A major limitation to the assessment of catchment transit time (TT) stems from the use of stable isotopes or chloride as hydrological tracers, because these tracers are blind to older contributions. Yet, accurately capturing the TT of the old water fraction is essential, as is the assessment of its temporal variations under non-stationary catchment dynamics. In this study we used lumped convolution models to examine time series of tritium, stable isotopes and chloride in rainfall, streamwater and groundwater of a catchment located in subtropical Australia. Our objectives were to determine the different contributions to streamflow and their variations over time, and to understand the relationship between catchment TT and groundwater residence time. Stable isotopes and chloride provided consistent estimates of TT in the upstream part of the catchment. A young component to streamflow was identified that was partitioned into quickflow (mean TT ≈ 2 weeks) and discharge from the fractured igneous rocks forming the headwaters (mean TT ≈ 0.3 years). The use of tritium was beneficial for determining an older contribution to streamflow in the downstream area. The best fits between measured and modelled tritium activities were obtained for a mean TT of 16–25 years for this older groundwater component. This was significantly lower than the residence time calculated for groundwater in the alluvial aquifer feeding the stream downstream (≈ 76–102 years), emphasising the fact that water exiting the catchment and water stored in it had distinctive age distributions. When simulations were run separately on each tritium streamwater sample, the TT of old water fraction varied substantially over time, with values averaging 17 ± 6 years at low flow and 38 ± 15 years after major recharge events. This counterintuitive result was interpreted as the flushing out of deeper, older waters shortly after recharge by the resulting pressure wave propagation. Overall, this study shows the usefulness of collecting tritium data in streamwater to document short-term variations in the older component of the TT distribution. Our results also shed light on the complex relationships between stored water and water in transit, which are highly non-linear and remain poorly understood. © Author(s) 2016. CC Attribution 3.0 License.