Uncertainty Analysis of Climate Change Impacts on Streamflow Extremes in Zayandeh-Rud River by Bayesian Model Averaging

The evaluation of climate change impact on hydrological cycle includes uncertainty. This study aimed to evaluate the uncertainty of climate change impact on the Zayandeh-Rud Reservoir inflow during the future period of 2020-2049. The outputs of 22 GCM models were used under the three emission scenarios including RCP2.6, RCP4.5 and RCP8.5. The Bayesian Model Averaging (BMA) was used as the uncertainty analysis for weighting the 22 GCM models based on their ability to simulate the baseline 1990-2005 period. Results showed that different GCM models had different abilities in estimating climatic and hydrological variables and the application of uncertainty analysis in climate change studies could be necessary. The monthly temperature in the upstream of Zayandeh-Rud reservoir could be raised by 0.85 to 1 ◦C; also, the precipitation might be increased by 2 to 3 percent. The high flow during winter season will increase under climate change, while the spring and autumn seasons’ low flows are expected to reduce. Additionally, the annual reservoir inflow may decrease by 1 to 8 percent, showing the necessity for change in Zayandeh-Rud reservoir’s rule curve and allocation of water resources.