Transpiration is a crucial process in the water cycle and its quantification is essential for understanding terrestrial ecosystem dynamics. Solely relying on sap flow measurements may not fully assess tree transpiration due to its complexity. Self-potential (SP), a passive geophysical method, may provide constraints on transpiration rates even if many questions remain about tree electrophysiological effects. In this study, we continuously measured tree SP and sap velocity on three tree species for one year in a Mediterranean climate. Using wavelet coherence analysis and variational mode decomposition, we explored the empirical relationship between tree SP and transpiration. Our analysis revealed strong coherence between SP and sap velocity at diurnal time scales, with coherence weakening and phase shifts increasing on days with higher water supply.We estimated electrokinetic coupling coefficients using a linear regression model between SP and sap velocity variations at the diurnal scale, resulting in values typically found in porous geological media. During a dry growing season, the electrokinetic effect emerges as the primary contribution to tree SP, indicating its potential utility in assessing transpiration rates. Our results emphasize the need for improved electrode configurations and physiochemical modeling to elucidate tree SP in relation to transpiration.