Journals / Tekirdağ Ziraat Fakültesi Dergisi / 2024 / Cilt: 21 Sayı: 5

Analyze of The Effects of Possible Climate Change Scenarios for Biomass and Grain Yields of Sunflower and Winter Wheat with AquaCrop Model in The Thrace Region of Türkiye

Trakya Bölgesi'nde Olası İklim Değişikliği Senaryolarının Ayçiçeği ve Kışlık Buğdayın Biyokütle ve Tane Verimine Etkilerinin AquaCrop Modeli ile Analizi

Fatih Bakanoğulları(TEKİRDAĞ BÜYÜKŞEHİR BELEDİYESİ TARIMSAL HİZMETLER DAİRE BAŞKANLIĞI)0000-0001-6329-5422
Pages
1267–1281
Publication Date
2024-12-23
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Finally, with the defined sensitivity scenarios, the correlation coefficients between biomass and grain yield of sunflower and winter wheat under similar climate but different soil types in two locations were found to be R2= 0.88 and 0.87 for KRK and R2 = 0.56, and 0.79, for EOR, respectively.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Prediction of crop yield and biomass in agricultural production is crucial for both food safety and national economic projections.
📊
Key Findings & Data:This study aimed to determine the relationship between the effects of climate change and biomass and grain yield of two crops (winter wheat and sunflower) at two locations, Kirklareli (KRK), Edirne-Orhaniye (EOR), with different soil textures, in the Thrace region.
💡
Conclusion & Impact:Finally, with the defined sensitivity scenarios, the correlation coefficients between biomass and grain yield of sunflower and winter wheat under similar climate but different soil types in two locations were found to be R2= 0.88 and 0.87 for KRK and R2 = 0.56, and 0.79, for EOR, respectively.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Agrometeoroloji · Kışlık buğday · Ayçiçeği

Abstract

Prediction of crop yield and biomass in agricultural production is crucial for both food safety and national economic projections. This study aimed to determine the relationship between the effects of climate change and biomass and grain yield of two crops (winter wheat and sunflower) at two locations, Kirklareli (KRK), Edirne-Orhaniye (EOR), with different soil textures, in the Thrace region. The scenarios (n=S1, S2,…,S65) of sensitivity analysis established by considering the expected trend of climate change were evaluated in terms of biomass and grain yield for sunflower and winter wheat crops with the AquaCrop model. The model predicted the highest losses of grain yield and biomass, when the air temperature was increased by 5 °C and the precipitation was decreased by 50% during the growing seasons of both crops (in the scenario S42). In the scenarios where only temperature was increased, grain and biomass yield values of sunflower was decreased, while those of winter wheat was increased. The combined effects of increased global solar radiation and decreased temperature had a negative effect on wheat production at EOR. For both sunflower and wheat, the most negative impacts on yield and biomass production were observed with the combined scenarios of various temperature increases and precipitation decreases during each growing season at each location. According to the simulation results of the defined single and combined scenarios in both spatial areas, while the grain and biomass yields of the summer planted sunflower plant were negative linear relations every scenario, non-linear relations were determined in the yields of the winter-wheat plant. Finally, with the defined sensitivity scenarios, the correlation coefficients between biomass and grain yield of sunflower and winter wheat under similar climate but different soil types in two locations were found to be R2= 0.88 and 0.87 for KRK and R2 = 0.56, and 0.79, for EOR, respectively.

Özet

Tarımsal üretimde ürün verimi ve biyokütlenin tahmini hem gıda güvenliği hem de ulusal ekonomik projeksiyonlar açısından büyük önem taşımaktadır. Bu çalışmada, Trakya bölgesinde, Kırklareli (KRK), Edirne-Orhaniye (EOR) de, farklı toprak bünyesine sahip iki lokasyonda iklim değişikliğinin etkileri ile iki ürünün (kışlık buğday ve ayçiçeği) biyokütle ve tane verimi arasındaki ilişkinin belirlenmesi amaçlamıştır. İklim değişikliğinin beklenen eğilimi dikkate alınarak oluşturulan hassaslık analizi senaryoları (n=S1, S2,…,S65) AquaCrop modeli ile ayçiçeği ve kışlık buğday bitkisi için biyokütle ve tane verimi açısından değerlendirilmiştir. Model, her iki ürünün yetiştirme sezonu boyunca hava sıcaklığının 5 °C arttığı ve yağışların %50 azaldığı senaryoda (S42) dane ve biyokütle veriminde en yüksek kayıpları tahmin etmiştir. Sadece sıcaklığın artırıldığı senaryolarda ayçiçeğinin dane ve biyokütle verim değerleri düşerken, kışlık buğdayın dane ve biyokütle verim değerleri arttı. Artan global güneş radyasyonu ve azalan sıcaklığın birleşik etkileri, EOR istasyonunda buğday dane üretimi üzerinde negatif bir etki yarattı. Hem ayçiçeği hem de buğday için, dane ve biyokütle üretimi üzerindeki en olumsuz etkiler, her iki gelişme sezonu boyunca, iki lokasyonda da çeşitli sıcaklık artışları ve yağış düşüşlerinin bir araya getirildiği senaryolarla gözlemlendi. Oluşturulan hassaslık analiz senaryolarının tekli ve birleşik senaryoların her iki mekânsal alanda simülasyon sonuçlarına göre, yazlık ekilen ayçiçeği bitkisinin tane ve biyokütle verimleri her senaryoda negatif doğrusal ilişkiler gösterirken, kışlık buğday bitkisinin dane verimlerinde doğrusal olmayan ilişkiler belirlenmiştir. Son olarak, tanımlanan duyarlılık senaryoları ile benzer iklim ancak farklı toprak tiplerine sahip iki lokasyondaki ayçiçeği ve kışlık buğdayın biyokütle ve tane verimi arasındaki korelasyon katsayıları sırasıyla KRK için R2= 0,88 ve 0,87 ve EOR için R2 = 0,56 ve 0,79 olarak bulunmuştur.

🔖

Cite This Article

Bakanoğulları, F. (2024). Analyze of The Effects of Possible Climate Change Scenarios for Biomass and Grain Yields of Sunflower and Winter Wheat with AquaCrop Model in The Thrace Region of Türkiye. Tekirdağ Ziraat Fakültesi Dergisi, Cilt: 21 Sayı: 5, 1267–1281. https://doi.org/10.33462/jotaf.1475379

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (31)

  1. Andarzian, B., Bannayan, M., Steduto, P., Mazraeh, H., Barati, M., Barati, M. and Rahnama, A. (2011). Validation and testing of the AquaCrop model under full and deficit irrigated wheat production in Iran. Agric. Water Management, 100: 1-8. https://doi.org/10.1016/j.agwat.2011.08.023
  2. Argentel-Martínez, L., Peñuelas-Rubio, O., Ponce, J. A. L., Arredondo, T., Garatuza-Payan, J. And Yepez, E. A. (2021). Correlation among vegetative and reproductive variables in wheat under a climate change simulation. Bragantia, 80: e4221 https://doi.org/10.1590/1678-4499.20210067
  3. Bello, Z. and Walker, S. (2017). Evaluating AquaCrop model for simulating production of amaranthus (Amaranthus cruentus) a leafy vegetable under irrigation and rainfed conditions. Agricultural and Forest Meteorology, 247: 300-310. https://doi.org/10.1016/j.agrformet.2017.08.003
  4. Çaldağ, B., Şaylan, L., Akataş N., Bakanoğulları, F. and Özgür, E. (2017). Investigation of the adaptation potential of winter wheat crop to future climatic conditions in northwest of Turkey. Fresenius Environmental Bulletin, 26(1): 29-37.
  5. Doorenbos, J. and Kassam, A. H. (1979). Yield response to water. FAO Irrigation and Drainage, Paper 33, 193 p. Rome, Italy.
  6. Eitzinger, J., Thaler, S., Schmid, E., Strauss, F., Ferrise, R., Moriondo, M. and Kersebaum, K. C. (2013). Sensitivities of crop models to extreme weather conditions during flowering period demonstrated for maize and winter wheat in Austria. The Journal of Agricultural Science, 151(6): 813-835. https://doi.org/10.1017/S0021859612000779
  7. Food and Agriculture Organization of the United Nations (FAO) (2009). ETo calculator version 3.1. Evapotranspiration from Reference Surface. Land and Water Division, Rome, Italy.
  8. Fuso, F., Bombelli, G. M. and Bocchiola, D. (2023). Ex-post assessment of climate and hydrological projections: reliability of CMPI6 outputs in Northern Italy. Theoretical and Applied Climatology, 155: 1343–1362. https://doi.org/10.1007/s00704-023-04698-5
  9. Iqbal, M. A., Shen, Y., Stricevic, R., Pei, H., Sun, H., Amiri, E., Penas, A. and del Rio, S. (2014). Evaluation of the FAO AquaCrop model for winter wheat on the North China Plain under deficit irrigation from field experiment to regional yield simulation. Agricultural Water Management, 135: 61-72. https://doi.org/10.1016/j.agwat.2013.12.012
  10. Jin, X., Li, Z., Nie, C., Xu, X., Feng, H., Guo, W. and Wang, J. (2018). Parameter sensitivity analysis of the AquaCrop model based on extended fourier amplitude sensitivity under different agro-meteorological conditions and application. Field Crops Research, 226: 1-15. https://doi.org/10.1016/j.fcr.2018.07.002
  11. Kale, S. (2016). Assessment of AQUACROP model in the simulation of wheat growth under different water regimes. Scientific Papers. Series A. Agronomy, 59: 308-314.
  12. Konukcu, F., Deveci, H. and Altürk, 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): 77-95. https://doi.org/10.33462/jotaf.593883
  13. Mkhabela, M. S. and Bullock, P. R. (2012) Performance of the FAO AquaCrop model for wheat grain yield and soil moisture simulation in Western Canada. Agricultural Water Management, 110: 16-24. https://doi.org/10.1016/j.agwat.2012.03.009
  14. Nazeer, M. and Ali, H. (2012) Modelling the response of onion crop to deficit irrigation. Journal of Agricultural Technology, 8(1): 393-402.
  15. Nyathi, M. K., Halsema, G. E., Annandale, J. G., Struik, P. C. (2018). Calibration and validation of the AquaCrop model for repeatedly harvested leafy vegetable grown under different irrigation regimes. Agricultural Water Management, 208: 107– 119. https://doi.org/10.1016/j.agwat.2018.06.012
  16. Öztürk, İ. (2024). Environment effect on yield and quality parameters and stability in bread wheat (Triticum aestivum L.) cultivars under rainfed conditions. Journal of Tekirdag Agricultural Faculty, 21(2): 324-334. https://doi.org/10.33462/jotaf.1222062
  17. Paredes, P., Wei, Z., Liu, Y., Xu, D., Xin, Y., Zhang, B. and Pereira, L. S. (2015). Performance assessment of the FAO-AquaCrop model for soil water soil evaporation biomass and yield of soybeans in North China Plain. Agricultural Water Management, 152: 57–71. https://doi.org/10.1016/j.agwat.2014.12.007
  18. Pirmoradian, N. and Davatgar, N. (2019) Simulating the effects of climatic fluctuations on rice irrigation water requirement using AquaCrop. Agricultural Water Management, 213: 97-106. https://doi.org/10.1016/j.agwat.2018.10.003
  19. Raes, D., Steduto, P., Hsiao, T. C., and Fereres, E. (2018). AquaCrop Version 6.0-6.1 Reference Manual. Rome, Italy: Food and Agriculture Organization of the United Nations. https://www.fao.org/land-water/databases-and-software/aquacrop/en/
  20. Raes, D., Steduto, P., Hsiao, T.C. and Fereres, E. (2009). AquaCrop—The FAO crop model for predicting yield response to water: II. Main algorithms and soft ware description. Agronomy Journal, 101: 438–447.
  21. Şaylan, L., Çaldağ, B., Bakanoğulları, F., Akataş, N., Yeşilköy, S. and Aslan, T (2017) Comparison of simulation models for determination of future wheat yields in Thrace, Turkey. Journal of International Scientific Publications: Agriculture and Food, 5: 453-460. https://www.scientific-publications.net/en/article/1001439/
  22. 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.
  23. Supit, I., Van Diepen, C., De Wit, A., Wolf, J., Kabat, P., Baruth, B. and Ludwig, F. (2012). Assessing climate change effects on European crop yields using the Crop Growth Monitoring System and a weather generator. Agricultural and Forest Meteorology, 164: 96-111. https://doi.org/10.1016/j.agrformet.2012.05.005
  24. Toumi, J., Er-Raki, S., Ezzahar, J., Khabba, S., Jarlan, L. and Chehbouni, A. (2016). Performance assessment of AquaCrop model for estimating evapotranspiration, soil water content and grain yield of winter wheat in Tensift Al Haouz (Morocco): Application to irrigation management. Agricultural Water Management, 163: 219-235. https://doi.org/10.1016/j.agwat.2015.09.007
  25. Trombetta, A., Iacobellis, V., Tarantino, E. and Gentile, F. (2016) Calibration of the AquaCrop model for winter wheat using MODIS LAI images. Agricultural Water Management, 164: 304-316. https://doi.org/10.1016/j.agwat.2015.10.013
  26. Vanuytrecht, E., Raes, D., Steduto, P., Hsiao, T.C., Fereres, E., Heng, L. K., Vila, M. G. and Moreno, P. M. (2014). AquaCrop: FAO’s crop water productivity and yield response model. Environmental Modelling & Software, 62: 351-360. https://doi.org/10.1016/j.envsoft.2014.08.005
  27. Voloudakis, D., Karamanos, A., Economou, G., Kalivas, D., Vahamidis, P., Kotoulas, V., Kapsomenakis, G. and Zerefos, C. (2015). Prediction of climate change impacts on cotton yields in Greece under eight climatic models using the AquaCrop crop simulation model and discriminant function analysis. Agricultural Water Management, 147: 116-128. https://doi.org/10.1016/j.agwat.2014.07.028
  28. Xing, H. M., Xu, X. G., Li, Z. H., Chen, Y. J., Feng, H. K., Yang, G. J. and Chen, Z. X. (2017). Global sensitivity analysis of the AquaCrop model for winter wheat under different water treatments based on the extended Fourier amplitude sensitivity test. Journal of Integrative Agriculture, 16(11): 2444-2458. https://doi.org/10.1016/S2095-3119(16)61626-X
  29. Xiuliang, J., Zhenhai, L., Chenwei, N., Xingang, X., Haikuan, F., Wenshan, G. and Jihua, W. (2018). Parameter sensibility analysis of the AquaCrop model based on extended fourier amplitude sensibility under different agro-meteorological conditions and application. Field Crops Research, 226: 1-15. https://doi.org/10.1016/j.fcr.2018.07.002
  30. Yeşilköy, S. and Şaylan, L. (2020). Assessment and modelling of crop yield and water footprint of winter wheat by aquacrop. Italian Journal of Agrometeorology, 3: 3-14. https://doi.org/10.13128/ijam-859
  31. Zeleke, K. and Nendel, C. (2020). Testing and application of the AquaCrop model for wheat production under different field management conditions in South-Eastern Australia. Agricultural Research, 9(3): 379-391. https://doi.org/10.1007/s40003-019-00438-2