ارزیابی اثر تغییر ‌اقلیم بر خشکسالی کشاورزی به‌کمک شاخص SMDIبا استفاده از مدل‌ها و سناریوهای گزارش پنجم

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه علوم و مهندسی آب، دانشکده کشاورزی، دانشگاه بیرجند، بیرجند، ایران

2 استادیار گروه علوم و مهندسی آب دانشکده کشاورزی دانشگاه بیرجند، بیرجند، ایران

چکیده

رطوبت خاک یک پارامتر تعیین‌‌کننده در بسیاری از فرآیند‌های پیچیده زیست محیطی است و نقش تعیین‌کننده‌ای در وقوع خشکسالی کشاورزی دارد. لذا در این تحقیق، با استفاده از داده‌های برآورد شده رطوبت خاک توسط مدل SWAP و داده‌های گزارش پنجم تغییر ‌اقلیم، خشکسالی کشاورزی به‌کمک شاخص کمبود رطوبت خاک برای دوره آتی (2039-2020) برای مزرعه گندم فاروب نیشابور تعیین شد. داده‌های اقلیمی به­کمک شش مدل GCM و دو سناریو انتشار 5/4 و 5/8 برآورد و توسط مدل LARS-WG ریزمقیاس شدند. سپس داده­های اقلیمی ریزمقیاس شده به‌همراه داده­های زراعی، خاک و آبیاری وارد مدل SWAP گردید. در نهایت با استفاده از داده‌های رطوبت عمق صفر تا 30 سانتی‌متری خاک، خشکسالی کشاورزی به‌کمک شاخص SMDI مورد ارزیابی قرار گرفت. نتایج نشان داد، دمای مینیمم، ماکزیمم و بارش در دوره آتی نسبت به دوره پایه افزایش یافته است و سناریو 5/8 نسبت به سناریو 5/4 دمای بیشتر و بارش کمتری را برآورد کرده است. همچنین میانگین SMDI در دوره آتی نسبت به دوره پایه برای هر دو سناریو افزایش یافته است. نتایج قطعیت مدل‌های GCM در برآورد شاخص SMDI نیز نشان داد. تحت سناریو 5/4 مدل‌های‌ IPSL و MIROC بیشترین قطعیت و مدل Canesm2 کمترین قطعیت ولی تحت سناریو 5/8 مدل‌ MIROC بیشترین قطعیت و مدل‌های Csiromk-3.6 و GFDL کمترین قطعیت را دارند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

The Evaluation of Climate Change Impact on Agricultural Drought by Soil Moisture Deficit Index Using Fifth Report Models and Scenarios

نویسندگان [English]

  • saeid ghavamsaeidi noghabi 1
  • mostafa yaghoobzadeh 2
  • Mohammad Hossein Najafi Mood 2
1 Department of Science and Water Engineering, Faculty of Agriculture, University of Birjand, Birjand, Iran
2 Assistant Professor, Department of Science and Water Engineering, Faculty of Agriculture, University of Birjand, Birjand, Iran
چکیده [English]

Soil moisture is a determinative parameter in many of the complex environmental processes and plays a decisive role in the occurrence of agricultural drought. So, in this study, based on estimated soil moisture data by SWAP model and Fifth Report Data of Climate Change, agricultural drought was determined by Soil Moisture Deficit Index for the upcoming period (2020-2039) for the wheat field of Faroub in Neyshabour. The climatic data were estimated using six models of GCM and two emission scenarios of 4.5 and 8.5 and were downscaled by LARS-WG model. Then the downscaled climatic data along with field, irrigation and soil data were entered into the SWAP model. Finally, using soil moisture data of 0-30 cm depth, agricultural drought was evaluated using SMDI index. The results showed that the minimum and maximum temperatures and precipitation in the upcoming period have increased compared to the base period and 8.5 scenario have estimated a higher temperature and lower rainfall than the 4.5 scenario. Also, the average SMDI in the upcoming period has increased relative to the base period for both scenarios. The certainty results of GCM models for estimation of SMDI index also showed that under the 4.5 scenario, the IPSL and MIROC models have the highest certainty and the Canesm2 model has the lowest certainty. Under the 8.5 scenario, MIROC model has the highest certainty and Ciromk-3.6 and GFDL models have the lowest certainty.

کلیدواژه‌ها [English]

  • Emotion scenario
  • GCM model
  • Soil Moisture Deficit Index
  • SWAP model
  • uncertainty
Babaeian, E., Nagafineik, Z., Zabolabasi, F., Habeibei, M., Adab, H. and Malbisei, S. (2009). Climate change assessment over Iran during 2010-2039 by using statistical downscaling of ECHO- G model. Geography And Development Iranian Journal, 7(16), 135-152. (In Farsi)
Chunping, T., Jianping, Y. and Man, L. (2015). Temporal-spatial  variation  of  drought  indicated  by  SPI  and  SPEI  in  Ningxia  Hui  autonomous  region,  China. Journal  of  Atmosphere, 6, 1399-1421.
Dubrovsky, M., Svoboda, M.D., Trnka, M., Hayes, M.J., Wilhite, D.A., Zalud, Z. and Hlavinka, P. (2009). Application of relative drought indices in assessing climate change impacts on drought conditions in Czechia. Theoretical and Applied Climatology, 96(1-2), 155-171.
Ghorbani Aghdam, M., Dinpazhuh, Y., Fakheri Fard, A. and Darbandi, S. (2012). Regionalization of Urmia lake basin from the view of drought using factor analysis. Journal of Water and Soil, 26(5), 1268-1276. (In Farsi)
Hosseinzadeh, J., Tongo, A., Najafifar, A. and Hosseini, A. (2018). Relationship between soil moisture changes and climatic indices in the Mele-Siah forest site of Ilam province. Journal of Water and Soil, 32(4), 821-830. (In Farsi)
Jalali, L., Bazrafshan, J. and Tavakoli, A.R. (2013). Evaluation of soil moisture deficit index (SMDI) for agricultural drought monitoring (the case study: Maragheh). 1th National Congress on Agricultural Science, Aug 2013., Payame noor University of Technology, Naghade, Iran. (In Farsi)
Khadempour, F., Khozeymehnezhad, H. and amirabadizadeh, M. (2019). Investigating the effects of climate change on daily evapotranspiration in models with different mathematical structures in various climates of Iran. Journal of Water Research in Agriculture, 33.1(1), 149-162. (In Farsi)
Keshavarz, M.R., Vazifedoust, M. and Alizadeh, A. (2011). Development of soil wetness deficit index (SWDI) using MODIS satellite data. Iranian Journal of lrrigation and drainage, 4(3), 465-477. (In Farsi)
Lalehzari, R., Yaghoobzadeh, M. and Haghayeghi Moghaddam, S.A. (2017). Evaluation of climate change effect on soil moisture of farms by SWAP and AOGCM models. Journal of Water and Soil Science, 27(1), 95-106. (In Farsi)
Narasimhan, B. and Srinivasan, R. (2005). Development and evaluation of soil moisture deficit index (SMDI) and evapotranspiration deficit index (ETDI) for agricultural drought monitoring. Agricultural and Forest Meteorology, 133(1-4), 69-88.
Palmer, W.C. (1968). Keeping track of crop moisture conditions, nationwide: The new crop moisture index. Weatherwise, 21, 156-161.
Pirnia, A., Golshan, M., Bigonah, S. and Solaimani, K. (2018). Investigating the drought characteristics of Tamar basin (upstream of Golestan dam) using SPI and SPEI indices under current and future climate conditions. Iranian Journal of Ecohydrology, 5(1), 215-228. (In Farsi)
Ramezani Etedali, H., Liaghat, A.M. and Parsinejad, M. (2012). Status of agricultural droughts based on soil moisture in Qazvin. Journal of Water Research in Agriculture, 26(1), 83-93. (In Farsi)
Sayari, N., Bannayan, M., Alizadeh, A. and Farid, A. (2013). Using drought indices to assess climate change impacts on drought conditions in the northeast of Iran (case study: Kashafrood basin). Meteorological Applications, 20(1), 115-127.
Semenov, M.A. (2008). Impacts of climate change on wheat in England and Wales. Journal of the Royal Society Interface, 6(33), 343-350.
Stocker, T.F., Qin, D., Plattner, G.K., Tignor, M., Allen, S.K., Boschung, J. and Midgley, P.M. (2013). Contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. Climate change.
Vicente-Serrano, S.M., Miralles, D.G., Domínguez-Castro, F., Azorin-Molina, C., El Kenawy, A., McVicar, T.R., Tomás-Burguera, M., Beguería, S., Maneta, M. and Peña-Gallardo, M. (2018). Global assessment of the standardized evapotranspiration deficit index (SEDI) for drought analysis and monitoring. Journal of Climate, 31(14), 5371-5393.
Yaghoobzadeh, M. (2015). The simulation of evapotranspiration and moisture soil for agricultural drought evaluation in the base line and future by using remote sensing. Ph. D. dissertation, Shahid Chamran University of Ahvaz, Ahvaz. (In Farsi)
Yaghoobzadeh, M., Amirabadizadeh, M., Ramezani, Y. and Pourreza-bilondi, M. (2017). The investigation of uncertainty emissions scenarios of climate change in soil moisture estimation during the growing season of wheat. Iranian Journal of Irrigation and Drainage, 11(4), 586-596. (In Farsi)
Yaghoobzadeh, M., Amirabadizadeh, M., Ramezani, Y. and Pourreza-bilondi, M. (2018). An uncertainty analysis of general circulation models for estimation of soil moisture affected by climate change. Iranian Jornal of Soil and Water Research, 48(5), 1109-1119. (In Farsi)