Soil Moisture （SM） is an important parameter for grape development， and accurate monitoring of SM in grape-growing areas is beneficial for scientifically guiding field irrigation and other measures， thereby promoting grape quality and yield. We took Jingyang County， Shaanxi Province as a typical study area， calculated six remote sensing indicators， including Normalized Difference Water Index （NDWI）， Vegetation Supply Water Index （VSWI）， Temperature Condition Index （TCI）， Crop Water Stress Index （CWSI）， etc.， based on MODIS reflectance， surface temperature， and evapotranspiration products from 2009 to 2016， preferentially selected indicators through sensitivity analysis of remote sensing indicators on SM， and constructed a comprehensive remote sensing model of SM using the classification regression tree （CART） algorithm to achieve 8-day resolution scale estimation and drought monitoring of SM at key growth stages of grape. The results showed that NDWI， VSWI and CWSI could better characterize the temporal and spatial variations of SM in the grape-growing area， and NDWI has the most timely response to SM changes and the highest correlation. The comprehensive estimation model of SM constructed using the three preferred NDWI， VSWI and CWSI indicators achieve an R² of 0.6 or more for all time phases except 121 and 169， and an R² of 0.8 or more for all time phases at mid-ripening stage. From 2009 to 2016， the drought in the grape-growing area of Jingyang County occurs mostly during the flowering stage and mid-ripening stage of grapes. This study can provide reference for drought monitoring in grape-growing areas.