Physical effects of thermal pollution in lakes

Abstract

Anthropogenic heat emissions into inland waters influence water temperature and affect stratification, heat and nutrient fluxes, deep water renewal, and biota. Given the increased thermal stress on these systems by growing cooling demands of riparian/coastal infrastructures in combination with climate warming, the question arises on how to best monitor and manage these systems. In this study, we investigate local and system‐wide physical effects on the medium‐sized perialpine Lake Biel (Switzerland), influenced by point‐source cooling water emission from an upstream nuclear power plant (heat emission ∼700 MW, ∼18 W m−2 lake wide). We use one‐dimensional (SIMSTRAT) and three‐dimensional (Delft3D‐Flow) hydrodynamic numerical simulations and provide model resolution guidelines for future studies of thermal pollution. The effects on Lake Biel by the emitted excess heat are summarized as: (i) clear seasonal trend in temperature increase, locally up to 3.4°C and system‐wide volume mean ∼0.3°C, which corresponds to one decade of regional surface water climate warming; (ii) the majority of supplied thermal pollution (∼60%) leaves this short residence time (∼58 days) system via the main outlet, whereas the remaining heat exits to the atmosphere; (iii) increased length of stratified period due to the stabilizing effects of additional heat; (iv) system‐wide effects such as warmer temperature, prolonged stratified period, and river‐caused epilimnion flushing are resolved by both models whereas local raised temperature and river short circuiting was only identifiable with the three‐dimensional model approach. This model‐based method provides an ideal tool to assess man‐made impacts on lakes and their downstream outflows.

Tributaries affect the thermal response of lakes to climate change

“…2) represents a point-source of thermal pollution. Planned for decommission in 2019, the plant emits ∼ 700 MW of heat into the Aare and substantially warms the river water (Råman Vinnå et al, 2017). The ∼ 8 km long Zihlkanal, LB's second largest tributary, supplies ∼ 32 % of the lake inflow and connects LB to Lake Neuchâtel (Fig.…”

“…The model calculates heat fluxes and vertical mixing driven by wind and the internal wave field using a k − ε turbulence closure scheme. It has been adapted to and validated for multiple lakes including Lake Zürich , LG (Perroud and Goyette, 2010;Schwefel et al, 2016), Lake Neuchâtel , Lake Constance (Fink et al, 2014b;Wahl and Peeters, 2014) and LB (Råman Vinnå et al, 2017). The model contains seven tunable parameters, including p 1 (irradiance absorption), p 2 (sensible heat flux) and K (vertical light absorption) for heat flux adjustments from the atmosphere to the lake.…”

“…To include the effect of seasonally varying stratification strength, we followed Schwefel et al (2016) and varied α: α S for summer (April to September) and α W for winter (October to March), where α S > α W . Here we used the best-fit parameter setup (Table 3) already established and validated for LG and LB by Schwefel et al (2016) and Råman Vinnå et al (2017).…”

“…5e; Råman Vinnå et al, 2017) causes approximately twice as much heating in winter relative to warming from climate change in the far-future. In summer, the relationship reverses with minor MNPP warming relative to that induced by climate change.…”

“…Several studies of large lakes suggest that major tributaries play only a minor role in climate-induced warming and deep-water oxygen renewal (Fink et al, 2014a;Schwefel et al, 2016). Mediumand smaller-scale lakes are, however, more abundant than large lakes (Verpoorter et al, 2014) and exhibit a greater degree of sensitivity to point sources of anthropogenic thermal input which can affect temperature and stratification (Kirillin et al, 2013;Råman Vinnå et al, 2017). Medium-and L. Råman Vinnå et al: Tributaries affect the thermal response of lakes to climate change small-sized lakes also make a more significant contribution to the temperature-dependent global greenhouse gas budget (Holgerson and Raymond, 2016).…”