Enhanced characterization of hydraulic conductivity via standard penetration test for sandy soils and weathered rocks.

This study introduces a novel methodology for predicting hydraulic conductivity (K) from standard penetration test (SPT) N-values, addressing the critical challenges of conventional field measurements that result in sparse K data. The research objectives were to: (1) establish empirical correlations between N and K, (2) develop a robust prediction model with quantifiable bounds, and (3) demonstrate practical applications for enhanced subsurface characterization. Analysis of 3508 boreholes across South Korea revealed a statistically significant negative correlation between N and K in sandy soils. Quantile regression enabled prediction of both point estimates and percentile ranges. Evaluation of six empirical equations for K estimation identified the Chapuis equation as optimal, which was integrated with field measurements to strengthen the regression model. For weathered rocks, a consistent K range was established. The methodology's novelty lies in combining readily available SPT data with advanced statistical techniques to generate high-resolution 3D K domains, as demonstrated through kriging. Despite relatively low R values, the methodology achieves practical accuracy with most predictions falling within one order of magnitude of measured values. This approach significantly enhances spatial and depth-wise characterization of subsurface K, offering a practical solution for groundwater flow modeling and geotechnical design with improved resolution.