واکنش رشد و عملکرد رقم گندمِ میهن به اثرات تغییر اقلیم در دو منطقه کرمان و اردبیل

نوع مقاله : مقاله پژوهشی

نویسندگان

گروه تولیدات گیاهی، دانشکده کشاورزی بردسیر، دانشگاه شهید باهنر کرمان، کرمان، ایران.

چکیده

این مطالعه با هدف شبیه‏سازی اثرات تغییر اقلیم بر دوره رشد، شاخص سطح برگ، عملکرد زیست‌توده و دانه گندم رقم میهن در دو استان کرمان و اردبیل اجرا شد. برای این منظور، مدل گردش عمومی HadGEM2-ES تحت دو سناریوی RCP4.5 و RCP8.5 در دو دوره زمانی 2055-2021 و 2090-2056 به‌کار برده شد. برای شبیه‏سازی پارامترهای اقلیمی و ایجاد فصل رشد احتمالی برای هر دوره از نرم‌افزار MarkSIMGCM و برای شبیه‏سازی رشد گندم از مدل CERES- Wheat در نرم‌افزار DSSAT استفاده گردید. نتایج ارزیابی مدل نشان داد که MarkSIMGCM دقت قابل قبولی برای پیش‌بینی پارامترهای اقلیمی و شبیه‏سازی فصل رشد احتمالی در شرایط تغییر اقلیم آینده داشت. طول دوره رشد گندم تحت تأثیر تغییر اقلیم در هر دو سناریو برای دوره‏های مورد سنجش و در هر دو منطقه مورد بررسی بین 51/0 تا 59/4 درصد کاهش خواهد یافت. نتایج شبیه‏سازی نشان داد که تا سال 2055 عملکرد بر اساس سناریوی RCP4.5 در منطقه کرمان نسبت به شرایط کنونی 87/3 درصد کاهش خواهد یافت. امّا، طبق سناریوی RCP8.5 در کرمان و هر دو سناریوی یاد شده در اردبیل، عملکرد گندم در آینده بین 99/0 تا 15/15 درصد افزایش خواهد یافت. در دوره بلندمدت (2090) عملکرد گندم برای منطقه کرمان طبق هر دو سناریوی RCP4.5 و RCP8.5 نسبت به زمان کنونی کاهشی ( به‌ترتیب 39/7- و 36- درصد) بوده و در اردبیل بر اساس سناریوی RCP4.5 افزایشی (36/20 درصد) و طبق سناریوی RCP8.5 کاهشی (89/2- درصد) خواهد بود. این نشان می‏دهد، نقش منفیِ افزایش  دما با گذشت زمان بیشتر از اثر مثبت افزایش 2CO خواهد بود. به‌طور کلی، نتایج تأیید نمود که رقم میهن در شرایط آینده اقلیمی اردبیل عملکرد قابل قبولی تولید خواهد نمود، ولی در کرمان باید راهکارهایی جهت سازگاری به این شرایط سنجیده شود.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Growth and Yield Response of Wheat (Mihan variety) to Future Climate Change in Kerman and Ardebil

نویسندگان [English]

  • Rooholla Moradi
  • Mehdi Naghizadeh
Department of Plant Productions, Agricultural Faculty of Bardsir, Shahid Bahonar University of Kerman, Kerman, Iran.
چکیده [English]

Introduction
Global warming has already been occurring in Iran and will probably continue during the 21st century. There has been an increased intensity and frequency of hot daytime temperatures in the last two decades in the country. Winter wheat (Triticum aestivum L.) is the most important staple food crop in the country, with a total farming area of nearly 6.33 million ha and a production exceeding 14 million tons in 2017. Wheat production in Iran is an important component of national food security. The crop is grown almost all over the country under varied soil and climatic conditions. Most parts of Iran have an arid and semi-arid climate with long dry summer and winter rainfall, which climate change may negatively affect wheat production sustainability in these vulnerable environments. Wheat is a thermo-sensitive crop, and a change in air temperature may alter the length of its growing period and grain yield. Wheat production mainly depends on the duration of the reproductive period; thus, precise crop phenology estimation is essential for yield prediction under current and future climate conditions. The variety of C-84-8, which is named "Mihan," was introduced from the cross between the domestic variety “Barkat” and the Chinese variety “Zhong87-90” in Karaj for normal irrigation conditions and drought stress after the flowering stage in the cold regions of Iran in 2009. Mihan variety is known as a high yielded potential. The actual yield of this variety in Ardabil province has been reported between 8.13 to 10.31 tons per hectare.
Materials and Methods
The aim of this study was to simulate the climate change effects on the growth period, LAI, and biological and grain yield of wheat (Mihan variety) in the Kerman and Ardebil regions. For this purpose, we employed the HadGEM2-ES model as affected by two RCP4.5 and RCP8.5 scenarios for two time periods, 2021-2055 and 2056-2090. MarkSIMGCMmodel was used to produce daily climatic parameters as one stochastic growing season for each projection period, and the CERES-wheat model in DSSAT software was used to simulate wheat growth. Calibration and validation of the model in Kerman were performed with two-year experiments designed at the Shahid Bahonar University farm in Kerman, and for the Ardabil region, it performed with the data of the wheat projects of the Agricultural Research and Training Center and Natural Resources of Ardabil province.
Results and Discussion
The results of the model evaluation showed that MarkSIMGCM had an appropriate prediction for simulating climatic parameters and stochastic growing seasons in future climate change conditions. In both studied regions, the RCP8.5 scenario has a higher temperature and radiation increase than the RCP4.5 scenario, and these changes are greater in the long-term period than in the short-term period. Rainfall changes in both investigated regions did not show a regular trend. The growing period length was reduced by 0.51% -4.59% as affected by various climate change scenarios and periods. In the near period time (2055), simulating results showed that wheat grain yield would decrease by 3.87% compared to the current condition based on the RCP4.5 scenario. But, the traits will be increased by 0.99%-15.15% according to the RCP8.5 scenario in Kerman and Ardebil based on both scenarios. In the far period time (2090), the grain yield for the Kerman region will respectively decrease by -7.39% and -36% according to both RCP4.5 and RCP8.5 scenarios compared to the current time, and in Ardabil, based on the scenario RCP4.5 will be improved by 20.36%, and it will be declined by -2.89% according to the RCP8.5 scenario. This indicates that the negative impacts of warming will outweigh to the positive effect of CO2 enrichment over time.
Conclusion
In general, the results confirmed that the Mihan variety would produce acceptable grain yield in the future climate change conditions of Ardabil, but in Kerman, mitigating strategies should be considered to adapt wheat to the adverse impacts of climate change.

کلیدواژه‌ها [English]

  • CO2
  • Downscaling
  • Global warming
  • Scenario
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