions. However, the integrated coevolution of landscapes under change is notoriously difficult to investigate. Laboratory studies are typically limited in spatial and temporal scale, while field studies lack observational density and control. To bridge the gap between controlled lab and uncontrolled field studies, the University of Arizona – Biosphere 2 built a macrocosm experiment of unprecedented scale: the Landscape Evolution Observatory (LEO). LEO consists of three replicated, 330m2 hillslope landscapes inside a 5000m2 environmentally controlled facility. The engineered landscapes contain 1m depth of basaltic tephra ground to homogenous loamy sand that will undergo physical, chemical, and mineralogical changes over many years. Each landscape contains a dense sensor network capable of resolving water, carbon, and energy cycling processes at submeter to wholelandscape scale. Embedded sampling devices allow for quantification of biogeochemical processes, and facilitate the use of chemical tracers applied with the artificial rainfall. LEO is now fully operational and intensive forcing experiments have been launched. While operating the massive infrastructure poses significant challenges, LEO has demonstrated the capacity of tracking multiscale matter and energy fluxes at a level of detail impossible in field experiments. Initial sensor, sampler, and restricted soil coring data are already providing insights into the tight linkages between water flow, weathering, and (micro) biological community development during incipient landscape evolution. Over the years to come, these interacting processes are anticipated to drive the model systems to increasingly complex states, potentially perturbed by changes in climatic forcing. By intensively monitoring the evolutionary trajectory, integrating data with models, and fostering communitywide collaborations, we envision that emergent landscape structures and functions can be linked and significant progress can be made toward predicting the coupled hydrobiogeochemical and ecological responses to global change.
 Troch, P. A., Zeng, X., Wang, Y., Van Haren, J. L., Tuller, M., Sibayan, M., Schaap, M. G., Saleska, S. R., Ruiz, J., Rasmussen, C., Pelletier, J. D., Niu, G., Monson, R. K., Meredith, L., Alves Meira Neto, A., Matos, K. A., Maier, R. M., Kim, M., Hunt, E. A., , Harman, C. J., et al. (2017, December). Controlled Experiments of Hillslope Coevolution at the Biosphere 2 Landscape Evolution Observatory: Toward Prediction of Coupled Hydrological, Biogeochemical, and Ecological change. AGU International Annual Meeting. New Orleans, LA: American Geophysical Union (AGU).
 Kulkarni, R., Kulkarni, R., Tuller, M., Schaap, M. G., Schaap, M. G., Rodriguez, J. J., Rodriguez, J. J., Rodriguez, J. J., Schaap, M. G., Kulkarni, R., Tuller, M., & Tuller, M. (2016, November). Synthesis of Sphere Packings for Evaluation of Image Segmentation Algorithms. ASACSSASSSA International Annual Meeting. Phoenix, AZ: Soil Science Society of America (SSSA).
 Kulkarni, R., Schaap, M. G., Rodriguez, J. J., & Tuller, M. (2016, Nov. 69). Synthesis of Sphere Packings for Evaluation of Image Segmentation Algorithms. ASACSSASSSA Intl. Annual Meeting. Phoenix, AZ: Soil Science Society of America (SSSA).
 Larsen, J. D., & Schaap, M. G. (2016, 2016). A porescale approach to colloidsurface interaction in liquid using lattice Boltzmann models.. AGU Fall meeting. San Francisco: USDANIFA.
 Larsen, J. D., & Schaap, M. G. (2016, October). Fundamental Pore Scale Mechanisms, Simplifications and Practical Relevance for Risk Analysis.. USDANIFA meeting October 1213, Washington DC. Washington DC: USDANIFA.
 Zhang, Y., Andersson, L., Herring, A., Wildenschild, D., & Schaap, M. G. (2016, December). Porescale Simulations of Capillary Trapping of CO2 Under Supercritical Conditions. AGU Fall meeting. San Francisco: DOE.
 Shepard, C., Schaap, M. G., & Rasmussen, C. (2015, Fall). EP31B1009 Probabilistic modeling of soil development variability with time. AGU Fall Meeting. San Francisco.
 Shepard, C., Schaap, M. G., & Rasmussen, C. (2015, Fall). Probabilistic modeling of soil property variability with time. CALS Research Forum. UA.
 Larsen, J. D., Schaap, M. G., Tuller, M., Kulkarni, R., & Guber, A. (2014, December). Challenges in the Segmentation and Analysis of Xray MicroCT Image Data.. AGU International Annual Meeting. Francisco, CA: American Geophysical Union.
 Schaap, M. G., & Wildenschild, D. (2014, December). Simulation of H2Ovapor and BrineCO2 in porous media with a Lattice Boltzmann Model. AGU Fall meeting 2014. San Francisco: DOE.More infoThis DOEBES funded study is a collaboration between Oregon State University (led by Dr. Dorthe Wildenschild) and the University of Arizona to investigate porescale aspects of capillary trapping to enhance the efficiency of geological CO2 sequestration. For the purposes of this project it is important to correctly simulate the physical conditions under which supercritical CO2 will be present after injection into the host rock. This means that the LB model should be able to handle the pressures, densities, temperatures in deep geological media. A logical way of dealing with is is to combine a singlecomponent LB model with and Equation of State (EOS) that describes the physical interrelations among pressure, temperature and density. Previously, we showed that the PengRobinson (PR) EOS provides an excellent fit to supercritical conditions for the pure CO2 system. However, it is necessary to consider multicomponent systems as the supercritical CO2 will be present with brines of varying salinity. A natural extension to the work under is to also treat the brine with an EOS. The brine will of be in a subcritical state and it is therefore important to find an EOS that can faithfully match the physical conditions of brine between temperatures of 300 and 400K and pressures between 7 and 30 MPa. This study will present a number of EOS alternatives that attempt to correctly capture the density of the liquid branch of the water system for relevant temperatures and pressures. We will also propose modifications that allow us to deal with different brine concentrations and compare LB modeled interfacial tension and viscosity with published data. As a secondary objective we investigate whether it is possible to match watervapor systems under ambient surface conditions relevant for vadose zone transport. Support: DOE DEFG0211ER16278
 Schaap, M. G., & Wildenschild, D. (2014, May). Optimizing capillary trapping of CO2 during geological carbon sequestration: Realistic Equations of State in a Lattice Boltzmann Model. DOEBES Geosciences meetin, Gaitherburg. Gaithersburg: DoE.More infoA relatively new mechanism for geologic sequestration of CO2 is the capillary trapping process, sometimes also referred to as residual trapping or relative permeability hysteresis trapping, which immobilizes CO2 at the porescale, thus preventing largescale movement of CO2 within an aquifer. As a sequestration mechanism, capillary trapping has several advantages over structural trapping, including not being affected by potentially compromised reservoir caprock; facilitating enhanced dissolution of gaseous CO2 into the brine; and allowing gaseous CO2 to be distributed over a larger reservoir volume, thus enhancing the potential for mineral weathering and carbonate precipitation. To date, relatively few experiments and models have addressed capillary trapping mechanisms in detail and at relevant reservoir conditions. Compared to most current largescale reservoir studies, the proposed research takes several steps back in scale to observe and model trapping at the porescale and to learn how these findings translate into continuum scale properties that can subsequently support improved modeling of sequestration at large spatiotemporal scales.A companion abstract by Dorthe Wildenschild describes our first experiments regarding the effect of varying interfacial tension, viscosity and flow rate on the resulting trapped amount of supercritical CO2 or its functional analogs. The current presentation deals with development of functionality into lattice Boltzmann models that to handle the physical conditions found in the experiments as well as relevant pressure and temperatures found in candidate geological reservoirs. The current focus is to test several van der Waalstype Equations of State (EOS, the relation between pressure, density and temperature) for the pure watervapor and the CO2 system near their respective critical points. We show that a wide range of conditions can be simulated and demonstrate that liquid and vapor densities and surface tension qualitatively (but not yet quantitatively) agree with published experimental data. Future modifications to the parametrization of the equation of state should lead to a better quantitative match for the watervapor and CO2 systems as well as the brine – super critical CO2 system. After obtaining suitable EOS's the Lattice Boltzmann models will be verified using the tomography results obtained by Wildenschild.
 Zeng, W., Xu, C., Huang, J., Wu, J., Schaap, M. G., & Tuller, M. (2014, November). A Novel Method for Estimation of Root Zone Moisture Content from EO1 Hyperion Hyperspectral Imagery. ASACSSASSSA International Annual Meetings. Long Beach, CA: Soil Science Society of America.
 Zhang, Y., & Schaap, M. G. (2014, December). Improved Rosetta Pedotransfer Estimation of Hydraulic Properties and Their Covariance. AGU Fall meeting 2014. San Francisco: DOE.More infoQuantitative knowledge of the soil hydraulic properties is necessary for most studies involving water flow and solute transport in the vadose zone. However, it is always expensive, difficult, and time consuming to measure hydraulic properties directly. Pedotransfer functions (PTFs) have been widely used to forecast soil hydraulic parameters. Rosetta is is one of many PTFs and based on artificial neural network analysis coupled with the bootstrap sampling method. The model provides hierarchical PTFs for different levels of input data for Rosetta (H1H5 models, with higher order models requiring more input variables). The original Rosetta model consists of separate PTFs for the four “van Genuchten” (VG) water retention parameters and saturated hydraulic conductivity (Ks) because different numbers of samples were available for these characteristics. In this study, we present an improved Rosetta pedotransfer function that uses a single model for all five parameters combined; these parameters are weighed for each sample individually using the covariance matrix obtained from the curvefit of the VG parameters to the primary data. The optimal number of hidden nodes, weights for saturated hydraulic conductivity and water retention parameters in the neural network and bootstrap realization were selected. Results show that root mean square error (RMSE) for water retention decreased from 0.076 to 0.072 cm3/cm3 for the H2 model and decreased from 0.044 to 0.039 cm3/cm3 for the H5 model. Mean errors which indicate variable matric potentialdependent bias were also reduced significantly in the new model. The RMSE for Ks increased slightly (H2: 0.717 to 0.722; H5: 0.581 to 0.594); this increase is minimal and a result of using a single model for water retention and Ks. Despite this small increase the new model is recommended because of its improved estimation of water retention, and because it is now possible to calculate the full covariance matrix of soil water retention parameters and saturated hydraulic conductivity together in one neural network model, which will be useful in stochastic modeling and riskbased analysis.
 Schaap, M. G. (2013, December). Evaluation of Equations of State and Mixing Models for Simulating the BrineCO2 System with a Lattice Boltzmann Model Under Reservoir Conditions.. AGU Fall meeting 2013. San Fancisco: AGU (poster: DOEBES).
 Schaap, M. G., Neuman, S. P., Riva, M., & Guadagnini, A. (2013, December). 43. Heterogeneity Preserving Inversion Method for Subsurface Unsaturated Flow.. AGU Fall meeting 2013. San Fancisco: AGU (posyer: DOECRESPIII).
 Schaap, M. G., Schaap, M. G., Kopp, E. S., Kopp, E. S., Pohlman, M. A., Pohlman, M. A., Jones, C. A., Jones, C. A., Chorover, J. D., & Chorover, J. (2013, December). Pre and PostFire Infiltration Rates in a Montane Mixed Conifer Ecosystem. AGU Fall meeting 2013. San Fancisco: AGU (poster: NSFCZO).
Reviews
 Vereecken, H., Weynants, M., Javaux, M., Pachepsky, Y., Schaap, M. G., & van Genuchten, M. T. (2013. Using Pedotransfer Functions to Estimate the van GenuchtenMualem Soil Hydraulic Properties: A Review(pp 795820).More infoWe reviewed the use of the van GenuchtenMualem (VGM) model to parameterize soil hydraulic properties and for developing pedotransfer functions (PTFs). Analysis of literature data showed that the moisture retention characteristic (MRC) parameterization by setting shape parameters m = 1  1/n produced the largest deviations between fitted and measured water contents for pressure head values between 330 (log(10) pressure head [pF] 2.5) and 2500 cm (pF 3.4). The Schaapvan Genuchten model performed best in describing the unsaturated hydraulic conductivity, K. The classical VGM model using fixed parameters produced increasingly higher root mean squared residual, RMSR, values when the soil became drier. The most accurate PTFs for estimating the MRC were obtained when using textural properties, bulk density, soil organic matter, and soil moisture content. The RMSR values for these PTFs approached those of the direct fit, thus suggesting a need to improve both PTFs and the MRC parameterization. Inclusion of the soil water content in the PTFs for K only marginally improved their prediction compared with the PTFs that used only textural properties and bulk density. Including soil organic matter to predict K had more effect on the prediction than including soil moisture. To advance the development of PTFs, we advocate the establishment of databases of soil hydraulic properties that (i) are derived from standardized and harmonized measurement procedures, (ii) contain new predictors such as soil structural properties, and (iii) allow the development of timedependent PTFs. Successful use of structural properties in PTFs will require parameterizations that account for the effect of structural properties on the soil hydraulic functions.