Hydrogeochemical evaluation and entropy-driven water quality assessment of Lakshmipur District's groundwater, Southeastern Bangladesh.

Abstract

Coastal communities in Bangladesh heavily depend on groundwater as a primary source of drinking water. However, these sources are under increasing threat due to natural and human-induced factors (geogenic and anthropogenic effects), including excessive salinity, contamination through heavy metals, runoff from agricultural fields, and municipal sewage. To assess seasonal variations in hydrogeochemistry, water quality, pollution status, and potential health threats, we collected 46 groundwater samples from Lakshmipur District. Of these, 23 samples were collected during the pre-monsoon (March-April 2024) season and 23 samples were collected during the post-monsoon (October-November 2024) season. The evaluation was conducted by assessing the major physicochemical characteristics of the groundwater samples, as well as the major ionic species and selected trace metals, using standard field/laboratory methodology. Pre-monsoon groundwater showed salinity exceedance in 54.16% of samples, while 58.33% of samples had Na⁺ and Cl^- exceeding the limits. In 75% and 91.67% of the samples, Fe and Mn surpassed the DoE criteria, respectively, whereas K⁺ did so in 71.17% and As in 66.67%. Following the post-monsoon season, 43.48% of samples had salinity exceedance, followed by Na⁺ and Cl^- in 65.22% and 47.83%, Fe²⁺ and Mn⁺ in 86.96% and 73.91%, K⁺ in 60.87%, and As in 95.65%. Groundwater evolution was strongly associated with mineral dissolution and water-rock interaction, according to integrated hydrogeochemical investigations. Positive CAI readings suggest the occurrence of reverse ion exchange, whereas Na/Cl ratios (< 1) showed chloride enrichment from evaporation and localized saline-water influence. In the pre-monsoon season, EWQI (Entropy Water Quality Index) values showed that 20% of the samples were rated as excellent, 35% as good, and 30% as Extremely Poor. In the post-monsoon, the number of excellent samples increased to 30%, but the number of Extremely Poor samples also rose to 43%, showing that the overall water quality worsened in some areas. Fuzzy inference and three-dimensional response surface analyses indicated that Fe-K and Mn-As interactions were strongly associated with variations in EWQI. Pollution indices (HPI, HEI, C_d, and NPI) confirmed widespread heavy metal contamination. Health risk assessment revealed that children face greater non-carcinogenic risks than adults, with Hazard Index (HI) values exceeding the safe threshold (HI > 1). The novelty of this study is to integrate an entropy-based water quality assessment with fuzzy logic modeling, pollution indices, hydrogeochemical interpretation, and health risk assessment to determine the major factors controlling the seasonal degradation of groundwater quality in a coastal aquifer. These findings highlight the need for seasonal groundwater monitoring, safe-well mapping, treatment of metal-contaminated wells, and sustainable coastal aquifer management in the Lakshmipur District. Future research should include long-term seasonal observations, denser sampling networks, and ambiguity and sensitivity analyses to improve groundwater quality assessment and management strategies under changing climatic and anthropogenic conditions.