Comparative Analysis of Groundwater Recharge Using Geophysical Methods Across Regions

Thesis Abstract

Groundwater recharge is increasingly threatened by climatic variability and land-use change, yet comparative assessments across hydrogeologically diverse regions remain limited, hindering transferable management strategies. This study addresses the problem of regional disparities in recharge estimation by integrating multi-method geophysical probes to achieve a cross-regional synthesis of recharge dynamics under varying meteorological regimes and soil-vegetation–land-use configurations. The aim is to quantify and compare groundwater recharge rates across three geologically distinct regions using a geophysical data fusion approach, with objectives to (i) characterize subsurface hydrogeological properties influencing recharge, (ii) estimate recharge volumes employing electrical resistivity tomography (ERT), magnetotellurics (MT), and time-domain electromagnetic (TDEM) methods calibrated with lithological controls, (iii) test the consistency of geophysical recharge estimates with hydrological indicators and climate normals, and (iv) identify region-specific drivers and transferability of recharge estimation methodologies. The study adopts a comparative cross-sectional design, drawing on a regional population comprising 12 monitoring wells per region and 40 shallow boreholes for calorimetric and lysimetric validation, selected to represent major aquifer systems in arid, semi-arid, and humid climates. Data collection employs integrated geophysical surveys across 150–200 m transects per region, coupling ERT (sensitivity down to 100 m), MT for deeper resistivity structure, and TDEM to resolve fine-scale heterogeneity, complemented by borehole logging, slug tests, and soil moisture profiling. Instrument validity is ensured through calibration against 20 independently measured recharge events using lysimeters, rainfall-runoff data, and groundwater level records, with reliability tested via cross-validation and inter-method consistency checks. Data analysis proceeds in three stages (i) geophysical inversion and petrophysical linkage using Petrophysical Inversion and Archie's law to derive hydraulic conductivity and porosity, (ii) recharge estimation through water-balance modeling constrained by geophysically inferred storage changes and hydrological time series, employing regression analysis and ANCOVA to test regional differences while controlling for antecedent moisture and land-use factors, and (iii) synthesis through Bayesian model averaging to quantify uncertainty and identify most influential regional drivers. The theoretical framework rests on poroelastic and hydrogeochemical paradigms, with principal theories including Darcy’s law for subsurface flow, Richards’ equation for vadose-zone processes, and the theory of hydraulic tomography as a backbone for parameter transfer between geophysical signals and hydraulic properties. Expected findings indicate statistically significant differences in recharge rates and storage dynamics among the three regions, driven by variances in attenuation lengths, soil conductivities, and aquifer porosity, with MT data revealing deeper structural controls on regional recharge pathways. The study anticipates strong concordance between geophysically derived recharge estimates and hydrometeorological indicators in humid regions, and moderate alignment in arid zones due to increased evapotranspiration and intermittently recharged aquifers, highlighting method- and region-specific uncertainties. The contribution to knowledge includes (1) a robust, transferable methodology for cross-regional recharge estimation that integrates ERT, MT, and TDEM with hydrological validation, (2) a comparative framework linking geophysical signatures to recharge processes across climate zones, and (3) empirical insights into the influence of lithology, soil moisture, and land-use on recharge detectability with scalable uncertainty assessments. The study concludes that regionally tailored geophysical-recharge models outperform uniform approaches in predictive accuracy and decision support. Recommendations emphasize adopting multimodal geophysical surveys as standard practice in groundwater assessments, developing region-specific calibration datasets, and incorporating real-time monitoring networks to improve recharge forecasts under changing climate and land-use scenarios.