Detection and quantification of preferential flow using artificial rainfall with multiple experimental approaches

Preferential flow in the unsaturated zone strongly influences important hydrologic processes, such as infiltration, contaminant transport, and aquifer recharge. Because it entails various combinations of physical processes arising from the interactions of water, air, and solid particles in a porous medium, preferential flow is highly complex. Major research is needed to improve the ability to understand, quantify, model, and predict preferential flow. Toward a solution, a combination of diverse experimental measurements at multiple scales, from laboratory scale to mesoscale, has been implemented to detect and quantify preferential paths in carbonate and karstic unsaturated zones. This involves integration of information from (1) core samples, by means of mercury intrusion porosimeter, evaporation, quasi-steady centrifuge and dewpoint potentiometer laboratory methods, to investigate the effect of pore-size distribution on hydraulic characteristics and the potential activation of preferential flow, (2) field plot experiments with artificial sprinkling, to visualize preferential pathways related to secondary porosity, through use of geophysical measurements, and (3) mesoscale evaluation of field data through episodic master recession modeling of episodic recharge. This study demonstrates that preferential flow processes operate from core scale to two different field scales and impact on the qualitative and quantitative groundwater status, by entailing fast flow with subsequent effects on recharge rate and contaminant mobilizing. The presented results represent a rare example of preferential flow detection and numerical modeling by reducing underestimation of the recharge and contamination risks.

Automated summary

Preferential flow in the unsaturated zone is complex, but plays a significant role in hydrologic processes. Diverse experimental methods have been used to detect and quantify preferential pathways. Understanding preferential flow is crucial for accurate prediction of groundwater recharge and contamination risks.