Alshahri, M., Al-Mashhadany, M. (2025). Evaluation of Surface Water Quality for Aquatic Life Using Artificial Intelligence Method. Egyptian Journal of Aquatic Biology and Fisheries, 29(1), 2879-2892. doi: 10.21608/ejabf.2025.415221
Mohammed Alshahri; Mohammed Al-Mashhadany. "Evaluation of Surface Water Quality for Aquatic Life Using Artificial Intelligence Method". Egyptian Journal of Aquatic Biology and Fisheries, 29, 1, 2025, 2879-2892. doi: 10.21608/ejabf.2025.415221
Alshahri, M., Al-Mashhadany, M. (2025). 'Evaluation of Surface Water Quality for Aquatic Life Using Artificial Intelligence Method', Egyptian Journal of Aquatic Biology and Fisheries, 29(1), pp. 2879-2892. doi: 10.21608/ejabf.2025.415221
Alshahri, M., Al-Mashhadany, M. Evaluation of Surface Water Quality for Aquatic Life Using Artificial Intelligence Method. Egyptian Journal of Aquatic Biology and Fisheries, 2025; 29(1): 2879-2892. doi: 10.21608/ejabf.2025.415221
Evaluation of Surface Water Quality for Aquatic Life Using Artificial Intelligence Method
Surface water is considered one of the most invaluable natural resources in the world, finding its application for many purposes. Water quality is affected by many natural changes and human activities; therefore, assessment of its suitability is of great importance. This study determined the suitability of Wadi Akab and the Tigris River waters for aquatic life using pH, temp., TDS, Tur., PO4, NO3, F. coli, and DO%. Samples were collected every two weeks and analyzed from 7 sites from June 2024 to December 2024 with 10 replicates. ANFIS artificial intelligence model was applied, and the results showed that Wadi Akab water is unsuitable for aquatic life, and it was classified as poor except for the first site, which was very poor due to the high level of most of the measured parameters and the low saturated oxygen concentration that did not exceed 20%. The performance of ANFIS was verified by applying the NSFWQI model and comparing it using the statistical criteria R2, RMSE and MAPE and the results were 0.9, 3.86 and 6.85 respectively. These results confirmed the degree of convergence between the NSFWQI model and the ANFIS model. The ANFIS model can be used as an effective tool for estimating surface water quality indicators for aquatic life purposes in the study area and other areas with similar conditions.
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