Monitoring Groundwater Pumping Using Time‐Lapse Tomography From Ambient Seismic Noise

Abstract Management of water resources will be of critical importance as the effects of climate change accelerate. This implies the need to monitor water resources with high spatial and temporal resolution. One way to meet this need could be passive seismic methods using ambient seismic noise. In this study, we present a novel approach using time‐lapse probabilistic tomography to monitor a hydrological pumping test in the municipality of Nickelsdorf (Austria). We deployed a dense array of nodal seismic sensors that recorded seismic noise for approximately 4 months in early 2023. To assess changes in subsurface properties associated with the pumping, we conducted trans‐dimensional probabilistic tomography with daily time resolution using train‐generated noise. Our results show a clear correlation between water table fluctuations and shear wave velocities. We interpret this to be due to variations in saturation caused by groundwater pumping. Mapping these spatio‐temporal variations enables water resource monitoring that complements well‐based point‐wise measurements. Such an approach can lead to improved understanding of groundwater dynamics such as inflow from external water resources.