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Impacts of the river water pollution control on the health of aquatic animals in downstream | ||
| Caspian Journal of Environmental Sciences | ||
| دوره 20، شماره 5، اسفند 2022، صفحه 939-946 اصل مقاله (891.84 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22124/cjes.2022.6041 | ||
| نویسندگان | ||
| Tasneem Younus Taraki* 1؛ Sarab W. Alwash2؛ Taif Ahmed3؛ Shaymaa Bdulhameed Khudair4؛ Ahmed S. Abed5؛ Ayoob Murtadha Alshaikh Faqri6 | ||
| 1Department of Dentistry, Al-Noor University College, Bartella, Iraq | ||
| 2Medical Laboratory Techniques Department, Al-Mustaqbal University College, 51001 Hillah, Babylon, Iraq | ||
| 3college of pharmacy, Al-Farahidi University/ Iraq | ||
| 4Advanced Biomedical Science/ Al-Nisour University College/ Baghdad/ Iraq | ||
| 5Department of Prosthetic Dental Technology/ Hilla University college, Babylon, Iraq | ||
| 6Mazaya University College/ Iraq | ||
| چکیده | ||
| 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 60-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 (0-10 km), while the slightest change occurred in the farthest reaches of the study area (50-60 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. | ||
| کلیدواژه‌ها | ||
| Pollution؛ Artificial neural networks؛ Aquatic animals؛ Euphrates River | ||
| مراجع | ||
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