Four decades of full-depth profiles reveal layer-resolved drivers of reservoir thermal regimes and event-scale hypolimnetic warming

Abstract. Thermal structure shapes ecological dynamics in lakes and reservoirs. Yet full-profile temperature records over multi-decades remain scarce, constraining mechanistic understanding of depth-resolved thermal changes and subseasonal extremes (e.g., surface heat waves and late-season hypolimnetic warming). In this study, we focused on Rappbode Reservoir—Germany’s largest drinking-water reservoir—and compiled four decades of high-resolution, full-depth temperature profiles with concurrent hydro-meteorological records that are rarely available for stratified systems. Building on these data, we developed a novel two-step analytical framework that integrates long-term monitoring and process-based modelling to yield a high-resolution, internally consistent dataset of spatiotemporal temperature dynamics. We then applied interpretable machine learning to quantify dominant external controls on depth-specific stratification dynamics and determine causal mechanisms governing late-stratification hypolimnetic warming. Our results suggested that influence of external drivers on the thermodynamic structure varied markedly with depth and stratification phase: stratification-strength metrics governed by atmospheric heat fluxes (i.e., surface temperature, vertical temperature difference, Schmidt stability) were controlled mainly by 30-day antecedent shortwave radiation and air temperature. For hypolimnetic temperatures and mixed-layer depth, outflow discharge turned out to be the primary driver during late stratification. Further analysis indicated that episodic hypolimnetic warming up to 10 °C in four specific years was mainly triggered by intensified deep withdrawals that weakened the density gradient and shortened the compensatory-flow pathway. The dual-perspective framework developed here—integrating process-based and machine-learning approaches—is broadly transferable for analyzing ecological processes and supporting evidence-based management in stratified waters.