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بررسی تغییرات عملکرد و طول مراحل فنولوژی گندم دیم تحت سناریوی RCP با استفاده از دو مدل DSSAT و AquaCrop در غرب ایران | ||
تحقیقات آب و خاک ایران | ||
دوره 52، شماره 10، دی 1400، صفحه 2665-2677 اصل مقاله (1.2 M) | ||
نوع مقاله: مقاله پژوهشی | ||
شناسه دیجیتال (DOI): 10.22059/ijswr.2021.321307.668925 | ||
نویسندگان | ||
محمد لطفی1؛ غلامعلی کمالی* 2؛ امیرحسین مشکوتی3؛ وحید ورشاویان4 | ||
1دانشجوی دکتری هواشناسی کشاورزی، گروه علوم زمین، دانشگاه آزاد اسلامی واحد علوم و تحقیقات تهران،ایران | ||
2دانشیار هواشناسی کشاورزی، گروه علوم زمین، دانشگاه آزاد اسلامی واحد علوم و تحقیقات تهران، ایران | ||
3دانشیار هواشناسی، گروه علوم زمین، دانشگاه آزاد اسلامی واحد علوم و تحقیقات تهران، ایران | ||
4استادیار گروه علوم و مهندسی آب، دانشگاه بوعلی سینا، همدان، ایران | ||
چکیده | ||
تاثیر تغییر اقلیم به عنوان مهمترین عامل موثر بر کشاورزی و بهخصوص کشت دیم، مدیریت این منابع را در آینده با چالش همراه ساخته است. این مطالعه تلاش دارد تاثیر تغییر اقلیم را بر مقدار عملکرد و طول مراحل فنولوژی گندم دیم در غرب ایران مورد بررسی قرار دهد. به این منظور از دو مدل ریزمقیاسنمایی SDSM و LarsWG برای شبیهسازی اقلیم در دوره 30 ساله آتی استفاده شد. برای مدلسازی عملکرد و مراحل فنولوژی نیز از دو مدل AquaCrop و DSSAT در دوره پایه و دوره آتی با لحاظ نمودن سه سناریوی اقلیمی RCP 6/2، 5/4 و 5/8 استفاده شد. نتایج نشان داد کارایی مدل AquaCrop در مقایسه با DSSAT جهت پیشبینی عملکرد بهتر بوده و خطای کمتری دارد؛ به طوری که مقدار ضریب تبیین دادههای مشاهداتی و شبیهسازی شده در دوره پایه با مدل AquaCrop در ایستگاههای کرمانشاه، سنندج و ایلام بهترتیب 86/0، 64/0 و 89/0 و ضریب RMSE بهترتیب 6/198، 6/274 و 0/192 کیلوگرم در هکتار است. در صورتی که در مدل DSSAT مقدار ضریب تبیین بهترتیب 90/0، 11/0 و 82/0 و ضریب RMSE نیز به ترتیب 9/211، 1/288 و 238 کیلوگرم در هکتار است. نتایج کلی نشان میدهد در مدل ریزمقیاسنمایی LarsWG با مدل زراعی AquaCrop و DSSAT کمترین عملکرد برای ایستگاههای کرمانشاه، سنندج و ایلام به ترتیب در سناریوی 5/8، 5/4 و 5/8 و بیشترین عملکرد در سناریوی 6/2، 6/2 و 5/4 بهدست میآید که نشان دهنده کاهش عملکرد در سناریوی افزایش دما و افزایش دیاکسیدکربن است. این در حالی است که در مدل ریزمقیاسنمایی SDSM بیشترین عملکرد گندم دیم عمدتاً در سناریوهای 5/4 و 5/8 بوده و کمترین عملکرد در سناریوی 6/2 خواهد بود که با نتایج مدل LarsWG متفاوت است. با توجه به این نتایج میتوان بیان کرد نوع مدل ریزمقیاسنمایی و مدل زراعی میتواند در نتایج بهدست آمده موثر باشد. | ||
کلیدواژهها | ||
گندم دیم؛ عملکرد؛ RCP؛ تغییر اقلیم | ||
مراجع | ||
Ahmadali, Kh., Hosseini Pajouh, N. and Liaghat, A. (2015). Determination of optimal planting date of rainfed wheat, in Kurdistan Province, Iran, Applied field Crops Research, 28(4):9-18. DOI: 10.22092/AJ.2016.106737. (In Farsi) Akhavan, S, Delavar, N.. and Mehnatkesh, A. (2017). Climate Change Impact on Some Factors Affecting Rainfed Wheat Growth (Case Study: Chaharmahal and Bakhtiari Province), J. Water and Soil Sci (Sci. & Technol. Agric. & Natur. Resour.), 21 (2): 131-149.DOI: 10.18869/acadpub.jstnar.21.2.131. (In Farsi) Alexandrov, V. and Hoogenboom, G. (2000). Vulnerability and adaptation assessments of agricultural crops under climate change in the southeastern USA. Theor Appl Climatol 67:45–63. doi:10.1007/s007040070015 Allen, R.G., Periera, L.S., Raes, D. and Smith, M. (1998). Crop evapotranspiration: guideline for computing crop water requirement. FAO Irrigation and Drainage Paper No. 56. FAO: Rome, Italy. Amiri, E., Bahrani, A., Khorsand, A. and Haghjoo, M. (2016). Evaluating AquaCrop Model Performance to Predict Grain Yield and Wheat Biomass, Under Water Stress, Water and Soil Science, 25(4/2):217-229. (In Farsi) Andarzian, B., Bannayan, M., Steduto, P., Mazraeh, H., Barati, M.E., Barati, M.A. and Rahnama, A. (2011). Validation and testing of the AquaCrop model under full and deficit irrigated wheat production in Iran, Agricultural Water Management 100: 1-8 Andarzian, B., Hoogenboom, G., Bannayan, M., Shirali, M. and Andarzian, B. (2015). Determining optimum sowing date of wheat using CSM-CERES-Wheat model, Journal of the Saudi Society of Agricultural Sciences, 14, 189–199. Anwar, M.R., O’Leary, G., McNeil, D., Hossain, H., Nelson, R. (2007). Climate change impact on rainfed wheat in south-eastern Australia. Field Crops Res. 104, 139–147. Azizi, A.H. and Safarkhani, A. (2002). Drought Assessment and Its Impact on Dryland Wheat Yield in Ilam Province with Emphasis on Recent Droughts (2000-2001), Modares Journal of Humanities: 79-61. (In Farsi) Bannayan, M., Lotfabadi, S.S., Sanjani, S., Mohamadian, A. and Aghaalikhani, M. (2011). Effects of precipitation and temperature on crop production variability in northeast Iran. Int J Biometeorol, 55:387-401. doi:10.1007/s00484-010-0348-7 Delghandi, M., Andarzian, B., Broomandnasab, S., Massah Bovani, A. and Javaheri, E. (2014). Evaluation of DSSAT 4.5-CSM-CERES-Wheat to Simulate Growth and Development, Yield and Phenology Stages of Wheat under Water Deficit Condition (Case Study: Ahvaz Region), Journal of Water and Soil, 28 (1):82-91. DOI: 10.22067/JSW.V0I0.20658. (In Farsi) Dettori, M., Cesaraccio, C., Motroni, A., Spano, D. and Duce,P., 2011. Using CERES-Wheat to simulate durum wheat production and phenology in Southern Sardinia, Italy, Field Crops Research 120:179–188. De la Casa, A., Ovando, G., Bressanini, L., & Martínez, J. (2013). AquaCrop model calibration in potato and its use to estimate yield variability under field conditions. Atmospheric and Climate Sciences, 3, 397-407 Eyni Nargeseh, H., Deihimfard, R., Soufizadeh, S., Haghighat, M. and Nouri, O. (2015). Predicting the impacts of climate change on irrigated wheat yield in Fars province using APSIM model, EJCP, 8(4):203-224. (In Farsi) Eyshi Rezaie, E. and Bannayan, M. (2012). Rainfed wheat yields under climate change in northeastern Iran. Meteorol.Appl.19: 346– 354. Farajzadeh Asl, M., Kashki, A. and Shayan, S. (2009). Analysis of yield variability of dryland wheat crop with the approach of climate change (study area of Khorasan Razavi province), Human Sciences MODARES, 256-227. (In Farsi) Farajzadeh Asl, M., Khourani, A., Bazgir, S. And Ziaeian, P. (2011). Identification and analysis of the effect of climatic parameters and indicators of agricultural climatology on different stages of dryland wheat Phenology in Kurdistan province, , Human Sciences MODARES:1-17. (In Farsi) Fischer, G., Shah, M. and Van Velthuizen, H., 2002. Climate Change and Agricultural Vulnerability. Special Report for the UN World Summit on Sustainable Development, 26 August–4 September. International Institute for Applied Systems Analysis, Johannesburg, Laxenburg, Austria152. Helali, J. (2018). Seasonal prediction of rainfed wheat yield by combining crop models and statistical methods, Phd thesis in Agrometeorology, University of Tehran, Karaj, Iran. Iqbal, M., 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. Jamieson, P.D., Porter, J.R., Goudriaan, J., Ritchie, J.T., van Keulen, H. and Stol, W. (1998). A comparison of the models AFRCWHEAT2, CERES-Wheat, Sirius, SUCROS2 and SWHEAT with measurements from wheat grown, under drought, Field Crops Research, 55:23-44. Johnen, T. Boettcher, U. and Kage, H. (2012). A variable thermal time of the double ridge to flag leaf emergence phase improves the predictive quality of a CERES-Wheat type phenology model, Computers and Electronics in Agriculture, 89:62–69. 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. DOI:10.1016/S1161-0301(02)00107-7 Keating, B.A., Carberry, P.S., Hammer, G.L., Probert, M.E., Robertson, M.J., Holzworth, D., Huth, N.I., Hargreaves, J.N.G., Meinke, H., Hochman, Z., McLean, G., Verburg, K., Snow, V., Dimes, J.P., Silburn, M., Wang, E., Brown, S., Bristow, K.L., Asseng, S., Chapman, S., McCown, R.L., Freebairn, D.M., Smith, C.J., 2003. An overview of APSIM, a model designed for farming systems simulation. European Journal of Agronomy, 18(3-4): 267-288. DOI:10.1016/S1161-0301(02)00108-9 Kamali, Gh.A. and Bazigar, S., 2008. Wheat yield prediction using agro meteorological indices for some regions of the Western of the country, J. Agric. Sci. Natur. Resour., 15(2):113-121. (In Farsi) Kamali, Gh.A., Mollaei, P. and Behyar, M.B. ( 2010). Development of Zanjan Province Dry Land Wheat Atlas by using Climatic Data and GIS, Journal of Water and Soil, 24(5):894-907. (In Farsi). Kamali, Gh.A., Sadaghiani Poor, A. and Sedaghat Kerdar, A. (2008). The climatic zoning of dryland wheat in Eastern Azerbaijan, Water and Soil, 22 (2):467-483.10.22067/JSW.V0I22.1045. (In Farsi) Khalili, N., Davary, K., Alizadeh, A., Kafi, M. and Ansari, K. (2014). Simulation of Rainfed Wheat Yield using AquaCrop Model, Case Study: Sisab Rainfed Researches Station, Northern Khorasan, Journal of Water and Soil, 28(5):930-939. (In Farsi) Koocheki, A. and Nassiri, M. (2008). Impacts of climate change and CO2 concentration on wheat yield in Iran and adaptation strategies. Iran. J. Field Crops Res. 6(1): 139-153. (In Farsi). Kouchaki, A., Nassiri, M., Sharifi, H.R.,Soltani, A.A.F., and Kamali, G.A. (2003). Simulation of changes in climatic parameters of Iran under doubles CO2 concentration using General Circulation Models, Desert, 8(2):179-191. Kobayashi, K. and Salam, M.U., 2000. Comparing simulated and measured values using mean squared deviation and its components, Agronomy Journal, 92 (2): 345-352. McCown, R.L., Hammer, G.L., Hargreaves, J.N.G., Holtzworth, D.P. and Freebairn, D.M., 1996. APSIM: a novel software system for model development, model testing and simulation in agricultural systems research. Agric. Syst. 50(3): 255-271. DOI: 10.1016/0308-521X(94)00055-V Mahru Kashani, A.H., Soltani, A., Galeshi, S. and Kalate-Arabi, M. (2010). Estimates of genetic coefficients and evaluation of model DSSAT for Golestan province, EJCP, 3(2):229-253. Mavromatis, T. (2016). Spatial resolution effects on crop yield forecasts: An application to rainfed wheat yield in north Greece with CERES-Wheat, Agricultural Systems, 14: 38-48 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. Mohammadi, A. Yazdanpanah, H., and Mohammadi, F. (2014). Investigation of the occurrence of climate change and its effect on planting time and growth period of durum wheat (rainfed), Case study: Sararoud Station, Kermanshah, Natural Geography Research, 46: 231-246. Mohammadi, H. (2005). Determining the appropriate calendar for dryland wheat cultivation in Ilam province using rainfall start index, Geographical research, 51: 31-15. (In Farsi). Nassiri, M., Koocheki, A., Kamali, G. and Shahandeh, H. (2006). Potential impact of climate change on rainfed wheat production in Iran, Archives of Agronomy and Soil Science, 52 (1): 113-124. Nouri, M., Homaee, M. and Bannayan, M., 2017. Climate variability impacts on rainfed cereal yields in west and northwest Iran, Int J Biometeorol, 61:1571-1583 Nouri, M., Homaee, M., Bannayan, M. and Hoogenboom, G., 2017. Towards shifting planting date as an adaptation practice for rainfed wheat response to climate change, Agricultural Water Management, 186:108-119. Ortiz, R., Sayre, K.D., Govaerts, B., Gupta, R., Subbarao, G.V., Ban, T., Hodson, D., Dixon, J.M., Ortiz Monasterio, J.R. and Reynolds, M., 2008. Climate change: Can wheat beat the heat?. Agric. Ecosyst Environ. 126(1):46-58. Rahmani, M., Jami Al-Ahmadi, M., Shahidi, A. and Hadizadeh Azghandi, M. (2015). 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 Farsi). Ranuzzi, A. and Srivastava, R. (2012). Impact of Climate Change on Agriculture and Food Security. ICRIER Policy Series, no. 16. Ray, D.K., Gerber, J.S., MacDonald, G.K. and West, P.C. (2015). Climate variation explains a third of global crop yield variability. Nature Commun 6, doi: 10.1038/ncomms6989 Saadi, S., Todorovic, M., Tanasijevic, L., Pereira, L.S., Pizzigalli, C. and Lionello, P. (2015). Climate change and Mediterranean agriculture: Impacts on winter wheat and tomato crop evapotranspiration, irrigation requirements and yield. Agric. Water Manage. 147: 103-115. Semenov, M.A. (2009). Impacts of climate change on wheat in England and wales. Roy. Soc. 6: 343-350. Shakiba, A.R., Shabkhiz, S. and Hashamdar, F. (2015). Possible effects of climate change on wheat crop in the state of Tehran, Researches in Earth Sciences, 23:53-65. (In Farsi). Soleymani Nanadegani, M., Parsinejad, M., Araghinejad, S. and Massah Bavani, A. (2011). Study on Climate Change Effect on Net Irrigation Requirement and Yield for Rainfed Wheat (Case Study: Behshahr), Journal of Water and Soil, 25(2):389-397. DOI: 10.22067/JSW.V0I0.9485 Steduto, P., Hsiao, T. C., and Fereres, E. (2007). On the conservative behavior of biomass water productivity. Irrigation Science, 25(3), 189-207. Steduto, P., Hsiao, T.C., Raes, D. and Fereres, E. (2009). AquaCrop-The FAO crop model to simulate yield response to water: concepts and underlying principles. Agronomy Journal, 101(3): 426-437. DOI: 10.2134/agronj2008.0139s Talliee, A.A. and Bahramy, N. (2003). The effects of Rainfall and Temperature on the yield of Dryland wheat in Kermanshah province, Irannian Journal of Soil and Waters Sciences, 17(1):106-112. Tavakoli, A., Liaghat, A. and Alizadeh, A. (2014). Soil Water Balance, Sowing Date and Wheat Yield Using AquaCrop Model under Rainfed and Limited Irrigation, Journal of Agricultural Engineering Research, 14(4):41-56. Van Keulen, H. and Wolf, J. (1986). Modelling of agricultural production: Weather soils and crops. Simulation Monographs. Pudoc, Wageningen, The Netherlands, p. 479. Van Ittersum, M.K., Le elaar, P.A., Van Keulen, H., Krop, M.J., Bastiaans, L., Goudriaan, J., 2003. On approaches and applications of the Wageningen crop models. European Journal of Agronomy, 18(3-4): 201–234. DOI: 10.1016/S1161-0301(02)00106-5 Xiangxiang, W., Quanjiu,W., Jun, F. and Qiuping, F. ( 2013). Evaluation of the AquaCrop model for simulating the impact of water deficits and different irrigation regimes on the biomass and yield of winter wheat grown on China’s Loess Plateau, Agricultural Water Management 129:95–104. Zhang, W., Liu, W., Xue, Q., Pei, H., Chen, J. and Han, X. (2013). Evaluation of the AquaCrop model for simulating yield response of winter wheat to water on the southern Loess Plateau of China. Water Science and Technology 68(4):821-828.
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