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Karami, M., Sarvestan, R., Sabouri, R. (2020). Prediction of climate change effects on monthly flood runoff of Karun River using multiple linear model. , 12(1), 44-56. doi: 10.22092/ijwmse.2019.122256.1503
Mokhtar Karami; Rasol Sarvestan; Reza Sabouri. "Prediction of climate change effects on monthly flood runoff of Karun River using multiple linear model". , 12, 1, 2020, 44-56. doi: 10.22092/ijwmse.2019.122256.1503
Karami, M., Sarvestan, R., Sabouri, R. (2020). 'Prediction of climate change effects on monthly flood runoff of Karun River using multiple linear model', , 12(1), pp. 44-56. doi: 10.22092/ijwmse.2019.122256.1503
Karami, M., Sarvestan, R., Sabouri, R. Prediction of climate change effects on monthly flood runoff of Karun River using multiple linear model. , 2020; 12(1): 44-56. doi: 10.22092/ijwmse.2019.122256.1503

Prediction of climate change effects on monthly flood runoff of Karun River using multiple linear model

مهندسی و مدیریت آبخیز
Article 4, Volume 12, Issue 1, April 2020, Pages 44-56    PDF (1.35 M)
Document Type: Research Paper
DOI: 10.22092/ijwmse.2019.122256.1503
Authors
Mokhtar Karami1; Rasol Sarvestan* 2; Reza Sabouri3
1Assistant Professor, Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar, Iran
2PhD Student, Faculty of Geography and Environmental Sciences, Hakim Sabzevari University, Sabzevar, Iran
3Researcher, Meteorological Office, of Sabzevar, Sabzevar, Iran
Abstract
The purpose of this study was to investigate the effect of climate change on the monthly discharge of Karoon Catchment as the largest basin in the country. In this study, five hydrometric stations (Bamdgeh, Telezang, Gharmaleh, Gotvand and Dezful) and three synoptic stations (Ahwaz, Dezful and Masjed Soleiman) were considered. Using the SDSM software, NCEP data and large-scale data from the general circulation model (HadCM3 for temperature and CgCM3 for water discharge) were scaled parameters under two climate scenarios A1B and A2 in the Karun Basin. Then, the climate change data and the output of the microscale model were applied to the SPSS 19 and Minitab 17 to predict the significance of water discharge for future climate courses (2020-2070) be simulated. Results of climate change analysis showed that under different scenarios, monthly air temperature in the scenario A1B increases by 1.60°C and in the scenario A2 1.58°C, but the average annual rate of stations in the scenario A1B is 19.82 m S-1 in size and 16.27 m S-1 in the A2 scenario. The modified Kendall and age tests were used to identify seasonal and semi-annual seasonal time series trends. Results also showed that under climate scenarios of discharge in spring and first half of the year, there was no significant trend at 95% of confidence, but in other seasons of the second half of the year, there was a significant decrease.
Keywords
CgCM3; Downscaling; Mann-Kendall; SDSM software; Temperature
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