Spatial and temporal variability in infiltration and soil characterization using ERT

Infiltration of the aquifer is one of the primary processes of the hydrological cycle. It plays a crucial role in the estimation of artificial groundwater recharge, surface runoff, and soil erosion. The electrical resistivity tomography (ERT) surveys were carried out to characterize the subsurface soil, and double-ring experiments were carried out at different locations in the study area. The results estimated from the double-ring infiltrometer data were compared with the infiltration rates obtained from various models such as Horton, Green-Ampt, Kostiakov, etc. The parameters are to be calibrated under the same hydrological site conditions, and these models’ water content and constants were estimated using the Graphical method. The best-fit models were estimated for each site, and the performance of the infiltration models was assessed based on the correlation coefficient, coefficient of determination, and root mean square error (RMSE). Horton model showed minimum RMSE, maximum correlation coefficient, and coefficient of determination, i.e. 5.24, 0.99, and 0.98, respectively, at most sites. The ERT data showed that sand is the predominant material available in the subsurface, and the saturated infiltration rate lies in the range of the sand. Nonlinear regression modeling was used to develop novel infiltration rate models from infiltration data.