Inverse Modeling of Contaminant Transport for Pollution Source Identification in Surface and Groundwaters: A Review

Abstract

Abstract Fast and accurate identification of unknown pollution sources is a crucial and challenging task in water resources management , in which the characteristics of unknown pollution sources should be determined from temporal or spatial distribution of concentration data at limited observation points. This field of research is currently in the stage of rapid development, but is not thorough yet. A review of the literature suggested that, one of the main gaps lies in the extension of methods to more realistic cases. Several methods were introduced to solve the source identification problem with novel variations and extensions, however most of them had never been tested in real-world applications and the underlying transport processes was greatly simplified. Most recently the paramount importance of the practical aspect of the pollution source identification problem is more appreciated. More particularly, there have been a growing interest to consider complex real-world scenarios, reduce associated computational cost and quantify the uncertainty in retrieved source characteristics. However, the dissemination of research results to practice has been slow. This paper reviews some studies in the context of pollution source identification in surface and groundwater. The current issues, limitations, and suggestions for future studies are also discussed.