Abstract: Two mono -window algorithms, i. e., radiation transfer model (RTM) and QK&B algorithm, were evaluated and compared for their performance on sea surface temperature (SST) calculation from Landsat8/TIRS data in coastal water of Hongyan River nuclear power station. The parameters of QK&B algorithm were modified for Landsat8 thermal infrared band 10 based on thermodynamic initial guess retrieval(TIGR) atmospheric profile data, and both atmospheric transmittance values obtained from water vapor content based on empirical model and from National Centers for Environmental Prediction (NCEP) data were employed for QK&B algorithm respectively with the purpose of comparing their feasibilities for SST retrieval. A validation with shipboard measurements of SST collected synchronically shows that the slightly better accuracy in SST retrieval is observed from RTM method(RMSE = 0. 525 0) than from modified QK&B algorithm (RMSE = 0. 638 0). QK&B algorithm using atmospheric transmittance simulated using NCEP data provided better accuracy than that using atmospheric transmittance estimated from water vapor content. Sensitivity analysis based on data simulated by MODTRAN4.0 using NCEP data was conducted. The results show that atmospheric transmittance has the greatest impact on the accuracy of SST retrieval among all parameters input RTM method, followed by atmospheric upward radiation. Atmospheric transmittance also shows greater sensitivity for RTM method than that for QK&B algorithm. For QK&B algorithm, atmospheric average temperature has greater impact on SST retrieval than other parameters input. Atmospheric upward radiation for RTM method, atmospheric average temperature for QK&B algorithm and atmospheric transmittance for both two algorithms show increasing impact on SST retrieval with increasing water vapor content.