Runoff Estimation Using IHACRES Model Based on CHIRPS Satellite Data and CMIP5 Models (Case Study: Gorganroud Basin- Aq Qala Area)

Document Type : Research Paper


1 Associate professor of Climatology Shahid Beheshti University The Faculty of Earth Sciences Tehran,Iran

2 Ph.D Student of Urban Climatology, Shahid Beheshti University, Tehran, Iran

3 MSC of Climatology, Shahid Beheshti University, Tehran, Iran


The catchment is a temporal-spatial dynamic hydrologic system; therefore, the process of rainfall-runoff is complicated. The hydrological models with their potentials are efficient tools to estimate runoff, especially under the conditions of climate change. The purpose of this study is to estimate runoff of Gorganroud Basin, located in the Aq Qala region, using the IHACRES semi-distributive model. For this purpose, the data of Gorgan Synoptic and Aq Qala Hydrometry Stations, four models; CanESM2, GFDL-CM3, HadGEM2, and MRI-CGCM3 from the CMIP5 models were applied under the SDSM and MarkSimGCM Statistical Downscaling methods. High-resolution CHIRPS precipitation data (0.05 × 0.05 arc degree) were also used. The statistical indices of R2, MBE, and RMSE were used for validation and non-parametric Mann-Kendall and Sen's Slope tests were used to evaluate the trend and slope trend of the data process. The results showed that the CanESM2 model downscaled with SDSM has a higher performance than the other models. CHIRPS data has also shown a good performance for rainfall studies. The long-term statistical behavior of discharge in Aq Qala showed that April and May have the maximum discharges among the other months. Although IHACRES model did not show an appropriate performance for prediction of maximum discharges, but in general, it's performance is acceptable. The rainfall-runoff trend during the proposed future period under the RCP2.6 and RCP4.5 scenarios will be reduced, whereas, it will be increased under the RCP8.5 scenario. Expected flood events in the region are also expected to show an increment trend with respect to the rainfall increment.


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