Delineation of Groundwater Potential Zones in Jharia Coalfield Region Using Geostatistics, Remote Sensing, and GIS Techniques

Groundwater research has advanced by incorporating remote sensing data and the geographical information system (GIS) to explore groundwater resources, which aids in evaluating, monitoring, and conserving groundwater resources. The groundwater potential zones for the study area have been developed by integrating various thematic maps such as drainage maps, slopes, geomorphology, soil, lineaments, and geology using remote sensing and GIS techniques. Demarcation of groundwater potential zones for this study is made by grouping the interpreted layer through weighted overlay analysis. Based on how each aspect affected the potential of groundwater, weights have been assigned to each individual. The groundwater potential zone of this research area can be categorized as good, moderate, bad, or very poor depending on how well it is developed. The groundwater potential map demonstrates that a good groundwater potential zone is concentrated in the Barakar Formation Region. About 8% fall in the poor zone, 33% fall in moderate conditions, and 54% fall in the good zone area. And 5% falls in a very good zone. The field of geostatistics consists of many statistical methods applied to spatial data. This chapter highlights the use of geostatistical methods in groundwater modeling and potential zone mapping in the Jharia coalfield region. A typical spatial data set, such as groundwater levels, monthly precipitations, or transmissivities, comprises scattered readings in space, denoted by z(x), where x represents the measurement location. Considering a combination of these data, geostatistics offers different approaches to address a range of hydrogeological resource issues, such as Estimation of (z) at an unmeasured location: interpolation and mapping of (z), Estimation of one parameter based on measurements of other parameters: Estimation of the gradient of z at an arbitrary site, Estimation of the integral of z over a defined block: estimation of contamination volume based on point measurements. The current results suggest that groundwater potential zone identification can be enhanced by considering all relevant parameters.