Water Use Efficiency (WUE) can be used to describe the relationship between water lossandcarbon fixationof plants in the process of photosynthesis, which is an important variable to link ecosystem carbon and water cycles. Estimating WUE with remote sensing data can enhance our ability to reveal how global change affects water and carbon cycles. Based on triangle model and CASA model which is used to estimate evapotranspiration(ET) and net primary production (NPP), this paper constructs the WUE remote sensing estimation models with improved water limiting parameters. Using the constructed model, this paper acquires the WUE of vegetation over the Weihe River Basin in 2010 based on MODIS imagery and meteorological data. Then this paper studies the relationship between WUE and temperature or precipitation. Results are shown as follows:1) The results of WUE estimated by different WUE models are different because these models are based on different definitions of WUE, different simulation areas, different data sources or different vegetation classifications. 2) The monthly variation of WUE roughly shows a double peak pattern over the Weihe River Basin in 2010 with the highest value in August. The seasonal WUE shows that the maximum value is in summer (1.05 gC?m~(-2)?mm~(-1)), followed by autumn (0.66 gC?m~(-2)?mm~(-1)), spring (0.57 gC?m~(-2)?mm~(-1)) and winter (0.12 gC?m~(-2)?mm~(-1)). 3) The spatial distribution of WUE shows that the high value pixels are in the forest region of Ziwuling, Huanglong Mountain, Liupan Mountain and the northern slope of Qinling, while the low value pixels are in the built- up regions of Xi'an city, low vegetation coverage regions of upper basin and some dry farming areas. 4) With the increase of temperature, the change of WUE can be divided into five stages, which are essentially invariant, slightly increased, rapid increased, stable and declined. With the increase of precipitation, the change of WUE over the Weihe River Basin also can be divided into five stages, which are rapidly increased, slowly increased, stable, slowly declined and rapidly declined.