ارزیابی اثرات تغییر اقلیم بر رواناب رودخانه فیروزآباد استان فارس، با ریزمقیاس نمایی خروجی مدل‌های گردش جوی به وسیله نرم‌افزارهای SDSM و LARS-WG

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانش آموخته کارشناسی ارشد /مهندسی عمران-مهندسی آب، دانشکده فنی و مهندسی، دانشگاه زابل

2 استادیار/ گروه عمران، دانشکده فنی و مهندسی، دانشگاه زابل

چکیده

در این مطالعه به ارزیابی اثرات تغییراقلیم بر رواناب رودخانه فیروزآباد واقع در استان فارس، ایران، پرداخته شده‌است. به منظور ریزمقیاس نمایی خروجی مدل‌های گردش جوی از نرم‌افزار LARS-WG در ایستگاه اصلی و از نرم‌افزار SDSM در ایستگاه بالادست استفاده شده‌است. در انتخاب مدل‌های گردش جوی مناسب با منطقه مطالعاتی، از وزن‌دهی اولیه به عنوان عنصر غربالگری استفاده شده‌است. به منظور بررسی اثرات تغییراقلیم بر رواناب از الگوریتم رقابت استعماری در تعیین وزن‌ها و بایاس شبکه عصبی استفاده شده‌است. نتایج بررسی تغییراقلیم نشان از افزایش دمایی بین 7/0 تا 8/1 درجه برای دمای حداقل و 7/0 تا 7/1 درجه‌ای برای دمای حداکثراست. برای بارش نیز هرچند میزان افزایش بسیار کم بوده است ولی نتایج افزایش 2 تا 12 درصدی میزان بارش را نشان می‌دهد. نتایج بررسی رواناب نشان از کاهش رواناب در ماه‌های آپریل، می، جون و آکتبر و افزایش در سایر ماه‌ها شده است. در بررسی عدم قطعیت، بیشترین عدم قطعیت رواناب در ماه‌های ژانویه و آپریل است.

کلیدواژه‌ها


عنوان مقاله [English]

Assessment of Impact of Climate Change on Firoozabad River Runoff with Downscaling of Atmospheric Circulation Models Output by SDSM and LARS-WG Softwares

نویسندگان [English]

  • A. Ajam Zadeh 1
  • M.R. Mollaeinia 2
1 M. Sc. Graduate, Department of Civil Engineering, College of Engineering, Zabol University
2 Assistant Professor, Department of Civil Engineering, College of Engineering, Zabol University.
چکیده [English]

This study investigates the effects of climate changes on the runoff of the Firoozabad River located in Fars Province, Iran. In order to downscale the output of the atmospheric circulation model, LARS-WG software was used in the base station and software SDSM is used in the upper station. In order to select atmospheric circulation models that fit the studied area, the initial weighting was used as the screening element. To examine the effects of climate changes on the runoff, ANN trained with ICA algorithm was used. The results of investigating the climate changes indicate the increase of temperature between 0.7 to 1.8°C for the minimum temperature and the increase of 0.7 to 1.7°C for the maximum temperature. Although the increase of precipitation was very low, the results indicate the increase of 2 to 12% of the rainfall. The results also indicate the decrease of runoff in April, May, June, and October and the increase of runoff in the other months. Considering the uncertainty, the highest runoff uncertainty is observed in January and April.

کلیدواژه‌ها [English]

  • LARS-WG
  • SDSM
  • runoff
  • Climate Changes
  • Artificial intelligence
  • ICA Algorithm
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