Identification of Groundwater Prospect in Bara Region of Allahabad District Based on Hydro-Geomorphological Analysis Using Satellite Imagery

Water scarcity is a major problem for villagers’ survival as it determines the population density and affects the migration pattern in Bara region. In the present study, groundwater resource endowment is studied and correlated with the distributional pattern of population, settlements and economic activity for analysing regional development in the study area. The study has been carried out using geospatial platforms, i.e. Erdas Imagine 2014 and ArcGis 10.2.2 software. Sentinel-2 satellite imagery and Cartosat-1 DEM data were the major data sources for extracting factor layers. Geomorphology and lineament maps of NRSC, District Resource Map of GSI, topographic maps and Google Earth images along with field surveys were ancillary database. Saaty’s 9-point rating scale of analytical hierarchy process was used to extract the GWPI by integrating factor layers of geomorphology, lineament density, slope, geology, rainfall, drainage density and land use land cover according to their relative influence. Final map shows different zones of groundwater prospects in the study region, which is validated from aquifer thickness data. Result shows that 39.19% (291.41 km 2 ) of the total area (743.64 km 2 ) is classified as high-to-excellent GWP, whereas 27.96% (207.89 km 2 ) of the area is under very poor-to-poor GWP. Areas having poor-to-poorest groundwater storage impact on population distribution, as 14% of the total population is lying over these zones. The descriptive statistical analysis showed that CGWPI and built-up area are significantly correlated ( F = 18.024 > 4.41*, t = − 4.245 > 2.101, R 2 = 50.03%). CGWPI is also correlated significantly with population density ( F = 18.855 > 4.41*, t = -4.342 > 2.101, R 2 = 50.16%). However, the relationship is not very high on linear regression model as expected since only 50% variations in population distribution can be attributed to CGWPI, for example, the Shankargarh town having the highest population density and the second highest built-up percentage in the whole study area in spite of being endowed with the lowest groundwater potential.