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Evaluating rice yield and adaptation strategies under climate change based on the CSM-CERES-Rice model: a case study for northern Iran

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Abstract

The goal of this simulation study was to explore how rice yield for different water supply levels will respond to climate change at a field scale in northern Iran. The CSM-CERES-Rice model was used in combination with downscaled outputs of a General Circulation Model. Three representative concentration pathways (RCP2.6, RCP4.5, RCP8.5) and seven irrigation treatments (FI (full irrigation), PRD10, PRD30, PRD60 (partial root drying in different rates), RDI10, RDI30, RDI60 (regulated deficit irrigation in different rates)) were used in this study. Moreover, three adaptation strategies were evaluated to mitigate the vulnerability of yield to climate change. The results showed that irrigated rice yield will decrease for climate change projections for 2026–2047, but the reduction was insignificant for all RCPs. Our findings confirm the hypothesis that adaptations can significantly increase the irrigated rice yield under climate change. Shifting transplanting date 2 weeks earlier with FI, RDI10, PRD10, RDI30, and PRD30 showed a higher average yield between 4.67 and 5.03 ton/ha relative to RDI60 and PRD60 reference irrigation treatments for all RCPs. Shifting nitrogen fertilizer application date 1 week earlier under RCP2.6 and RCP8.5 and 2 weeks earlier under RCP4.5 with FI resulted in the highest yield ranging from 3.13 and 4.33 ton/ha. By adjusting the amount of nitrogen fertilizer applied, the highest yield was obtained for 2.5 times the application of the current application amount with FI for all RCPs. The evaluation of these adaptation scenarios suggests that shifting transplanting date is the best strategy compared to the other two adaptations, which resulted in a higher yield with the same amount of water for all RCPs.

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Data availability

The authors declare that all data and materials as well as software applications support their claims and comply with field standards. The data sets generated during the current study are available in the main text, tables of the manuscript, and also in the link https://climate-scenarios.canada.ca/?page=pred-canesm2. For more detailed information, please contact the corresponding author.

Code availability (software application or custom code)

All software applications used in the submitted work are publicly available. The CSM-CERES-Rice model used in this study is part of the DSSAT crop modeling system and can be requested from the DSSAT portal at www.DSSAT.net.

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References

  • Ahiablame L, Sinha T, Paul M, Ji J, Rajib A (2017) Streamflow response to potential land use and climate changes in the James River watershed, Upper Midwest United States. J Hydrol 14:150–166. https://doi.org/10.1016/j.ejrh.2017.11.004

    Article  Google Scholar 

  • Ahmadi M, Ghermezcheshmeh B (2020) Evaluation of error and uncertainty in downscaling SDSM and ANN. Watershed Eng Manag (IJWMSE) 12(1):340–350. https://doi.org/10.22092/ijwmse.2019.108294.1226

    Article  Google Scholar 

  • Ahmed Z, Guha G, Shew A, Alam G (2021) Climate change risk perceptions and agricultural adaptation strategies in vulnerable riverine char islands of Bangladesh. Volume 103. Land Use Policy, https://doi.org/10.1016/j.landusepol.2021.105295

  • Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration: guidelines for computing crop water requirements. FAO irrigation and drainage paper No. 56. FAO, Rome.

  • Allen MR, Barros VR, Broome J, Cramer W, Christ R, Church JA, Clarke L, Dahe Q Dasgupta,P, Dubash NK (2014) IPCC fifth assessment synthesis report-climate change 2014 synthesis report. Intergovernmental Panel on Climate Change (IPCC), Geneva

  • Araya A, Kisekka I, Gowda PH, Prasad PVV (2017) Evaluation of water-limited cropping systems in a semi-arid climate using DSSAT-CSM. Agri Syst 150:86–90

    Article  Google Scholar 

  • Ashraf Vaghefi S, Mousavi SJ, Abbaspour KC, Srinivasan R, Yang H (2014) Analyses of the impact of climate change on water resources components, drought and wheat yield in semiarid regions: Karkheh River Basin in Iran. Hydrol Process 28(4):2018–2032. https://doi.org/10.1002/hyp.9747

    Article  Google Scholar 

  • Babel MS, Agarwal A, Swain DK, Herath S (2011) Evaluation of climate change impacts and adaptation measures for rice cultivation in Northeast Thailand. Clim Res 46(2):137–146. https://doi.org/10.3354/cr00978

    Article  Google Scholar 

  • Bajus P, Mraz M, Rigo I, Findura P, Fürstenzeller A, Kielbasa P, Malaga-Tobola U (2019) The influence of drying temperature and moisture of corn seeds planted on their damage. Agric Engin 23(1):5–12. https://doi.org/10.1515/agriceng-2019-0001

    Article  Google Scholar 

  • Basak JK, Ashraf Ali M, Nazrol Islam Md, Abdur Rashid Md (2010) Assessment of the effect of climate change on boro rice production in Bangladesh using DSSAT model. J Civ Eng 38(2):95–108

    Google Scholar 

  • Bates B, Kundzewicz ZW (2008) Climate change and water. Technical paper of the intergovernmental panel on climate change. IPCC Secretariat, Geneva, p 210

  • Belder P, Bouman B, Cabangon R, Guoan L, Quilang E, Yuanhua L, Spiertz J, Tuong T (2004) Effect of water-saving irrigation on rice yield and water use in typical lowland conditions in Asia. Agric Water Manag 65(3):193–210. https://doi.org/10.1016/j.agwat.2003.09.002

    Article  Google Scholar 

  • Boonwichai S, Shrestha S, Babel MS, Weesakul S, Datta A (2018) Climate change impacts on irrigation water requirements, crop water productivity and rice yield in the Songkhram River Basin. Thailand J Clean Prod 198:1157–1164. https://doi.org/10.1016/j.jclepro.2018.07.146

    Article  Google Scholar 

  • Boonwichai S, Shrestha S, Babel MS, Weesakul S, Datta A (2019) Evaluation of climate change impacts and adaptation strategies on rainfed rice production in Songkhram River Basin. Thailand Sci Total Environ 652:189–201. https://doi.org/10.1016/j.scitotenv.2018.10.201

    Article  Google Scholar 

  • Buddhaboon C, Jintrawet A, Hoogenboom G (2018) Methodology to estimate rice genetic coefficients for the CSM-CERES-Rice model using GENCALC and GLUE genetic coefficient estimators. J Agric Sci 156(4):1–11. https://doi.org/10.1017/S0021859618000527

    Article  Google Scholar 

  • Carpena F (2019) How do droughts impact household food consumption and nutritional intake? A study of rural India. World Dev 122:349–369. https://doi.org/10.1016/j.worlddev.2019.06.005

    Article  Google Scholar 

  • Charles A, Bertrand T, Elodie F, Harry H (2013) Analog downscaling of seasonal rainfall forecasts in the Murray Darling basin. Mon Weather Rev 141:1099–1117. https://doi.org/10.1175/MWR-D-12-00098.1

    Article  Google Scholar 

  • Chen Sh, Gong B (2020) Response and adaptation of agriculture to climate change: evidence from China. J Dev Econ 102557. https://doi.org/10.1016/j.jdeveco.2020.102557

  • Cheng H, Shu K, Zhu T, Wang L, Liu X, Cai W, Qi Z, Feng S (2022) Effects of alternate wetting and drying irrigation on yield, water and nitrogen use, and greenhouse gas emissions in rice paddy fields. J Clean Prod 349. https://doi.org/10.1016/j.jclepro.2022.131487

  • Chylek P, Li J, Dubey MK, Wang M, Lesins G (2011) Observed and model simulated 20th century Arctic temperature variability: Canadian Earth System Model CanESM2. Atmos Chem Phys 11:22893–22907. https://doi.org/10.5194/acpd-11-22893-2011

    Article  Google Scholar 

  • Darand M, Hamidi S (2021) Projected changes in Iran temperature based on different scenarios RCP. Nat Hazards 10(28):86–106 (In Persian)

    Google Scholar 

  • Darzi-Naftchali A, Karandish F (2016) Rice cultivation management in Mazandaran province in the conditions of climate change. Agric Water Manag 30(2):334–346

    Google Scholar 

  • Darzi-Naftchali A, Karandish F (2017) Adapting rice production to climate change for sustainable blue water consumption: an economic and virtual water analysis. Theor Appl Climatol 135(1):1–12. https://doi.org/10.1007/s00704-017-2355-7

    Article  Google Scholar 

  • Dharmarathna W, Herath S, Weerakoon SB (2014) Changing the planting date as a climate change adaptation strategy for rice production in Kurunegala district, Sri Lanka. Sustain Sci 9:103–111. https://doi.org/10.1007/s11625-012-0192-2

    Article  Google Scholar 

  • Dien DC, Mochizuki T, Yamakawa T (2019) Effect of various drought stresses and subsequent recovery on proline, total soluble sugar and starch metabolisms in Rice (Oryza sativa L.) varieties. Plant Prod Sci 22(4):530–545. https://ojs.nassg.org/index.php/rwae

  • Doulabian Sh, Golian S, Shadmehri Toosi A, Murphy C (2021) Evaluating the effects of climate change on precipitation and temperature for Iran uses RCP scenarios. J Water Clim Change 12(1):166–184. https://doi.org/10.2166/wcc.2020.114

    Article  Google Scholar 

  • Emediegwu L, Wossink A, Hall A (2022) The impacts of climate change on agriculture in sub-Saharan Africa: a spatial panel data approach. World Dev 158. https://doi.org/10.1016/j.worlddev.2022.105967

  • English MJ, Musick JT, Murty VVN (1990) Deficit irrigation: management of farm irrigation systems (Hoffman, G.J., Howell, T.A., and Solomon, K.H., Editors). ASAE Monograph no. 9. American Society of Agricultural Engineers publisher, 1020p.

  • Fageria NK, Baligar VC, Jones CA (1997) Growth and mineral nutrition of field crops, 2nd edn. Marcel Dekker, New York

    Google Scholar 

  • Feliciano D, Recha J, Ambaw G, MacSween K, Solomon D, Wollenberg E (2022) Assessment of agricultural emissions, climate change mitigation and adaptation practices in Ethiopia. Clim Policy:1–18. https://doi.org/10.1080/14693062.2022.2028597

  • Gholizade H, Ebadzadeh H, Hatami F, Hosseinpour R (2014) Crop Statistics, Ministry of Agriculture, Deputy of Planning Economical, Information and Communication Technology Center (In Persian).

  • Giorgi F, Mearns LO (1991) Approaches to the simulation of regional climate change: a review. Rev Geophys 29:191–216. https://doi.org/10.1029/90RG02636

    Article  Google Scholar 

  • Guo Y, Wu W, Du M, Liu X, Wang J, Bryant CR (2019) Modeling climate change impacts on rice growth and yield under global warming of 1.5°C and 2.0°C in the Pearl River delta. China. Atmosphere 10(10):567. https://doi.org/10.3390/atmos10100567

    Article  Google Scholar 

  • Hasheminia SM (2004) Water management in agriculture, First Edition, Ferdowsi University of Mashhad Press, 533 p.

  • Hessami M, Gachon P, Quarda TBMJ, St-Hilaire A (2008) Automated regression based statistical downscaling tool. Environ Model Softw 23(6):813–834

    Article  Google Scholar 

  • Hoogenboom G, CH Porter, KJ Boote, V Shelia, PW Wilkens, U Singh, JW White, S Asseng, JI Lizaso, LP Moreno, W Pavan, R Ogoshi, LA Hunt, GY Tsuji, JW Jones (2019a) The DSSAT crop modeling ecosystem. In: p.173–216 [K.J. Boote, editor] Advances in crop modeling for a sustainable agriculture. Burleigh Dodds Science Publishing, Cambridge, United Kingdom. https://doi.org/10.19103/AS.2019a.0061.10

  • Hoogenboom G, CH Porter, V Shelia, KJ Boote, U Singh, JW White, LA Hunt, R Ogoshi, JI Lizaso, J Koo, S Asseng, A Singels, LP Moreno, JW Jones (2019b) Decision Support System for Agrotechnology Transfer (DSSAT) Version 4.7.5. DSSAT Foundation, Gainesville, Florida. https://DSSAT.net

  • Hunt LA, Pararajasingham S, Jones JW, Hoogenboom G, Imamura DT, Ogoshi RM (1993) SOFTWARE GENCALC: software to facilitate the use of crop models for analyzing field experiment. J Agron 85:1090–1094

    Article  Google Scholar 

  • Huo ZY, Gu HY, Ma Q, Yang X, Li M, Li GY, Dai QG, Xu K, Wei HY, Gao H, Lu Y, Zhang HC (2012) Differences of nitrogen absorption and utilization in rice varieties with different productivity levels. Acta Agron Sinica 38:2061–2068

    Article  Google Scholar 

  • IPCC (2021) Climate Change 2021: the physical science basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, In press, https://doi.org/10.1017/9781009157896.

  • Jones JW, Hoogenboom G, Porter CH, Boote KJ, Batchelor WD, Hunt LA, Wilkens PW, Singh U, Gijsman AJ, Ritchie JT (2003) The DSSAT cropping system model. Eur J Agron 18(3–4):235–265

    Article  Google Scholar 

  • Kapela K, Sikorska A, Niewęgłowski M, Krasnodębska E, Zarzecka K, Gugała M (2020) The impact of nitrogen fertilization and the use of bio stimulants on the yield of two maize varieties (Zea mays L.) cultivated for grain. Agronomy 10(9):1408. https://doi.org/10.3390/agronomy10091408

    Article  Google Scholar 

  • Kenzie RM (1998) Crop nutrition and fertiliser requirements. Food and Rural Development, Lethbridge.

  • Lotfirad M, Adib A, Salehpoor J, Ashrafzadeh A, Kisi O (2021) Simulation of the impact of climate change on runoff and drought in an arid and semiarid basin (the Hablehroud, Iran). Appl Water Sci 11(168):1–24. https://doi.org/10.1007/s13201-021-01494-2

    Article  Google Scholar 

  • Maneepitak S, Ullah H, Paothong K, Kachenchart B, Datta A, Shrestha R (2019) Effect of water and rice straw management practices on yield and water productivity of irrigated lowland rice in the Central Plain of Thailand. Agric Water Manag 211:89–97. https://doi.org/10.1016/j.agwat.2018.09.041

    Article  Google Scholar 

  • Meinshausen M, Smith SJ, Calvin KV, Daniel JS, Kainuma MLT, Lamarque JF, Matsumoto K, Montzka SA, Raper SCB, Riahi K, Thomson AM, Velders GJM, van Vuuren D (2011) The RCP greenhouse gas concentrations and their extension from 1765 to 2300. Clim Change (special Issue). https://doi.org/10.1007/s10584-011-0156-z

    Article  Google Scholar 

  • Mekonnen MM, Hoekstra AY (2011) The green, blue and grey water footprint of crops and derived crop products. Hydrol Earth Syst Sci 15:1577–1600. https://doi.org/10.5194/hess-15-1577-2011

    Article  Google Scholar 

  • Mirfenderski R, Darzi-Naftchali A, Karandish F (2022) Climate-resilient agricultural water management to alleviate negative impacts of global warming in rice production systems. Theor Appl Climatol 147:409–422. https://doi.org/10.1007/s00704-021-03813-8

    Article  Google Scholar 

  • Moriasi DN, Arnold JG, Van Liew MW, Bingner RL, Harmel RD, Veith TL (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans ASABE 50(3):885–900

    Article  Google Scholar 

  • Moss RH, Edmonds JA, Hibbard KA, Manning MR, Rose SK, Van vuuren DP, Carter TR, Emori S, Kainuma M, Kram T, Meehl GA, Mitchell JFB, Nakicenovic N, Riahi K, Smith SJ, Stouffer RJ, Thomson AM, Weyant JP, Wilbanks TJ (2010) The next generation of scenarios for climate change research and assessment. Nature 463:747–756. https://doi.org/10.1038/nature08823

    Article  Google Scholar 

  • Nasir IR, Rasul F, Ahmad A, Asghar HN, Hoogenboom G (2020) Climate change impacts and adaptations for fine, coarse, and hybrid rice using CERES-Rice. Environ Sci Pollut Res 27:9454–9464. https://doi.org/10.1007/s11356-019-07080-z

    Article  Google Scholar 

  • Nicolas F, Migliaccio KW, Hoogenboom G, Rathinasabapathi BR, Eisenstadt WR (2020) Assessing the potential impact of climate change on rice yield in the Artibonite valley of Haiti using the CSM-CERES-RICE model. Am Soc Agric Biol Eng (ASABE) 63(5):1385–1400. https://doi.org/10.13031/trans.13868

    Article  Google Scholar 

  • Nikbakht Shahbazi AR (2019) Investigation of crop evapotranspiration and precipitation changes under climate change RCPs scenarios in Khouzestan province. J Water Soil Conserv 25(6):123–139 (In Persian)

    Google Scholar 

  • Palazzo A, Vervoort JM, Mason-D’Croz D, Rutting L, Havlík P, Islam S, Bayala J, Valin H, Kadi HAK, Thornton P, Zougmore R (2017) Linking regional stakeholder scenarios and shared socioeconomic pathways: quantified west African food and climate futures in a global context. Global Environ Change 45:227e242. https://doi.org/10.1016/j.gloenvcha.2016.12.002

    Article  Google Scholar 

  • Prasad S, Singh MP, Yadav RK (2012) Physio-chemical changes in rice varieties under drought stress condition. Plant Archives 12:63–66

    Google Scholar 

  • Prescott J (1940) Evaporation from a water surface in relation to solar radiation. Trans R Soc S Aust 64(1):114–118

    Google Scholar 

  • Priestley CHB, Taylor RJ (1972) On the assessment of surface heat flux and evaporation using large-scale parameters. Mon Weather Rev 100(2):81–92. https://doi.org/10.1175/1520-0493(1972)100%3c0081:OTAOSH%3e2.3.CO;2

    Article  Google Scholar 

  • Rezaei M, Asadi R (2013) The effect of using saline water under drought stress on rice yield. Final Project Report. National Rice Research Institute (In Persian).

  • Rutten M, Dijk M, Rooij W, Hilderink H (2014) Land use dynamics, climate change, and food security in Vietnam: a global-to-local modeling approach. World Dev 59:29e46. https://doi.org/10.1016/j.worlddev.2014.01.020

    Article  Google Scholar 

  • Sahebi M, Hanafi MM, Rafii MY, Mahmud TMM, Azizi P, Osman M, Miah G (2018) Improvement of drought tolerance in rice (Oryza sativa L.): genetics, genomic tools, and the WRKY gene family. BioMed Res. Int. 2018: 3158474. [CrossRef] [PubMed]. https://doi.org/10.1155/2018/3158474

  • Shi W, Wang M, Liu Y (2020) Crop yield and production responses to climate disasters in China. Sci Total Environ 750. https://doi.org/10.1016/j.scitotenv.2020.141147

  • Sakoda K, Taniyoshi K, Wamori W, Tanaka Y (2021) Drought stress reduces crop carbon gain due to delayed photosynthetic induction under fluctuating light conditions. Genet Resour Crop Evol 174(1):1–15. https://doi.org/10.1111/ppl.13603

    Article  Google Scholar 

  • Sheidaeian M, Ziatabar Ahmadi MKh, Fazloula R (2015) Study on climate change effect on net irrigation requirement and yield for rice crop (case study: Tajan Plain). Journal of Water and Soil 28(6):1284–1297

    Google Scholar 

  • Shrestha S, Deb P, Bui TTT (2014) Adaptation strategies for rice cultivation under climate change in Central Vietnam. Mitig Adapt Strateg Glob Change 21(1):15–37. https://doi.org/10.1007/s11027-014-9567-2

    Article  Google Scholar 

  • Soler CMT, Sentelhas PC, Hoogenboom G (2007) Application of the CSM-CERES-Maize model for planting date evaluation and yield forecasting for maize grown off-season in a subtropical environment. Eur J Agron 27(2–4):165–177. https://doi.org/10.1016/j.eja.2007.03.002

    Article  Google Scholar 

  • Swain DK, Yadav A (2009) Simulating the impact of climate change on rice yield using CERES-Rice model. J Environ Inform 13(2):104–110. https://doi.org/10.3808/jei.200900145

    Article  Google Scholar 

  • Tayefeh M, Sadeghi SM, Noorhosseini SA, Bacenetti J, Damalas CA (2018) Environmental impact of rice production based on nitrogen fertilizer use. Environ Sci Pollut Res 25:15885–15895. https://doi.org/10.1007/s11356-018-1788-6

    Article  Google Scholar 

  • Taylor KE, Stouffer RJ, Meehl GA (2009) A summary of the CMIP5 experiment design. CMIP Report, p 30

  • Thiemig V, Rojas R, Zambrano-Bigiarini M, De Roo A (2013) Hydrological evaluation of satellite-based rainfall estimates over the Volta and Baro-Akobo Basin. J Hydrol 499:324–338. https://doi.org/10.1016/j.jhydrol.2013.07.012

    Article  Google Scholar 

  • USDA (2021) US Department of Agriculture. https://ipad.fas.usda.gov/countrysummary/Default.aspx?id=IR&crop=Rice

  • Wilby RL (1999) The weather generation game: a review of stochastic weather models. Prog Phys Geogr 23(3):329–357. https://doi.org/10.1177/030913339902300302

    Article  Google Scholar 

  • Wilby RL, Dawson CW (2007) SDSM 4.2 a decision support tool for the assessment of regional climate change impacts, user manual.

  • Wu L, Yuan S, Huang L, Sun F, Zhu G, Li G, Fahad S, Peng S, Wang F (2016) Physiological mechanisms underlying the high-grain yield and high-nitrogen use efficiency of elite rice varieties under a low rate of nitrogen application in China. Front Plant Sci 7:1024. https://doi.org/10.3389/fpls.2016.01024

    Article  Google Scholar 

  • Yadav MK, Singh R, Singh K, Mall R, Patel C, Yadav S, Singh M (2015) Assessment of climate change impact on productivity of different cereal crops in Varanasi. India J Agrometeorol 17(2):179–184. https://doi.org/10.54386/jam.v17i2.1000

    Article  Google Scholar 

  • Yan D, Zhu Y, Wang S, Cao W (2006) A quantitative knowledge-based model for designing suitable growth dynamics in rice. Plant Prod Sci 9(2):93–105. https://doi.org/10.1626/pps.9.93

    Article  Google Scholar 

  • Yarmohammadi S, Zakerinia M, Ghorbani KH, Soltani A (2017) Investigation of the effect of climate change on evapotranspiration and wheat water requirement in Bojnord region. J Water Res Eng 10(35):97–110 (In Persian)

    Google Scholar 

  • Yousefian M (2018) Investigation of the effects of partial root zoon drying and regulated deficit irrigation on water productivity, methane emission and some physiological traits of rice (Hashemi cultivar). Dissertation, Sari Agricultural Sciences and Natural Resources University (In Persian)

  • Zhang Z, Zhang S, Yang J, Zhang J (2008) Yield, grain quality and water use efficiency of rice under non-flooded mulching cultivation. Field Crops Res 108(1):71–81. https://doi.org/10.1016/j.fcr.2008.03.004

    Article  Google Scholar 

  • Zhang L, Zhang Z, Tao F, Luo Y, Zhang J, Cao J (2022) Adapting to climate change precisely through cultivars renewal for rice production across China: when, where, and what cultivars will be required? Agric For Meteorol 316. https://doi.org/10.1016/j.agrformet.2022.108856

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Authors and Affiliations

  1. Water Engineering Department, Sari Agricultural Sciences and Natural Resources University, Sari, Iran

    Dorsa Darikandeh

  2. Faculty of Agriculture, Water Engineering Department, Sari Agricultural Sciences and Natural Resources University, P.O. Box 578, Sari, Iran

    Ali Shahnazari & Mojtaba Khoshravesh

  3. Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL, 32611-0570, USA

    Gerrit Hoogenboom

  4. Food Systems Institute, University of Florida, Gainesville, FL, 32611-0570, USA

    Gerrit Hoogenboom

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Contributions

Dorsa Darikandeh wrote the manuscript with support from Ali Shahnazari, Mojtaba Khoshravesh and Gerrit Hoogenboom. Ali Shahnazari and Mojtaba Khoshravesh supervised the project and Gerrit Hoogenboom advised the project. Gerrit Hoogenboom aided in interpreting the results from CSM-CERES-Rice model and helped shape the research process, both in terms of content, as well as its impact. All authors provided critical feedback and commented on the final version of the manuscript.

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Correspondence to Ali Shahnazari.

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Darikandeh, D., Shahnazari, A., Khoshravesh, M. et al. Evaluating rice yield and adaptation strategies under climate change based on the CSM-CERES-Rice model: a case study for northern Iran. Theor Appl Climatol 151, 967–986 (2023). https://doi.org/10.1007/s00704-022-04188-0

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