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Abstract Water temperature, ice cover, and lake stratification are important physical properties of lakes and reservoirs that control mixing as well as bio-geo-chemical processes and thus influence the water quality. We used an ensemble of vertical one-dimensional hydrodynamic lake models driven with regional climate projections to calculate water temperature, stratification, and ice cover under the A1B emission scenario for the German drinking water reservoir Lichtenberg. We used an analysis of variance method to estimate the contributions of the considered sources of uncertainty on the ensemble output. For all simulated variables, epistemic uncertainty, which is related to the model structure, is the dominant source throughout the simulation period. Nonetheless, the calculated trends are coherent among the five models and in line with historical observations. The ensemble predicts an increase in surface water temperature of 0.34 K per decade, a lengthening of the summer stratification of 3.2 days per decade, as well as decreased probabilities of the occurrence of ice cover and winter inverse stratification by 2100. These expected changes are likely to influence the water quality of the reservoir. Similar trends are to be expected in other reservoirs and lakes in comparable regions. 

Lakes are classified by thermal mixing regimes, with shallow waterbodies historically categorized as continuously mixing systems. Yet, recent studies demonstrate extended summertime stratification in ponds, underscoring the need to reassess thermal classifications for shallow waterbodies. In this study, we examined the summertime thermal dynamics of 34 ponds and shallow lakes across temperate North America and Europe to categorize and identify the drivers of different mixing regimes. We identified three mixing regimes: rarely (n = 18), intermittently (n = 10), and often (n = 6) mixed, where waterbodies mixed an average of 2%, 26%, and 75% of the study period, respectively. Waterbodies in the often mixed category were larger (≥4.17 ha) and stratification weakened with increased wind shear stress, characteristic of “shallow lakes.” In contrast, smaller waterbodies, or “ponds,” mixed less frequently, and stratification strengthened with increased shortwave radiation. Shallow ponds (<0.74 m) mixed intermittently, with daytime stratification often breaking down overnight due to convective cooling. Ponds ≥0.74 m deep were rarely or never mixed, likely due to limited wind energy relative to the larger density gradients associated with slightly deeper water columns. Precipitation events weakened stratification, even causing short‐term mixing (hours to days) in some sites. By examining a broad set of shallow waterbodies, we show that mixing regimes are highly sensitive to very small differences in size and depth, with potential implications for ecological and biogeochemical processes. Ultimately, we propose a new framework to characterize the variable mixing regimes of ponds and shallow lakes. 

Abstract Small waterbodies have potentially high greenhouse gas emissions relative to their small footprint on the landscape, although there is high uncertainty in model estimates. Scaling their carbon dioxide (CO₂) and methane (CH₄) exchange with the atmosphere remains challenging due to an incomplete understanding and characterization of spatial and temporal variability in CO₂and CH₄. Here, we measured partial pressures of CO₂(pCO₂) and CH₄(pCH₄) across 30 ponds and shallow lakes during summer in temperate regions of Europe and North America. We sampled each waterbody in three locations at three times during the growing season, and tested which physical, chemical, and biological characteristics related to the means and variability ofpCO₂andpCH₄in space and time. Summer means ofpCO₂andpCH₄were inversely related to waterbody size and positively related to floating vegetative cover;pCO₂was also positively related to dissolved phosphorus. Temporal variability in partial pressure in both gases weas greater than spatial variability. Although sampling on a single date was likely to misestimate mean seasonalpCO₂by up to 26%, mean seasonalpCH₄could be misestimated by up to 64.5%. Shallower systems displayed the most temporal variability inpCH₄and waterbodies with more vegetation cover had lower temporal variability. Inland waters remain one of the most uncertain components of the global carbon budget; understanding spatial and temporal variability will ultimately help us to constrain our estimates and inform research priorities.