Applied Research in Water Engineering

Applied Research in Water Engineering

Hydrogeochemical Investigation of Kakarza River Surface Water and Evaluation of Artificial Intelligence Performance in Estimating Its Quality Parameters

Document Type : Original Article

Authors
1 Department of Geology, Lorestan University, Lorestan, Iran.
2 Geological Laboratory Expert, Lorestan University, Lorestan, Iran.
3 Department of Environment, Faculty of Natural Resources, Lorestan University, Iran.
Abstract
Surface waters or rivers are one of the most important water sources that play an important role in supplying water for various activities. In recent years, the optimal use of artificial intelligence models has been common to predict and simulate of the quantitative and qualitative parameters of water to prevent the pollution of surface water and rivers. The Kakareza river is located in the city of Selseleh, Lorestan province, the water of this river is mostly used for irrigation, thus it is very important to assess the quality and estimate the quality parameters of the water of this river. In this research hydrogeochemical methods and artificial intelligence have been used. The findings showed that bicarbonate, calcium and magnesium ions have a major role on the water quality of this river. The water quality index of Kakareza River is favorable in the period 1347 to 1398 and can be used for drinking and agriculture purposes. Also, the results of the artificial neural network show the high ability of the neural network in simulation and prediction the parameter index, the model with 9 inputs (HCO3, Cl, SO4, Ca, Mg, Na, TDS, pH, Q) is shown the best performance in estimated value of EC. Finally, in order to implement the management program of water organizations to make optimal use of water resources in the region (such as the Kakareza River) by using hydrogeochemical studies and quantitative and qualitative predictions of water, it is possible to have a more accurate understanding of the water quality conditions, which makes better decisions about the use of these water resources.
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Volume 2, Issue 1
June 2024
Pages 123-136

  • Receive Date 11 September 2024
  • Revise Date 17 October 2024
  • Accept Date 21 October 2024