Groundwater quality assessment with respect to fuzzy water quality index (FWQI): an application of expert systems in environmental monitoring

Abstract

Water quality degradation affects socio-economic development inappropriately and has dire effects on human health too. Water quality indexes (WQIs) are the methods widely used for modelling water quality status. However, using these indexes is limited by some constraints like deficiency of necessary database or uncertainty of decision-making. Throughout the ongoing research, fuzzy water quality indexes (FWQIs) were developed based on the Mamdani fuzzy inference system (FIS) to overcome the above-mentioned limitations. In other words, seven FWQIs models with different water quality parameters have been developed based on triangular and trapezoidal membership functions. Later, the developed indexes were employed to evaluate the water quality of 17 wells in Saveh Plain, Iran. Compared to the conventional WQI, the results showed that the elimination of some needed parameters in development of FWQI did not decrease the accuracy of water quality classification. However, omitting some other parameters with undesirable values made the classification of water quality unreliable. According to the results, some 35 % of wells benefitted from proper drinking water quality, while approximately 30 and 35 % of them suffered from unsuitable and very poor drinking water quality, respectively.