Multi-decadal groundwater variability analysis using geostatistical method for groundwater sustainability

The general aim of the present study was to understand the groundwater level change of period 2001–2020 using geostatistical analysis at village level of Cuddalore district, Tamil Nadu, India. Further, three specific objectives were delineated as follows: to find the spatial pattern of groundwater level change, to estimate hot and cold spots of groundwater level change, and to model spatially varying relationship between change in groundwater level and population density. The groundwater level data have been downloaded from Central Ground Water Board (CGWB), Government of India. Gridded Population version 4 (GPWv4.11) dataset was downloaded for population density analysis. The Moran’s I method was applied to remove spatial autocorrelation as it is a correlation coefficient that measures the spatial autocorrelation present in a data. Hotspot analysis was performed to create statistically significant map of hot and cold spots with the help of Getis-Ord Gi* statistic. Geographically weighted regression (GWR) tool was implemented for modeling spatially varying relationship. The analysis results show the spatial pattern of groundwater level change is highly clustered, the z-score (57.53), which verify that the clustered sequence could be the outcome of random chance due to less than 1% likelihood. Groundwater level is found decreasing in 75% of the study area. The results of the GWR model show more groundwater level change than expected in relation to change in population density as 143 villages were classified within the band of 0.5–1.5 standard deviation, 35 villages were classified within the band of 1.5–2.5 standard deviation and 25 villages were classified in the band of > 2.5 standard deviation. Further, results indicate that groundwater level is decreasing at an alarming rate in the area. Hence, it is particularly important for policy makers to formulate policies, programs and projects specific to this region and to minimize groundwater level depletion.