Assessing infiltration dynamics using integrated hydrogeophysical monitoring in a managed aquifer recharge pond

Managed Aquifer Recharge (MAR) ponds are widely used to enhance groundwater, but efficiency is limited by uncertain infiltration pathways, heterogeneous sediments, and surface clogging. Understanding infiltration responses to variable inflow and evolving subsurface conditions is essential for optimizing pond performance. This study applied an automated multielectrode Direct Current Resistivity and Induced Polarisation (DCIP) system, complemented by Ground Penetrating Radar (GPR) and hydrological monitoring, to investigate infiltration dynamics over eight months. DCIP results captured resistivity reductions from dry conditions (>2000 Ωm) to saturated zones (70–250 Ωm), coinciding with groundwater-level rises of up to 1.6 m near the eastern inlet and 1.0 m at the distal end during peak inflow (58 l s−1). GPR revealed the lower limit of the artificial filter layer at ∼1 m depth and deeper reflections corresponding to the transition from vadose to saturated zones, matching groundwater levels in nearby wells. Both methods identified a westward-dipping layer along the pond (surface to ∼2–3 m depth; 100–50 m along the profile), interpreted as a high-permeability layer guiding lateral infiltration. Decreasing GPR reflection amplitudes over time indicate increasing water content in the unsaturated zone, consistent with DCIP observations. DCIP inversions captured immediate subsurface responses to inflow, including localized groundwater mounding, progressive saturation, and drying during interruptions. Groundwater levels rose fastest at the inlet, more slowly at mid-distance, and minimally at the far end, reflecting inflow proximity and lateral hydraulic connectivity. Saturation estimations derived using Archie’s law corroborate these observations, showing moderate-to-high wetting zones, while later stages indicate signs of clogging and biofilm development. The integrated DCIP–GPR–hydrological approach effectively delineates subsurface structure heterogeneity and time-dependent infiltration, supporting adaptive inflow management under variable hydrological conditions.