INTEGRATED REMOTE SENSING AND AUTOMATIC CAVE-DRIP MONITORING TO CHARACTERIZE GROUNDWATER INFILTRATION - A STUDY AT NATURAL BRIDGE CAVERNS, TEXAS
Automatic drip rate loggers along with LiDAR is used to evaluate water infiltration through the limestone over one hydrological year. Twenty drip loggers were installed at actively dripping sites throughout the Castle of the White Giants and the Hall of the Mountain King chambers, and the connecting passageways, covering a range of elevation gradients. Similarities between drip time series are interpreted regarding flow patterns, cave chamber morphology, and host lithology. Multidimensional scaling and k-means clustering is combined to categorize flow types based on time-series analysis. 3D point clouds of the study area were collected using a handheld terrestrial LiDAR. We analyzed stalactite morphology and their spatial distribution using LiDAR data to identify infiltration flow patterns. Finally, drip logger data was extrapolated to the entirety of the chambers and passageway to estimate the total infiltration within the study area, and this data was compared with local weather data.
Our preliminary analysis reveals significant findings. Many loggers display correlated (instantaneous or delayed) responses to rainfall events, suggesting a direct link via fracture transport through the limestone. However, others display varied responses, indicating that cave drip is not directly connected to rainfall but possibly driven by the overflow of stored water in the overlying limestone or from lateral flow within the vadose zone. This study's evaluation of karst controls on subsurface water movement provides crucial insight into the complex responses of cave dripping to local rainfall events, contributing to our better understanding of this intricate system.