Groundwater quality status based on a modification of water quality index in an arid area, Iran

Abstract

Increasing population, high demand for food, and uncontrolled abstraction of aquifers have severely affected the water quality. This study aimed to evaluate the water quality of 17 deep agricultural wells in Bahabad plain from the perspective of irrigation and drinking. In order to determine the water quality of wells and analyze the water quality index (WQI), a set of statistical methods such as Fuzzy Analytic Hierarchy Process (FAHP) and TOPSIS were used. WQI is considered one of the primary methods for assessing drinking water quality. Still, due to the discrepancy between the results and the WQI(WHO), it was decided to modify the WQI method. The integrated use of FAHP-WQI and the TOPSIS method led to significant changes in the grading and the classification of water wells. The results showed that these two methods combined could be used as a good and complementary technique to eliminate ranking inconsistencies by WQI. Combining WQI results with GIS also allows for a deeper analysis of drinking water quality. The results showed that most of the water quality problems are due to wells in the northern region of the plain, and more than 41% of wells in this region are not in good condition.

Water Quality Index Estimations Using Machine Learning Algorithms: A Case Study of Yazd-Ardakan Plain, Iran

“…The WQI is used to assess groundwater quality and for various purposes, such as drinking and irrigation. WQI has been used by various researchers in different parts of the world [24][25][26]. Water quality index, as per the World Health Organization (WHO) requirements, was calculated using the permissible limits for the parameters listed in Table 1.…”