The Comparison of Inverse approaches Simulation-Optimization and Surrogate Transport Model for Pollution Source Characteristics Identification in Aquifer-River Integrated Systems

Document Type : Research Paper

Authors

1 Ph.D. Candidate, Engineering and Water Management Department, Faculty of Agriculture, Tarbiat Modares University, Tehran, Iran.

2 Professor, Engineering and Water Management Department, Faculty of Agriculture, Tarbiat Modares University, Tehran, Iran.

3 Retired Professor, Civil Engineering Department, Faculty of Civil Engineering and Architecture, Shahid Chamran University of Ahvaz, Iran (Visiting Professor at Tarbiat Modares University).

4 Associate Professor, Engineering and Water Management Department, Faculty of Agriculture, Tarbiat Modares University, Tehran, Iran

Abstract

The identification of potential pollution sources and their continuous monitoring is one of the most important measures in the quality management of groundwater and surface water resources. Since the relation between these two systems and the injected pollution pattern at the source is not easily discernible, inverse methods are recommended. In this paper, the inverse solution of the ADE equation is conducted using the simulation-optimization approach to identify the characteristics of a pollution source that is released in a confined aquifer and reaches a river, then moves along the stream to a monitoring cross-section where it is detected. The proposed case studies were not investigated before.
The inverse method combines the forward model and an optimization algorithm. To speed up the computation, the transfer function theory is applied to create a surrogate transport forward model. The two approaches are compared in terms of accuracy and speed of solution for two hypothetical cases (The second example, considering the geometric dimensions of the Karun River in Iran). The result show transfer function methodology used to create a surrogate transport model is convenient, very fast compared to other existing approaches, and more accurate in the reconstruction of source characteristics even in presence of noise on observations. Moreover, each application of the transfer function to surrogate the transport process requires only 0.56 percent of the computation time of the complete simulation model. So due to its effect on significantly increasing the reverse resolution speed, it can be used for real scenarios of pollutant transport problems that generally face time constraints.

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