High-frequency data reveal complex water quality processes in a mixed land use, groundwater dominated catchment in England

Rapid-response, mixed land-use, groundwater-dominated catchments represent a unique yet highly complex class of river systems, where the identification of multiple pollution sources is hindered by the coexistence of several competing hydrological and biogeochemical processes. Traditional regulatory water-quality monitoring typically captures baseline conditions but often fails to resolve short-lived, rainfall-driven pollution dynamics. In this context, concentration–discharge (C–Q) analysis applied to high-frequency datasets provides a powerful framework for disentangling event-scale processes and pollutant sources.

Here, we analyse high-frequency water-quality data from a series of high-flow events in the Pix Brook, a groundwater-dominated chalk stream in Hertfordshire and Central Bedfordshire (England) characterised by flashy hydrological behaviour and heterogeneous land use (approximately 40% agricultural and 60% urban). The C–Q relationships of four parameters (ammonium, turbidity, conductivity, and dissolved oxygen) were examined across 18 rainfall-generated events. Event dynamics were quantified using established hysteresis metrics (Hysteresis Index, HI; Flush Index, FI) alongside a newly developed Complexity Index (CI) to characterise source proximity and process interactions.

Results reveal consistent buffering of hydrological responses by groundwater contributions, while ammonium, conductivity, and dissolved oxygen frequently exhibit dilution during high flows, suggesting limited in-stream sources or rapid dilution by surface runoff. In contrast, turbidity consistently shows accretion, indicating systematic sediment mobilisation during events. Notably, a temporal shift from distal to proximal sediment sources is observed midway through the monitoring period, pointing to the potential emergence of new, faster sediment delivery pathways. Overall, this study demonstrates how high-frequency C–Q hysteresis analysis can effectively resolve event-based water-quality processes and disentangle multiple pollution sources in complex mixed-use catchments, supporting targeted monitoring and pollution mitigation strategies.