Spatial vs temporal variability in German river water quality

River water quality is degraded by a multitude of diffuse and point sources impeding ecosystem functioning and constituting a severe risk for human water security all over the world. Monitoring campaigns are the basis of evaluating water quality by characterizing probability of concentrations in time and space, allowing to identify solute source zones and flow paths. This knowledge can then aid in the development of effective water quality management strategies. However, it is not clear, whether current monitoring approaches provide sufficient information to allow to soundly characterize concentration probability over time and localize pollution sources in space. We propose a space-time variance framework to characterize spatial and temporal variation in river water quality and analyze its interplay. Specifically, we assess for discharge and two contrasting solutes (anthropogenic: NO₃^-, biogenic: DOC) by analyzing time series data across 1386 stations in Germany (Ebeling et al. 2022) . Variability is quantified by using the Coefficient of Variation (CV) of mean temporal and spatial variation of subsets of catchments. We find a large span of both spatial and temporal CV for discharge, NO₃^- and DOC. Overall, variability of discharge was considerably higher in time and space than the variation of NO₃^- and DOC. Differences between CVs of NO₃^- and DOC were smaller than expected from their different landscape sources. Apart from analyzing national to continental-scale data records, we plan to analyze archetypal patterns of solutes by utilizing a stochastic modelling approach. Ultimately, the aim is to inform stakeholders whether monitoring strategies such as synoptic sampling are viable approaches and to disentangle anthropogenic and natural drivers to illuminate their role for spatial and temporal variation in river ecosystems.

Ebeling, P., Kumar, R., Lutz, S. R., Nguyen, T., Sarrazin, F., Weber, M., Büttner, O., Attinger, S., and Musolff, A.: QUADICA: water QUAlity, DIscharge and Catchment Attributes for large-sample studies in Germany, Earth Syst. Sci. Data, 14, 3715–3741, https://doi.org/10.5194/essd-14-3715-2022, 2022.