Mechanistic controls on river water quality dynamics across catchments

Rivers provide essential ecosystem services, supporting biodiversity, regulating water flow, and supplying resources important for human societies. However, anthropogenic pressures and climate change are increasingly impacting riverine ecosystems, leading to widespread decline in water quality. While substantial progress has been made in understanding long-term water quality trends, our understanding of water quality variations within different catchments is still limited. Moreover, there is a lack of insight into how these variations relate to each other across catchments, making it difficult to predict and manage water quality dynamics at larger spatial scales. Most studies to date have focused on individual sites or small catchment networks, providing valuable insights into site-specific functioning. However, these site-specific studies only offer limited support for understanding and predicting water quality dynamics across larger spatial scales and complex river networks. Understanding the drivers of these complex water quality dynamics is crucial for effective river management and the protection of aquatic ecosystems.

This study addresses this gap by analysing high-frequency water quality data from over 50 sites across England. We focus on key parameters, such as dissolved oxygen, turbidity, pH, and chlorophyll-a, and investigate how water quality fluctuates on diurnal, seasonal, and event-based timescales. We explore the role of event and catchment conditions—such as precipitation, temperature, antecedent conditions, and seasonal variation—in driving water quality variability, and how their importance shifts across time and space.

This research advances our mechanistic understanding of the complex and dynamic processes that govern water quality in rivers across England, with implications for water resource management, environmental monitoring, and the development of more effective strategies for mitigating pollution and protecting aquatic ecosystems.