Empirical approach for modeling of partition coefficient on lead concentrations in riverine sediment

Abstract

Since a large part of heavy metals input in aquatic system accumulates in sediment, their concentrations in sediment are regarded as an important indicator of the heavy metal pollution of aquatic environment. The partition coefficient (Kd) is an empirical parameter that can represent the interaction of heavy metals at the sediment-water interface in aquatic system, however, it is not always stable with environmental conditions. Therefore, the introduction of Kd model with dominant physicochemical parameters would facilitate and improve the simulation of heavy metals concentrations in riverine sediment. The present study aims to develop a Kd model considering four physicochemical properties in stream water in order to simulate heavy metal concentrations in sediment of severely polluted urban rivers. Lead (Pb) concentrations in sediment of Harrach River, Algeria, were simulated using one-dimensional distributed hydrological model incorporating with presented Kd model. Multivariable equation of Kd model with physicochemical parameters (pH, suspended solid concentration (SS), chemical oxygen demand (COD) and biological oxygen demand (BOD)) was obtained from multiple regression analysis with observation data in various environmental condition. Hydrological simulations were tested with Kd model comparing to giving constant Kd. The numerical results agreed better with Kd model than with constant Kd, where the results accuracy increased from R2 0.05 for constant Kd to R2 0.67 for Kd model.