Impact of Global Climate Change on Climate Data in Ravansar Sanjabi Basin, Kermanshah Province

Shahoei, Seyed Vahid; Fahiminezhad, Elham; Fatehi, Zaniar

doi:10.22034/jewe.2020.219388.1348

Document Type : Research Paper

Authors

¹ Assist. Professor, Department of Water Engineering and Management, Faculty of Civil Engineering, Tose Danesh Institute of Higher Education, Sanandaj, Iran

² Assist. Professor, Payame Noor University of Sabzevar, Sabzevar, Iran

³ M.Sc. Student, Department of Water Engineering and Management, Faculty of Civil Engineering, Tose Danesh Institute of Higher Education, Sanandaj, Iran

https://doi.org/10.22034/jewe.2020.219388.1348

Abstract

In this study, the effect of climate change on temperature and rainfall data in the Kermanshah Sanjabi basin was investigated. For this purpose, using climate and temperature data from 1979-2005 (observation period), the values of these variables in 2041-2100 (forecast period) were predicted under three scenarios RCP8.5, RCP4.5 and RCP2.6 and CanESM2 atmospheric general circulation model. The SDSM model was used to fine-tune the survey data in the study area. The results showed that the mean annual precipitation, maximum and minimum annual temperatures in the squared Ravansar basin will increase in the forecast period of 2041-2100. The most predicted values of these variables belong to the RCP8.5 scenario so that according to this scenario, the average increase in precipitation in December, in the forecast periods 2041-2070 and 2071 2100 is 153 and 159.6%, respectively, compared with the average rainfall in the observation period. Based on the results of this study, it is expected that in order to properly manage the water resources of the RWC due to the impact of climate change, a proper perspective on the future status of water resources in the watershed will be presented to water resource managers in the future.

Keywords

Main Subjects

Climatology

References

Asakereh H. and Kiani H. (2019). Evaluation of SDSM model performance in simulating the average temperature of Kermanshah City. Sci. Res. Quart. Geogr. Data, 27, 50-62 [In Persian].

Hesami N. and Asakereh H. (2018). Assessing the application of artificial neural networks and SDSM models to simulate the minimum and maximum temperatures at Isfahan Station. J. Geogr. Res. Desert Areas, 6(2), 133-158 [In Persian].

Babaian E., Najaf Z., Zabolabbasi F., Habibitookhandan M., Adab H. and Malboosi S. (2010). Country Climate change assessment in the period of 2011-2039 using the exponential micro scale exposure climate model (EHO-G), Geogr. Develop. J., 7(16), 135-152 [In Persian].

Babaeifeini O., Ghasemi E. and Fattahi E. (2017). Investigating the impact of climate change on the trend of Iran land limits. J. Spatial Anal. Environ. Hazard., 1(3), 85-103 [In Persian].

Dehghan Z., Fathian F. and Eslamian S. (2015). Comparative evaluation of SDSM, IDW and LARS-WG models. J. Water Soil, 29(5), 1376-1390 [In Persian].

Easterling D. R., Meehl G. A., Parmesan C., Changnon S. A., Karl T. R. and Mearns L.O. (2000). Climate extremes: observations, modeling, and impacts. Sci., 289, 2068-2074.

Fatehi A., Jabarian B. and Mohhamdzadeh N. (2017). Downscaling the atmospheric general circulation model's data and its application in simulating the climatic parameters (Case study: Guilan province). J. Nat. Environ., 1, 143-158 [In Persian].

Hajimohhamdi M., Azizian A. and Ghermezcheshmeh B. (2018). Evaluation of the impact of climate change on runoff in Kan Watershed. Watershed Eng. Manage., 10(2), 144-156 [In Persian].

IPCC. (2007). Summary for Policymarkers, in: Climate Change (2007). Solomon S., Qin D., Manning M., Chen Z., Marquis M., Averyt K. B., Tignor M. and Miller H. L. eds. (2007). Climate Change 2007: The Physical Science Basis, Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental.

Kaviani M. and Alijani B. (1993). Applied climatology. Samt Publisher: 254p.

Kazemirad L. and Mohhamdi V. (2016). Climate change assessment by using LARS-WG Model in Gilan Province (Iran). Geogr. Environ. Hazard., 5, 55-74 [In Persian].

Khaliliaghdam N., Mosaedi A., Soltani A. and Kamkar B. (2013). Evaluation of LARS-WG model in prediction of some climate parameters. Soil Water Conserv. Res. J., 19(4), 85-102 [In Persian].

SajadiBami Y. and Neshat A. (2017). The prediction of the climate change effect on the temperature parameter by the general circulation models HadCM3: a case study of Kerman and Bam. Water Resour. Eng., 9(30), 51-62 [In Persian].

Shahoei S. V., Porhemmat J., Sedghi H., Hosseini M. and Saremi A. (2018). Monthly runoff simulation through SWAT hydrological model and evaluation of model in calibration and validation periods, case study: Ravansar Sanjabi Basin in Kermanshah Province, Iran. Watershed Eng. Manage., 10(3), 464-477 [In Persian].

Sillmann J. and Roeckner E. (2008). Indices for extreme events in projections of anthropogenic climate change. Climat. Change, 86, 83-104.

Wilby R. L., Conway D. and Jones P. D. (2002). Prospects for downscaling seasonal precipitation variability using conditioned weather generator parameters. Hydrol. Process., 16, 1215-1234.

Zhang X. and Yang F. (2004). RClimDex (1.0) User Manual. Climate Research Branch Environment Canada Downsview, Ontario Canada.

Zulkaranian, H and Arun H. S. (2012). Application of statistical downscaling model for long lead rainfall prediction in kurau river catchment of Malaysia. Malaysian J. Civil Eng., 24(1), 1-12.

Environment and Water Engineering

Impact of Global Climate Change on Climate Data in Ravansar Sanjabi Basin, Kermanshah Province

References

References

Volume 6, Issue 1
April 2020
Pages 45-57

Impact of Global Climate Change on Climate Data in Ravansar Sanjabi Basin, Kermanshah Province

References

References

Volume 6, Issue 1April 2020Pages 45-57

Volume 6, Issue 1
April 2020
Pages 45-57