Abstract
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.
Highlights
Understanding the effects of ongoing climatic changes on the environment is a major issue for the coming years
The results of our simulations strengthen the idea that the low surfaces calculated from the geometrical shapes of minerals provide good estimates of the reactive surfaces within this type of environment (Brantley and Mellott, 2000; Gautier et al, 2001; White and Brantley, 2003; Zhu, 2005; Li et al, 2017b). They are certainly the values to be used for hydrogeochemical modeling such as that performed in this work, in addition to the use of the experimental kinetic constants for mineral dissolution
Our study demonstrates that 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
Summary
Understanding the effects of ongoing climatic changes on the environment is a major issue for the coming years. The global increase in temperature is expected to affect the hydrological cycle at a large scale, and providing a precise estimation of its repercussions for the evolution of soils and for the chemistry of waters remains difficult. This challenge results from the wide diversity of hydrological, geochemical and biological processes, and of their coupling, which operate at the Earth’s surface (e.g., Gislason et al, 2009; Goddéris et al, 2013; Beaulieu et al, 2012, 2016). Ackerer et al.: Crossing hydrological and geochemical modeling study of concentration–discharge relations (C–Q relations) has been intensively used to assess the coupling between hydrological and geochemical processes at the hillslope or watershed scales (Godsey et al, 2009; Kim et al, 2017; Ameli et al, 2017; Diamond and Cohen, 2018)
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