Improving the estimation precision of the mapping of groundwater salinity by employing the Indicator Kriging Technique

In tropical and semiarid areas, saline sub-surface water irrigation presents difficulties, resulting in salinized soil and reduced agricultural yields. In the pre-monsoon and post-monsoon seasons of 2022, this study evaluated electrical conductivity (EC) in 30 wells in Yamunanagar and Ambala, Haryana. The results showed that the danger of sub-surface water salinity, which could cause soil salinization, ranged from moderate (Group C2) to high (Group C3). Additionally, the data showed typical fluctuations. In the absence of field data, the Ordinary Kriging Technique (OKT) and Indicator Kriging Technique (IKT) were used to estimate salinity using the semivariogram approach to groundwater salinity levels. OKT tends to underestimate high salt levels and overestimate low salinity. By using nonlinear and nonparametric techniques with electrical conductivity thresholds, the IKT improved the salinity estimates’ spatial distribution accuracy. IKT was useful for public health, water management, and agricultural planning since it offered a more accurate and probabilistic prediction of high salinity levels. The shortcomings of conventional kriging are addressed by this development in geostatistical modeling, which also aids in environmental management, especially in areas vulnerable to contamination and seawater intrusion.