The self-potential (SP) method is a passive geophysical technique, which may offer insights about water and ionic fluxes in the vadose zone. The main obstacles presently prohibiting its routine use in quantitative vadose zone hydrology are the superposition of signals arising from various source mechanisms, difficult-to-predict electrode polarization effects that depend on electrode design and age, as well as incomplete knowledge on water saturation, pore water chemistry, clay content, and temperature in the immediate vicinity of the electrodes. We present a unique long-term SP monitoring experiment focusing on the first four years of data acquired at different depths in the vadose zone within the HOBE hydrological observatory in Denmark. Using state-of-the-art SP theory combined with flow and transport simulations, we attempt to replicate the observed data and suggest reasons for observed discrepancies. The predictions are overall satisfactory during the first six months of monitoring after which both the patterns and magnitudes of the observed data change drastically. Our main observations are (1) that predicted SP magnitudes are strongly sensitive to how the effective excess charge (or alternatively, the voltage coupling coefficient) scales with water saturation implying that continued research is needed to build more accurate models of electrokinetic phenomena in unsaturated conditions, (2) that significant changes in electrode polarization occur in the shallowest electrodes at time scales of a year, most likely due to desaturation by capillarity of the fluids filling the electrodes, suggesting that electrode effects cannot be ignored and that explicit electrode modeling should be considered in future monitoring studies, and (3) that multi-rate mass transfer and reactive transport modeling, with specific emphasis on fluid-mineral interactions, are needed to better predict salinity and pore water conductivity. We hope to stimulate other researchers to test new SP modeling approaches and interpretation strategies against these data by making the SP and complimentary (temperature, dielectric constant, potential/actual evapotranspiration, precipitation) data time-series available.