Global scale estimation of evaporative losses from large lakes located in different climatic zones

Reliable projection of evaporative fluxes from lakes is at the core of a wide range of hydrological, climatological, and environmental modeling processes. Evaporation results in losses of blue water from lakes in regions with limited freshwater resources and affects aquatic and terrestrial biodiversity. While current estimates of evaporative losses from lakes remain largely empirical depending on locally calibrated heat and mass transfer coefficients or remotely sensed surface temperature data, we propose a physically-based framework that builds on inherent lake characteristics (e.g., bathymetry, light attenuation characteristics) and atmospheric forcing variables to quantify energy dynamics of the water body and surface evaporative fluxes from the largest lakes across different climatic zones on a global scale. To evaluate the performance of the model, the modelling results determining the seasonal variation of vertical temperature profiles and latent heat loss were compared with in situ measurements of water temperature and surface heat fluxes measured in Lake Mead, in the Southwestern USA. We found good agreements between the physically-based estimations and the measured data. We then quantified evaporative losses from 30 lakes in 30 different climate zone sub-types with an average depth ranging from 1.1 m to 577 m and a surface area of 45 km² to 82,000 km². Our preliminary findings for 2020 indicate that variation of first-order atmospheric parameters (i.e., wind, radiation, air temperature, and humidity) across climatic zones and the change in lake bathymetry altering local vertical temperature profiles within the water body significantly affect evaporative losses. The energy-constrained model enables quantifying the extent of evaporative water losses from lakes and provides a theoretical basis for delineating potential impacts on water management and ecological and climatological processes under different climate change scenarios.