بررسی سازگاری جو آبی در استان‌های همدان و لرستان با شرایط تغییر اقلیم

Ahmadi H, Ghalhari GF and Baaghideh, M. 2019a. Impacts of climate change on apple tree cultivation areas in Iran. Climatic Change, 153 (1): 91-103. https://doi.org/10.1007/s10584-018-2316-x

Ahmadi M, Dadashi Roudbari A, Akbari Azirani, T and Karami J. 2019b. The Performance of the HadGEM2-ES Model in the Evaluation of Seasonal Temperature Anomaly of Iran under RCP scenarios. Journal of the Earth and Space Physics, 45 (3): 625-644. https://doi.org/10.22059/JESPHYS.2019.279480.1007109 (In Persian with English abstract).

Almorox J, Benito M and Hontoria C. 2005. Estimation of monthly Angstrom–Prescott equation coefficients from measured daily data in Toledo, Spain. Renewable Energy, 30: 931–936. https://doi.org/10.1016/j.renene.2004.08.002

Amiri S, Eyni-Nargeseh H, Rahimi-Moghaddam S and Azizi K. 2021. Water use efficiency of chickpea agro-ecosystems will be boosted by positive effects of CO2 and using suitable genotype× environment× management under climate change conditions. Agricultural Water Management, 252: 106928. https://doi.org/10.1016/j.agwat.2021.106928

Anonymous, 2017. Lorestan province crop statistics, Agricultural Jihad Organization of Lorestan Province. (In Persian with English abstract).

Archontoulis SV, Miguez FE and Moore KJ. 2014. Evaluating APSIM maize, soil water, soil nitrogen, manure, and soil temperature modules in the Midwestern United States. Agronomy Journal, 106 (3): 1025–1040. https://doi.org/10.2134/agronj2013.0421

Attri SD and Rathore LS. 2003. Simulation of impact of projected climate change on wheat in India. International Journal of Climatology, 23: 693–705. https://doi.org/10.1002/joc.896

Bento VA, Ribeiro AF, Russo A, Gouveia CM, Cardoso RM and Soares PM. 2021. The impact of climate change in wheat and barley yields in the Iberian Peninsula. Scientific reports, 11 (1): 15484. https://doi.org/10.1038/s41598-021-95014-6

Callens C, Fernandez-Goméz J, Tucker MR, Zhang D and Wilson ZA. 2023. Heat stress responses vary during floret development in European spring barley cultivars. Frontiers in Plant Science, 13: 918730. https://doi.org/10.3389/fpls.2022.918730

Chen CQ, Qian CR, Deng AX and Zhang WJ. 2012. Progressive and active adaptations of cropping system to climate change in Northeast China. European Journal of Agronomy, 38: 94–103. https://doi.org/10.1016/j.eja.2011.07.003

Chenu K, Deihimfard R and Chapman SC. 2013. Large-scale characterization of drought pattern: a continent-wide modelling approach applied to the Australian wheatbelt–spatial and temporal trends. New Phytologist, 198 (3): 801–820. https://doi.org/10.1111/nph.12192

Deihimfard R, Rahimi-Moghaddam S and Chenu K. 2019. Risk assessment of frost damage to sugar beet simulated under cold and semi-arid environments. International Journal of Biometeorology, 63: 511-521. https://doi.org/10.1007/s00484-019-01682-5

Deihimfard R, Rahimi-Moghaddam S, Eyni-Nargeseh H and Collins B. 2023a. An optimal combination of sowing date and cultivar could mitigate the impact of simultaneous heat and drought on rainfed wheat in arid regions. European Journal of Agronomy, 147: 126848. https://doi.org/10.1016/j.eja.2023.126848

Deihimfard R, Rahimi-Moghaddam S, Javanshir F and Pazoki A. 2023b. Quantifying major sources of uncertainty in projecting the impact of climate change on wheat grain yield in dryland environments. Journal of Arid Land, 15: 545–561. https://doi.org/10.1007/s40333-023-0056-x

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 (1): 179–188. https://doi.org/10.1016/j.fcr.2010.09.008

Dietzel R, Liebman M, Ewing R, Helmers M, Horton R, Jarchow M and Archontoulis S. 2016. How efficiently do corn-and soybean-based cropping systems use water? A systems modeling analysis. Global Change Biology, 22: 666-681. https://doi.org/10.1111/gcb.13101

Ejaz M and von Korff M. 2017. The genetic control of reproductive development under high ambient temperature. Plant Physiology, 173: 294–306. https://doi.org/10.1104/pp.16.01275

Gao Z, Feng HY, Liang XG, Zhang L, Lin S, Zhao X, Shen S, Zhou LL and Zhou SL. 2018. Limits to maize productivity in the North China Plain: A comparison analysis for spring and summer maize. Field Crops Research, 228: 39–47. https://doi.org/10.1016/j.fcr.2018.08.022

Gaydon DS, Wang E, Poulton PL, Ahmad B, Ahmed F, Akhter S, Ali I, Amarasingha RP, Chaki AK, Chen C and Choudhury BU. 2017. Evaluation of the APSIM model in cropping systems of Asia. Field Crops Research, 204: 52-75. https://doi.org/10.1016/j.fcr.2016.12.015

Ghahreman N, Tabatabaei M and Babaeian I. 2015. Investigation of uncertainty in the IPCC AR5 precipitation and temperature projection over Iran under RCP Scenarios. Investigation of uncertainty in the IPCC AR5 precipitation and temperature projection over Iran under RCP Scenarios. In: Proceedings of Common Future under Climate Change, 7-10 Jul., Paris, France.

Gong DP and Gong WL. 2020. Impacts of Climate Change on Maize Production in Northeast China and Countermeasures. Journal of Agriculture, 10: 35–38. https://doi.org/10.3389/fenvs.2022.954940

Hemming MN, Walford SA, Fieg S, Dennis ES and Trevaskis B. 2012. Identification of high temperature-responsive genes in cereals. Plant Physiology, 158: 1439-1450. https://doi.org/10.1104/pp.111.192013

Holzworth DP, Huth NI, deVoil PG, Zurcher EJ, Herrmann NI, McLean G, Chenu K, van Oosterom EJ, Snow V, Murphy C and Moore AD. 2014. APSIM–evolution towards a new generation of agricultural systems simulation. Environmental Modelling & Software, 62: 327-350. https://doi.org/10.1016/j.envsoft.2014.07.009

Ji RP, Zhang YS, Jiang LX, Zhang SJ, Feng R, Chen PS, Wu, JW and Mi N. 2012. Effect of climate change on maize production in Northeast China. Geographical Research, 31: 290–298. https://doi.org/10.1016/j.apcbee.2014.01.073

Keating BA, Carberry PS, Hammer GL, Probert ME, Robertson MJ, Holzworth D, Huth NI, Hargreaves JN, Meinke H, Hochman Z and McLean G. 2003. An overview of APSIM, a model designed for farming systems simulation. European Journal of Agronomy, 18(3-4): 267-288. https://doi.org/10.1016/S1161-0301(02)00108-9

Lee JY, Marotzke J, Bala G, Cao L, Corti S, Dunne JP, Engelbrecht F, Fischer E, Fyfe JC, Jones C, Maycock A,  Mutemi J, Ndiaye O, Panickal S and Zhou E. 2021: Future Global Climate: Scenario-Based Projections and NearTerm Information. In 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, Zhai P, Pirani A, Connors SL, Péan C, Berger S, Caud N, Chen Y, Goldfarb L, Gomis MI, Huang M, Leitzell K, Lonnoy E, Matthews JBR, Maycock TK, Waterfield T, Yelekçi O, Yu R and Zhou B (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 553–672, https://doi.org/10.1017/9781009157896.006.

Liu Z, Hubbard KG, Lin X and Yang X. 2013. Negative effects of climate warming on maize yield are reversed by the changing of sowing date and cultivar selection in Northeast China. Global Change Biology, 19 (11): 3481-3492. https://doi.org/10.1111/gcb.12324

Liu Z, Yang X, Xie R, Lin X, Li T, Batchelor WD, Zhao J, Zhang Z, Sun S and Zhang F. 2021. Prolongation of the grain filling period and change in radiation simultaneously increased maize yields in China. Agricultural and Forest Meteorology, 308–309: 108573. https://doi.org/10.1016/j.agrformet.2021.108573

Mendenhall W, Sincich T and Boudreau NS. 1996. A second course in statistics: regression analysis. Prentice Hall Upper Saddle River, New Jersey.

Moghaddam H, Oveisi M, Mehr MK, Bazrafshan J, Naeimi MH, Kaleibar BP and Müller-Schärer H. 2023. Earlier sowing combined with nitrogen fertilization to adapt to climate change effects on yield of winter wheat in arid environments: Results from a field and modeling study. European Journal of Agronomy, 146: 126825. https://doi.org/10.1016/j.eja.2023.126825

Rahimi-Moghaddam S and Azizi K. 2018. Early sowing date as a strategy for improvement of maize yield and maize physiological and phonological characteristics in climate change conditions at Kermanshah Province. Journal of Crop Production, 10 (4): 91-105. https://doi.org/10.22069/EJCP.2018.12078.1930 (In Persian with English abstract).

Rahimi-Moghaddam S, Dehimfard R, Azizi K and Roostei M. 2021. Characterizing spatial and temporal trends in drought patterns of rainfed wheat (Triticum aestivum L.) across various climatic conditions: a modelling approach. European Journal of Agronomy, 129: 126333. https://doi.org/10.1016/j.eja.2021.126333

Seifert E. 2014. OriginPro 9.1: Scientific Data Analysis and Graphing Software—Software Review. Journal of Chemical Information and Modeling, 54 (5): 1552–1552. https://doi.org/10.1021/ci500161d

Valizadeh J, Ziaei SM and Mazloumzadeh SM. 2014. Assessing climate change impacts on wheat production (a case study). Journal of the Saudi Society of Agricultural Sciences, 13(2): 107-115. https://doi.org/10.1016/j.jssas.2013.02.002

Wallach D and Goffinet B. 1987. Mean squared error of prediction in models for studying economic and agricultural systems. Biometrics, 43: 561–576. https://doi.org/10.2307/2531995

Willmott CJ and Matsuura K. 2005. Advantages of the mean absolute error (MAE) over theroot mean square error (RMSE) in assessing average model performance. Climate Research, 30: 79–82. https://doi.org/10.3354/cr030079

 Willmott CJ. 1982. Some comments on the evaluation of model performance. Bulletin of the American Meteorological Society, 63: 1309–1313. https://doi.org/10.1175/15200477(1982)063%3C 1309:SCOTEO%3E2.0.CO;2