Analysing the Effectiveness of MCDM and Integrated Weighting Approaches in Groundwater Quality Index Development

Groundwater, a vital resource crucial for human civilization, faces unprecedented threats due to negligence in maintenance, jeopardizing our survival. Overpopulation in developing countries like India has exacerbated issues like over-extraction and pollution, underscoring the need for urgent quality assessment and management. The Groundwater Quality Indexing (GwQI) method although simplifies ranking water reserves often fails to portray complete quality and consider certain critical factors. This study addresses these challenges by integrating Multi-criteria decision-making (MCDM) approaches into groundwater quality assessment. Three decision-making methods—Weighted Sum Model (WSM), Grey Relational Analysis (GRA), and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)—are applied to refine GwQI findings for shallow open wells in Varanasi, Uttar Pradesh, India. Two integrated weighting approaches, namely, Distance-Relation Method (DRM) and Bayes Method (BM), incorporating objective (Entropy-based) and subjective (AHP or Analytical Hierarchy Process-based) weights, are further explored for their effectiveness in decision-making. The results indicate an overall consistency in the ranks of the best and worst wells (except for the ranks of intermediate wells) with each method. Further, it was found that DRM (r2 = 0.6741) and AHP (r2 = 0.6693) weighting methods complied greatest with GwQI findings. For GRA, AHP performed better while for WSM and TOPSIS, EWM was observed to have better R2 value. Among the methods used, the gain in r-square value is highest from AHP-TOPSIS to BM-TOPSIS (+ 7.7