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.

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In mountainous area, spring water constitutes the only drinking water resource and local economy is highly dependent on forest health and productivity. However, climate change is expected to make extreme water shortage episodes more and more frequent. Forest is therefore more and more exposed to water stress. It appears necessary to quantify the drought induced by water deficit to evaluate forest vulnerability and to plan the future of forest management. In this study we quantified the 2018 water deficit experienced by the forest in the Strengbach catchment, located in the French Vosges mountains. Three methods for estimating catchment water storage changes (WSC) have been compared. The first relies on superconducting gravimeter monitoring while the second relies on catchment water balance. The third one relies on global hydrological model MERRA2. We show that WSC estimated from measured gravity changes correlate well with WSC estimated from catchment water balance while WSC inferred from MERRA2 significantly differs. The Strengbach catchment water cycle is mostly annual but exhibits significant interannual variability associated with the 2018 drought episode: August 2018 has a water deficit of 37 mm (as inferred from catchment water balance) or 76 mm (as seen with superconducting gravimetry) compared to August 2017. We illustrate here the use of superconducting gravimeter monitoring as an independent proxy for WSC in a mountainous catchment while most of hydro-gravimetric studies have been conducted on relatively flat areas. We therefore contribute to expand the area of use of high precision gravity monitoring for the hydrological characterization of the critical zone in mountainous context. This innovative method may help to assess forest vulnerability to drought in the context of climate change.

Recent advances in molecular biomonitoring open new horizons for aquatic ecosystem assessment. Rapid and cost-effective methods based on organismal DNA or environmental DNA (eDNA) now offer the opportunity to produce inventories of indicator taxa that can subsequently be used to assess biodiversity and ecological quality. However, the integration of these new DNA-based methods into current monitoring practices is not straightforward, and will require coordinated actions in the coming years at national and international levels. To plan and stimulate such an integration, the European network DNAqua-Net (COST Action CA15219) brought together international experts from academia, as well as key environmental biomonitoring stakeholders from different European countries. Together, this transdisciplinary consortium developed a roadmap for implementing DNA-based methods with a focus on inland waters assessed by the EU Water Framework Directive (2000/60/EC). This was done through a series of online workshops held in April 2020, which included fifty participants, followed by extensive synthesis work. The roadmap is organised around six objectives: 1) to highlight the effectiveness and benefits of DNA-based methods, 2) develop an adaptive approach for the implementation of new methods, 3) provide guidelines and standards for best practice, 4) engage stakeholders and ensure effective knowledge transfer, 5) support the environmental biomonitoring sector to achieve the required changes, 6) steer the process and harmonise efforts at the European level. This paper provides an overview of the forum discussions and the common European views that have emerged from them, while reflecting the diversity of situations in different countries. It highlights important actions required for a successful implementation of DNA-based biomonitoring of aquatic ecosystems by 2030.

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.

Abstract. Rohrschollen Island is an artificial island of the large Upper Rhine river whose geometry and hydrological dynamics are the result of engineering works during the 19th and 20th centuries. Before its channelization, the Rhine river was characterized by an intense hydromorphological activity which maintained a high level of biodiversity along the fluvial corridor. This functionality considerably decreased during the two last centuries. In 2012, a restoration project was launched to reactivate typical alluvial processes, including bedload transport, lateral channel dynamics, and surface–subsurface water exchanges. An integrated hydrological model has been applied to the area of Rohrschollen Island to assess the efficiency of the restoration regarding surface and subsurface flows. This model is calibrated using measured piezometric heads. Simulated patterns of water exchanges between the surface and subsurface compartments of the island are checked against the information derived from thermal infrared (TIR) imaging. The simulated results are then used to better understand the evolutions of the infiltration–exfiltration zones over time and space and to determine the physical controls of surface–subsurface interactions on the hydrographic network of Rohrschollen Island. The use of integrated hydrological modeling has proven to be an efficient approach to assess the efficiency of restoration actions regarding surface and subsurface flows.