In spite of trying to understand processes in the same spatial domain, the catchment hydrology and water quality scientific communities are relatively disconnected and so are their respective models. This is emphasized by an inadequate representation of transport processes, in both catchment-scale hydrological and water quality models. While many hydrological models at the catchment scale only account for pressure propagation and not for mass transfer, catchment scale water quality models are typically limited by overly simplistic representations of flow processes. With the objective of raising awareness for this issue and outlining potential ways forward we provide a nontechnical overview of (1) the importance of hydrology-controlled transport through catchment systems as the link between hydrology and water quality; (2) the limitations of current generation catchment-scale hydrological and water quality models; (3) the concept of transit times as tools to quantify transport; and (4) the benefits of transit time based formulations of solute transport for catchment-scale hydrological and water quality models. There is emerging evidence that an explicit formulation of transport processes, based on the concept of transit times has the potential to improve the understanding of the integrated system dynamics of catchments and to provide a stronger link between catchment-scale hydrological and water quality models.

We discuss a recent theoretical approach combining catchment-scale flow and transport processes into a unified framework. The approach is designed to characterize the hydrochemistry of hydrologic systems and to meet the challenges posed by empirical evidence. StorAge Selection functions (SAS) are defined to represent the way catchment storage supplies the outflows with water of different ages, thus regulating the chemical composition of out-fluxes. Biogeochemical processes are also reflected in the evolving residence time distribution and thus in age-selection. Here we make the case for the routine use of SAS functions and look forward to areas where further research is needed.

[1] Travel time distributions are often used to characterize catchment discharge behavior, catchment vulnerability to pollution and pollutant loads from catchments to downstream waters. However, these distributions vary with time because they are a function of rainfall and evapotranspiration. It is important to account for these variations when the time scale of interest is smaller than the typical time-scale over which average travel time distributions can be derived. Recent studies have suggested that subsurface mixing controls how rainfall and evapotranspiration affect the variability in travel time distributions of discharge. To quantify this relation between subsurface mixing and dynamics of travel time distributions, we propose a new transformation of travel time that yields transformed travel time distributions, which we call Storage Outflow Probability (STOP) functions. STOP functions quantify the probability for water parcels in storage to leave a catchment via discharge or evapotranspiration. We show that this is equal to quantifying mixing within a catchment. Compared to the similar Age function introduced by Botter et al. (2011), we show that STOP functions are more constant in time, have a clearer physical meaning and are easier to parameterize. Catchment-scale STOP functions can be approximated by a two-parameter beta distribution. One parameter quantifies the catchment preference for discharging young water; the other parameter quantifies the preference for discharging old water from storage. Because of this simple parameterization, the STOP function is an innovative tool to explore the effects of catchment mixing behavior, seasonality and climate change on travel time distributions and the related catchment vulnerability to pollution spreading.

[1] Nitrate pollution of surface waters is widespread in lowland catchments with intensive agriculture. For identification of effective nitrate concentration reducing measures the nitrate fluxes within catchments need to be quantified. In this paper we applied a mass transfer function approach to simulate catchment-scale nitrate transport. This approach was extended with time-varying travel time distributions and removal of nitrate along flow paths by denitrification to be applicable for lowland catchments. Numerical particle tracking simulations revealed that transient travel time distributions are highly irregular and rapidly changing, reflecting the dynamics of rainfall and evapotranspiration. The solute transport model was able to describe 26 years of frequently measured chloride and nitrate concentrations in the Hupsel Brook catchment (6.6 km 2 lowland catchment in the Netherlands) with an R 2 value of 0.86. Most of the seasonal and daily variations in concentrations could be attributed to temporal changes of the travel time distributions. A full sensitivity analysis revealed that measurements other than just surface water nitrate and chloride concentrations are needed to constrain the uncertainty in denitrification, plant uptake, and mineralization of organic matter. Despite this large uncertainty, our results revealed that denitrification removes more nitrate from the Hupsel Brook catchment than stream discharge. This study demonstrates that a catchment-scale lumped approach to model chloride and nitrate transport processes suffices to accurately capture the dynamics of catchment-scale surface water concentration as long as the model includes detailed transient travel time distributions.