Evaluation of the Impacts of Climate Change on Sunflower with Aquacrop Model

Öz

Climate change has become one of the most significant risk factors in agricultural production. Plant productivity declines caused by climate change pose a serious threat to food supply and security. Crop simulation models have been widely used in recent years for the assessment of the impacts of climate change on agricultural production. In Konya, there have been limited studies on the potential effects of climate change on sunflower production. Sunflower, the main crop of the most imported agricultural product group, in which the production amount is currently insufficient to cover domestic consumption demand, is strategically important for the Turkish economy. The goal of this study was to examine the effects of climate change on sunflower yield in Türkiye by using the Aquacrop model. The data of the field experiment carried out on the Ekllor sunflower cultivar for two years in Konya conditions were used as material. The daily projection dataset of three Global Climate Models (HadGEM2-ES, MPI-ESM-MR, GFDL-ESM2M) and two scenarios (RCP4.5 and RCP8.5) were used to analyze climate change impacts. The 1971-2000 period was considered as the reference period and the 2022-2098 period was selected as the future period. The results confirmed that the Aquacrop model was able to satisfactorily simulate yield with NRMSE 2.10 % for the rainfed condition and 10.55 % for the irrigated condition, a d-index of 0.97, and a modeling efficiency of 0.91. Aqaucrop climate change impacts simulation which was based on 3 global climate models covering with 2022 -2098 period simulations projected that sunflower yield would be decreased in a range of 21% to 44% for RCP4.5 and 18% to 50% for RCP8.5 scenarios under rainfed conditions. In contrast, the yield would be increased in a range of 11% to 23% for RCP4.5 and 10% to 33% for RCP8.5 scenarios under irrigated conditions. The findings point to the use of appropriate water management measures for future sunflower production as a means of adapting to climate change.

Anahtar Kelimeler

• Aquacrop
• Crop simulation model
• Climate change
• Sunflower
• Crop yield changes

Teşekkür

The author thanks Prof. Dr. Nilgün Bayraktar, Prof. Dr. Yusuf Ersoy Yildirim (Ankara University Faculty of Agriculture), Dr. Arzu Gündüz (General Directorate of Agricultural Research and Policies), Dr. Hüseyin Bulut, Osman Eskioğlu and, Yusuf Çalık (Turkish State Meteorological Service) for their contributions to the study.

İklim Değişikliğinin Ayçiçeği Üzerine Etkilerinin Aquacrop Modeli ile Değerlendirilmesi

Öz

İklim değişikliği tarımsal üretim için en önemli risk faktörlerinden biri haline gelmiştir. İklim değişikliğinin neden olduğu bitki verimliliği düşüşleri, gıda arzı ve güvenliği için ciddi bir tehdit oluşturmaktadır. Bitki simülasyon modelleri son yıllarda iklim değişikliğinin tarımsal üretim üzerine etkilerinin değerlendirilmesinde giderek yaygın olarak kullanılmaya başlamıştır. Türkiye’de iklim değişikliğinin tarımsal üretim üzerine olası etkileri ile ilgili çalışma sınırlı sayıdadır. Üretim miktarı henüz iç tüketim talebini karşılayamayan ve en fazla ithalatı yapılan tarımsal ürün gurubunun temel ürünü olan ayçiçeği Türkiye ekonomisi için stratejik öneme sahiptir. Bu çalışmanın amacı, Türkiye’de iklim değişikliğinin ayçiçeği verimi üzerine etkilerinin Aquacrop modeli kullanılarak analiz edilmesidir. Konya koşullarında iki yıl süreyle Ekllor ayçiçeği çeşidi üzerine yürütülen tarla denemesine ait veriler materyal olarak kullanılmıştır. İklim değişikliği etki analizi için ise 3 Küresel İklim Modeli (HadGEM2-ES, MPI-ESM-MR, GFDL-ESM2M) ve 2 senaryoya (RCP4.5 ve RCP8.5) ait günlük veriler kullanılmıştır. 1971 - 2000 dönemi referans, 2022 – 2098 dönemi ise iklim değişikliği etki analizi dönemi olarak ele alınmıştır. Çalışma sonuçları Aquacrop modelinin susuz koşullarda %2.10 ve sulu koşullarda %10.55 NRMSE değeri, 0.97 d-indeks ve 0.91 model etkinliği istatistiksel analizleri ile verimi başarılı bir şekilde simüle edebildiğini ortaya koymuştur. 3 küresel iklim modeli ve 2022-2098 yılları arası dönem özelinde oluşturulan Aquacrop iklim değişikliği projeksiyon sonuçlarına göre ayçiçeği veriminin susuz koşullarda RCP4.5 senaryosuna göre %21-44, RCP8.5 senaryosuna göre ise %18-50 aralığında azalması öngörülmektedir. Bunun aksine sulu koşullarda RCP4.5 senaryosuna göre %11-23, RCP8.5 senaryosuna göre %10-33 aralığında verim artışı sağlanabilecektir. Bulgular, iklim değişikliğine uyum sağlamanın bir yolu olarak gelecekteki ayçiçeği üretimi için uygun su yönetimi uygulamalarının kullanılmasına işaret etmektedir.

Anahtar Kelimeler

• Aquacrop
• Bitki simülasyon modeli
• İklim değişikliği
• Ayçiçeği
• Bitki verim değişimleri

Kaynakça

1. Akcakaya, A., Sumer, U. M., Demircan, M., Demir, O., Atay, H., Eskioglu, O., Gürkan, H., Yazici, B., Kocaturk, A., Sensoy, S., Boluk, E., Arabaci, H., Acar, Y., Ekici, M., Yagan, S. and Cukurcayir, F. (2015). Turkey climate projections with new scenarios and climate change-TR2015-CC. Turkish State Meteorological Service. 149 pg. Ankara, Turkey.
2. Altürk, B., Bakanoğulları, F., Konukçu, F., Albut S. (2019). TR21 Trakya Bölgesi'nde İklim Değişikliğinin Ayçiçeği ve Buğday Verimine Etkisinin Modellenmesi. TR21 Trakya Bölgesinde İklim Değişikliğinin Etkileri ve Uyum Stratejileri, Tekirdag Namik Kemal University Publications, pg: 104-117, Tekirdag, Türkiye.
3. Boote, K. J., Jones, J. W., Hoogenboom, G. and White, J. W. (2010). The role of crop systems simulation in agriculture and environment. International Journal of Agricultural and Environmental Information Systems, 1(1): 41-54.
4. Bulut, H. 2015. The effect of climate factors and climate change on the yield of opium poppy (Papaver somniferum L.) in Turkey. (MSc. Thesis) Department of Field Crops, Graduate School of Natural and Applied Sciences, Ankara University, Ankara.
5. Debaeke, P., Casadebaig, P., Flenet, F. and Langlade, N. (2017). Sunflower crop and climate change: vulnerability, adaptation, and mitigation potential from case-studies in Europe. OCL Oilseeds and Fats Crops and Lipids, 24(1): 15-21.
6. Dellal, I. (2012). Economic impacts of climate change on agriculture in Turkey. Turkey II. National Declaration Preparation Project Publication. Republic of Turkey Ministry of Environment and Urbanization Publication, Ankara, Turkey.
7. Demir, I. (2013). Oilseed crop cultivation in TR71 region and effects of climate change. Turkish Journal of Agriculture-Food Science and Technology, 1(2): 73-78.
8. Demircan, M., Gürkan, H., Eskioglu, O., Arabaci, H. and Coskun, M. (2017). Climate change projections for Turkey: three models and two scenarios. Turkish Journal of Water Science and Management, 1(1): 22-43.

9. Deveci, H. (2015). Modeling the effect of climate change on surface water resources, soil water profile and plant yield in Thrace region. (PhD Thesis) Namık Kemal University, Graduate School of Applied Science, Tekirdağ, Türkiye.
10. Deveci, H., Konukçu, F. and Altürk, B. (2019). Effect of Climate Change on Wheat Grown Soil Moisture Profile in Thrace District. Journal of Tekirdag Agricultural Faculty, 16(2): 202-218.
11. Donatelli, M., Srivastava, A.K., Duveiller, G., Niemeyer, S. and Fumagalli, D. (2015). Climate change impact and potential adaptation strategies under alternate realizations of climate scenarios for three major crops in Europe. Environmental Research Letters, 10(7): 075005.
12. Easterling, W. E., Aggarwal, P. K., Batima, P., Brander, K. M., Erda, L., Howden, S. M., Kirilenko, A., Morton, J., Soussana, J. F., Schmidhuber, J. and Tubiello, F. N. (2007). Food, Fibre and Forest Products. Climate Change 2007, Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, 273–313, Cambridge, UK.
13. Elsheikh, E. (2015). Water productivity of sunflower under different irrigation regimes at gezira clay soil, Sudan. (PhD Thesis). The Academic Board of Wageningen University and the Academic Board of the UNESCO-IHE Institute for Water Education. in Delft, the Netherlands.
14. FAO (2016). The State of Food and Agriculture 2016 Climate Change, Agriculture, and Food Security. Rome, Italy.
15. FAO (2022). FAO Agricultural Production Rankings by Country. www.fao.org/faostat/en/#rankings/countries_by_commodity (Accessed 15 October 2022).
16. Garcia-Vila, M., Fereres, E., Mateos, L., Orgaz, F. and Steduto, P. (2009). Deficit irrigation optimization of cotton with AquaCrop. Agronomy Journal, 101(3): 477-487.
17. Gitay, H., Brown, S., Easterling, W. and Jallow, B. 2001. Ecosystems and their goods and services. In: McCarthy, J.J., Canziani, O.F., Leary, N.A., Dokken, D.J., White, K.S. (Eds.), Climate Change 2001: Impacts, Adaptation, and Vulnerability. Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, 235–342, Cambridge, UK.
18. Gunduz, A., Gunduz, O., Dundar, M. A., Cagirgan, O. and Cay, S. 2018. The Effect of different water level with water stress on yield and quality of sunflower under Konya conditions. SDU Journal of Faculty of Agriculture, 13(2): 249-258.
19. Gürkan, H. (2019). Estimation of possible effects of climate change on sunflower (Helianthus annuus L.) yield in Konya Basin. (Ph. D. Thesis) Ankara University Graduate School of Applied Science Department of Agronomy, , Ankara, Turkey.
20. Gürkan, H., Ozgen, Y., Bayraktar, N., Bulut, H. and Yildiz, M. (2020). Possible Impacts of Climate Change on Sunflower Yield in Türkiye. Intechopen, Book of Climate Change & Food Security, United Kingdom. DOI: 10.5772/intechopen.91062
21. Gürkan, H., Shelia, V., Bayraktar, N., Ersoy Yıldırım, Y., Yesilekin, N., Gunduz, A., Boote, K., Porter, C. and Hoogenboom, G. (2021). estimating the potential impact of climate change on sunflower yield in the Konya Province of Türkiye. The Journal of Agricultural Science, 158(10): 806-818.
22. Hoogenboom, G. (2000). Contribution of agrometeorology to the simulation of crop production and its applications. Agricultural and Forest Meteorology, 103(1-2): 137-157.
23. Hoogenboom, G., White, J.W. and Messina, C.D. (2004). From genome to crop: integration through simulation modeling. Field Crops Research, 90(1): 145-163.
24. Hsiao, T. C., Heng, L., Steduto, P., Rojas-Lara, B., Raes, D. and Fereres, E. (2009). AquaCrop-the FAO crop model to simulate yield response to water: III. Parameterization and testing for maize. Agronomy Journal, 101(3): 448-459.
25. IPCC. 2018. Special Report: Global Warming of 1.5 °C Summary for policymakers. Available online from https://www.ipcc.ch/sr15/chapter/summary-for-policy-makers/ (Accessed 11 July 2020).
26. Jones, J. W., Hoogenboom, G., Porter, C. H., Boote, K. J., Batchelor, W. D., Hunt, L. A., Wilkens, P. W., Singh, U., Gijsman, A. J. and Ritchie, J. T. (2003). The DSSAT cropping system model. European Journal of Agronomy, 18(3-4): 235-265.
27. Kale, S. and Madenoğlu, S. (2017). Evaluating aquacrop model for winter wheat under various irrigation conditions in Turkey. Journal of Agricultural Sciences, 24(2): 205-217.
28. Karimi, A. M. (2021). The effect of drought on wheat yield in Altinova Farm. (MSc. Thesis) Ankara University Graduate School of Applied Science Department of Agronomy, Ankara, Türkiye.
29. Konukcu, F., Deveci, H., Öztürk, B. (2020). Modelling of the effect of climate change on wheat yield in Thrace Region with AquaCrop and WOFOST models. Journal of Tekirdag Agricultural Faculty, 17(1): 77 - 96.
30. Long, S. P., Ainsworth, E. A., Leakey, A. D., Nösberger, J. and Ort, D. R. (2006). Food for thought: lower-than-expected crop yield stimulation with rising CO2 concentrations. Science, 312(5782): 1918-1921.
31. Nash, J. E. and Sutcliffe, J. V. (1970). River flow forecasting through conceptual models part I-A discussion of principles. Journal of Hydrology, 10(3): 282-290.
32. Osman, A. A. (2018). Evaluation of the FAO-Aquacrop model to simulate yield response to water for eggplant. (MSc. Thesis) Ondokuz Mayıs University Graduate School of Applied Science, Samsun, Türkiye.
33. Raes, D., Steduto, P., Hsiao, T.C. and Fereres, E. 2009. AquaCrop-the FAO crop model to simulate yield response to water: II. Main algorithms and software description. Agronomy Journal, 101(3): 438-447.
34. Raoufi, R.S. and Soufizadeh, S. 2020. Simulation of the impacts of climate change on phenology, growth, and yield of various rice genotypes in humid sub-tropical environments using AquaCrop-Rice. International Journal of Biometeorology, 64(10): 1657-1673.
35. Reddy, A. R., Rasineni, G. K. and Raghavendra, A. S. (2010). The impact of global elevated CO₂ concentration on photosynthesis and plant productivity. Current Science, 99(1): 46-57.
36. Reilly, J., Baethgen, W., Chege, F.E., Van de Geijn, S.C., Lin, Erda., Iglesias, A., Kenny, G., Patterson, D., Rogasik, J., Rötter, R., Rosenzweig, C., Sombroek, W., Westbrook, J., Bachelet, D., Brklacich, M., Dämmgen, U. and Howden, M. (1996) Agriculture in a changing climate: impacts and adaptation. In R. T. Watson, M. C. Zinyowera, & R. H. Moss (Eds.), Climate change 1995; impacts, adaptations and mitigation of climate change: scientific-technical analyses Cambridge University Press, 427-467.
37. Riahi, K. Rao, S., Krey, V., Cho, C., Chirkov, V., Fischer, G. Kindermann, G., Nakicenovic, N. and Rafaj, P. (2011). RCP8.5-A scenario of comparatively high greenhouse gas emissions. Climatic Change. 109: 33-57.
38. Steduto, P. (2003). Biomass water-productivity. Comparing the growth-engines of crop models. FAO Expert Consultation on Crop Water Productivity Under Deficient Water Supply, Rome. 26–28 Feb. 2003. FAO, Rome.
39. 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.
40. Stricevic, R., Cosic, M., Djurovic, N., Pejic, B. and Maksimovic, L. (2011). Assessment of the FAO AquaCrop model in the simulation of rainfed and supplementally irrigated maize, sugar beet and sunflower. Agricultural Water Management, 98(10): 1615-1621.
41. Stricevic, R., Vujadinović-Mandić, M., Đurović, N. and Lipovac, A. 2021. Application of two measures of adaptation to climate change for assessment on the yield of wheat, corn and sunflower by the Aquacrop model. Zemljište i biljka, 70(1): 41-59.
42. Thomson, A., Calvin, K., Smith, S., Kyle, P., Volke, A., Patel, P., Delgado-Arias, S., Bond-Lamberty, B., Wise, M., Clarke, L. and Edmonds, J. (2011). RCP4.5: a pathway for stabilization of radiative forcing by 2100. Climatic Change, 109: 77-94.
43. Todorovic, M., Albrizio, R., Zivotic, L., Saab, M. T. A., Stöckle, C. and Steduto, P. (2009). Assessment of AquaCrop, CropSyst, and WOFOST models in the simulation of sunflower growth under different water regimes. Agronomy Journal, 101(3): 509-521.
44. TURKSTAT. 2022. TurkStat, Agricultural Production Statistics. Ankara, Turkey. Available online from https://biruni.tuik.gov.tr/medas/?locale=tr (Accessed 15 January 2023).
45. USDA. 2021. Oilseeds: World Market And Trade Reports. United States Department of Agriculture Foreign Agricultural Service. September 2021, USA.
46. Valverde, P., de Carvalho, M., Serralheiro, R., Maia, R., Ramos, V. and Oliveira, B. (2015). Climate change impacts on rainfed agriculture in the Guadiana river basin (Portugal). Agricultural Water Management, 150: 35-45.
47. White, J. W., Hoogenboom, G., Kimball, B. A. and Wall, G. W. 2011. Methodologies for simulating impacts of climate change on crop production. Field Crops Research, 124(3): 357-368.
48. Willmott, C. J. (1982). Some comments on the evaluation of model performance. Bulletin of the American Meteorological Society, 63(11): 1309-1313.
49. Willmott, C. J., Ackleson, S. G., Davis, R. E., Feddema, J. J., Klink, K. M., Legates, D. R., O'Donnell, J. and Rowe, C. M. (1985). Statistics for the evaluation and comparison of models, J. Geophys. Res., 90(C5): 8995– 9005.
50. WMO (2022). WMO Statement on State of the Slimate in 2021. WMO-No: 1290, Geneva, Switzerland. Yesilkoy, S. (2020). Determination and Modelling Water Footprint in Agricultural Ecosystem in Thrace Region. (Ph.D. Thesis) Istanbul Technical University Graduate School of Applied Science Department of Agronomy, Istanbul, Türkiye.
51. Yigit, D. B. and Candogan, B. N. (2019). Estimation of Potato Yield Using FAO AquaCrop Model Under Different Irrigation Schedules. COMU Journal of Agriculture Faculty, 7(1): 91-98.