LAKE 2.0: a model for temperature, methane, carbon dioxide and oxygen dynamics in lakes

Abstract

Abstract. A one-dimensional (1-D) model for an enclosed basin (lake) is presented, which reproduces temperature, horizontal velocities, oxygen, carbon dioxide and methane in the basin. All prognostic variables are treated in a unified manner via a generic 1-D transport equation for horizontally averaged property. A water body interacts with underlying sediments. These sediments are represented by a set of vertical columns with heat, moisture and CH 4 transport inside. The model is validated vs. a comprehensive observational data set gathered at Kuivajärvi Lake (southern Finland), demonstrating a fair agreement. The value of a key calibration constant, regulating the magnitude of methane production in sediments, corresponded well to that obtained from another two lakes. We demonstrated via surface seiche parameterization that the near-bottom turbulence induced by surface seiches is likely to significantly affect CH 4 accumulation there. Furthermore, our results suggest that a gas transfer through thermocline under intense internal seiche motions is a bottleneck in quantifying greenhouse gas dynamics in dimictic lakes, which calls for further research.

Methane and carbon dioxide fluxes over a lake: comparison between eddy covariance, floating chambers and boundary layer method

“…CH 4 accumulation near the bottom usually happens in the anoxic conditions in late autumn (Stepanenko et al, 2016). CH 4 concentration at 11 m depth was still three times lower than the maximum concentration found in Stepanenko et al (2016) in late September and 2 times lower than found at 12 m depth in Miettinen et al (2015) in September. A clear increase in CH 4 surface water concentration is seen on 23 September due to upwelling and concentration up to 0.19 mmol m −3 was measured with the automatic system on 24 September.…”

“…CO 2 concentration at 11 m depth was 10 times higher than at the surface and comparable to those measured in Miettinen et al (2015) at 12 m depth. Diel variation observed in CO 2 concentration at 11 m could be caused by either lake-side cooling and convection or by internal waves (Stepanenko et al, 2016).…”

“…At 11 m depth CH 4 concentration was almost 10 times higher than at the surface. Diel variation of CH 4 concentration at 11 m could be caused by lake-side cooling and convection or, more likely, by internal waves (Stepanenko et al, 2016), triggering the lake-bottom CH 4 -rich sediments.…”

A General Lake Model (GLM 2.4) for linking with high-frequency sensor data from the Global Lake Ecological Observatory Network (GLEON)

“…The weightings provided by each layer to the sediment are based on the relative depth overlap of a layer with the depth range of the sediment zone. This approach makes the model suitable for long-term assessments of wetland, lake and reservoir 5 biogeochemical budgets, including for C, N and other attribute balances as required (Stepanenko et al, 2016). Secondly, the water quality modules feed back to GLM properties related to the water and/or heat balance.…”

Optimizing the parameterization of deep mixing and internal seiches in one-dimensional hydrodynamic models: a case study with Simstrat v1.3

“…The algorithms and assumptions applied by these models vary greatly, as does their complexity, which ranges from simple box models to intricate three-dimensional models (Stepanenko et al, 2016;Wang et al, 2016;Ji, 2008;Hodges et al, 2000). For climate change studies, long-time lake simulations are needed, often utilizing vertical one-dimensional (1-D) models (Wood et al, 2016;Butcher et al, 2015;Komatsu et al, 2007;Hostetler and Small, 1999).…”