Tree transpiration is a critical process of the water cycle and its observation and quantification are essential to better understand terrestrial ecosystem dynamics. While sap flow measurements provide direct estimates of individual tree transpiration, their reliance on empirical calibration and a rather high energy consumption (due to heat generation) can be strong limiting factors. The self-potential (SP) method, a passive geophysical approach, presents a promising alternative for assessing transpiration rates, although the electrophysiological processes driving SP signals in trees remain underexplored (Fig. 1). This study presents a year-long monitoring of SP and sap velocity in three tree species at three Critical Zone Observatories different in a Mediterranean climate (from OZCAR and ICOS research infrastructures). Using wavelet coherence analysis and variational mode decomposition, our findings reveal strong coherence between SP and sap velocity at diurnal time scales, with coherence diminishing and phase shifts increasing under higher water supply conditions. Electrokinetic coupling coefficients, derived from linear regression between SP and sap velocity variations, align with values typical of porous geological media. During dry seasons, the electrokinetic effect dominates SP signals, suggesting its potential as a tool for evaluating transpiration rates. This research demonstrates the feasibility of integrating geophysical techniques into long-term observations of ecohydrological systems to better understand plant-water interactions in the Critical Zone.