In this study,the Surface Energy Balance Algorithms for Land(SEBAL) model and Moderate Resolution Imaging Spectroradiometer(MODIS) products from Terra satellite were combined with meteorological data to estimate evapotranspiration(ET) over the Sanjiang Plain,Northeast China.Land cover/land use was classified by using a recursive partitioning and regression tree with MODIS Normalized Difference Vegetation Index(NDVI) time series data,which were reconstructed based on the Savitzky-Golay filtering approach.The MODIS product Quality Assessment Science Data Sets(QA-SDS) was analyzed and all scenes with valid data covering more than 75% of the Sanjiang Plain were selected for the SEBAL modeling.This provided 12 overpasses during 184-day growing season from May 1st to October 31st,2006.Daily ET estimated by the SEBAL model was misestimaed at the range of-11.29% to 27.57% compared with that measured by Eddy Covariance system(10.52% on average).The validation results show that seasonal ET from the SEBAL model is comparable to that from ground observation within 8.86% of deviation.Our results reveal that the time series daily ET of different land cover/use increases from vegetation on-going until June or July and then decreases as vegetation senesced.Seasonal ET is lower in dry farmland(average(Ave):491 mm) and paddy field(Ave:522 mm) and increases in wetlands to more than 586 mm.As expected,higher seasonal ET values are observed for the Xingkai Lake in the southeastern part of the Sanjiang Plain(Ave:823 mm),broadleaf forest(Ave:666 mm) and mixed wood(Ave:622 mm) in the southern/western Sanjiang Plain.The ET estimation with SEBAL using MODIS products can provide decision support for operational water management issues. In this study, the Surface Energy Balance Algorithms for Land (SEBAL) model and Moderate Resolution Imaging Spectroradiometer (MODIS) products from Terra satellite were combined with meteorological data to estimate evapotranspiration (ET) over the Sanjiang Plain, Northeast China. Land cover / land use was classified by using a recursive partitioning and regression tree with MODIS Normalized Difference Vegetation Index (NDVI) time series data, which were reconstructed based on the Savitzky-Golay filtering approach. The MODIS product Quality Assessment Science Data Sets (QA-SDS) was analyzed and all scenes with valid data covering more than 75% of the Sanjiang Plain were selected for the SEBAL modeling. This provided 12 overpasses during 184-day growing season from May 1st to October 31st, 2006. Daily ET estimated by the SEBAL model was misestimaed at the range of-11.29% to 27.57% compared with that measured by Eddy Covariance system (10.52% on average). The validation results show that seasonal ET from the SEBAL model is comparable to that from ground observation within 8.86% of deviation. Our results reveal that the time series daily ET of different land cover / use increases from vegetation on-going until June or July and then decreases as vegetation senesced. is lower in dry farmland (average (Ave): 491 mm) and paddy field (Ave: 522 mm) and increases in wetlands to more than 586 mm. As expected, higher seasonal ET values ​​are observed for the Xingkai Lake in the southeastern part of the Sanjiang Plain (Ave: 823 mm), broadleaf forest (Ave: 666 mm) and mixed wood (Ave: 622 mm) in the southern / western Sanjiang Plain. The ET estimation with SEBAL using MODIS products can provide decision support for operational water management issues.