The assessment of regional evapotranspiration (ET) and its variation attribution under changing environment are currently international frontier on water sciences. The planting structure and water-use patterns of farmland have changed a lot in recent decades in most river basins of China under double impacts of the climate change and human activities,. Existing spatial and temporal distributions of farmland ET consumption also take on new patterns accordingly and there is short of a series of mature attribution analysis theory and methods for farmland ET change. Thus, the Guanzhong area of Weihe River basin under the strong influence of climate change and human activities is selected as the study area, a distributed hydrological model which considers the impact of the climate change and human activities, and the two-layer remote sensing ET model are built for daily ET estimation. Then, the Ensemble Kalman Filter (EnKF) will be used to assimilate the both models to construct a data assimilation system for simulate the ET process with high accuracy, and the observed ET data will be used to test and optimize the simulation. The factor of human activity is fully considered to improve the classical climate elastic coefficient method, and the new attribution approach will be used to quantitatively analyze the impact of climate change and human activities on farmland ET, and the uncertainty of these approaches also will be discussed. The study will reveal the mechanism of the temporal and spatial change for farmland water consumption and the mutual impact mechanism with climate change, and will provide a scientific support for efficient utility of farmland water and regional regulation for sustainable water resources.