برآورد نیاز آبی و عملکرد گندم (Triticum aestivum L.) تحت تأثیر تغییر اقلیم (مطالعه موردی: دشت قزوین)

نوع مقاله : مقاله پژوهشی

نویسندگان

• مژگان احمدی
• هادی رمضانی اعتدالی

گروه علوم ومهندسی آب، دانشگاه بین المللی امام خمینی(ره)، قزوین، ایران.

10.22067/agry.2021.68517.1015

چکیده

در عصر حاضر، تغییر اقلیم به‌عنوان یکی از عوامل مهم و تأثیرگذار در توسعه پایدار، کشاورزی و امنیت غذایی مطرح می‌باشد. گندم (Triticum aestivum L.) یکی از محصولات مهم و استراتژیک در جهان و ایران محسوب می‌شود. به همین منظور، در این پژوهش به تأثیر تغییر اقلیم بر عملکرد و نیاز آبی گندم آبی در دشت قزوین در دوره‌های آتی پرداخته شده است. برای ارزیابی، از مدل‌های گردش عمومی موجود در مدل LARS-WG (EC-Earth،GFDL-CM3 ،HadGEM2-ES ، MIROC5، MPI-ESM-MR) و سناریوهای RCP2.6، RCP4.5 و RCP8.5 در دوره پایه 2015- 1986و در دوره‌های آتی2040- 2021، 2060-2041، 2080- 2061 و 2100- 2081 استفاده شد. نیاز آبی و عملکرد گندم در دوره پایه و دوره‌های آتی با نرم‌افزار Aqua Crop محاسبه شد. در این پژوهش، نتایج حاصل از سناریوها با داده ایستگاه قزوین برای محصول گندم، توسط معیارهای آماری خطا شامل آماره­های ضریب تبیین (R²)، خطای جذر میانگین مربعات (RMSE)، حداکثر خطا (ME)، مقایسه شدند. نتایج شبیه‌سازی مدل LARS-WG در دوره پایه نشان داد که مدل در شبیه‌سازی دمای حداقل و حداکثر دقت بیشتری نسبت به بارش دارد. میانگین عملکرد گندم برای دوره پایه 67/7 (تن بر هکتار بر فصل) به‌دست آمد. نتایج شبیه‌سازی نشان داد که میانگین عملکرد گندم در دوره‌های آتی افزایش می‌یابد که این میزان در دوره 2100-2081 و مدل HadGEM2-ES با سناریوی RCP8.5 بیشترین مقدار را دارد. میانگین نیاز آبی در دوره پایه 14/127 (میلی‌متر بر فصل) به‌دست آمد که این میزان در دوره‌های آتی کاهش می‌یابد. بنابراین، پیش‌بینی افزایش عملکرد در دشت قزوین بیانگر آن است که این منطقه از پتانسیل مطلوبی در کشت و توسعه این محصول برخوردار خواهد بود که علاوه‌بر مساعد بودن شرایط اقلیمی، بهبود مدیریت و نهاده‌های کشاورزی نیز می‌تواند باعث افزایش عملکرد این محصول در طی سال‌های آتی گردد.

کلیدواژه‌ها

• سناریوهای RCP
• مدل‌های گردش عمومی اتمسفر
• مدل LARS-WG
• Aqua Crop

موضوعات

• کارآیی مصرف منابع در کشاورزی

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عنوان مقاله [English]

Estimation of Water Requirement and Wheat (Triticum aestivum L.) Yield under the Impact of Climate Change

نویسندگان [English]

• Mojgan Ahmadi
• Hadi Ramezani Etedali

Department of Water Sciences and Engineering, Imam Khomeini International University, Qazvin, Iran.

چکیده [English]

Introduction
Crop production is directly dependent on climatic conditions, and climate determines the sources of production and productivity of agricultural activities. Therefore, long-term forecasting of climate variables and taking the necessary measures to mitigate the adverse effects of climate change have been considered by many researchers around the world. Climate change affects water requirement and crop yields in the future, so it is important to study changes in meteorological parameters and their impact on water requirement and crop yields in each region. So, in this study, the effect of climate change on the yield and water requirement of wheat in Qazvin synoptic station was investigated.
 
Materials and methods
In this study, the results of the scenarios were compared with the data of Qazvin station for wheat crop by statistical error criteria including Explanation coefficient statistics (R²), root mean square error (RMSE) and maximum error (ME). For evaluation, from the general circulation models in the LARS-WG model (EC-Earth, GFDL-CM3, HadGEM2-ES, MIROC5, MPI-ESM-MR) and the scenarios of RCP2.6, RCP4.5 and RCP8.5 in the baseline 1986-2015 was used. Yield and water requirement of wheat in the baseline and future periods 2021-2040, 2041-2060, 2061-2080 and 2081-2100 were calculated with Aqua Crop software.
 
Result and discussion
 The coefficient of explanation for the maximum and minimum temperatures simulated with the LARS-WG model shows that the simulated data and the synoptic station data are highly correlated. An explanation coefficient greater than 90% indicates that more than 90% of the variance in the minimum and maximum temperature data of the synoptic station is described by the LARS-WG model data. The value of RMSE at the minimum and maximum temperature is less than 3 °C, which indicates the low temperature deviation simulated with the LARS-WG model compared to the actual temperature. The ME index value was obtained for the minimum temperature equal 6.93 °C and for the maximum temperature equal 7.76 °C. The coefficient of explanation for the precipitation simulated with the LARS-WG model shows that the simulated data and the data of the synoptic station do not have a high correlation and the coefficient of explanation decreases to less than 0.5. The values of RMSE and ME were 33.28 mm and 183.10 mm, respectively. The results show that the model is more accurate in simulating minimum and maximum temperatures than precipitation. In a study, Goudarzi et al. (2015) investigated the performance of LARS-WG and SDSM microscopic exponential models in simulating climate change in the catchment area of Lake Orumieh. The results showed that both models are more accurate in simulating temperature than precipitation, which is consistent with the results of the present study. The average wheat yield for the baseline was 7.67 (tons/ha). The yield average will increase in future periods, which is the highest in the HadGEM2-ES model with the RCP8.5 scenario and the period 2081-2100. Water requirement was obtained in the baseline 127.14 mm. The water requirement average will decrease in future periods.
Conclusion
The simulation results of the LARS-WG model in the baseline showed that the model has more accurate in the simulation of minimum temperature (Tmin) and maximum temperature (Tmin) than precipitation. This study findings have also showed that the temperature will increase in future periods. Precipitation changes were seen as both decreasing and increasing trend. The yield increased in future periods, which is the highest in the HadGEM2-ES model with the RCP8.5 scenario and the period 2081-2100. The water requirement decreased in future periods.

کلیدواژه‌ها [English]

• Aqua Crop
• General Atmospheric Circulation Models
• LARS-WG Model
• RCP Scenarios

مراجع

Adabi, V., Azizian, A., Ramezani Etedali, H., Kaviani, and A., Ababaei, B., 2020. Local swnsitivity analysis of Aqua Crop model for wheat and maize in plain and Moghan Pars-Abad in Iran. Iranian Journal of Irrigation and Derainage 6(13): 1565-1579. (In Persian with English Summary)

Akbari, M., Najafi Alamdalo, H., and Mosavi, S.H., 2019. Impacts of climate change and drought on imcome risk and crop pattern in Qazvin plain irrigation network. Journal of Water Research in Agriculture 33(2): 265-282.  DOI:10.22092/JWRA.2019.119742 .(In Persian with English Summary)

Arefinia, A., Ahmadali, K., and Nasiri Mirian, M., 2020. Estimation of water requirement of winter wheat in Gorgan plain in the conditions of climate change. Iranian Soil and Water Research 51(7): 1868-1857. (In Persian with English Summary)

Asadi, M., Zarabianeh, H., Delavar, N., and Asadi, A., 2020. The effect of climate change phenomenon on climate parameters of Hamedan. Environmental Science and Technology 21(9): 1-14. (In Persian with English Summary)

Azuara, J., Howitt, R., MacEwan, D., and Lund, J., 2011. Economic impacts of climate-related changes to California agriculture. Journal of Climatic Change 109: 387-405.

Babolhakami, A., Gholami-Sefidkoohi, M., and Emadi, M., 2020. The effect of climate change on the evaporation of reference transpiration in Mazandaran province. Iranian Soil and Water Research 51(2): 387-401. (In Persian with English Summary)

Burkart, S., Manderscheid, R., Wittich, K.P., Löpmeier, F., and Weigel, H.J., 2011. Elevated CO₂ effects on canopy andsoil water flux parameters measured using a large chamber in crops grown with free-air CO₂ enrichment. Plant Biol (Stuttg)13: 258-269.  DOI: 10.1111/j.1438-8677.2010.00360.x

Deihimfard, D., Eyni Nargeseh, H., and Farshadi, S., 2017. Modeling the effects of climate change on irrigation requirement and water use efficiency of wheat fields of Khuzestan province. Journal of Water and Soil 31(4): 1015-1030.

Eyshi Rezaie, E., and Bannayan, M., 2012. Rainfed wheat yields under climate change in Northeastern Iran. Meteorological Application 19: 346-354.

Goudarzi, M., Salahi, B., and Hosseini, S.A., 2015. Performance assessment of LARS-WG and SDSM Downscaling Models in simulation of climate changes in Urmia Lake Basin. Iranian Journal of Watershed Management Science and Engineering 9(31):11-22. (In Persian with English Summary)

IPCC. Summary for policymakers. In: Climate Change. 2014. Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change Cambridge University Press, Cambridge. United Kingdom and New York. NY. USA. pp. 1-32.

Jalali, M., Sarai Tabrizi, M., and Babazadeh, H., 2020. Investigation of the effect of climate change on runoff and water balance of Latian dam catchment using SWAT model. Echo Hydrology 7(1): 17-28. (In Persian with English Summary)

Janjua, P.Z., Samad, G., and Khan, N., 2014. Climate change and wheat production in Pakistan. Autoregressive distributed lag approach. NJAS – Wageningen. Journal of Life Sciences (68): 13-19.

Joinior, W., Loireau, M., Fargette, M., Filho, B., and Wele, A., 2017. Correlation between soil erodibility and satellite data on areas of current desertification: A case study in Senegal. Ciência & Trópico. 42(2): 51-66.

Kamali, B., Ramezani Etedali, H., and Sotoodehnia, A., 2016. Determining appropriate time for rainfed lentil sowing and supplementary irrigation in Qazvin’s Plain using AquaCrop Model. Iranian Journal of Irrigation and Derainage 5(10): 613-621. (In Persian with English Summary)

Karimi, T., Stöckle, C., Higgins, S., and Nelson, R., 2017. Climate change and dryland wheat systems in the US Pacific Northwest. Agricultural Systems. 159: 144-156. DOI.org/10.1016/j.agsy.2017.03.014

Kemfert, C., 2009. Climate protection requirements the economic impact of climate change. Bausch & Burkhard Schwenker (ed.), Handbook Utility Management, chapter 42, 725-739. doi.org/10.1007/978-3-540-79349-6_42.

Khaliliaqdam, N., Masaedi, A., Soltani, A., and Kamkar, B., 2012. Evaluation of the ability of LARS-WG model in predicting some atmospheric parameters of Sanandaj. Journal of Soil and Water Conservation Research (4)19: 122-85. (In Persian with English Summary)

Koohi, M., Shirmohammadi, Z., Khani, A., Mohammadian, A., and Habibi-Nokhandan, H., 2020. Spatial-temporal distribution of reference temperature and evapotranspiration using CRU data in Khorasan Razavi and predicting future changes based on CMIP5 climate models. Remote Sensing and GIS Iran 12(1): 72-55. (In Persian with English Summary)

Ludwig, F., and Asseng, S., 2008. Impacts and adaptation to climate change in Western Australian wheat cropping systems. Agricultural Systems, 90: 159-179.

Lv, Z., Lio, X., Cao, W., and Zhu, Y., 2013. Climate change impacts on regional winter wheat production in main wheat production regions of China. Agricultural of Forest Meteorology 171: 234-248.

Mohammadi, E., Movahedi, S., Mohammadi, R., and Golgari, S. 2020. Investigation of climate change occurrence and its impact on dryland wheat yield phenology in the West and Northwest of Iran. Climatological Research. 11(43): 159-170. (In Persian with English Summary)

Nazari., R., and Kaviani., A., 2016. Evaluation of potential evaporation and transpiration methods and evaporation pan with elysimeter values ​​in a semi-arid climate (Case study: Qazvin plain). Echo Hydrology 3(1): 19-30. (In Persian with English Summary)

Nikbakhtshahbazi, A., 2018. Investigation of precipitation changes and evapotranspiration of agricultural products in Khuzestan province under the influence of climate change. Water and Soil Conservation Research 25(6): 139-123. (In Persian with English Summary)

Rahmani, M., Jami Al-Ahmadi, M., Shahidi, A., and Hadizadeh Azghandi, M., 2016. Effects of climate change on length of growth stages and water requirement of wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.) (Case study: Birjand plain). Journal of Agroecology 7(4): 443-460. (In Persian with English Summary)

Reilly, J., 1999. What does climate change mean for agriculture in developing countries? A comment on Mendelsohn and Dinar. The World Bank Research Observer. (14): 295-305.

Samadi, Z., Massahbovani, A., and Madavi, M., 2007. Investigating the effect of small regression scaling methods on river flood regime. Technical workshop on the effects of climate change on water resources management. https://civilica.com/doc/115812

Soria-Ruiz, J., Fernandes-Ordonez, Y., Quijano-Carranza, A., Macías-Cervantes, J., Sauceda, P., Gonzalez, D., and Quintana, J., 2012. Remote Sensing and Simulation Model for Crop Management. Proceedings of the PIERS Proceedings, Kuala Lumpur, Malaysia, 27-30.

Srivastava, A.K., Mboh, C.M., Zhao, G., Gaiser, T., and Ewert, F., 2018. Climate change impact under alternate realizations of climate scenarios on maize yield and biomass in Ghana. Agricultural Systems.159: 157-174. DOI.org/10.1016/j.agsy.2017.03.011

Steduto, P., Hsiao, T.C., Fereres, E., and Raes, D., 2012. Crop yield response to water (Vol. 1028): Food and Agriculture Organization of the United Nations Rome.

Steduto, P., Hsiao, T.C., Raes, D., and Fereres, E., 2009. AquaCrop—The FAO crop model to simulate yield response to water: I. Concepts and underlying principles. Agronomy Journal 101(3): 426-437.

Sun, S.K., Li, C., Wu, P.T., Zhao, X.N., and Wang, Y.B., 2018. Evaluation of agricultural water demand under future climate change scenarios in the Loess Plateau of Northern Shaanxi, China. Ecological Indicators 84: 811-819.

Tao, X.E., Chen, H., Xu, C.Y., Hou, Y.K., and Jie, M.X., 2015. Analysis and prediction of reference evapotranspiration with climate change in Xiangjiang River Basin, China. Water Science and Engineering 8(4): 273-281.

Xing, W., Wang, W., Shao, Q., and Ding, Y., 2018. Estimating net irrigation requirements of winter wheat across Central-Eastern China under present and future climate scenarios. Journal of Irrigation and Drainage Engineering 144(7): 05018005.

Zarei, K., Mohammadi, H., and Bazgir, S., 2019. Simulation of Gorgan Synoptic Station Temperature and Precipitation with RCP Scenarios. Physical Geography Research 51(4): 579-563. (In Persian with English Summary) DOI.10.22059/jphgr.2019.280943.1007378

Zeinali Mobarakeh, Z., Deihimfard, R., Kambouzia, J. 2019. Evaluation of the effects of climate change and its adaptation strategies on the performance and efficiency of water use of water wheat (Triticum aestivum): a case study of Razavi Khorasan province. Plant production research (agricultural sciences and natural resources) 26 (3): 71-87.