تحلیل دهه‌ای_فضایی خشک‌سالی‌های ایران جهت پشتیبانی فرآیندهای تصمیم‌گیری محیطی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه اقلیم شناسی، دانشکده علوم زمین، دانشگاه شهید بهشتی ، تهران، ایران

2 گروه جغرافیا، دانشکده انسانی ، دانشگاه زنجان

چکیده

افزایش دمای جهانی باعث افزایش فراوانی رویدادهای شدید آب و هوایی ازجمله خشک‌سالی‌ها شده است.  پایش و پیش‌بینی رفتار مکانی_ زمانی این پدیده برای پیشگیری از تبعات منفی اقتصادی_ اجتماعی و برنامه‌ریزی‌های محیطی دارای  اهمیت زیادی است. تاکنون ارزیابی جامعی از تحلیل فضایی خشک‌سالی در کشور در بلندمدت صورت نگرفته است. در این راستا ابتدا خشک‌سالی‌ها دهه‌ای با شاخص PDSI از سال 1980 تا 2020 استخراج و سپس مورد تحلیل فضایی قرار گرفت. نتایج نشان داد شدت شاخص خشک‌سالی در ایران  از 12/2- تا 45/1 به  73/5- تا 34/1 افزایش پیداکرده، یعنی از طبقه خشک به فوق‌العاده خشک تغییر یافته است. راستای بیضوی سه انحراف معیار در هر چهار دهه موردبررسی، شمال غرب و جنوب شرق را از خود نشان داده که به تبعیت از راستای بارشی ایران در جهت ناهمواری‌ها قرار داشت. جهت مشخص نمودن نوع الگوی مکانی، شاخص خوشه‌بندی جی استار محاسبه‌شده که نتایج نشان داد در دهه اول بازه مورد لکه‌های داغ (خوشه‌بندی خشک‌سالی شدید) در قسمت‌های کوچکی از مرکز ایران و بر روی استان‌های کم بارش و کویرها قرار داشته است در دهه دوم لکه‌های داغ در جنوب غرب ایران شامل استان‌های بوشهر و خوزستان قرارگرفته در دهه سوم در قسمت‌های زیادی از مرکز ایران ازجمله استان‌های تهران، سمنان، اصفهان، فارس و کهکیلویه و بویر احمد و در دهه چهارم لکه‌های داغ  در قسمت جنوب و جنوب شرق ایران شامل استان هرمزگان و سیستان بلوچستان به‌صورت الگوهای خوشه‌ای معنادار خود را نشان داند. پراکندگی مکانی شدت‌های مختلف خشک‌سالی حاکی از تغییر مکان و شدت سامانه‌های بارشی به‌صورت دهه‌ای است که نشان می‌دهد که همه نقاط کشور ممکن است در معرض مخاطره خشک‌سالی قرار گیرند. چنین تحقیقاتی می‌تواند موجب شناسایی مناطق در معرض شدید خشک‌سالی شده و در برنامه‌ریزی‌های محیطی مورداستفاده قرار گیرد.

کلیدواژه‌ها


عنوان مقاله [English]

Spatio- Decade analysis of Iranian droughts to environmental decision-making

نویسندگان [English]

  • mahmud ahmadi 1
  • Muhammad Kamangar 2
1 Department of Climatology, Faculty of Earth Sciences, Shahid Beheshti University, Tehran, Iran
2 Department of Geography, Faculty of Humanities, Zanjan University
چکیده [English]

Global warming have led to an increase in the frequency of severe weather events, including droughts. Monitoring and predicting spatio-temporal behavior phenomenon is very important to prevent negative socio-economic consequences and environmental planning. There has been no comprehensive long-term assessment of drought spatial analysis for Iran. For this purpose, first a decade of droughts with the PDSI index from 1980 to 2020 were extracted and then analyzed spatially. The results showed that the intensity of Palmer drought index in Iran increased from -2.12 to 1.45 to -5.73 to 1.34 and changed from dry to extremely dry.The elliptical direction showed three standard deviations in each of the four decades studied northwest and southeast, which was in the direction of unevenness, following the direction of Iran's rainfall. In order to clarify the type of spatial pattern, the G-Star clustering index was calculated and the results showed that in the first decade of the interval, hot spots (severe drought clustering) were found in small parts of the center of Iran and on low rainfall provinces and deserts. Second, hot spots in the southwest of Iran, including Bushehr and Khuzestan provinces, located in the third decade in many parts of the center of Iran, including Tehran, Semnan, Isfahan, Fars, Kohkiloyeh and Boyer Ahmad provinces, and in the fourth decade, hot spots in the south and southeast of Iran. including Hormozgan province and Sistan Baluchistan showed itself as meaningful cluster patterns.The spatial distribution of drought intensities indicates the displacement and intensity of rainfall systems over the decades, indicating that all parts of the country may be at risk of drought. Such research can identify areas at high drought risk and be used in environmental planning.

کلیدواژه‌ها [English]

  • Rainfall Lack
  • Spatial Standard Deviation
  • Climate Change
  • J. Gates Statistics
  • Iran
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