نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مهندسی عمران، دانشکده فنی و مهندسی شهید نیکبخت، دانشگاه سیستان و بلوچستان، ایران

2 دانشگاه سیستان و بلوچستان

3 گروه مهندسی عمران، دانشکده‌ی مهندسی شهید نیکبخت، دانشگاه سیستان و بلوچستان، ایران

4 گروه جغرافیای طبیعی، دانشکده جغرافیا و برنامه ریزی محیطی، دانشگاه سیستان و بلوچستان، ایران

چکیده

این مطالعه اثرات تغییر اقلیم بر نیاز آبی گیاه زعفران را در 13 منطقه­ی خراسان جنوبی و خراسان رضوی برای سه دوره­ی زمانی 2030-2050، 2055-2075 و 2080-2100 با استفاده از الگوریتم­های ترکیبی ANN-NSGA-II و ANN-ICA بررسی می­کند. این تحقیق برای اولین بار به محاسبه نیاز آبی زعفران براساس تغییر اقلیم با استفاده از مدل­های CMIP6 و سناریوهای SSP245 و SSP585 پرداخته است. علاوه بر آن برای اولین بار به محاسبه پارامترهای اصلی مدل­های CMIP6 برای پیشنمایی متغیرهای اقلیمی پرداخته است. برای ریزگردانی و درون­یابی فضایی داده­های CMIP6 به ترتیب از روش ریزگردانی آماری و تکنیک وزن دهی فاصله معکوس استفاده شد. از مدل ANN-NSGA-II برای انتخاب پارامترهای مناسب و از مدل ANN-ICA برای پیشنمایی آینده متغیرهای اقلیمی و درنهایت از مدل کراپ وات برای محاسبه نیاز آبی زعفران استفاده شد. نتایج انتخاب پارامترها نشان داد، پارامترهای Hfls و Hfss در 90 درصد موارد برای پیشنمایی آینده انتخاب شدند.  میانگین درصد کاهش بارش و افزایش دمای بیشینه و کمینه مدل­های GFDL-CM4، MIROC6 و NorESM2-LM در سناریو SSP245 به ترتیب برابر با (6/8، 1-، 10)، (10، 7/5، 7/8) و (6/6، 6/0، 1/9) و در سناریو SSP585 به ترتیب برابر با (7/5، 6/5، 13)، (12، 4/2، 6/11) و (2/8، 7/4، 3/17) محاسبه شد. نیاز آبی در 90 درصد ایستگاه­ها، GCMs و سناریوها نسبت به دوره­ی پایه افزایش یافت. بیشترین افزایش نیاز آبی در گلمکان به میزان 1/87 میلیمتر برای مدل MIROC6 و دوره­ی زمانی 2055-2075 بدست آمد.

کلیدواژه‌ها

Ahmadee, M., Khashei Siuki, A., & Sayyari, M. h. (2016). Comparison of Efficiency of Different Equations to Estimate the Water Requirement in Saffron (Crocus sativus L.) (Case Study: Birjand Plain, Iran). Journal of Agroecology, 8(4), 505-520. [in Persian].
Aliakbari, P., salari, a., & KhasheiSiuki, A. (2018). Determine of the Actual and Potential Evapotranspiration and Appropriate Model for Determining Water Requirement of Saffron (Case study: Torbat Heydarieh). Iranian journal of Ecohydrology, 5(3), 1051-1061. [in Persian].
Alizade, A., & Kamali, G. A. (2007). Crops water requirements in Iran. Astan Qods Razavi. [in Persian].
Alizadeh, A., Mahdavi, M., Iranloo, M., & Bazari, M. E. (1999). Evapo-transpiration and crop coefficient of saffron (Crocus sativus). Geographical Research, 54, 29-42. [in Persian].
Allen, R. G., Pereira, L. S., Raes, D., & Smith, M. (1998). Crop Evapotranspiration-Guidelines for Computing Crop Water Requirements-FAO Irrigation and drainage paper 56. Fao, Rome.
Almazroui, M., Islam, M. N., Saeed, F., Saeed, S., Ismail, M., Ehsan, M. A., & Barlow, M. (2021). Projected changes in temperature and precipitation over the United States, Central America, and the Caribbean in CMIP6 GCMs. Earth Systems and Environment, 5(1), 1-24.
Araya-Osses, D., Casanueva, A., Román-Figueroa, C., Uribe, J. M., & Paneque, M. (2020). Climate change projections of temperature and precipitation in Chile based on statistical downscaling. Climate Dynamics, 54(9), 4309-4330.
Aref, M. A., & Alijani, B. (2018). Investigation of temperature and precipitation variations of Yazd-Ardakan basin with SDSM under the conditions of future climate change. Arid Biome, 8(1), 89-101. [in Persian].
Asseng, S., Cao, W., Zhang, W., & Ludwig, F. (2009). Crop physiology, modelling and climate change: impact and adaptation strategies. Crop Physiol, 511-543.
Atashpaz-Gargari, E., & Lucas, C. (2007). Imperialist competitive algorithm: an algorithm for optimization inspired by imperialistic competition. In 2007 IEEE congress on evolutionary computation. 4661-4667.
Baran, A., Lerch, S., El Ayari, M., & Baran, S. (2021). Machine learning for total cloud cover prediction. Neural Computing and Applications, 33(7), 2605-2620.
Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. A. M. T. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE transactions on evolutionary computation, 6(2), 182-197.
Díaz-Álvarez, A., Clavijo, M., Jiménez, F., Talavera, E., & Serradilla, F. (2018). Modelling the human lane-change execution behaviour through multilayer perceptrons and convolutional neural networks. Transportation research part F: traffic psychology and behavior, 56, 134-148.
Eslamian, S., Khordadi, M. J., & Abedi-Koupai, J. (2011). Effects of variations in climatic parameters on evapotranspiration in the arid and semi-arid regions. Global and Planetary Change, 78(3-4), 188-194.
farajnia, A., & Moravej, K. (2020). Agro climatic Zoning of Saffron Culture in East Azarbayjan Province. Journal of Saffron Research, 7(2), 251-267. [in Persian].
Frederick, K. D. & Major, D. C. (1997). Climate change and water resources. Climatic change, 37(1), 7-23.
Gocić, M., Motamedi, S., Shamshirband, S., Petković, D., Ch, S., Hashim, R., & Arif, M. (2015). Soft computing approaches for forecasting reference evapotranspiration. Computers and Electronics in Agriculture, 113, 164-173.
ghavamsaeidi noghabi, S., Khashei-Siuki, A., Hammami, H., shahidi, A., & Yaghoobzadeh, M. (2020). Determination of Evapotranspiration and Crop Coefficient of Saffron (Crocus sativus L.) by Lysimetric Method in the Dry- Desert Climate of Birjand. Journal of Saffron Research, 8(1), 161-172. [in Persian].
Goodfellow, I., Bengio, Y., & Courville, A. Deep Learning. MIT press, 2016.
Hargreaves, G. H., (1994). Defining and using reference evapotranspiration. Journal of irrigation and drainage engineering, 120(6), 1132-1139.
Harmsen, E. W., Miller, N. L., Schlegel, N. J., & Gonzalez, J. E. (2009). Seasonal climate change impacts on evapotranspiration, precipitation deficit and crop yield in Puerto Rico. Agricultural water management, 96(7), 1085-1095.
Huth, R., (2002). Statistical downscaling of daily temperature in central Europe. Journal of Climate, 15(13), 1731-1742.
(IPCC 2007) Parry, M.L., Canziani, O.F., Palutikof, J.P. Climate change 2007: impacts, adaptation and vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, 2007.
(IPCC 2013) Stocker, T.F., Qin, D., Plattner, G. K., Tignor, M., Allen, S.K., Boschung, J., Nauels, A., Xia, Y., Bex, V., & Midgley, P.M. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, 2013.
Jafarzadeh, A., Khashei-Siuki, A., & Shahidi, A. (2015). Modeling of climate change effects on saffron water requirement in south Khorasan province by GIS. Journal of Saffron Research, 3(2), 163-174. [in Persian].
Kafi, M., Koocheki, A., & Rashed, M. H. (2006). Saffron (Crocus Sativus): Production and Processing. Ferdowsi University of Mashhad. [in Persian].
Khashei Siuki, A., Shahidi, A., Behdani, M. A., Hjiabadi, F., & Shirzadi, F. (2020). Determination of Single and Dual Crop Coefficients of Saffron (Crocus sativus L.) in the First Year of cultivation. Journal of Saffron Research. [in Persian].
Khashei Siuki, a., Shahidi, A., pourrezabilondi, m., Amirabadizadeh, m., & jafarzadeh, a. (2018). Performance Assessment of ANN and SVR for downscaling of daily rainfall in dry regions. Iranian Journal of Soil and Water Research, 49(4), 781-793. [in Persian].
Knox, J. W., Díaz, J. R., Nixon, D. J., & Mkhwanazi, M. (2010). A preliminary assessment of climate change impacts on sugarcane in Swaziland. Agricultural systems, 103(2), 63-72.
Koutroulis, A. G., Grillakis, M. G., Tsanis, I. K., & Papadimitriou, L. (2016). Evaluation of precipitation and temperature simulation performance of the CMIP3 and CMIP5 historical experiments. Climate Dynamics, 47(5), 1881-1898.
Lashkari, A., Alizadeh, A., Rezaei, E. E., & Bannayan, M. (2012). Mitigation of climate change impacts on maize productivity in northeast of Iran: a simulation study. Mitigation and adaptation strategies for global change, 17(1), 1-16.
Liu, X., Xu, C., Zhong, X., Li, Y., Yuan, X., & Cao, J. (2017). Comparison of 16 models for reference crop evapotranspiration against weighing lysimeter measurement. Agricultural water management, 184, 145-155.
Lovino, M. A., Pierrestegui, M. J., Müller, O. V., Berbery, E. H., Müller, G. V., & Pasten, M. (2021). Evaluation of historical CMIP6 model simulations and future projections of temperature and precipitation in Paraguay. Climatic Change, 164(3), 1-24.
Maleki, F., Kazemi, H., Siahmargue, A., & Kamkar, B. (2019). Investigation of climatic factors of Azadshahr township (Golestan province) in order to development of saffron cropping. Journal of Saffron Research, 7(1), 123-143. [in Persian].
McCabe Jr, G. J. & Wolock, D. M. (1992). sensitwity of irrigation demand in a humid‐temperate region to hypothetical climatic change 1. Jawra Journal of the American Water Resources Association, 28(3), 535-543.
Ngoma, H., Wen, W., Ayugi, B., Babaousmail, H., Karim, R., & Ongoma, V. (2021). Evaluation of precipitation simulations in CMIP6 models over Uganda. International Journal of Climatology, 41(9), 4743-4768.
Pourmohamadi, s., Dastourani, m., Masahbavani, a., Rahimian, M. H., & Jafari, H. (2019). Evaluation of climate change impact on climate parameters in Tuyserkan Catchment using general circulation models. Water Resources Engineering, 12(42), 142-153. [in Persian].
Schlenker, W., Hanemann, W. M. & Fisher, A. C. (2007). Water availability, degree days, and the potential impact of climate change on irrigated agriculture in California. Climatic Change, 81(1), 19-38.
Shepard, D., (1968). A two-dimensional interpolation function for irregularly-spaced data. In Proceedings of the 1968 23rd ACM national conference.
Simonovic, S. P., Schardong, A., Sandink, D., & Srivastav, R. (2016). A web-based tool for the development of intensity duration frequency curves under changing climate. Environmental modelling & software, 81, 136-153.
Smith, J. B., & Pitts, G. J. (1997). Regional climate change scenarios for vulnerability and adaptation assessments. Climatic Change, 36(1), 3-21.
Woldemeskel, F. M., Sharma, A., Sivakumar, B., & Mehrotra, R. (2016). Quantification of precipitation and temperature uncertainties simulated by CMIP3 and CMIP5 models. Journal of Geophysical Research: Atmospheres, 121(1), 3-17.
Zamani, Y., Monfared, S. A. H., Azhdarimoghaddam, m., & Hamidianpour, M. (2020). A comparison of CMIP6 and CMIP5 projections for precipitation to observational data: the case of Northeastern Iran. Theoretical and Applied Climatology, 142(3), 1613-1623.