Mapping Spatiotemporal Variations of Near‐Surface Seismic Velocity to Monitor Groundwater in Central Oklahoma

Global climate changes have intensified drought events, necessitating accurate groundwater monitoring. Traditional methods often lack the spatial and temporal resolution to track groundwater variations. This study calculates instantaneous travel‐time shifts, , from ambient noise cross‐correlation functions in central Oklahoma and projects them onto 2‐D near‐surface seismic velocity maps by using sensitivity kernels of coda‐wave interferometry. The lateral variations in these maps align with major bedrock aquifers in Oklahoma, revealing correlations between near‐surface seismic velocity, surface deformation, and gravity field, highlighting the role of water storage across time and space. The maps suggest that near‐surface seismic velocity responds are sensitive to groundwater dynamics, including discharge, recharge, and lateral flow. The confined and unconfined aquifers in Oklahoma, with diverse depth ranges and adaptive capacities, are characterized by distinct spatiotemporal patterns in our maps. This study demonstrates the potential of ambient seismic noise to improve spatial and temporal resolution in groundwater monitoring.