پهنه بندی وقوع خشک‌سالی در استان فارس تحت تأثیر شرایط تغییر اقلیم با استفاده از شاخص بارش استاندارد

نوع مقاله : علمی - پژوهشی

نویسندگان

1 تهران -دانشگاه شهید بهشتی - پژوهشکده علوم محیطی

2 تربیت مدرس

3 سازمان هواشناسی کشور

چکیده

موضوع تغییر اقلیم یکی از مهم ترین چالش های محققین در قرن 21 است و با توجه به نقش حیاتی آب در زندگی بشر، بررسی اثرات تغییر اقلیم بر شدت و فراوانی خشک‌سالی برای هر منطقه ضروری و مهم می باشد. هدف از این مطالعه پیش بینی پارامترهای هواشناسی استان فارس در شرایط تغییر اقلیم، محاسبه شاخص خشکی و پهنه بندی آن در این استان است. در این مطالعه به منظور پیش بینی اقلیم آینده در 9 شهرستان استان فارس (شیراز، اقلید، فسا، لار، لامرد، داراب، زرقان، نیریز و آباده) از دو مدل اقلیمی (HadCM3 و IPCM4) تحت سه سناریو (B1، A1B و A2) در سه دوره (30-2011، 65-2046 و 99-2080) استفاده شد. همچنین برای ریزمقیاس کردن پارامترهای اقلیمی از LARS-WG استفاده شد. برای محاسبه شاخص خشکی سالی از شاخص SPI در مقیاس زمانی 12 ماه استفاده شد. نتایج نشان داد که در دوره پایه شهرستان های آباده و لار در طبقه خشکی حاد (48/2- و 09/2-) قرار داشتند درصورتی‌که تحت شرایط تغییر اقلیم آینده شهرستان لامرد در طبقه خشکی حاد قرار می گیرد. بیشترین شدت خشک سالی با استفاده از مدل HadCM3 تحت سناریوی A2 در دوره 2099-2080 در نیریز (33/1) و کمترین شدت خشک سالی در شهرستان لامرد (58/2-) در دوره 2065-2046 با استفاده از مدل IPCM4 و تحت سناریوی A1B بدست آمد. به طور کلی نتایج نشان داد که در دوره پایه بخش عمده ای از مناطق استان فارس با استفاده از شاخص SPI در طبقه نرمال (نیمه جنوبی استان) و خشکی ملایم (نیمه شمالی استان) قرار دارند درحالی که در آینده عمده مناطق استان فارس در طبقه نرمال قرار خواهند گرفت.

کلیدواژه‌ها


عنوان مقاله [English]

Climate model; Downscaling; Fars; GIS; Interpolation

نویسندگان [English]

  • Reza Deihimfard 1
  • Hamed Eyni Nargeseh 2
  • Masoud Haghighat 3
1 Shahid Beheshti University
2 Tarbiat Modares University
3 Iran Meteorological Organisation
چکیده [English]

Introduction
Today, Climate change issue is one of the main challenges for scientists and due to the critical role of water in human life, the study of climate change impacts on severity and frequency of drought in each region seems to be indispensable (Hulme et al., 1999). Drought is usually occurred over a period of water shortage owing to less rainfall, high evapotranspiration and pumping a huge amount of water from water tables. This issue could have extensive consequences on agriculture, ecosystems and communities. The objectives of this study were to predict meteorological parameters, calculation of drought index and its zoning under the changing climate in Fars province.

Materials and methods
In order to predict the future climate in nine districts of Fars province (including Shiraz, Eghlid, Fasa, Lar, Lamerd, Darab, Zarghan, Neiriz and Abadeh), two climate models (HadCM3 and IPCM4) was applied under three scenarios (B1, A1B and A2). LARS-WG software was applied to downscale climate parameters (Semenov and Barrow, 2002). To predict incident probability of drought in the all study locations, a drought index (Standardize Precipitation Index, SPI) was calculated at a time scale of 12 months. SPI is the most commonly used drought index. SPI is calculated based upon the differences between monthly rainfall and average rainfall for a certain period of time according to the time scale (Mckee et al., 1995). In this study the SPI time series have been estimated for the historical base period 1980-1990 and for three future periods (2011-2030, 2046-2065, 2080-2099). Finally, drought maps and zoning were conducted in the whole province using GIS and based on IDW interpolation method.

Results and discussion
Results of climate models evaluation indicated that LARS-GW well predicted radiation, and maximum and minimum temperatures (RMSE of 0.51, 0.46 and 1.02%, respectively). However, the accuracy in prediction of rainfall was not as good as the other climatic variables (RMSE of 11.48%). This is mainly due to the fact that there is a high variability in rainfall under arid and semi-arid conditions. Other studies also showed that LARS-WG often over- or underestimate rainfall compared with other climatic variables. According to the simulated aridity index in the baseline period, Abadeh and Lar classified into extreme drought class (-2.48 and -2.09) while under future climate change Lamerd categorized in the extreme drought class. The most severe drought occurred in Neyriz (1.33) using HadCM3 model under A2 scenario in 2080-2099. While, the lowest drought severity obtained in Lamerd (-2.58) using IPCM4 model under A1B scenario in 2046-2065. According to the zoning maps, a vast majority of Fars province had normal climate in the baseline which, are mainly located in southern part of Fars including Neyriz, Darab, Fasa, Lamerd and Eghlid. In contrast, only a limited part of the study locations classified as drought included Abadeh, Zarghan and Lar. Results of t-test also showed that there is no difference between HadCM3 and IPCM4 climate models in terms of future climate prediction (p≥0.05). Results also revealed that for most of study locations, SPI would be in normal class for the all three periods compared with the baseline.
Drought zoning in the baseline in 12 month time scale indicated that the lowest drought was occurred in southern part of Fars while the most severe was observed in both northern areas and some limited part of the south. It was generally concluded that the major part of the Fars province was in normal (the southern half of the province) and moderate class (the northern half of the province) for baseline period according to SPI. However, for projected period, major part of regions would be in normal class. As the Fars province is one of the major producers of cereals in the country, it is estimated the area will benefit from climate change in the future particularly under rainfed conditions.

Conclusion
The results of the current study showed that drought would be intensified under climate change in Fars province and most of the area will benefit from changing climate in the future. However, it is necessary for the authorities to take the results into account, and have applicable water resources management strategies to be able to deal with possible problems in the future decades. Decision makings also should be accomplished with especial considerations to the uncertainties that almost appear in the results.

Acknowledgements
The authors acknowledge the financial support of the project (No. 600/4330 on March 2015) by Vice President for Research and Technology, Shahid Beheshti University, G.C., Iran.

کلیدواژه‌ها [English]

  • Climate change
  • Drought index
  • SPI
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