Ability of Artificial Neural Networks (ANNs) to Simulate Hydrochemical Variables of Kermanshah Drinking Water Wells

Water quality monitoring is one of the most important problems in drinking water resources management. The one that should be done with the time consuming and expensive process of water sampling and chemical analysis of these resources. In this study Back Propagation Neural Networks (BPNNs) was used to simulate hydrochemical variables like Total Dissolved Solids(TDS), alkalinity, total hardness, hardness, and some special ions (Ca2+, Mg2+, K+, Na+, HCO3 -, Cl-, SO4 2-, NO3-, NO2 -, PO4 3-, F- and NH3) in some of drinking water wells located in Miandarband Plain (Kermanshah, Iran).The study emphasizes high ability of ANNs in simulation of these variables.

Keywords:

Artificial Neural Networks (ANNs) , Simulation , Hydrochemical Variables , Miandarband Plain