Geospatial assessment of groundwater quality using entropy-based irrigation water quality index and heavy metal pollution indices.

Groundwater contamination has become a serious environmental threat throughout the world in the era of Anthropocene. Thus, the present study examined the groundwater quality for irrigation purposes based on the entropy method and heavy metal pollution indices. To compute the entropy-based groundwater irrigation quality index (EIWQI), physicochemical parameters such as pH, chloride (Cl-) and nitrate (NO3-), irrigation indices including electrical conductivity (EC), sodium absorption ratio (SAR), sodium percentage (%Na), soluble sodium percentage (SSP), residual sodium carbonate (RSC), magnesium hazard (MH), Kelley's ration (KR), permeability index (PI) and heavy metals such as manganese (Mn), iron (Fe), zinc (Zn) and arsenic (As) have been employed for the 37 sample wells of the Damodar fan delta (DFD), India, which is a semi-critical agriculture-dominated region. Shannon's entropy method has been used to assign the weights of the different parameters for constructing the EIWQI. The results portray a spatial variation of the irrigation water quality in the DFD. The EIWQI revealed that 27.03%, 59.46%, 8.11%, 2.7% and 2.7% of the sample wells, respectively, contain excellent, good, moderate, poor and very poor quality of irrigation water. On the other hand, heavy metal pollution indices (modified degree of contamination, pollution load index, Nemerow index and modified heavy metal pollution index) show that 15-20% of sample wells of the DFD are contaminated by heavy metal pollution. The pockets of pollution are concentrated in the southwestern, northeastern and central parts of the DFD. The study found that the spatial variation in groundwater quality is controlled by the higher sodium concentration, carbonate weathering and expansion of agricultural and urban-industrial areas.