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Climate change impact on precipitation and cardinal temperatures in different climatic zones in Iran: analyzing the probable effects on cereal water-use efficiency

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Abstract

Global greenhouse gases increase could be a threat to sustainable agriculture since it might affect both green water and air temperature. Using the outputs of 15 general circulation models (GCMs) under three SRES scenarios of A1B, A2 and B1, the projected annual and seasonal precipitation (P) and cardinal temperatures (T) were analyzed for five climatic zones in Iran. In addition, the probable effects of climate change on cereal production were studied using AquaCrop model. Data obtained from the GCMs were downscaled using LARS-WG for 52 synoptic stations up to 2100. An uncertainty analysis was done for the projected P and T associated to GCMs and SRES scenarios. Based on station observations, LARS-WG was capable enough for simulating both P and T for all the climatic zones. The majority of GCMs as well as the median of the ensemble for each scenario project positive P and T changes. In all the climatic zones, wet seasons have a higher P increase than dry seasons, with the highest increase (27.9–83.3%) corresponding to hyper-arid and arid regions. A few GCMs project a P reduction mainly in Mediterranean and hyper-humid climatic regions. The highest increase (11.2–44.5%) in minimum T occurred in Mediterranean climatic regions followed by semi-arid regions in which a concurrent increase in maximum T (2.9–14.6%) occurred. The largest uncertainty in P and cardinal T projection occurred in rainy seasons as well as in hyper-humid regions. The AquaCrop simulation results revealed that the increased cardinal T under global warming will cause 0–28.5% increase in cereal water requirement as well as 0–15% reduction in crop yield leading to 0–30% reduction in water use efficiency in 95% of the country.

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References

  • Abahussain AA, Abdu AS, Al-Zubari WK, El-Deen NA, Raheen MA (2002) Desertification, in the Arab region: analysis of current status and trends. J Arid Environ 51:521–545

    Article  Google Scholar 

  • Abbaspour CK, Faramarzi M, Seyed Ghasemi S, Yong H (2009) Assessing the impact of climate change on water resources in Iran. Water Res 45:1–16

    Google Scholar 

  • Agarwal A, Babel MS, Maskey SH (2014) Analysis of future precipitation in the Koshi river basin, Nepal. J Hydrol 513:422–434

    Article  Google Scholar 

  • Aldaya M, Allan J, Hoekstra A (2010) Strategic importance of green water in international crop trade. Ecol Econ 69:887–894

    Article  Google Scholar 

  • Alizade A, Sayyari N, Hesami Kermani MR, Banayan Avval M, Farid Hosseini E (2010) Assessment of effects of climate change on water resources and agriculture water using water. Soil J 24:815–835

    Google Scholar 

  • Almasi P, Soltani S (2016) Assessment of the climate change impacts on flood frequency. Stoch Environ Res Risk Assess. doi:10.1007/s00477-016-1263-1

    Google Scholar 

  • Azarakhshi M, Farzadmehr J, Eslah M, Sahabi H (2013) An investigation trends of annual and seasonal rainfall and temperature in different climatologically regions of Iran. J Range Watershed Manag 66(1):1–16

    Google Scholar 

  • Baker JT, Allen LH (1993) Contrasting crop species responses to CO2 and temperature: rice, soybean, and citrus. Vegetatio 104(105):239–260

    Article  Google Scholar 

  • CCSP (2008) Climate models: an assessment of strengths and limitations. In: A Report by the U.S. Climate Change Science Program and the Subcommittee on Global Change Research. Department of Energy, Office of Biological and Environmental Research, Washington, DC

  • Chen J, Brissette FP, Leconte R (2011) Uncertainty of downscaling method in quantifying the impact of climate change on hydrology. J Hydrol 401:190–202

    Article  Google Scholar 

  • Chen H, Gue J, Zhang Z, Xu CY (2013) Prediction of temperature and precipitation in Sudan and South Sudan by using LARS-WG in future. Theor Appl Climatol 113:363–375

    Article  Google Scholar 

  • Christensen J, Hewitson B, Busuioc A, Chen A, Gao X, Held I, Jones R, Kolli R, Kwon WT, Laprise R, Rueda VM, Mearns L, Menéndez C, Räisänen J, Rinke A, Sarr A, Whetton P (2007) Regional climate projections. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Climate change 2007: the physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, UK

  • Commuri PD, Jones RD (2001) High temperatures during endosperm cell division in maize: a genotypic comparison under in vitro and field conditions. Crop Sci 41:1122–1130

    Article  Google Scholar 

  • Dastorani MT, Poormohammadi S (2012) Evaluation of the effects of climate change on temperature, precipitation and evapotranspiration in Iran. In: International Conference on Applied Life Sciences, Turkey, 2012, pp 73–79

  • Enete AA, Amusa TA (2010) Challenges of agricultural adaptation to climate change in Nigeria: a synthesis from the literature, Field Actions Science Reports. http://factsreports.revues.org/678

  • Etemadi H, Samadi SZ, Sharifikia M (2012) Statistical downscaling of climatic variables in Shadegan Wetland Iran. Earth Sci Clim Chang 1:508. doi:10.4172/scientificreports.508

    Google Scholar 

  • Etemadi H, Samadi S, Sharifikia M (2014) Uncertainty analysis of statistical downscaling models using general circulation model over an international wetland. Clim Dyn 42:2899–2920

    Article  Google Scholar 

  • Evans J, Geerken R (2004) Discrimination between climate and human-induced dryland degradation. J Arid Environ 57:535–554

    Article  Google Scholar 

  • FAO (2012) AquaCrop reference manual. FAO, Land and Water Division Rome, Italy

    Google Scholar 

  • Fowler HJ, Blenkinsop S, Tebaldi C (2007) Linking climate change modeling to impact studies: recent advances in downscaling techniques of hydrological modeling. Int J Climatol 27:1547–1578

    Article  Google Scholar 

  • Ghahraman B (2006) Time trend in the mean annual temperature of Iran. Turk J Agric For 30:439–448

    Google Scholar 

  • Gil-Alana LA (2012) Long memory, seasonality and time trends in the average monthly temperatures in Alaska. Theor Appl Climatol 108:385–396

    Article  Google Scholar 

  • Girvetz EH, Zganjar C, Raber GT, Maurer EP, Kareiva P (2009) Applied climate-change analysis: the climate wizard tool. PLoS ONE 4(12):e8320. doi:10.1371/journal.pone.0008320

    Article  Google Scholar 

  • Goodarzi E, Dastorani M, Massah Bavani A, Talebi A (2015) Evaluation of the change-factor and LARS-WG methods of downscaling for simulation of climatic variables in the future (case study: Herat Azam Watershed, Yazd—Iran). Ecopersia 3(1):833–846

    Google Scholar 

  • Goyal RK (2004) Sensitivity of evapotranspiration to global warming: a case study of arid zone of Rajasthan (India). Agric Water Manag 69:1–11

    Article  Google Scholar 

  • Hamdi MR, Abu-Allaban M, Al-Shayeb A, Jaber M, Momani NM (2009) Climate change in Jordan: a comprehensive examination approach. Am J Environ Sci 5(1):58–68

    Article  Google Scholar 

  • Hashmi MZ, Shamseldin AY, Melville BW (2011) Comparison of SDSM and LARS-WG for simulation and downscaling of extreme precipitation events in a watershed. Stoch Environ Res Risk Assess 25:475–484

    Article  Google Scholar 

  • Haskett JD, Pachepsky YA, Acock B (2000) Effect of climate and atmospheric change on soybean water stress: a study of Iowa. Ecol Model 135(2–3):265–277

    Article  CAS  Google Scholar 

  • Hewitson BC, Crane RG (1996) Climate downscaling: techniques and application. Clim Res 7:85–95

    Article  Google Scholar 

  • IPCC (2007) Summary for policymakers. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) In climate change 2007: the physical science basis. Contribution ofWorking Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK

  • Karandish F (2016) Improved soil-plant water dynamics and economic water use efficiency in a maize field under locally water stress. Arch Agron Soil Sci 62(9):1311–1323

    Article  Google Scholar 

  • Karandish F, Kalanaki M, Saberali SF (2016) Projected impacts of global warming on cropping calendar and water requirement of maize in a humid climate. Arch Agron Soil Sci. doi:10.1080/03650340.2016.1177176

    Google Scholar 

  • Kazemi-Rad L, Mohammadi H (2015) Climate change assessment in Gilan Province, Iran. Int J Agric Crop Sci 8(2):86–93

    Google Scholar 

  • Kendall MG (1975) Rank correlation methods. Griffin, London.

    Google Scholar 

  • Klocke NL, Schneekloth JP, Melvin S, Clark RT, Payero JO (2004) Field scale limited irrigation scenarios for water policy strategies. Appl Eng Agric 20:623–631

    Article  Google Scholar 

  • Knutti R, Stocker TF, Joos F, Plattner GK (2003) Probabilistic climate change projections using neural networks. Clim Dyn 21:257–272

    Article  Google Scholar 

  • Konar M, Dalin C, Hanasaki N, Rinaldo A, Rodriguez-Iturbe I (2012) Temporal dynamics of blue and green virtual water trade netweork. Water Resour Res 48:1–11

    Article  Google Scholar 

  • Luo Q (2011) Temperature threshold and crop production: a review. Clim Chang 109:583–598

    Article  Google Scholar 

  • Luo Q (2016) Necessity for post-processing dynamically downscaled climate projections for impact and adaptation studies. Stoch Environ Res Risk Assess. doi:10.1007/s00477-016-1233-7

    Google Scholar 

  • Mann HB (1945) Nonparametric tests against trend. Econometrica 13:245–259

    Article  Google Scholar 

  • Minville M, Brissette F, Leconte R (2008) Uncertainty of the impact of climate change on the hydrology of a nordic watershed. J Hydrol 358:70–83

    Article  Google Scholar 

  • Modarres R, da Silva VPR (2007) Rainfall trends in arid and semi-arid regions of Iran. J Arid Environ 70:344–355

    Article  Google Scholar 

  • Nazemosadat MJ, Samani N, Barry DA, Molaii Niko M (2006) ENSO forcing on climate change in Iran: precipitation analyses. Iran J Sci Technol Trans B 30(B4):47–61

    Google Scholar 

  • Osman Y, Al-Ansari N, Abdellatif M, Aljawad SB, Knutsson S (2014) Expected future precipitation in central Iraq using LARS-WG stochastic weather generator. Engineering 6:948–959

    Article  Google Scholar 

  • Ouyang F, Lu H, Zhu Y, Zhang J, Yu Z, Chen X, Li M (2014) Uncertainty analysis of downscaling methods in assessing the influence of climate change on hydrology. Stoch Environ Res Risk Assess 28:991–1010

    Article  Google Scholar 

  • Partal T, Kahya E (2006) Trend analysis in Turkish precipitation data. Hydrol Process 20:2011–2026

    Article  Google Scholar 

  • Payero JO, Melvin SR, Irmak S, Tarkalson D (2006) Yield response of corn to deficit irrigation in a semiarid climate. Agric Water Manag 84:101–112

    Article  Google Scholar 

  • Peng S, Huang J, Sheehy JE, Lanza RC, Visperas RM, Zhong X, Centeno GS, Khush GS, Cassman KG (2004) Rice yields decline with higher night temperatures from global warming. Proc Natl Acad Sci USA. http://www.pnas.org/cgi/content/full/101/27/9971

  • Peterson TC, Golubev VS, Groisman PY (2002) Evaporation losing its strength. Nature 377:687–688

    Article  Google Scholar 

  • Pradhan GP, Prasad PVV, Fritz AK, Kirkham MB, Gill BS (2012) High temperature tolerance in Aegilops species and its potential transfer to wheat. Crop Sci 52:292–304

    Article  Google Scholar 

  • Randall DA, Wood RA, Bony S, Colman R, Fichefet T, Fyfe J, et al. (2007) Cilmate models and their evaluation. In: Climate change 2007: the physical science basis. Contribution of Working Group I to the ARIV of IPCC. Cambridge University Press, Cambridge, UK

  • Raziei T, Daneshkar Arasteh P, Saghfian B (2005) Annual rainfall trend in arid and semi-arid regions of Iran. In: ICID 21st European Regional Conference, Germany

  • Reddy KS, Kumar M, Maruthi V, Umesha B, Vijayalaxmi, NageswarRao CVK (2014) Climate change analysis in southern Telangana region, Andhra Pradesh using LARS-WG model. Curr Sci India 107(1):54–62

    Google Scholar 

  • Sarker MAR, Alam K, Gow J (2012) Exploring the relationship between climate change and rice yield in Bangladesh: An analysis of time series data. Agricultural System, Elsevier Ltd., pp 11–16

  • Selvaraj IC, Nagarajan P, Thiyagarajan K, Bharathi M, Rabindran R (2011) Genetic parameters of variability, correlation and path coefficient studies for grain yield and other yield attributes among rice blast disease resistant genotypes of rice (Oryza Sativa L.). Afr J Biotechnol 10:3322–3334

    Article  Google Scholar 

  • Semenov MA, Barrow EM (2002) A stochastic weather generator for use in climate impact studies. User’s manual, Version 3.0

  • Semenov MA, Stratonovitch P (2010) Use of multi-model ensembles from global climate models for assessment of climate change impacts. Clim Res 41(1):1–14

    Article  Google Scholar 

  • Sen PK (1968) Estimates of the regression coefficient based on Kendall’s tau. J Am Stat Assoc 63(324):1379–1389

    Article  Google Scholar 

  • Shah NH, Paulsen GM (2003) Interaction of drought and high temperature on photosynthesis and grain-filling of wheat. Plant Soil 257:219–226

    Article  CAS  Google Scholar 

  • Smadi MM (2006) Observed abrupt changes in minimum and maximum temperatures in Jordan in the 20th century. Am J Environ Sci 2(3):114–120

    Article  Google Scholar 

  • Stone LR (2003) Crop water use requirements and water use efficiencies. In: Proceedings of the 15th annual Central Plains Irrigation Conference and Exposition, Colby, Kansas, pp. 127–133

  • Stone PJ, Nicolas ME (1995) Effect of timing of heat stress during grain filling on two wheat varieties differing in heat tolerance. I. Grain growth. Aust J Plant Physiol 22:927–934

    Article  Google Scholar 

  • Tabari H, Talaee Hosseinzadeh P (2011) Temporal variability of precipitation over Iran: 1966–2005. J Hydrol 396(3):313–320

    Article  Google Scholar 

  • Tabari H, Marofi S, Hosseinzadeh Talaee P, Mohammadi K (2011) Trend analysis of reference evapotranspiration in the western half of Iran. Agric For Meteorol 151(2):128–136

    Article  Google Scholar 

  • Tabari H, Hosseinzadeh Talaee P, Mousavi Nadoushani SS, Willems P, Marchetto A (2014) A survey of temperature and precipitation based aridity indices in Iran. Quat Int 345:158–166

    Article  Google Scholar 

  • Tabari H, Taye MT, Willems P (2015) Water availability change in central Belgium for the late 21st century. Glob Planet Chang 131:115–123

    Article  Google Scholar 

  • Ugarte C, Calderini DF, Slafer GA (2007) Grain weight and grain number responsiveness to preanthesis temperature in wheat, barley and triticale. Field Crop Res 100:240–248

    Article  Google Scholar 

  • Vollenweider P, Gunthardt-Goerg MS (2005) Diagnosis of abiotic and biotic stress factors using the visible symptoms in foliage. Environ Pollut 137:455–465

    Article  CAS  Google Scholar 

  • Wahid A, Gelani S, Ashraf M, Foolad MR (2007) Heat tolerance in 1260 plants: an overview. Environ Exp Bot 61:199–223

    Article  Google Scholar 

  • Wheeler TR, Craufurd PQ, Ellis RH, Porter JR, Vara Prasad PV (2000) Temperature variability and the yield of annual crops. Agric Ecosyst Environ 82:159–167

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Wilby RL, Charles SP, Zorita E, Timbal B, Whetton P, Mearns LO (2004) Guidelines for use of climate scenarios developed from statistical downscaling methods. Supporting material of the Intergovernmental Panel on Climate Change, available from the DDC of IPCC TGCIA 27

  • Xing W, Weiguang W, Quanxi S, Shizhang P, Zhongbo Y, Bin Y, John T (2014) Changes of reference evapotranspiration in the Haihe River Basin: present observations and future projection from climatic variables through multi-model ensemble. Glob Planet Chang 115:1–15

    Article  Google Scholar 

  • Xu CY (1999) From GCMs to river flow: a review of downscaling methods and hydrologic modelling approaches. Prog Phys Geogr 23:229–249

    Article  Google Scholar 

  • Yang H, Wang L, Abbaspour K, Zehnder A (2006) Virtual water trade: an assessment of water use efficiency in the international food trade. Hydrol Earth Syst Sci 10:443–454

    Article  Google Scholar 

  • Yu PS, Yang TC, Chou CC (2002) Effects of climate change on evapotranspiration from paddy fields in southern Taiwan. Clim Chang 54:165–179

    Article  Google Scholar 

  • Zhang X, Xu YP, Fu G (2014) Uncertainties in SWAT extreme flow simulation under climate change. J Hydrol 515:205–222. doi:10.1016/j.jhydrol.2014.04.064

    Article  Google Scholar 

  • Zickfeld K, Knopf B, Petoukhov V, Schellnhuber HJ (2005) Is the Indian summer monsoon stable against global change? Geophys Res Lett 32:L15707

    Article  Google Scholar 

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Authors and Affiliations

  1. Water Engineering Department, University of Zabol, Zabol, Iran

    Fatemeh Karandish & Seyed Saeed Mousavi

  2. Hydraulics Division, Department of Civil Engineering, KU Leuven, Louvain, Belgium

    Hossein Tabari

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  1. Fatemeh Karandish
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  2. Seyed Saeed Mousavi
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  3. Hossein Tabari
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Correspondence to Fatemeh Karandish.

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Karandish, F., Mousavi, S.S. & Tabari, H. Climate change impact on precipitation and cardinal temperatures in different climatic zones in Iran: analyzing the probable effects on cereal water-use efficiency. Stoch Environ Res Risk Assess 31, 2121–2146 (2017). https://doi.org/10.1007/s00477-016-1355-y

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