Predicting changes in monthly streamflow to Karaj dam reservoir, Iran, in climate change condition and assessing its uncertainty

Climate change may cause great uncertainties in streamflow prediction. For better understanding of and planning for future conditions these uncertainties should be considered. This research investigated some of them by using two Global climate model (GCMs), four downscaling methods (DSMs), and four representative concentration pathways (RCPs) (a total of thirty two different runs). The inflow was predicted for a future period (2013-2045) and compared with both observed and modelled data in the base period (1985-2012). Average annual hydrograph and cumulative distribution functions of annual streamflow was compared. The study shows that all three factors namely GCM, DSM and RCP have great influence on the future streamflow prediction and should be considered in water resources planning. Although there are changes in flow pattern and in most scenarios two peaks in April and May are recorded. More uncertainty in streamflow amounts especially in high low values has been investigated. (C) 2019 The Authors. Published by Elsevier B.V. on behalf of Faculty of Engineering, Ain Shams University.