High-frequency water quality measurements in streams and rivers have expanded in scope and sophistication during the last two decades. Existing technology allows in situ automated measurements of water quality constituents, including both solutes and particulates, at unprecedented frequencies from seconds to subdaily sampling intervals. This detailed chemical information can be combined with measurements of hydrological and biogeochemical processes, bringing new insights into the sources, transport pathways, and transformation processes of solutes and particulates in complex catchments and along the aquatic continuum. Here, we summarize established and emerging high-frequency water quality technologies, outline key high-frequency hydrochemical data sets, and review scientific advances in key focus areas enabled by the rapid development of high-frequency water quality measurements in streams and rivers. Finally, we discuss future directions and challenges for using high-frequency water quality measurements to bridge scientific and management gaps by promoting a holistic understanding of freshwater systems and catchment status, health, and function.

Combined sewer overflows (CSOs) prevent surges in sewer networks by releasing untreated wastewater into nearby water bodies during intense storm events. CSOs can have acute and detrimental impacts on the environment and thus need to be managed. Although several gray, green and hybrid CSO mitigation measures have been studied, the influence of network structure on CSO occurrence is not yet systematically evaluated. This study focuses on evaluating how the variation of urban drainage network structure affects the frequency and magnitude of CSO events. As a study case, a sewer subnetwork in Dresden, Germany, where 11 CSOs are present, was selected. Scenarios corresponding to the structures with the lowest and with the highest number of possible connected pipes, are developed and evaluated using long-term hydrodynamic simulation. Results indicate that more meshed structures are associated to a decrease on the occurrence and magnitude of CSO. Event frequency reductions vary between 0% and 68%, while reduction of annual mean volumes and annual mean loads ranged between 0% and 87% and 0% and 92%. These rates were mainly related to the additional sewer storage capacity provided in the more meshed scenarios, following a sigmoidal behavior. However, increasing network connections causes investment costs, therefore optimization strategies for selecting intervention areas are needed. Furthermore, the present approach of reducing CSO frequency may provide a new gray solution that can be integrated in the development of hybrid mitigation strategies for the CSO management.

The European Union Water Framework Directive (2000/60/EC; WFD) aims to achieve a good ecological and chemical status of all bodies of surface water by 2027. The development of integrated guidance on surface water chemical monitoring (e.g., WFD Guidance Document No. 7/19) has been transferred into national German law (Ordinance for the Protection of Surface Waters, OGewV). For the majority of compounds, this act requires monthly sampling to assess the chemical quality status of a body of surface water. To evaluate the representativeness of the sampling strategy under the OGewV, high-frequency online monitoring data are investigated under different sampling scenarios and compared with current, monthly grab sampling data. About 23 million data points were analyzed for this study. Three chemical parameters (dissolved oxygen, nitrate-nitrogen, and chloride concentration) and discharge data were selected from four catchments of different sizes, ranging from 51,391 km² to 84 km² (Elbe, Vereinigte Mulde, Neiße and two stations at Lockwitzbach). In this paper, we propose short-term online-monitoring (STOM) as a sampling alternative. STOM considers the placement of online sensors over a limited duration and return interval. In general, we: (I) compare the results of conventional grab sampling with STOM, (II) investigate the different performance of STOM and grab sampling using discharge data as a proxy for analyzing event-mobilized pollutants, and (III) investigate the related uncertainties and costs of both sampling methods. Results show that STOM outperforms grab sampling for parameters where minimum/maximum concentrations are required by law, as the probability of catching a single extreme value is higher with STOM. Furthermore, parameters showing a pronounced diurnal pattern, such as dissolved oxygen, are also captured considerably better. The performance of STOM showed no substantial improvements for parameters with small concentration variability, such as nitrogen-nitrate or chloride. The analysis of discharge events as a proxy parameter for event-mobilized pollutants proves that the probability of capturing samples during events is significantly increased by STOM.

Numerical simulations of rainfall-runoff processes are useful tools for understanding hydrological processes and performing impact assessment studies. The advancements in computer technology and data availability have assisted their rapid development and wide use. This project aims to evaluate the applicability of a physically based, fully distributed rainfall-runoff model TOPKAPI-X for the simulation of flood events in two small watersheds of Saxony, Germany. The results indicate that the model was calibrated well for 4.88 km² Wernersbach catchment (NSE 0.89), whereas 276 km² Wesenitz catchment calibration was only satisfactory (NSE 0.7). The addition of the second soil layer improved the model’s performance in comparison to the simulations with only one soil layer for Wernersbach (NSE increase from 0.83 to 0.89). During the validation process, the model showed a variable performance. The best performance was achieved for Wernersbach for the year with the highest runoff (NSE 0.95) in the last decade. The lowest performance for the Wernersbach and Wesenitz catchments was 0.64 for both. The reasons for the model’s low performance in some years are discussed, and include: (i) input data quality and data insufficiency, (ii) methods used within the simulations (interpolation, ETP estimation, etc.), and (iii) assumptions made during the calibration (manual calibration, parameter selection, etc.).

This study presents the results from a monitoring campaign at two urban streams with multiple monitoring sites along an increased urban gradient, carried out in April to August 2022. The aim of the monitoring campaign was to identify pressures and sources of organic micropollutants using large-volume solid phase extraction. The campaign was using different sampling modes to distinguish between baseflow and evens. Samples were analysed for 735 compounds; the measured concentrations were aggregated for compound classes and related to discharge data. A source analysis showed different emission patterns for compound classes, using the correlation between concentration and discharges during baseflow. The number of detected compounds followed an increasing trend along the streams during baseflow and increased during events. The comparison between baseline samples and event samples showed that events cause a significant increase in the number of detected chemicals as well as in their concentration and relative loads. The event samples also yield higher ecological concerns based on a comparison of measured with effect concentrations (Toxic unit approach). We did not find correlations with different event characteristics (i.e. peak discharge, event duration, etc.). A high variability of compounds among the catchments and sampling sites within the catchments was evident.