Impacts of the river water pollution control on the health of aquatic animals in downstream

Water pollution is one of the most significant environmental issues and problems. Surface water, running water, and rivers are always the most polluted, due to passing through numerous areas. The objective of this study is to investigate the water quality of Euphrates River in central Iraq in terms of aquaculture, as well as how to control the concentrations of pollutants. About ۶۰-km length of Euphrates River was modeled using artificial neural networks (ANN) using qualitative data. The standard range of polluting substances for aquaculture was evaluated, and the effect of implementing the scenario of controlling point sources of pollution and preventing the flow from coming into contact with waste piles and animal excrement were studied. Statistical criteria, including NSE, RMSE, and MAE, were used to evaluate the model performance in the training and testing phases. According to the results, implementing the desired scenario has reduced the concentrations of all pollutants to an acceptable level for aquaculture. The most significant decrease occurred in the regions closest to the industries and factories (۰-۱۰ km), while the slightest change occurred in the farthest reaches of the study area (۵۰-۶۰ km). The findings of this study can be used to implement water quality controls at the optimal time and location to influence the Euphrates River general state.

Keywords:

Pollution , Artificial Neural Networks , Aquatic animals , Euphrates river