Assessment of groundwater suitability for irrigational utilization determined by distinct quality indices and information entropy theory in the Indian Sundarban region

Abstract

Abstract For sustainable agricultural practices, groundwater quality must be suitable for irrigation; otherwise, it can degrade soil and diminish crop production. The entropy information theory, several irrigational indices, multivariate statistics, GIS and geostatistics are used in this work to evaluate the geographical distribution and quality of groundwater in the Indian Sundarban region. 33 samples of groundwater have been collected in total, and they were evaluated for major cations, anions as well as other parameters like electrical conductivity (EC), soluble sodium percentage (SSP), potential salinity (PS), total dissolved solids (TDS), Kelly ratio (KR), Sodium absorption ratio (SAR), permeability index (PI), residual sodium carbonate (RSC), Magnesium Hazard (MH) and residual sodium bicarbonate (RSBC). The overall trend of the principal cations and anions is in the sequence of Na+ ≥ Mg2+ ≥ Ca2+ ≥ K2+ and HCO3− ≥ Cl− ≥ NO3− ≥ SO42− ≥ F−, respectively, whereas the spatial variation of %Na, SAR, RSBC, and MH demonstrate very poor irrigation water quality, and spatial variation of KR, RSC, SSP, PI, and PS signifies that the irrigation water quality is excellent to good. The hydrochemical facies indicates that mixed type makes up the bulk (51.51%) of the water samples. Following the Wilcox plot, more than 75% of the water samples are good to doubtful; however, by the US salinity hazard map, roughly 60.60% of the samples had high salinity (C3-S1 zone). As per the entropy-weighted water quality index for irrigation (EWQII), 60.60% of samples possess good to average quality, while the remaining 39.40% (poor) require severe restrictions before use in agricultural operations. As a result, to assure sustainable agricultural development, in the research area, continuous monitoring and water resource management are required.