Modelling of phytoplankton–zooplankton dynamics under environmental change in a temperate dimictic reservoir

Understanding how freshwater ecosystems respond to interacting climatic and anthropogenic pressures requires modelling frameworks that represent coupled physical, chemical, and biological processes across multiple trophic levels. Here, we combined a unique 20-year high-frequency monitoring dataset with the process-based model CE-QUAL-W2 to investigate phytoplankton–zooplankton dynamics in the temperate dimictic Římov Reservoir (Czech Republic). The model represented four phytoplankton functional groups (chlorophytes, cryptophytes, cyanobacteria, and diatoms) and two zooplankton groups (cladocerans and copepods), enabling assessment of bottom-up and top-down ecological controls. Hydrodynamic and thermal processes were reproduced with high accuracy (KGE > 0.89), providing a robust foundation for ecosystem simulations. Although predictive performance varied among individual plankton groups, reflecting the complexity of biological communities over multi-decadal timescales, the model successfully reproduced key ecosystem patterns, including seasonal succession and the spring clear-water phase. Sensitivity analyses identified metabolic parameters, temperature-dependent growth responses, and nutrient uptake kinetics as the principal drivers of simulated community dynamics. Scenario analyses showed that warming (+2 °C) combined with increased phosphorus loading (+30%) enhanced cyanobacterial dominance and shortened the spring clear-water phase. Increased zooplankton grazing partially mitigated these effects, but responses remained sensitive to assumptions regarding trophic interactions and plankton functional traits. The results demonstrate that functional-group resolution can improve the ecological interpretation of process-based reservoir models without requiring unnecessary increases in model complexity. Overall, integrating long-term ecological observations with mechanistic modelling provides a valuable framework for understanding reservoir responses to environmental change and informing adaptive water-resource management.