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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Preprints
https://doi.org/10.5194/hess-2020-349
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-2020-349
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  05 Aug 2020

05 Aug 2020

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This preprint is currently under review for the journal HESS.

Lake thermal structure drives inter-annual variability in summer anoxia dynamics in a eutrophic lake over 37 years

Robert Ladwig1, Paul C. Hanson1, Hilary A. Dugan1, Cayelan C. Carey2, Yu Zhang3, Lele Shu4, Christopher J. Duffy5, and Kelly M. Cobourn6 Robert Ladwig et al.
  • 1Center for Limnology, University of Wisconsin-Madison, Madison, WI, USA
  • 2Department of Biological Sciences, Virginia Tech, Blacksburg, VA, USA
  • 3Earth and Environmental Sciences, Los Alamos National Laboratory, Los Alamos, NM, USA
  • 4Department of Land, Air and Water Resources, University of California, Davis, Davis, CA, USA
  • 5Department of Civil & Environmental Engineering, The Pennsylvania State University, State College, PA, USA
  • 6Department of Forest Resources and Environmental Conservation, Virginia Tech, Blacksburg, VA, USA

Abstract. The concentration of oxygen is fundamental to lake water quality and ecosystem functioning through its control over habitat availability for organisms, redox reactions, and recycling of organic material. In many eutrophic lakes, oxygen depletion in the bottom layer (hypolimnion) occurs annually during summer stratification. The temporal and spatial extent of summer hypolimnetic anoxia is determined by interactions between the lake and its external drivers (e.g., catchment characteristics/nutrient loads, meteorology), as well as internal feedback mechanisms (e.g., organic matter recycling, phytoplankton blooms). How these drivers interact to control the evolution of lake anoxia over decadal time scales will determine, in part, the future lake water quality. In this study, we used a vertical one-dimensional hydrodynamic-ecological model (GLM-AED2) coupled with a calibrated hydrological catchment model (PIHM-Lake) to simulate the thermal and water quality dynamics of the eutrophic Lake Mendota (USA) over a 37-year period. The calibration and validation of the lake model consisted of a global sensitivity evaluation as well as the application of an evolutionary optimization algorithm to improve the fit between observed and simulated data. By quantifying stability indices (Schmidt Stability, Birgean Work, stored internal heat), we identified spring mixing and summer stratification periods, and quantified the energy required for stratification and mixing. To qualify which external and internal factors were most important in driving the inter-annual variation in summer anoxia, we applied a random-forest classifier and multiple linear regression to modeled ecosystem variables (e.g., stratification onset and offset, ice duration, gross primary production.) Lake Mendota exhibited prolonged hypolimnetic anoxia each summer, lasting between 50–60 days. The summer heat budget, as well as the timing of thermal stratification, were the most important predictors of the spatial and temporal extent of summer anoxia periods in Lake Mendota. An earlier onset of thermal stratification in combination with a higher vertical stability strongly affected the duration and spatial extent of summer anoxia. As the heat budget depended primarily on external meteorological conditions, the spatial and temporal extent of summer anoxia in Lake Mendota is likely to increase in the near future as a result of projected climate change in the region.

Robert Ladwig et al.

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Robert Ladwig et al.

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Short summary
Using a modeling framework applied to 37 years of dissolved oxygen time series data from Lake Mendota, we identified the timing and intensity of thermal energy stored in the lake water column, the lake's resilience to mixing, and surface primary production as the most important drivers of interannual dynamics of low oxygen concentrations at the lake bottom. Due to climate change, we expect an increase in the spatial and temporal extent of low oxygen concentrations at Lake Mendota.
Using a modeling framework applied to 37 years of dissolved oxygen time series data from Lake...
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