Canopy conductance (G_c) has a crucial influence on vegetation transpiration and photosynthesis. In this study, we measured the evapotranspiration (ET) of a Tamarix spp. stand in the 2013 growing season in the lower Tarim River basin using the eddy covariance technology. Meteorological variables including temperature (T), vapor pressure deficit (VPD), solar radiation (S), and photosynthetically active radiation (PAR) were also measured. We calculated G_c using the inverted Penman-Monteith equation and analyzed its daily and seasonal variation. The relationships between G_c and leaf area index (LAI), T, PAR and VPD were assessed through monadic and multivariate regression analysis. We used data from odd days of the year (DOYs) to build a predictive model and used data for even DOYs to evaluate it. The results showed that:(1) G_c of the Tamarisk spp. stand had a similar variation pattern during the greening-up period (GP), maturity period (MP), and senescence period (SP). G_c increased rapidly in the morning, reached a maximum at 10:30 am, and decreased gradually until 6:00 pm at which point there was a sharp decrease; (2) the seasonal variation of G_c was significant. G_c increased rapidly, decreased slowly, and decreased rapidly with mean values of 0.56 in GP, 1.27 in MP and 0.59 in MP, respectively; (3) LAI was the main driver of G_c, the determinative coefficient was 0.746 in the monadic regression analysis and the partial correlation coefficient reached 0.715, followed by T, PAR, and VPD. Multivariate regression analysis that included all the variables had a determinative coefficient (R²) of 0.79; and finally, (4) the prediction model from odd DOYs had a multiple correlation coefficient of 0.885 with a P value less than 0.01. The model test performed using predicted and calculated G_c over even DOYs resulted in a R² of 0.790, a root mean square error (RMSE) of 0.169 mm/s, and the Nash-Sutcliffe model efficiency coefficient (NSE) of 0.814, indicating that the model had a relatively high accuracy.