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Impact of Climate Change on Maximum Discharges: Case Study of Aidoghmoush Basin, East Azerbaijan
P. Ashofteh, A. R. Massah Bouani,
Volume 14, Issue 53 (10-2010)
Abstract
Climate change has different impacts on extreme events such as flood and drought. However, in Iran there are few researches about the impacts. This research was aimed to investigate maximum annual discharge (magnitude and frequency) that may occur due to climate change in Aidoghmoush Basin during 2040-2069 (2050s). At first, monthly temperature and precipitation data of HadCM3 model under the SRES emission scenario, namely A2 , was provided for the basin. Then, these data were downscaled spatially and temporally to Aidoghmoush basin by proportional and change factor downscaling methods. Results showed that the temperature increases (between 1.5 to 4) and the precipitation varies (30 to 40 percent) in 2040-2069 compared with baseline period (1971-2000). A semi-conceptual model (IHACRES) for simulation of daily runoff was calibrated. Downscaled temperature and Precipitation for 2050s were introduced to IHACRES and daily runoff was simulated for the future. Probability distribution was fitted to maximum annual discharge series and the maximum discharge regime of the future was compared with the baseline. Results indicated that climate change affects Maximum discharge in the regime of the basin. Also, the analysis showed that the intensity of maximum discharges for the time period less than 50 does not show any significant difference but by increasing the return period, the intensity increases in future periods. Moreover, it was shown that the probability of maximum discharges with constant intensity will decrease in the future compared to the baseline.
Investigating the Effect of Climate Change on Inflow Runoff into the Karun-4 Dam Based on IPCC's Fourth and Fifth Report
A. Mansouri, B. Aminnejad, H. Ahmadi,
Volume 22, Issue 2 (9-2018)
Abstract
In the present paper, fluctuations of inflow into the Karun-4 Dam under different scenarios of the climate change for the future period of 2021-2050 were investigated. For this purpose, the outputs of the HadCM3 model under the scenarios of B1 (optimistic) and A2 (pessimistic) were utilized for the fourth report; additionally, the outputs of the ensemble model under RCP 2.6 (optimistic) and RCP 8.5 (pessimistic) scenarios were used for the fifth report. Moreover, in order to estimate runoff in the future period, the artificial neural network was considered as a rainfall-runoff model. The results indicated that the average annual precipitation in the five study stations under B1 and RCP 2.6 scenarios was increased by 15 and 5%, respectively, while it showed a decrease equal to 8 and 6%, respectively under the scenarios A2 and RCP 8.5. Furthermore, the average annual temperature in all scenarios showed increase, which was at least 1.06 ⁰C under the scenario B1 and 1.89 ⁰C under scenario RCP 8.5. Examining the input inflow into the Karun-4 dam showed that under both B1 and RCP 2.6 scenarios, the annual inflow will be increased by 1.8 and 1.5%, respectively; under the two scenarios A2 and RCP of 8.5, the annual inflow will be decreased   to 10.4 and 9.8%, respectively.

Evaluation of the Effects of Climate Change on Meteorological Parameters under Different Scenarios in Yazd Meteorological Station
H. Fathizad, M. Tavakoli, M. A. Hakimzadeh Ardakani, R. Taghizadehmehrjardi, H. Sodaiezadeh,
Volume 24, Issue 4 (2-2021)
Abstract
The purpose of this research was to investigate the trend of annual changes in Yazd station's meteorological parameters including minimum and maximum average daily temperature and average daily precipitation (1961-2005), as well as the predicted annual mean of these parameters in the three upcoming thirty years of the 2040s, 2070s and 2100s, by the SDSM model, under RCP2.6, RCP4.5, RCP8.5, A2, and B2 scenarios. Accordingly, by using the coefficient of determination and the MAE, R2, RMSE indicators, we evaluated the data generated by the SDSM model in comparison with the observed data in the base period. The lowest value of R2 based on the calibration and validation of the mean values of observed and simulated SRES was obtained for precipitation (86 and 80%). In terms of the R2 evaluation index, the accuracy of the small-scaled results of the minimum and maximum average temperature values was more than that of the average precipitation; however, in terms of the MAE and RMSE evaluation indicators, the accuracy of the small-scaled results of the average precipitation was higher than that of the minimum and maximum average temperature values. Subsequently, HadCM3 large-scale climatological data was used to predict the future periods (2010-2100). The results indicated that the temperature was raised in all months and seasons and the precipitation was decreasing in most of them, thereby confirming that the climate was changing in the studied region.
 

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