Application of improvement fuzzy logic technique for groundwater quality assessment in Naiman Banner

This research develops an improved fuzzy logic technique for groundwater quality assessment using nine key parameters (total hardness, total dissolved solids, SO42−, NO3−, total Fe, F−, Pb, pH, and turbidity) classified per China's GB/T 14848-2017 standard. Results show that the improved method allocates 27, 45, and 23% of samples to grades Ⅰ-Ⅲ, respectively, the enhanced fuzzy logic model more accurately assesses groundwater quality, showing 95% in Grades I-III versus 80% rated Grade V by traditional methods, indicating broadly suitable water quality and aligning more closely with actual conditions than traditional methods that overstate grade Ⅴ contamination. The improved model effectively resolved the classification ambiguities in multi-factor systems and exhibited strong scalability for large-region assessments. The Fuzzy-SPSS approach provides a robust theoretical and practical framework for optimized groundwater management and protection by enabling multivariate analysis to elucidate the mechanistic impacts of hydrogeological, extraction, and usage factors on water quality.