Journal of Arid Land

Article Title

Climate change impacts on the streamflow of Zarrineh River, Iran


Zarrineh River is located in the northwest of Iran, providing more than 40% of the total inflow into the Lake Urmia that is one of the largest saltwater lakes on the earth. Lake Urmia is a highly endangered ecosystem on the brink of desiccation. This paper studied the impacts of climate change on the streamflow of Zarrineh River. The streamflow was simulated and projected for the period 1992–2050 through seven CMIP5 (coupled model intercomparison project phase 5) data series (namely, BCC-CSM1-1, BNU-ESM, CSIRO-Mk3-6-0, GFDL-ESM2G, IPSL-CM5A-LR, MIROC-ESM and MIROC-ESM-CHEM) under RCP2.6 (RCP, representative concentration pathways) and RCP8.5. The model data series were statistically downscaled and bias corrected using an artificial neural network (ANN) technique and a Gamma based quantile mapping bias correction method. The best model (CSIRO-Mk3-6-0) was chosen by the TOPSIS (technique for order of preference by similarity to ideal solution) method from seven CMIP5 models based on statistical indices. For simulation of streamflow, a rainfall-runoff model, the hydrologiska byrans vattenavdelning (HBV-Light) model, was utilized. Results on hydro-climatological changes in Zarrineh River basin showed that the mean daily precipitation is expected to decrease from 0.94 and 0.96 mm in 2015 to 0.65 and 0.68 mm in 2050 under RCP2.6 and RCP8.5, respectively. In the case of temperature, the numbers change from 12.33°C and 12.37°C in 2015 to 14.28°C and 14.32°C in 2050. Corresponding to these climate scenarios, this study projected a decrease of the annual streamflow of Zarrineh River by half from 2015 to 2050 as the results of climatic changes will lead to a decrease in the annual streamflow of Zarrineh River from 59.49 m3/s in 2015 to 22.61 and 23.19 m3/s in 2050. The finding is of important meaning for water resources planning purposes, management programs and strategies of the Lake's endangered ecosystem.


climate change, water resources management, climate model intercomparison project phase5 (CMIP5), artificial neural network (ANN), bias correction, hydrologiska byrans vattenavdelning (HBV-Light), Zarrineh River

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