Published Paper Details:

In semi-arid locations, climate change and human activities have a significant impact on groundwater properties. Mastering the groundwater dynamic variation and giving scientific recommendations for the sensible exploitation and management of groundwater resources require analysing the change in groundwater level and measuring the contributions of influencing elements. For the Bankura Sadar sub-division in West Bengal's semi-arid climatic zones, an attempt was made to find probability distributions using seasonal (January, April, August, and November for 2019 to 2020) statistics on groundwater table. The study describes how a geostatistical method was used to improve an existing network of groundwater samples. Semivariogram analysis was performed to fit the best theoretical model with experimental model. The study shows that ordinary kriging provides the best answer, and that the error variance can be used to add more observation wells for the best groundwater level tracking network infrastructure. The exponential semivariogram model derived from conventional kriging provides the best fit model, according to spatial and seasonal evaluations. The results revealed that the groundwater level demonstrated amazing regularity with seasonal use throughout the year. Consequently, the interannual groundwater level continued to fall, resulting in the depression cone. For appropriate groundwater monitoring, these methods can be implemented for intra-district water level depth analysis.