Abstract. Understanding the variability of the chemical composition of surface waters is a major issue for the scientific community. To date, the study of concentration–discharge relations has been intensively used to assess the spatiotemporal variability of the water chemistry at watershed scales. However, the lack of independent estimations of the water transit times within catchments limits the ability to model and predict the water chemistry with only geochemical approaches. In this study, a dimensionally reduced hydrological model coupling surface flow with subsurface flow (i.e., the Normally Integrated Hydrological Model, NIHM) has been used to constrain the distribution of the flow lines in a headwater catchment (Strengbach watershed, France). Then, hydrogeochemical simulations with the code KIRMAT (i.e., KInectic Reaction and MAss Transport) are performed to calculate the evolution of the water chemistry along the flow lines. Concentrations of dissolved silica (H4SiO4) and in basic cations (Na+, K+, Mg2+, and Ca2+) in the spring and piezometer waters are correctly reproduced with a simple integration along the flow lines. The seasonal variability of hydraulic conductivities along the slopes is a key process to understand the dynamics of flow lines and the changes of water transit times in the watershed. The covariation between flow velocities and active lengths of flow lines under changing hydrological conditions reduces the variability of water transit times and explains why transit times span much narrower variation ranges than the water discharges in the Strengbach catchment. These findings demonstrate that the general chemostatic behavior of the water chemistry is a direct consequence of the strong hydrological control of the water transit times within the catchment. Our results also show that a better knowledge of the relations between concentration and mean transit time (C–MTT relations) is an interesting new step to understand the diversity of C–Q shapes for chemical elements. The good match between the measured and modeled concentrations while respecting the water–rock interaction times provided by the hydrological simulations also shows that it is possible to capture the chemical composition of waters using simply determined reactive surfaces and experimental kinetic constants. The results of our simulations also strengthen the idea that the low surfaces calculated from the geometrical shapes of primary minerals are a good estimate of the reactive surfaces within the environment.

 Magnetic resonance soundings are used to condition hydrological model parameters.  The output of hydrological model simulations provides the subsurface water content.  The estimated water content is then used to simulate the MRS signal.  The comparison with observations allows selecting sets of model parameters.  The approach is applied on a hard-rock headwater catchment.

The temporal variability of transit-time distributions (TTDs) and residence-time distributions (RTDs) has received particular attention recently, but such variability has barely been studied using distributed hydrological modeling. In this study, a low-dimensional integrated hydrological model is run in combination with particle-tracking algorithms to investigate the temporal variability of TTDs, RTDs, and StorAge Selection (SAS) functions in the small, mountainous Strengbach watershed belonging to the French network of critical-zone observatories. The particle-tracking algorithms employed rely upon both forward and backward formulations that are specifically developed to handle time-variable velocity fields and evaluate TTDs and RTDs under transient hydrological conditions. The model is calibrated using both traditional streamflow measurements and magnetic resonance sounding (MRS)-which is sensitive to the subsurface water content-and then verified over a ten-year period. The results show that the mean transit time is rather short, at 150-200 days, and that the TTDs and RTDs are not greatly influenced by water storage within the catchment. This specific behavior is mainly explained by the small size of the catchment and its small storage capacity, a rapid flow mainly controlled by gravity along steep slopes, and climatic features that keep the contributive zone around the stream wet all year long.