Evaluation of groundwater quality using an integrated approach of set pair analysis and variable fuzzy improved model with binary semantic analysis: A case study in Jiaokou Irrigation District, east of Guanzhong Basin, China.

The study proposes a new set pair analysis - variable fuzzy improved model (SPA-VFIM) by integrating the set pair analysis (SPA), variable fuzzy sets (VFS) theory, and binary semantic (BS). The SPA-VFIM method gets over the shortcomings of the existing SPA and VFS methods. The use of BS solves the problem of the weighted average principle (WAP) not being conducive to the timeliness of assessment. The existing and newly proposed methods were used to evaluate the groundwater quality in the Jiaokou Irrigation District, China, to show the advantages of the SPA-VFIM method. The results of SPA-VFIM method show that more than 80% of the groundwater, mainly distributed in the central and western parts of the study region, is assessed as level IV and level V, according to the Chinese Groundwater Quality Standards (GB/T 14848-2017). The assessment results are consistent with ground-based measurements of water quality, and NO3-, Na+, SO42-, Total Hardness (TH), and Cl- are the main pollutants. The SPA-VFIM and existing methods were compared. The results indicate that 57.69% and 76.92% of the assessment results by the SPA-VFIM method agree well with that of the SPA and VFS methods, respectively, indicating that the new SPA-VFIM method is reasonable and effective in groundwater quality. The results of groundwater quality assessment show that local authorities should pay more attention to areas with poor and very poor groundwater quality. These findings are beneficial to the future groundwater management plans dealing with drinking and irrigation and the sustainable development of water resources in this irrigation district.