Prediction Impact of Climate Change on the Temperature & Precipitation by General Circulation Model, a Strategy for Sustainable Agriculture: (Case of Kermanshah Township)

Subject Areas : Sustainable Development

Samireh Seymohammadi ¹ , Mohsen Tavakoli ² , Kiumars Zarafshani ³ , Hossien Mahdizadeh ⁴ , Farzad Amiri ⁵

1 - PHD of Agricultural development, College of Agriculture, Razi University, Kermanshah, Iran.
2 - Associate Professor, College of Agriculture, Ilam University, Ilam, Iran. *(Corresponding Author)
3 - Associate Professor, College of Agriculture, Razi University, Kermanshah, Iran.
4 - Assistant Professor, College of Agriculture, Ilam University, Ilam, Iran
5 - Assistant Professor, Department of Engineering Management, Kermanshah University of Technology, Kermanshah, Iran.

Received: 2016-11-15 Accepted : 2017-02-15 Published : 2021-08-23

Keywords: SDSM, Global circulation model, Prediction, HadCM3, Climate Change,

Abstract :

Background and Objectives: Concern about climate change and its effects on various aspects of human life in general and agricultural production in particular is growing. Therefore, the main purpose of this study is to assess and predict of climate change induced temperature and precipitation of Kermanshah township.Method: The calibration and validation of the HadCM3 model was performed 1961-2001 of daily temperature and precipitation. The data on temperature and precipitation from 1961 to 1990 were used for calibration whereas data from 1991 to 2001 were used for model validation. SDSM version 4.2 as a downscaling model used to downscale general circulation models to station scales.  Findings: The least difference between observed data and simulation data during calibration and validation showed that the parameter was precisely modeled for most of the year. This study under A2 scenario, three time periods (2020, 2050, 2080) were simulated.  Discussion and Conclusion: According to our simulated model, precipitation showed a decreasing trend whereas temperature showed an increasing trend. The result of this study can also be used as an optimal model for land allocation in agriculture.

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