Crossing hydrological and geochemical modeling to understand the spatiotemporal variability of water chemistry in an elementary watershed (Strengbach, France)

Abstract

Abstract. Understanding the spatiotemporal variability of the chemical composition of surface waters is a major issue for the scientific community, especially given the prospect of significant environmental changes for the next decades. To date, the study of concentration-discharge relationships 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 our ability to model and predict the water chemistry with only geochemical approaches. This study demonstrates the potential of coupling mathematical hydrology with hydrogeochemical modeling to better understand the spatiotemporal variability of the composition of surface waters. In a first step, 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 that are feeding the springs. In a second step, hydrogeochemical simulations with the code KIRMAT (KInectic Reaction and MAss Transport) have been performed to calculate the evolution of the water chemistry along the flow lines. The results indicate that the concentrations of dissolved silica (H4SiO4) and in basic cations (Na+, K+, Mg2+, and Ca2+) in the spring waters are correctly reproduced with a simple integration along the flow lines. The results also show that the modest variabilities of the flow line distribution and of the flow velocity imply that the water transit times only vary from approximately 1.5 to 3 months from floods to drought events. These findings demonstrate that the chemostatic behavior of the spring chemistry is a direct consequence of the strong hydrological control of the water transit times within the catchment. The good matching 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 standard kinetic constants. The results of our simulation strengthen the idea that the low surfaces calculated from the geometrical shapes of minerals are a good estimate of the reactive surfaces within the natural environment and certainly the one 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. Overall, this work shows that the hydrogeochemical functioning of an elementary watershed, such as the Strengbach catchment, is relatively simple. The acquisition and variability of the water chemistry can be explained through process-based modeling approaches and by only formulating few hypotheses on the functioning of the watershed.

Determining How Critical Zone Structure Constrains Hydrogeochemical Behavior of Watersheds: Learning From an Elevation Gradient in California's Sierra Nevada

“…To highlight the control of CZ structure on C-Q relations, we recommend working with a lithogenic solute sensitive to transit time variations along the subsurface flow lines: a solute with a strong Concentration-Mean Transit Time slope (C-MTT slope, Ackerer et al, 2020). The C-MTT slope considers the competition between primary mineral dissolution and incorporation into clay minerals, and indicates how fast a solute concentration rises with an increase of water transit time.…”

“…In contrast, a solute with a low C-MTT slope may have stream water concentrations that are weakly responsive to the seasonal variability of transit times. In granitic watersheds, Ca 2+ and H 4 SiO 4 typically have strong C-MTT slopes, while K + and Mg 2+ frequently show lower C-MTT slopes (Ackerer et al, 2020). We focused in this study on the detailed understanding of C-Q relations for Ca 2+ as this ion has an extensive database, a strong C-MTT slope, and shows the most contrast in C-Q relations across the KREW.…”

“…The KIRMAT code also considers feedback effects between mineral mass budgets, reactive surfaces, and changes in bedrock porosity (Ngo et al, 2014). The framework of geochemical modeling with KIRMAT in granitic watersheds is available in Ackerer et al (2018Ackerer et al ( , 2020. More specific data on the geochemical modeling, kinetic and thermodynamic constants are available in Tables SM2-SM5.…”

“…The modeling strategy to consider the variability of the CZ structure over the KREW is adapted from Ackerer et al (2018Ackerer et al ( , 2020. Reactive-transport modeling was first performed on P301, as this reference watershed has the most extensive database and a high density of regolith-thickness measurements.…”

Characterization of groundwater circulations in a headwater catchment from an analysis of chemical concentrations, Sr-Nd-U isotope ratios, and CFC, SF6 gas tracers (Strengbach CZO, France)

“…These parameters also control its future evolution in response to environmental modifications, whether related to global climate change or to human activities of more local impact. This information, in particular, the partitioning between deep and subsurface circulations, is also important to achieve a sustainable management of the world's water resources and to model their future evolution in response to ongoing climate change (e.g., Gleeson et al, 2016;Ameli et al, 2017;Liu et al, 2017;O'Geen et al, 2018;Weill et al, 2019;Ackerer et al, 2020a).…”