An ontology-based approach for modeling the heavy metals' temporal and spatial variations in groundwater resources by using fuzzy multi-criteria group decision-making models and geographical information system

In water quality monitoring, one of the main concerns is the increasing level of heavy metals in water resources due to human activities. This study aimed to present a framework in which, first, a new ontology-based water quality index (WQI) was developed by multi-criteria decision-making models in fuzzy environment and then, it was coupled with geographic information system (GIS) in order to model the temporal and spatial water quality changes in groundwater resources that are being supplied for drinking. The study screened for heavy metals in 45 wells in the west and northwest side of Shiraz, Iran from for a 5-year period. Six heavy metals including Pb, Zn, Hg, Cd, As, and Cr were embedded in the WQI among which the annual mean concentrations of Pb, Zn, Cd, Cr, and As increased during the research period but remained below World Health Organization (WHO) standard values in all years but, only the mean concentration of mercury exceeded the recommended WHO standard values. The methodology clearly discovered that over the time, water quality degradation has been moved from the northern part to the middle and then the southern part of Shiraz because of significant increase in heavy metals concentration which was due to the industrial development in the eastern part of the city. Groundwater quality declined over the time leading to a gradual increase in number of wells with poor water quality; however, most of them demonstrated excellent or good quality for drinking purpose. The presented framework could provide a practical pathway to portray and predict how urban development will affect the groundwater quality in future and find out its pattern.