Prediction leaching of potassium using the convective–dispersive and the convective log-normal transfer function models

Abstract

There is increasing concern about soil enrichment with K⁺ and subsequent potential losses following long-term application of poor quality water to agricultural land. Different models are increasingly being used for predicting or analyzing water flow and chemical transport in soils and groundwater. The convective–dispersive equation (CDE) and the convective log-normal transfer function (CLT) models were fitted to the potassium (K⁺) leaching data. The CDE and CLT models produced equivalent goodness of fit. Simulated breakthrough curves for a range of CaCl₂ concentration based on parameters of 15 mmol l⁻¹ CaCl₂ were characterised by an early peak position associated with higher K⁺ concentration as the CaCl₂ concentration used in leaching experiments decreased. In another method, the parameters estimated from 15 mmol l⁻¹ CaCl₂ solution were used for all other CaCl₂ concentrations, and the best value of retardation factor (R) was optimised for each data set. A better prediction was found. With decreasing CaCl₂ concentration the value of R is required to be more than that measured (except for 10 mmol l⁻¹ CaCl₂), if the estimated parameters of 15 mmol l⁻¹ CaCl₂ are used. The two models suffer from the fact that they need to be calibrated against a data set, and some of their parameters are not measurable and cannot be determined independently.