Pedo-transfer functions with multiple linear regressions to predict solute-transport parameters
Abstract
Transport
parameters of soluble chemicals through soils are needed to assess the
pollution risks of soil and groundwater resources. But, it is time consuming,
laborious, expensive and, practically, impossible to experimentally measure
such parameters for a wide range of solutes and soil types. So, indirect
estimate of the parameters by pedo-transfer function is becoming popular. The
aim of this study was to develop and evaluate pedo-transfer functions (PTFs)
for solute-transport parameters by multiple linear regression (MLR) analysis.
For this, transport parameters of three heavy metal /metalloid
compounds (NaAsO2, Pb(NO3)2, Cd(NO3)2),
a pesticide (carbendazim) and an inert salt (CaCl2) through 14
agricultural soils of Bangladesh were determined. The transport experiments
were done in repacked soil columns under unsaturated steady-state water flow
conditions. Breakthrough data of the solutes were measured with time-domain
reflectometry (TDR), and velocity (V),
dispersion coefficient (D) and
retardation factor (R) of the solutes
were determined by analyzing the data by a transfer-function method. Bulk
density (g),
organic carbon (OC) content, clay (C) content, pH, median grain diameter (D50) and uniformity
coefficient (Cu) of the
soils were determined. Regression models for V, D and R were developed with g, OC, C,
pH, D50 and Cu as the input variables.
Bulk density and clay content were found the most sensitive input variables to
the MLR models. The MLR models fairly predicted V, D and R, and thus provide a way of
significantly enhancing prediction of reactive solute transport through
agricultural soils.
Keywords
References
- Achat, D.L., Pousse, N., Nicolas, M., Brédoire, F., Augusto, L., 2016. Soil properties controlling inorganic phosphorus availability: general results from a national forest network and a global compilation of the literature. Biogeochemistry 127(2–3): 255–272.
- Alibuyog, N.R., 2007. Development of pedotransfer functions for predicting soil hydraulic properties and solute-transport parameters using artificial neural network analysis. Ph.D. Thesis in Agricultural Engineering, University of the Philippines Los Baños, Philippines.
- Black, C.A., 1965. Method of soil analysis. Part-I and II. Agronomy No. 9. American Society of Agronomy, Madison, Wisconsin, USA.
- Bouma, J., 1989. Using soil survey data for quantitative land evaluation. In: Advances in Soil Science. Springer, New York, NY. pp. 177–213.
- Bromly, M., Hinz, C., Aylmore, L.A.G., 2007. Relation of dispersivity to properties of homogeneous saturated repacked soil columns. European Journal of Soil Science 58(1): 293–301.
- BS 1377, 1990. Methods of Test for Soils for Civil Engineering Purposes. British Standards Institution, London. 2004.
- Dian-qing, L.V., Wang, H., Pan, Y., Wang, L., 2010. Effect of bulk density changes on soil solute transport characteristics. Journal of Natural Science of Hunan Normal University 33(1): 75–79.
- Draper, N.R., Smith, H., 1981. Applied Regression Analysis. 2nd edn. John Wiley and Sons. New York, USA.
Details
Primary Language
English
Subjects
-
Journal Section
Research Article
Authors
Md. Abdul Mojid
*
This is me
Bangladesh
A.b.m. Zahid Hossain
This is me
Bangladesh
Guido C.l. Wyseure
This is me
Belgium
Md. Ali Ashraf
This is me
Bangladesh
Publication Date
July 1, 2019
Submission Date
October 11, 2018
Acceptance Date
April 15, 2019
Published in Issue
Year 2019 Volume: 8 Number: 3
Cited By
Artificial neural network model to predict transport parameters of reactive solutes from basic soil properties
Environmental Pollution
https://doi.org/10.1016/j.envpol.2019.113355Comparative performance of multiple linear regression and artificial neural network models in estimating solute-transport parameters
SAINS TANAH - Journal of Soil Science and Agroclimatology
https://doi.org/10.20961/stjssa.v18i1.49207