Document Type : Original Research Paper

Authors

• Hamid Sarkheil ¹
• Emad Rostamian ²
• Shahrokh Rahbari ³
• Razieh Lak ⁴
• Yasaman Mohtat ¹

¹ School of Mining Engineering, College of Engineering, University of Tehran, Tehran, Iran

² School of Mining, College of Engineering, University of Tehran, Tehran, Iran

³ Department of Process Engineering, Faculty of Chemical Engineering, Tarbiat Modares University (TMU), Tehran, Iran

⁴ Research Institute for Earth Sciences, Geological Survey of Iran, Tehran, Iran

Abstract

Deep groundwater resources are crucial for mining, industrial, agricultural, and drinking water applications in disadvantaged regions. This creates an inherent conflict with ecological preservation, requiring advanced water quality indices (WQIs). This study presents three fuzzy logic-based indices that are tailored for deep‑groundwater assessment. First, the Fuzzy Drinking Water Quality Index (FDWQI) utilizes pH, TOC, TDS, TH, and nitrate (29 rules). Second, the Fuzzy Agricultural Water Quality Index (FAWQI) employs SAR, PI, EC, and MAR (20 rules). Finally, the Fuzzy Industrial Water Quality Index (FIWQI) incorporates TSS, COD, turbidity, DO, and T-Alk (25 rules). These are synthesized into a comprehensive Fuzzy Deep Groundwater Sustainability Index (FDGSI). All indices employ a Mamdani-type fuzzy reasoning method with five membership categories (Very Bad to Very Good), developed using US-EPA, WHO, and researcher expertise. The findings demonstrate that the FDGSI is a robust and viable alternative to traditional linear methods. By successfully capturing non-linear hydrogeochemical complexities, this integrated tool provides a structured framework for sustainability-aimed governance, essential for the long-term management of deep groundwater in climate-smart mining and industrial sectors.

Keywords

• Fuzzy Water Quality Index (FWQI), Smart Governance
• Deep Groundwater
• Climate Change Adaptation, Fuzzy Deep Groundwater Sustainability Index (FDGSI)

Main Subjects

• Environmental Management