Canopy temperature measured with infrared thermometers or other remote infrared sensors is an important tool for detecting crop water stress. The crop water stress index (CWSI) is the most often used index which is based on canopy temperature to detect crop water stress. This study evaluates the application of three different forms of CWSI for winter wheat water stress monitoring in the North China Plain (NCP): the Idso empirical model, the Jackson theoretical model, and the new Alves model,
which replaces the radiometric surface temperature with a surface “wet bulb” temperature, thereby avoiding the evaluation of the surface  esistance of the crop. The results show that the CWSI based on Jackson’s definition and Alves’ definition are better than the empirical CWSI for monitoring winter wheat water stress in NCP. Both definitions are useful tools to evaluate winter wheat water stress in NCP, but the CWSI based on Alves’ definition is more practical for monitoring winter wheat water stress in NCP, mainly due to not having to estimate the crop surface resistance, while the CWSI based on Jackson’s definition is more reasonable for quantifying winter wheat water stress in NCP.