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 pedotransfer 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 (γ), 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 γ, 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.