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Making the crop water use status clear in time is important to assess crop water deficit and develope water-saving irrigation strategies. It is of high theoretical and practical significance to promote the sustainable use of regional water resources and improve crop water use efficiency. The field trials of winter wheat under different water treatments were carried out during 2012—2016, the crop canopy reflectance and leaf water content were observed during the major winter wheat growth period. Then the simulated reflectances for the spectral bands of several different satellites were generated by combing the crop canopy reflectance and spectral response functions of Quickbird, IKONOS, GF-2, GF-1, Landsat8, HJ-1A/B, GF-4 and MODIS satellite sensors. Following the forms of normalized vegetation index (NDVI), ratio vegetation index (RVI) and difference vegetation index (DVI), every two simulated reflectances of all satellites were used to establish new vegetation indices. Then the correlations between vegetation indices and leaf water content were systematically analyzed. The response of combination bands and vegetation indices at different spatial resolutions (2.44m, 4m, 8m, 30m, 50m and 250m) to crop water status and irrigation activities were evaluated. The results showed that the sensitive distribution patterns of NDVI, RVI and DVI indices to crop water status were similar. The correlation coefficients between the nearinfrared band reflectance of eight satellites and leaf water content were positive, while the correlation coefficients for other bands were negative. Better correlations were obtained between leaf water content and vegetation indices, including NDVI (GF-1 green band, GF-2 green band), RVI (GF-1 green band, GF-2 green band) and DVI (GF-2 blue band, GF-4 blue band), with R2 of 0.776, 0.774 and 0.886, respectively. Among which the vegetation index in the form of DVI got the best accuracy when estimating leaf water content. Comparing with the existed vegetation indices, the vegetation indices selected had higher accuracy when estimating leaf water content. The above works provided a technical and methodological support for the assessment of crop water conditions and monitoring of crop irrigation at regional scale.