In general, uncertainty means doubts about the results obtained and the parameters, models and structure of a subject iired by human knowledge deficiencies or the nature and variability of nature. It is always important and especially in the current society, to consider the uncertainty factor in a variety of decisions, especially undesirables that challenge goals. For this reason, in the case study of the Zayandeh-rood Basin, the uncertainty of the SPI, SPEI and RDI drought indexes under three emission and climate scenarios RCP2.6, RCP4.5 and RCP8.5 using nine models of AOGCM that have been downscaled by LARS-WG6.0, estimated by the wavelet method. The advantage of this method is simultaneous localization of frequency and time and establishing an ideal fit between the two factors according to the Heisenberg uncertainty principle as well as higher accuracy. To obtain these uncertainties, cross wavelet or XWT was used at a 95% confidence level and 5% significance level. In this study, a wavelet- method was developed to calculate the uncertainty of prediction of temperature and precipitation parameters as well as drought indexes on 15 meteorological stations approved by the Ministry of Energy and Meteorological Organization at Zayandeh-rood Basin and Its sub-basins were evaluated. For this purpose, three commonly used meteorological drought indexes with 12 month scale were selected for analysis. To validate the developed method, part of the climatic forecasts from 2006 to 2017 is used, whose data are available both on climate change scenarios (RCPs) and on meteorological stations. According to the results, the Arithmetic mean of predicted and recorded uncertainty error for SPI, SPEI and RDI indexes based on RMSE error function in upstream and downstream of the basin were 17.74% and 14.97%, respectively and based on MAE error index were 16.38% and 12.47%, respectively. In this research, to calculate the total uncertainty for 16 sub-basins with a certain number of meteorological stations from WTC was used. SPI index had the lowest average uncertainty in comparison with reality and other two indexes (SPEI and RDI) that mean prediction uncertainty with SPI index for upstream and downstream watersheds were calculated 22.69% and 20.61% based on observational data. In the upstream of the basin and in all the stations studied, the least uncertainty was obtained for RCP4.5 but in the downstream of the basin different results were obtained from the RC finally, the developed method for calculating the uncertainty was obtained. The accuracy of drought indexes based on climate data predicted by RCPs from 2020 to 2099 was used. The results show uncertainties of 18.97, 14.51 and 12.56 percent for SPI, SPEI and RDI in upstream and 19.85, 12.85 and 12.16 percent in downstream, respectively. Based on the results of this study, for more reliable future climate assessments, the RCP8.5 in upstream and downstream and the RDI index are suggested for a more reliable forecast of drought. Keywords: Uncertainty, Wavelet Analysis, XWT, WTC, Drought Index.