Assessing and projecting lake health in a changing world using a coupled physical–biogeochemical model: a case study of Windermere

Lake ecosystems are increasingly exposed to multiple stressors arising from the combined effects of climate change and human activities, leading to a range of lake health issues, including oxygen depletion, eutrophication, algal blooms, and even regime shifts. These interacting stressors complicate the diagnosis of lake health and underscore the need for integrative, process-based approaches that explicitly link physical and biogeochemical processes. In this study, we apply a process-based lake ecosystem model (GOTM-WET) to assess and project the ecosystem health of Windermere (South Basin) in the Lake District National Park, UK, a deep, dimictic lake with extensive long-term observations. The model integrates meteorological forcing with in situ measurements of water temperature and dissolved oxygen (DO) to explicitly resolve physical mixing, thermal stratification, and biogeochemical oxygen dynamics. Model calibration is conducted in a stepwise and hierarchical manner, first constraining physical processes and subsequently ecosystem processes, thereby ensuring a robust representation of the coupled physical–biogeochemical lake system. Using the well-calibrated model, we derive a suite of process-based lake health indicators that capture both physical and ecological dimensions of lake functioning. These include stratification characteristics, vertical mixing efficiency, and seasonal hypolimnetic DO depletion rates, which together reflect the capacity of the lake to sustain oxygenated habitats and maintain resilient biogeochemical cycles. Model results demonstrate that variations in physical mixing regimes exert a dominant control on deep-water oxygen dynamics, with important implications for ecosystem stability and habitat quality. By linking observable lake health indicators to underlying ecosystem processes, this study demonstrates the value of process-based modelling for comprehensive lake health assessment. Unlike purely empirical or index-based approaches, the GOTM–WET enables scenario-based simulations and mechanistic interpretation, providing a powerful tool for evaluating lake ecosystem responses under multiple stressors. The approach and evaluation framework developed here is transferable to other lake systems and offers a foundation for scaling lake health assessments from individual lakes to broader regional applications.