Parametric Estimation of Water Retention Using Mgmdh Method and Principal Component Analysis

Mohammad Reza Neyshaburi, Hossein Bayat, Mostafa Rastgou, Kourosh Mohammadi, Andrew S. Gregory, Nader Nariman-Zadeh

Abstract


Performing a primary analysis, such as principal component analysis (PCA) may increase accuracy and reliability of developed pedotransfer functions (PTFs). This study focuses on the usefulness of the soil penetration resistance (PR) and principal components (PCs) as new inputs along with the others to develop the PTFs for estimating the soil water retention curve (SWRC) using a multi-objective group method of data handling (mGMDH). The Brooks and Corey (1964) SWRC model was used to give a description of the water retention curves and its parameters were determined from experimental SWRC data. To select eight PCs, PCA was applied to all measured or calculated variables. Penetration resistance, organic matter (OM), aggregates mean weight diameter (MWD), saturated hydraulic conductivity (Ks), macro porosity (Mp), micro porosity (Mip) and eight selected PCs were used as predictors to estimate the Brooks and Corey model parameters by mGMDH. Using PR or OM, Ks and MWD, improved the estimation of SWRC in some cases. Using the predicted PR can be useful in the estimation of SWRC. Using either the MP and Mip or the eight PCs significantly improved the PTFs accuracy and reliability. It would be very useful to apply PCA on the original variables as a primary analysis to develop parametric PTFs.

Keywords


Multi-objective group method of data handling; pedotransfer function; principal component analysis; Parametric estimation

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References


Atashkari K., Nariman-Zadeh N., Pilechi A., Jamali A., Yao X., 2005. Thermodynamic Pareto optimization of turbojet engines using multi-objective genetic algorithms. International Journal of Thermal Sciences, 44, 1061–1071.

Bayat H., Neyshabouri M., Mohammadi K., Nariman-Zadeh N., 2011. Estimating water retention with pedotransfer functions using multi-objective group method of data handling and ANNs. Pedosphere, 21, 107–114.

Bayat H., Neyshaburi M.R., Hajabbasi M.A., Mahboubi A.A., Mosaddeghi M.R., 2008. Comparing neural networks, linear and nonlinear regression techniques to model penetration resistance. Turkish Journal of Agriculture and Forestry, 32, 42–433.

Bayat H., Neyshaburi M.R., Mohammadi K., Nariman-Zadeh N., Irannejad M., 2013. Improving water content estimations using penetration resistance and principal component analysis. Soil and Tillage Research, 129, 83–92.

Bayat H., Neyshaburi M.R., Mohammadi K., Nariman-Zadeh N., Irannejad M., Gregory A.S., 2013. Combination of artificial neural networks and fractal theory to predict soil water retention curve. Computers and Electronics in Agriculture, 92, 92–103.

Bouma J., 1989. Using soil survey data for quantitative land evaluation. Journal, 177–213.

Brooks R., Corey T., 1964. HYDRAU UC PROPERTIES OF POROUS MEDIA.

Brooks R.H., Corey A.T., 1964. Hydraulic properties of porous media. Hydrology Papers, Colorado State University.

Clapp R.B., Hornberger G.M., 1978. Empirical equations for some soil hydraulic properties. Water resources research, 14, 601–604.

Cosby B., Hornberger G., Clapp R., Ginn T., 1984. A statistical exploration of the relationships of soil moisture characteristics to the physical properties of soils. Water Resources Research, 20, 682–690.

Davatgar N., Kavoosi M., Alinia M.H., Peykan M., 2006. Study of Potassiun Status and Effect of Physical and Chemical Properties of Soil on it in Paddy Soils of Guilan-Province. JWSS - Isfahan University of Technology, 9, 71-89.

Diebold F.X., Mariano R.S., 2002. Comparing predictive accuracy. Journal of Business & economic statistics, 20.

Effron B., Tibshirani R.J., 1994. An Introduction to the Bootstrap (Monographs on Statistics and Applied Probability). Journal.

Freund R., Littell R., 1991. SAS system for regression, 1991. SAS Institute, Cary, NC.

Grunwald S., Rooney D., McSweeney K., Lowery B., 2001. Development of pedotransfer functions for a profile cone penetrometer. Geoderma, 100, 25–47.

Jalali M., 2007. A study of the quantity/intensity relationships of potassium in some calcareous soils of Iran. Arid Land Research and Management, 21, 133–141.

Jana R.B., Mohanty B.P., 2011. Enhancing PTFs with remotely sensed data for multiscale soil water retention estimation. Journal of hydrology, 399, 201–211.

Jana R.B., Mohanty B.P., Springer E.P., 2007. Multiscale pedotransfer functions for soil water retention. Vadose Zone Journal, 6, 868–878.

Khodaverdiloo H., Homaee M., van Genuchten M.T., Dashtaki S.G., 2011. Deriving and validating pedotransfer functions for some calcareous soils. Journal of hydrology, 399, 93–99.

Luckner L., Van Genuchten M.T., Nielsen D., 1989. A consistent set of parametric models for the two–phase flow of immiscible fluids in the subsurface. Water Resources Research, 25, 2187–2193.

Mayr T., Jarvis N., 1999. Pedotransfer functions to estimate soil water retention parameters for a modified Brooks–Corey type model. Geoderma, 91, 1–9.

Minasny B., McBratney A., 2002. The Method for Fitting Neural Network Parametric Pedotransfer Functions. Soil Science Society of America Journal, 66, 352–361.

Mulqueen J., Stafford J., Tanner D., 1977. Evaluation of penetrometers for measuring soil strength. Journal of Terramechanics, 14, 137-151.

Nariman-Zadeh N., Atashkari K., Jamali A., Pilechi A., Yao X., 2005. Inverse modelling of multi-objective thermodynamically optimized turbojet engines using GMDH-type neural networks and evolutionary algorithms. Engineering Optimization, 37, 437–462.

Nemes A., Roberts R., Rawls W.J., Pachepsky Y.A., Van Genuchten M.T., 2008. Software to estimate− 33 and− 1500kPa soil water retention using the non-parametric k-Nearest Neighbor technique. Environmental Modelling & Software, 23, 254–255.

Nemes A., Schaap M., Wösten J., 2003. Functional evaluation of pedotransfer functions derived from different scales of data collection. Soil Science Society of America Journal, 67, 1093–1102.

Nemes A., Timlin D., Pachepsky Y.A., Rawls W., 2009. Evaluation of the Pedotransfer Functions for their Applicability at the US National Scale. Soil Science Society of America Journal, 73, 1638–1645.

Neyshaburi M.R., Bayat H., Mohammadi K., Nariman-Zadeh N., Irannejad M., 2014. Improvement in estimation of soil water retention using fractal parameters and multiobjective group method of data handling. Archives of Agronomy and Soil Science, 61, 257–273.

Pachepsky Y., Rawls W., Gimenez D., Watt J., 1998. Use of soil penetration resistance and group method of data handling to improve soil water retention estimates. Soil and Tillage Research, 49, 117–126.

Pachepsky Y.A., Rawls W., 1999. Accuracy and reliability of pedotransfer functions as affected by grouping soils. Soil Science Society of America Journal, 63, 1748–1757.

Pachepsky Y.A., Rawls W., Lin H., 2006. Hydropedology and pedotransfer functions. Geoderma, 131, 308–316.

Pan F., Pachepsky Y., Jacques D., Guber A., Hill R.L., 2012. Data assimilation with soil water content sensors and pedotransfer functions in soil water flow modeling. Soil Science Society of America Journal, 76, 829–844.

Rajkai K., Kabos S., Van Genuchten M.T., 2004. Estimating the water retention curve from soil properties: comparison of linear, nonlinear and concomitant variable methods. Soil and Tillage Research, 79, 145–152.

Rawls W., Brakensiek D., Saxton K., 1982. Estimation of soil water properties. Trans. Asae, 25, 1316–1320.

Rawls W., Pachepsky Y.A., Ritchie J., Sobecki T., Bloodworth H., 2003. Effect of soil organic carbon on soil water retention. Geoderma, 116, 61–76.

Saxton K., Rawls W.J., Romberger J., Papendick R., 1986. Estimating generalized soil-water characteristics from texture. Soil Science Society of America Journal, 50, 1031–1036.

Schaap M.G., Bouten W., 1996. Modeling water retention curves of sandy soils using neural networks. Water Resources Research, 32, 3033-3040.

Schaap M.G., Leij F.J., van Genuchten M.T., 1998. Neural network analysis for hierarchical prediction of soil hydraulic properties. Soil Science Society of America Journal, 62, 847–855.

Schaap M.G., Leij F.J., van Genuchten M.T., 2001. Rosetta: A computer program for estimating soil hydraulic parameters with hierarchical pedotransfer functions. Journal of hydrology, 251, 163–176.

Scheinost A., Sinowski W., Auerswald K., 1997. Regionalization of soil water retention curves in a highly variable soilscape, I. Developing a new pedotransfer function. Geoderma, 78, 129–143.

Sharma S.K., Mohanty B.P., Zhu J., 2006. Including topography and vegetation attributes for developing pedotransfer functions. Soil Science Society of America Journal, 70, 1430–1440.

Starks P.J., Heathman G.C., Ahuja L.R., Ma L., 2003. Use of limited soil property data and modeling to estimate root zone soil water content. Journal of Hydrology, 272, 131–147.

Tietje O., Tapkenhinrichs M., 1993. Evaluation of pedo-transfer functions. Soil Science Society of America Journal, 57, 1088–1095.

Timlin D., Ahuja L., Pachepsky Y., Williams R., Gimenez D., Rawls W., 1999. Use of Brooks-Corey parameters to improve estimates of saturated conductivity from effective porosity. Soil Science Society of America Journal, 63, 1086–1092.

To J., Kay B.D., 2005. Variation in penetrometer resistance with soil properties: The contribution of effective stress and implications for pedotransfer functions. Geoderma, 126, 261–276.

Tomasella J., Pachepsky Y., Crestana S., Rawls W., 2003. Comparison of two techniques to develop pedotransfer functions for water retention. Soil Science Society of America Journal, 67, 1085–1092.

Tóth B., Makó A., Guadagnini A., Tóth G., 2012. Water retention of salt-affected soils: quantitative estimation using soil survey information. Arid Land Research and Management, 26, 103–121.

Twarakavi N.K., Šimůnek J., Schaap M., 2009. Development of pedotransfer functions for estimation of soil hydraulic parameters using support vector machines. Soil Science Society of America Journal, 73, 1443–1452.

Ungaro F., Calzolari C., Busoni E., 2005. Development of pedotransfer functions using a group method of data handling for the soil of the Pianura Padano–Veneta region of North Italy: water retention properties. Geoderma, 124, 293–317.

Vanden Berg M., Klamt E., Van Reeuwijk L., Sombroek W., 1997. Pedotransfer functions for the estimation of moisture retention characteristics of Ferralsols and related soils. Geoderma, 78, 161–180.

Van Genuchten M.T., 1980. A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Science Society of America Journal, 44, 892–898.

Van Genuchten M.T., Leij F., Yates S., 1991. The RETC code for quantifying the hydraulic functions of unsaturated soils.

Vaz C.M., Bassoi L.H., Hopmans J.W., 2001. Contribution of water content and bulk density to field soil penetration resistance as measured by a combined cone penetrometer–TDR probe. Soil and Tillage Research, 60, 35–42.

Vereecken H., Diels J., Van Orshoven J., Feyen J., Bouma J., 1992. Functional evaluation of pedotransfer functions for the estimation of soil hydraulic properties. Soil Science Society of America Journal, 56, 1371–1378.

Vereecken H., Maes J., Feyen J., Darius P., 1989. Estimating the soil moisture retention characteristic from texture, bulk density, and carbon content. Soil science, 148, 389–403.

Wagner B., Tarnawski V., Wessolek G., Plagge R., 1998. Suitability of models for the estimation of soil hydraulic parameters. Geoderma, 86, 229–239.

Wösten J., Pachepsky Y.A., Rawls W., 2001. Pedotransfer functions: bridging the gap between available basic soil data and missing soil hydraulic characteristics. Journal of hydrology, 251, 123–150.




DOI: http://dx.doi.org/10.17951/pjss.2016.49.1.29
Date of publication: 2017-01-03 11:33:38
Date of submission: 2017-01-03 11:26:53


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Copyright (c) 2017 Mohammad Reza Neyshaburi, Hossein Bayat, Mostafa Rastgou, Kourosh Mohammadi, Andrew S. Gregory, Nader Nariman-Zadeh

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