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Accurately estimating soil moisture in arid regions is extremely important for agricultural development and soil and water conservation in drought prone areas. To reduce the error caused by surface temperature when inverting soil moisture content with the temperature-vegetation dryness index (TVDI), this study employed daily evapotranspiration (ET) as a parameter to replace land surface temperature (LST) and implemented a new spatial index to establish a soil moisture (SM) model in drought prone areas. The counties of Wugong and Fufeng in Shaanxi Province, China are used as the study areas to verify the novel SM monitoring approach by using daily ET and the normalized difference vegetation index (NDVI). The correlation between LST and ET was higher than 0.8, and the results demonstrated the feasibility of retrieving the SM content using ET in place of LST. In addition, the ET vegetation dryness index (EVDI) feature space can be used to retrieve the SM content through a decision support system for agrotechnology transfer cropping system model. A linear correlation of SM measured at different depths revealed that the EVDI is superior to the TVDI for obtaining soil water content and that soil moisture content measured at 0-10 cm has a high correlation with both the EVDI and TVDI than soil moisture content measured at depths of 20-30, 30-40, and 40-50 cm.