Abstract: It is a useful and powerful tool to estimate crop evapotranspiration（ ET） based on remote sensing technology for evaluation of water use efficiency and precision agriculture. To improve the accuracy of estimation,field continuous monitoring system and remote sensing data of Sentinel-2 were employed here to figure up the maize evapotranspiration. The hybrid dual-source scheme and trapezoid framework-based evapotranspiration model（ HTEM）, was selected as ET estimating model. The experimental fields located in Zhongwei City, Ningxia Hui Autonomous Region, and the main observations of the study area were during maize growing season（ from May to Aug.） in 2019. Sentinel-2 data and observed canopy temperature data were the key input data of the HTEM model. Water balance method was also used for comparisons and evaluation of remote sensed ET. Results showed that Sentinel-2 data had high spatial and temporal resolution,which can match the complex planting plots in the study area,reducing the presence of mixed pixels. Remote sensing inversion parameters fit well with ground observation data. The root mean square error（ RMSE） of net radiation over study area during study period was 36. 256 W/m2. Daily evapotranspiration of two maize experimental fields based on HTEM model were 4. 269 mm/d and 4. 339 mm/d,respectively. And total ET of study area were 525. 114 mm and 533. 690 mm during main growing period,respectively. The absolute error between remote sensed ET and calculated ET based on water balance method were 13. 533 mm and 7. 774 mm,respectively.Evaporation and transpiration can be also obtained based on HTEM model. According to the results,total transpiration of maize during study period were 363. 483 mm and 358. 196 mm,respectively. Water was mainly consumed by soil evaporation during the early growth phase. In the middle and late growth phase,transpiration became the main water consumption way. Thus it can be seen that Sentinel-2 data associated with site canopy temperature system would be more available in regional maize evapotranspiration estimation with high precision. These results could also provide technical support for regional crop evapotranspiration research and agricultural water management.