Variability Of Evaporation From Lake Taihu And Its Response To Climate Change

Evaporation is an important component of the distribution of energy and the hydrological cycle on the global scale, and is also an indicator of climatic,environmental, and ecosystem changes. In this paper, the variation of evaporation and energy balance over Lake Taihu was analyzed by using eddy covariance data from Bifengang station in 2012. Based on the observation data of Bifengang station,we evaluated three lake models performance at the lake surface heat flux. The global climate model product data and the lake model were used to simulate the future(2010-2100) Lake Taihu evaporation under different greenhouse gas emissions scenario. The results show:(1)The annual evaporation of Lake Taihu in 2012 is 1019.2mm. The latent heat flux was the dominant term of the net radiation energy, which occupied about 90% in 2012. The water body stores heat in the period from March to July, after which the net radiation increases to a maximum in July, and evaporation also reaches a maximum. Thereafter, net radiation reduces to a minimum in December, stored heat is released, and evaporation reaches a minimum in January. The latent heat flux has obvious diurnal variation characteristics, and the maximum value is reached from 13:00 to 14:00 in the afternoon. The minimum value is 5:00-6:00 in the morning.The latent heat flux is consistent with the diurnal variation trend of vapor pressure difference between lake surface and atmosphere. The correlation coefficient is 0.96.(2) CLM4-LISSS, K-? and LAKE lake models can simulate the diurnal variation characteristics of lake surface temperature in August 2012, the best simulation is CLM4-LISSS lake model, and The correlation coefficient between the observed surface temperature and the simulated is 0.94 and the root mean square error is 0.85?. Through the simulation of latent heat flux, three lake models estimate the latent heat flux. CLM4-LISSS model has the best simulation for the latent heat flux, the correlation coefficient between the observed value and the simulated value is 0.78, and the root mean square error is 55.32W m-2. However the correlation coefficient of K-s lake model is 0.72, the root mean square error is 64.53W m-2. the correlation coefficient of K-? lake model is 0.55, and the root mean square error is 61.96W m-2 .(3) In the period of 2010-2100, the evaporation of Lake Taihu increased under different greenhouse gas emission scenarios. According to the scenarios of RCP2.6,RCP4.5 and RCP8.5, the increase of evaporation per decade was 23.7mm, 29.2mm and 34.5mm, respectively. Evaporation rate increases with increasing amount of radiative forcing increases.