Recovering the salinity intensity of distributed sources in the river using inverse simulation-optimization approach

Document Type : Research Article

Authors

1 Department of Water Structures Engineering/Faculty of Agriculture,/Tarbiat Modares University/ tehran/iran

2 Department of Water Structures Engineering/Faculty of Agriculture,/Tarbiat Modares University/tehran/iran

3 Department of Water Engineering/ Faculty of Civil Engineering/Shahid Chamran University/ahvaz/iran

Abstract

In recent years, the issue of identifying the polluting sources in the rivers has been one of the most important topics in scientific research in the field of water. In the main research, the pollutant sources have been considered as the point sources, and in order to recover pollutant concentration, it is necessary to have an observation point for each source. In this study, the places where groundwater enters to river are considered as distributed sources with known locations and length and the goal is to recover the intensity of sources, using only one observation point. The sources which considered are distributed sources with constant loading and significant distance from each other. The existence of distance among sources prevents the complete mixing of concentration at the observation point. This matter and also the constant intensity of loading, makes it possible to recover several distributed sources using only one observation point. For this purpose, the inverse solution of the advection-dispersion equation is done using the simulation-optimization approach. To design the backward model, MIKE11, linked with a genetic algorithm in MATLAB. Considering one observation point for recovering the intensity of several distributed sources is the advantage of the present study. The model was verified by using hypothetical examples, 40km section of Karun River, and by applying 5 and 15 percent noise to the observation data. The results demonstrate that the backward model can recover the intensity of several sources not only with one observation point but also with data from the concentration versus time curve at the observation point. The accuracy of the model in recovering resource intensity, according to statistical indicators, is more than 99%.

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References

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Amirkabir Journal of Civil Engineering
Volume 55, Issue 12
2024
Pages 2503-2526

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