Hydrochemical data of karst springs provide valuable insights into the internal hydrodynamical functioning of karst systems and support model structure identification. However, the collection of high-frequency time series of major solute species is limited by analysis costs. In this study, we develop a method to retrieve the individual solute concentration time series and their uncertainty at high temporal resolution for karst springs by using continuous observations of electrical conductivity ((Figure presented.)) and low-frequency ionic measurements. Due to the large ion content and non-negligible concentrations of aqueous complexes in karst systems, the concentration of each solute species occurring as free ion and as part of aqueous complexes are computed separately. The concentration of species occurring as free ions are computed considering their contributions to the total (Figure presented.), whereas the concentration of the species as part of complexes are obtained from speciation calculations. The pivotal role of the complexation processes for the reconstruction of solute concentration time series starting from the (Figure presented.) signal is investigated in two karstic catchments with different geologies and temporal resolution of the available hydrochemical datasets, that is the Kerschbaum dolostone system in Austria and the Baget limestone system in France. The results show that complexation processes are significant and should be considered for the estimation of the total solute concentration in case of SO₄, Ca, Mg and HCO₃. The (Figure presented.) signal of a karst spring can be used to interpolate and quantify the dynamics of those solutes characterized by large contribution (approximately >6%) to the total (Figure presented.) and low relative variability, that is HCO₃, Ca and Mg. Moreover, the presented method can be used to estimate concentrations of solutes when applied to karst systems with stationary and hydrogeochemical homogeneous contributing area. On the contrary, the method is affected by large uncertainty in case of dynamic systems characterized by varying contributions of water from different geological areas. This study aims to contribute to the problem of hydrogeochemical data availability and to support future works on karst systems conceptualization.

Water transit time is now a standard measure in catchment hydrological and ecohydrological research. The last comprehensive review of transit time modeling approaches was published 15+ years ago. But since then the field has largely expanded with new data, theory and applications. Here, we review these new developments with focus on water-age-balance approaches and data-based approaches. We discuss and compare methods including StorAge-Selection functions, well/partially mixed compartments, water age tracking through spatially distributed models, direct transit time estimates from controlled experiments, young water fractions, and ensemble hydrograph separation. We unify some of the heterogeneity in the literature that has crept in with these many new approaches, in an attempt to clarify the key differences and similarities among them. Finally, we point to open questions in transit time research, including what we still need from theory, models, field work, and community practice.

The time that water takes to travel through the terrestrial hydrological cycle and the critical zone is of great interest in Earth system sciences with broad implications for water quality and quantity. Most water age studies to date have focused on individual compartments (or subdisciplines) of the hydrological cycle such as the unsaturated or saturated zone, vegetation, atmosphere, or rivers. However, recent studies have shown that processes at the interfaces between the hydrological compartments (e.g., soil-atmosphere or soil-groundwater) govern the age distribution of the water fluxes between these compartments and thus can greatly affect water travel times. The broad variation from complete to nearly absent mixing of water at these interfaces affects the water ages in the compartments. This is especially the case for the highly heterogeneous critical zone between the top of the vegetation and the bottom of the groundwater storage. Here, we review a wide variety of studies about water ages in the critical zone and provide (1) an overview of new prospects and challenges in the use of hydrological tracers to study water ages, (2) a discussion of the limiting assumptions linked to our lack of process understanding and methodological transfer of water age estimations to individual disciplines or compartments, and (3) a vision for how to improve future interdisciplinary efforts to better understand the feedbacks between the atmosphere, vegetation, soil, groundwater, and surface water that control water ages in the critical zone.

The ability to evaluate stream hydrochemistry is often constrained by the capacity to sample streamwater at an adequate frequency. While technology is no longer a limiting factor, costs and sample management can still be a barrier to high-resolution water quality instrumentation. We propose a new framework for investigating the electrical conductivity (EC) of streamwater, which can be measured continuously through inexpensive sensors. We show that EC embeds information about individual ion content that can be isolated to retrieve solute concentrations at high resolution. The essence of the approach is the decomposition of the EC signal into its "harmonics", i.e., the specific contributions of the major ions that conduct current in water. The ion contribution is used to explore water quality patterns and to develop algorithms that reconstruct solute concentrations starting from EC during periods where solute measurements are not available. The approach is validated on a hydrochemical data set from Plynlimon, Wales, showing that improved estimates of high-frequency solute dynamics can easily be achieved. Our results support the installation of EC probes to complement water quality campaigns and suggest that the potential of EC measurements in rivers is currently far from being fully exploited.