Predicting Transient Storage Model Parameters of Rivers by Genetic Algorithm

The presence of transient storage zone modifies the riverine pollutant transport. In the present work, new empirical expressions for three key parameters of transient storage model (TSM), an important method for predicting concentration variation of pollutants in rivers, have been derived employing genetic algorithm on published hydraulic data on river reaches and TSM parameters. The proposed expressions use few hydraulic and geometric characteristics of rivers that are usually available. Based on various performance indices, it can be concluded that the proposed expressions predict TSM parameters more reliably in comparison to the other empirical expressions for predicting TSM parameters. Copyright Springer Science+Business Media B.V. 2012