Assessing different sources of uncertainty in hydrological projections of high and low flows: case study for Omerli Basin, Istanbul, Turkey

Engin B. E., Yücel İ., Yılmaz A.

ENVIRONMENTAL MONITORING AND ASSESSMENT, vol.189, 2017 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 189
  • Publication Date: 2017
  • Doi Number: 10.1007/s10661-017-6059-3
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Keywords: Climate change, Extreme flow prediction, Uncertainty assessment, Statistical downscaling, Seasonality, CLIMATE-CHANGE IMPACTS, PRECIPITATION
  • Middle East Technical University Affiliated: Yes


This study investigates the assessment of uncertainty contribution in projected changes of high and low flows from parameterization of a hydrological model and inputs of ensemble regional climate models (RCM). An ensemble of climate projections including 15 global circulation model (GCM)/RCM combinations and two bias corrections (change factor (CF) and bias correction in mean (BC)) was used to generate streamflow series for a reference and future period using the Hydrologiska Byrans Vattenbalansavdelning (HBV) model with the 25 best-fit parameter sets based on four objective functions. The occurrence time of high flows is also assessed through seasonality index calculation. Results indicated that the inputs of hydrological model from ensemble climate models accounts for greater contribution to the uncertainty related to projected changes in high flows comparing to the contribution from hydrological model parameterization. However, the uncertainty contribution is opposite for low flows, particularly for CF method. Both CF and BC increases the total mean variance of high and low flows. The variability in the occurrence time of high flows through RCMs is greater than the variability resulted from hydrological model parameters with and without statistical downscaling. The CF provides more accurate timing than BC and it shows the most pronounced changes in flood seasonality.