Abstract
Today, the supply of safe drinking water is one of the most important problems in societies. In the present research, using a neural network, a method to determine the dispersal trend of groundwater pollutants was provided through a case study of heavy metals, including lead, zinc and arsenic in Qazvin plain. Then, using a sensitivity analysis, the actual significance of each parameter was determined in the model and by plotting graphs and response levels, the effects of abstraction, discharge, electrical conductivity, temperature, hydraulic gradient, lifetime, groundwater level and depth from surface to well screen on the concentration of metals were studied individually and two by two. The model was applied to predict the situation of the plain in the coming years, and only if the abstraction is reduced to a half rate, the plain condition would remain stable and the concentration of the metals would not be increased.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
