ارزیابی مدلهای فراکاوشی نوین در تحلیل کیفی آب رودخانه ها

Knowledge of the quality of water resources is one of the important requirements in the planning and development of water resources and its protection. Rivers are of particular importance as the main source of supply for drinking, agriculture and industry. Therefore, in this research, in order to estimate the amount of dissolved solids in the water of Kashkan river located in Lorestan province, a hybrid model of artificial neural network-bat algorithm was used, and for this purpose, qualitative parameters include hydrogen carbonate, chloride, sulfate, calcium, magnesium, sodium, and discharge. The flow in the monthly time scale during the statistical period (2012-2022) and the amount of dissolved solids in water were selected as output parameters. The criteria of correlation coefficient, root mean square error and Nash Sutcliffe coefficient were used to evaluate and perform the model. The obtained results showed that the investigated hybrid model has a correlation coefficient (0.998), root mean square error (0.037 mg/lit) and Nash Sutcliffe criterion (0.984) in the validation stage, it was able to estimate the amount with acceptable accuracy. Solids soluble in water.