Groundwater quality classification derivation using Multi-Criteria-Decision-Making techniques

Abstract

The paper introduces a novel framework of evaluating and validating the groundwater quality index (GWQI) by employing two Multi-Criteria-Decision-Making models (MCDMs) such as Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Compromise Programming (CP). GWQIs are plagued by discrete values which are attributed to excellent, good, poor, very poor, and unsuitable for drinking purpose classes. Furthermore, the existence of chemical parameters with low weights but high concentration values (or vice versa) reduces equilibrium of evaluations. Based on the literature review, MCDMs have not been applied so far to validate groundwater quality indexes. This simple yet practical structure assists the analysts to investigate robustness of a water quality index. In order to validate the classes, the intervals of classic GWQI were modified to figure out what changes were made to the classes of samples in the ranking table considering quality of 92 wells in the Varamin plain, Iran. After employment of the MCDMs, the results revealed that WQI could rarely evaluate water quality classes accurately. Several wells which were classified as “excellent quality” were belonged to the lower quality class. It also came true for other classes. The results demonstrated that TOPSIS could present a more precise analysis for the classes with a low number of wells. Moreover, increases in value of the sensitivity parameter of CP technique reduced the accuracy of results. Owing to proper application of MCDMs, one can suggest the use and development of MCDM-based water quality assessment models for future researches.