بررسی توزیع مکانی بارش آینده در دشت نهاوند، استان همدان

نویسندگان

1 دانشجوی دکترا، گروه مهندسی آب، دانشکده کشاورزی، دانشگاه بوعلی‌سینا، همدان، ایران

2 دانشیار گروه مهندسی آب، دانشکده کشاورزی، دانشگاه بوعلی‌سینا، همدان، ایران

3 استاد گروه مهندسی آب، دانشکده کشاورزی، دانشگاه بوعلی‌سینا، همدان، ایران

چکیده

افزایش دمای کره زمین موجب می­گردد اقلیم­ها دچار تغییر و دگرگونی در سطحی گسترده شوند که سبب بروز تغییراتی در زمان و مکان بارش می­شود. در این تحقیق بارش هفت ایستگاه هواشناسی برزول، فارسبان، فیروزان، گیان، گوشه سدوقاص، سینوپتیک و وراینه دشت نهاوند استان همدان در غرب ایران طی دوره 2020-1994 به­ صورت روزانه از سازمان مربوطه تهیه گردید. سپس با استفاده از مدل تغییر اقلیم LARS-WG6.0 تحت دو سناریو RCP4.5 و RCP8.5 طی چهار دوره زمانی 2040-2021، 2060-2041، 2080-2061 و 2100-2081 بارش پیش­بینی گردید. نتایج توزیع مکانی بارش به­صورت میانگین سالانه دوره مورد بررسی توسط نرم­افزار Arc GIS10.3 رسم گردید. نتایج کالیبراسیون مدل LARS-WG6.0 برای پیش­بینی بارش در منطقه میزان ضریب همبستگی بالای 94/0 و خطای nRMSE کمتر از 10 درصد را نشان می­دهد، که گواه دقت بالای این مدل در پیش­بینی بارش در منطقه است. نتایج توزیع مکانی بارش تحت دو سناریو و 4 دوره زمانی با استفاده از نرم­افزار Arc GIS10.3 نشان­دهنده آن است که سناریو RCP4.5 مقدار بارش را برای دوره 2060-2041 نسبت به سناریو RCP8.5 کمتر پیش­بینی کرده است و در سه دوره مورد بررسی دیگر میزان بارش تحت سناریو RCP4.5 بیشتر از سناریو RCP8.5 می­باشد. تحت دو سناریو و چهار دوره زمانی مورد بررسی همچنین در بین هفت ایستگاه مورد مطالعه ایستگاه برزول بیشترین درصد افزایش بارش را نسبت به دوره پایه دارد. تحت سناریو RCP8.5 نیز در دوره 2080-2061 میزان میانگین بارش دوره نسبت به دوره پایه کاهشی است (13/3 درصد)، بیشترین درصد کاهش متعلق به ایستگاه گوشه سدوقاص با میزان 99/7 درصد است.

کلیدواژه‌ها


عنوان مقاله [English]

Investigating the spatial distribution of future precipitation in Nahavand plain, Hamedan province

نویسندگان [English]

  • R. Fasihi 1
  • A. Taheri Tizro 2
  • S. Marofy 3
1 Ph. D. student of Water Engineering, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, Iran
2 Assoc. Prof., Dept., of Water Engineering, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, Iran
3 Prof., Dept., of Water Engineering, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, Iran
چکیده [English]

The increase in the temperature of the earth causes the climate changes and transform on a wide scale variations in the time and place of precipitation. In this research, the precipitation data of seven meteorological stations of Barzool, Faresban, Firoozan, Giyan, Gooshesadevaghas, Synoptic and Varayaneh,  in Nahavand Plain, Hamadan Province  which is in the west of Iran. The data obtained from the relevant organization for period of 1994-2020 and finally prepared on a daily basis. By using the LARS-WG6.0 climate change model, precipitation data was predicted under two scenarios RCP4.5 and RCP8.5 during four time periods: 2021-2040, 2041-2060, 2061-2080, and 2081-2100. The results of the spatial distribution were obtained as the annual average of the investigated period by Arc GIS 10.3 software. The calibration results of the LARS-WG6.0 model for predicting precipitation in the region showed a high correlation coefficient of 0.94 and nRMSE error of less than 10%. Which proves the high accuracy of this model in predicting precipitation in the region. The results of the spatial distribution of precipitation under two scenarios and 4 time periods using Arc GIS10.3 software show that the RCP4.5 scenarios has predicted less precipitation for the period 2041-2060 than the RCP8.5 scenarios. In the other three investigated periods, the amount of precipitation under the RCP4.5 scenarios is higher than the RCP8.5 scenarios. Under the two scenarios and four time periods, among the seven selected stations, Barzool station has the highest percentage of increase in precipitation compared to the base period. Under the RCP8.5 scenarios, in the period of 2061-2080, the average precipitation of the period will decrease (3.13%), the highest percentage of decrease belongs to Gooshe-sade-vaghas station with the amount of 7.99%.

کلیدواژه‌ها [English]

  • Nahavand
  • Precipitation
  • Climate change
  • Arc GIS
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