While evapotranspiration (ET) is normally measured as one hydrologic component, evaporation (E), and transpiration (T) result from different physical-biological processes. Using a two-source model, a trapezoid framework has been widely applied in recent years. The key to applying the trapezoid framework model is the determination of the dry/wet boundaries of the land surface temperature-fractional vegetation coverage trapezoid (LST-f_c). Although algorithms have been developed to characterize the two boundaries, there remains a significant uncertainty near the wet boundary which scatters in a discrete and uneven manner. It is therefore difficult to precisely locate the wet boundary. To address this problem, a Wet Boundary Algorithm (WBA) was developed in this study with the algorithm applied in the region of Huang-Huai-Hai plain of China, using the Pixel Component Arranging and Comparing Algorithm (PCACA) to retrieve ET from MODerate-resolution Imaging Spectroradiometer (MODIS) Data. The eddy covariance (EC) measurements from Yucheng station was used to verify the modified model where the root mean square error (RMSE) of 17.8 W/m², Bias of −7.2 W/m² for latent heat flux (LE) simulation in 28 cloudless test days. The ratio of transpiration to evapotranspiration (T/ET) varied between 0.48 and 0.81 over the Huang-Huai-Hai plain. The spatial and temporal distribution of ET revealed that agriculture practices have a significant influence on the hydrological cycle, where crop growth promotes the magnitude of ET. Likewise, harvesting activities significantly reduce ET. The proposed WBA algorithm significantly reduces the uncertainty of the trapezoid ET model caused by wet edge positioning. The analysis of the impact of agricultural activities on ET provide a better understanding how human activities change the hydrological cycle at regional scales.