Abstract. The core component of many hydrological systems, the moisture storage capacity available to vegetation, is impossible to observe directly at the catchment scale and is typically treated as a calibration parameter or obtained from a priori available soil characteristics combined with estimates of rooting depth. Often this parameter is considered to remain constant in time. This is not only conceptually problematic, it is also a potential source of error under the influence of land use and climate change. In this paper we test the potential of a recently introduced method to robustly estimate catchment-scale root zone storage capacities exclusively based on climate data (i.e. rainfall distribution and evaporation) to reproduce the temporal evolution of root zone storage under change. Using long-term data from three experimental catchments that underwent significant land use change, we tested the hypotheses that: (1) root zone moisture storage capacities are essentially controlled by land cover and climate, (2) root zone moisture storage capacities are dynamically adapting to changing environmental conditions, and (3) simple conceptual yet dynamic parametrization, mimicking changes in root zone storage capacities, can improve a model's skill to reproduce observed hydrological response dynamics. It was found that water-balance derived root zone storage capacities were similar to the values obtained from calibration of four different conceptual hydrological models. A sharp decline in root zone storage capacity was observed after deforestation, followed by a gradual recovery. Trend analysis suggested recovery periods between 5 and 13 years after deforestation. In a proof-of-concept analysis, one of the hydrological models was adapted to allow dynamically changing root zone storage capacities, following the observed changes due to deforestation. Although the overall performance of the modified model did not considerably change, it provided significantly better representations of high flows and peak flows, underlining the potential of the approach. In 54 % of all the evaluated hydrological signatures, considering all three catchments, improvements were observed when adding a time-variant representation of the root zone storage to the model. In summary, it is shown that root zone moisture storage capacities can be highly affected by deforestation and climatic influences and that a simple method exclusively based on climate-data can provide robust, catchment-scale estimates of this crucial and dynamic parameter.