Natural Hazards

, Volume 85, Issue 3, pp 1835–1850 | Cite as

Evaluation of climate change in northern Iran during the last four centuries by using dendroclimatology

  • V. Gholami
  • M. Ahmadi Jolandan
  • J. Torkaman
Original Paper


Climate change is currently one of the most important environmental issues. Dendrochronology is frequently used to identify the climatic changes most closely associated with changes in tree-ring extent. We applied dendroclimatology to determine the climate changes in the Roodbar region of Iran during the last four centuries. The climatic index of De Martonne (aridity index), annual precipitation, and annual mean temperature were simulated by using dendroclimatology (tree-rings) and an artificial neural network (ANN). Dendroclimatology studies were carried out with the use of the Cupressus sempervirens species. A multilayer perceptron network was adopted for the ANN. Tree-ring width was the input variable for the simulation, whereas annual precipitation, annual mean temperature, and the aridity index were the outputs. After the training process, the network was validated. The validated network and tree-rings were used to simulate changes in climatic factors during the last four centuries. The climatic factors simulated by using dendroclimatology can be used in drought studies and climate change evaluation. The results showed that in the last four centuries, the climate of the study area changed from semiarid to arid, and its annual precipitation decreased significantly. The significant changes in climate were found to occur in the mid-twentieth century.


Tree-ring Precipitation Temperature Aridity index ANN 



The authors would like to the Regional Water Company of Guilan (RWCG) for providing the secondary climatic data and for helping us with the data preprocessing.


  1. Abdoun F, Jull AJT, Guibal F, Thinon M (2005) Radial growth of the Sahara’s oldest trees: Cupressus dupreziana A. Camus. Trees-Struct Funct 19:661–670CrossRefGoogle Scholar
  2. Abhishek K, Singh MP, Ghosh S, Anand A (2012) Weather forecasting model using artificial neural network. Procedia Technol 4:311–318CrossRefGoogle Scholar
  3. Amiri MJ, Eslamian S (2010) Investigation of climate change in Iran. J Environ Sci Technol 3(4):208–216CrossRefGoogle Scholar
  4. Anctil F, Rat A (2005) Evaluation of neural networks streamflow forecastingon 47 watersheds. J Hydrol Eng ASCE 10(1):85–88CrossRefGoogle Scholar
  5. Babaeian I, Modirian R, Karimian M, Zarghami M (2015) Simulation of climate change in Iran during 2071–2100 using. PRECIS regional climate modeling system. Desert 20(2):123–134Google Scholar
  6. Bednarz Z (1984) The comparison of dendroclimatological reconstructions of summer temperatures from the Alps and Tatra mountains from 1714–1965. Dendrochronologia 2:63–72Google Scholar
  7. Blasing TJ, Stahle DW, Duvick DN (1988) Tree ring-based reconstruction of annual precipitation in the south-central United State from 1750–1980. Water Resour Res 24:163–171CrossRefGoogle Scholar
  8. Bradley RS, Jones DP (eds) (1992) Climate since. Routledge, London, p 679 Google Scholar
  9. Briffa KR, Jones PD, Schweingruber FH (1988) Summer temperature pattern over Europe: a reconstruction from 1750 A.D. based on maximum latewood density indices of conifers. Quat Res 30:36–52CrossRefGoogle Scholar
  10. Briffa KR, Bartholin TS, Eckstein D, Jones PD, Karlen W, Schweingruber FH, Zetterberg P (1990) A 1400-year tree-ring record of summer temperature in Fennos-candia. Nature 346:434–439CrossRefGoogle Scholar
  11. Briffa KR, Schweingruber FH, Jones PD, Osborn TJ, Shiyatov SG, Vaganov EA (1998) Reduced sensitivity of recent tree-growth to temperature at high northern latitudes. Nature 391:678–682CrossRefGoogle Scholar
  12. Buntgen U, Frank DC, Schmidhalter M, Neuwirth B, Seifert M, Esper J (2006) Growth/climate response shift in a long subalpine spruce chronology. Trees 20:99–110CrossRefGoogle Scholar
  13. Bush MB, Metcalfe S (2012) Latin America and the Caribbean, quaternary environmental change in the tropics, chapter 8. Blackwell, New York, pp 263–311Google Scholar
  14. Conkey L (1979) Response of tree-ring density to climate in Maine, USA. Tree-ring Bull 39:29–38Google Scholar
  15. Cook ER, Kairiukstis LA (1990) Methods of dendrochronology: applications in the environmental sciences. Kluwer, Boston, p 394CrossRefGoogle Scholar
  16. Cook ER, Woodhouse CA, Woodhouse CM, Eakin DM, Meko O, Stahle D (2004) Long-term aridity changes in the western United States. Science 306(5698):1015–1018CrossRefGoogle Scholar
  17. Cook ER, Seager R, Heim RR, Vose RS, Herweijer C, Woodhouse C (2010) Mega-droughts in North America: placing IPCC projections of hydroclimatic change in a long-term palaeoclimate context. J Quat Sci 25:48–61CrossRefGoogle Scholar
  18. Corona E (1970) Valore dendrocronologico del cipresso sempreverde. The value of Cupressus semperivens for dendrochronology. Monti e Boschi 21(5):21–25 (in Italian with English summary)Google Scholar
  19. De Martonne E (1926) Une nouvelle fonction climatologique: I’indice d’aridite. La Meteorologie 2:449–458Google Scholar
  20. Eric T, Sophan Chhin D, Skole D (2014) Dendrochronological potential and productivity of tropical tree species in Western Kenya. Tree-Ring Res 70(2):119–135CrossRefGoogle Scholar
  21. Fekedulegn D, Hicks RR, Colbert JJ (2003) Influence of topographic aspect, precipitation and drought on radial growth of four major tree species in an Appalachian watershed. For Ecol Manag 177:409–425CrossRefGoogle Scholar
  22. Fritts HC (1959) The relation of radial growth to maximum and minimum temperature in three tree species. Ecology 40:261–265CrossRefGoogle Scholar
  23. Fritts HC (1965) Tree ring evidence for climatic changes in western North America. Mon Weather Rev 93:421–443CrossRefGoogle Scholar
  24. Fritts HC (1976) Tree rings and climate. Academic Press, London, p 576Google Scholar
  25. Fritts HC (1991) Reconstructing large-scale climatic patterns from tree-ring data. University of Arizona Press, TucsonGoogle Scholar
  26. Gholami V, Chau KW, Fadaee F, Torkaman J, Ghaffari A (2015a) Modeling of groundwater level fluctuations using dendrochronology in alluvial aquifers. J Hydrol 529(3):1060–1069CrossRefGoogle Scholar
  27. Gholami V, Darvari Z, Mohseni Saravi M (2015b) Artificial neural network technique for rainfall temporal distribution simulation. Casp J Environ Sci 13(1):53–60Google Scholar
  28. Gray ST, Graumlich LJ, Betancourt JL (2007) Annual precipitation in the Yellowstone National Park region since AD 1173. Quat Res 68:18–27CrossRefGoogle Scholar
  29. Griggs C, Pearson C, Manning SW, Lorentzen B (2013) 250-year annual precipitation reconstruction and drought assessment for Cyprus from Pinus brutia Ten. tree-rings. Int J Climatol 34:2702–2714CrossRefGoogle Scholar
  30. Hung NQ, Babel MS, Weesakul S, Tripathi NK (2009) An artificial neural network model for rainfall forecasting in Bangkok, Thailand. Hydrol Earth Syst Sci 13(8):1413–1425CrossRefGoogle Scholar
  31. IPCC AR5 WG2 A, Field CB et al (eds) (2014) Climate change 2014: impacts, adaptation, and vulnerability. Part A: Global and Sectoral Aspects (GSA). Contribution of Working Group II (WG2) to the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), Cambridge University Press. Archived 25 June 2014Google Scholar
  32. IPCC AR5 WG3, Edenhofer O et al (eds) (2014) Climate change 2014: mitigation of climate change. Contribution of Working Group III (WG3) to the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC), Cambridge University Press. Also available at Archives: Main IPCC website: 27 November 2014; 30 December 2014Google Scholar
  33. Isik S, Kalin L, Schoonover J, Srivastava P, Lockaby BG (2013) Modeling effects of changing land use/cover on daily streamflow: an artificial neural network and curve number based hybrid approach. J Hydrol 485(2013):103–112CrossRefGoogle Scholar
  34. Kienast F, Schweingruber FH, Braker OU, Schar E (1987) Tree-ring studies on conifers along ecological gradients and the potential of single year analysis. Can J For Res 17:683–696CrossRefGoogle Scholar
  35. Knight TR, Meko DM, Baisan CH (2010) A bimillennial-length tree-ring reconstruction of precipitation for the Tavaputs Plateau, Northeastern Utah. Quat Res 73:107–117CrossRefGoogle Scholar
  36. Lapointe-Garant MP, Huang JG, Gea-Izquierdo G, Frédéric R, Bernier P, Berninger F (2010) Use of ree rings to study the effect of climate change on trembling aspen in Québec. Glob Change Biol 16:2039–2051CrossRefGoogle Scholar
  37. League K, Veblen T (2006) Climatic variability and episodic Pinus ponderosa establishment along the forest-grassland ecotones of Colorado. For Ecol Manag 228:98–107CrossRefGoogle Scholar
  38. Leal S, Nunes E, Pereira H (2008) Cork oak (Quercus suber L.) wood growth and vessel characteristics variations in relation to climate and cork harvesting. Eur J For Res 127:33–41CrossRefGoogle Scholar
  39. Leal S, Campelo F, Luisa Luz A, Fatima Carneiro M, Andrade Santos J (2015) Potential of oak tree-ring chronologies from Southern Portugal for climate reconstructions. J Dendrochronol 35(2015):4–13CrossRefGoogle Scholar
  40. Linares JC, Tíscar PA (2010) Climate change impacts and vulnerability of the southern populations of Pinus nigra subsp. Salzmannii. Tree Physiol 30:795–806CrossRefGoogle Scholar
  41. Loh W, Tim L (2000) A comparison of prediction accuracy, complexity, and training time of thirty three old and new classification algorithm. Mach Learn 40(3):203–238CrossRefGoogle Scholar
  42. Lopez L, Villalba R (2011) Climate influences on the radial growth of Centrolobium microchaete, a valuable timber species from the tropical dry forests in Bolivia. Biotropica 43:41–49CrossRefGoogle Scholar
  43. Lopez L, Villalba R, Pena-Claros M (2012) Diameter growth rates in tropical dry forests: contributions to the sustainable management of forests in the Bolivian Cerrado biogeographical province. Bosque 33:99–107CrossRefGoogle Scholar
  44. Maqsood I, Riaz Khan M, Abraham A (2004) An ensemble of neural networks for weather forecasting. Neural Comput Appl 13:112–122CrossRefGoogle Scholar
  45. Martinelli N (2004) Climate from dendrochronology: latest developments and results. Glob Planet Change 40(1–2):129–139CrossRefGoogle Scholar
  46. Meko DM, Stockton CW, Boggess WR (1995) The tree-ring record of severe sustained drought: American Water Resources Association. Water Resour Bull 31:789–801CrossRefGoogle Scholar
  47. Meko DM, Therrell MD, Baisan CH, Hughes MK (2001) Sacramento River flow reconstructed to A.D. 869 from tree rings. J Am Water Resour As 37:1029–1039CrossRefGoogle Scholar
  48. Naurzbaev MM, Hughes MK, Vaganov EA (2004) Tree-ring growth curves as sources of climatic information. Quat Res 6(2):16–133Google Scholar
  49. Nayebi M, Khalili D (2006) Daily stream flow predication capability of artificial neural networks as influenced by minimum air temperature data. Bio-syst Eng 95(4):557–567Google Scholar
  50. Nestor S (2006) Modeling the infiltration process with a multilayer perceptron artificial neural network. Hydrol Sci J 51:3–20CrossRefGoogle Scholar
  51. Nistor M (2016) Spatial distribution of climate indices in the Emilia-Romagna region: spatial distribution of climate indices. Meteorol Appl 23(2):304–313CrossRefGoogle Scholar
  52. Orwig DA, Abrams MD (1997) Variation of radial growth responses to drought among species, site, and canopy strata. Trees 11:474–484CrossRefGoogle Scholar
  53. Paredes-Villanueva K, Loppez L, Brookhouse M, Navarro Cerrillo RM (2015) Rainfall and temperature variability in Bolivia derived from the tree-ring width of Amburana cearensis (Fr. Allem.) A.C. Smith. Dendrochronologica 35:80–86CrossRefGoogle Scholar
  54. Pourtahmasi K, Brauning A, Poursartip L, Burchardt I (2012) Growth-climate responses of oak and juniper trees in different exposures of the Alborz Mountains, northern Iran. Climatology and ecology, vol 10, Scientific Technical Report STR 12/03, Potsdam, pp 49–53Google Scholar
  55. Rinntech F (2005) Time series analysis and presentation for dendrochronology and related applications. User Reference. Rinntech, HeidelbergGoogle Scholar
  56. Salzer MW, Kipfmueller KF (2005) Reconstructed temperature and precipitation on a millennial timescale from tree-rings in the southern Colorado Plateau, USA. Clim Change 70:465–487CrossRefGoogle Scholar
  57. Sarris D, Christodoulakis D, Korner C (2007) Recent decline in precipitation and tree growth in the eastern Mediterranean. Glob Change Biol 13:1187–1200CrossRefGoogle Scholar
  58. Shelly AR, Henry Gregory HR (2005) Dendrochronological potential of the Arctic Dwarf-Shrub Cassiope tetragona. Tree-Ring Res 61(1):43–53CrossRefGoogle Scholar
  59. Soliz-Gamboa C, Rozendaal D, Ceccantini G, Angyalossy V, Van der Borg K, Zuidema P (2011) Evaluating the annual nature of juvenile rings in Boliviantropical rainforest trees. Trees 25:17–27CrossRefGoogle Scholar
  60. Stockton CW, Jacoby GC (1976) Long-term surface-water supply and streamflow trends in the upper Colorado River basin based on tree-ring analyses: Lake Powell Research Project Bulletin, No. 18, p 70Google Scholar
  61. Stokes MA, Smiley TL (1968) An introduction to tree-ring dating. University of Chicago, ChicagoGoogle Scholar
  62. Timmerman A, Oberhuber J, Bacher A, Esch M, Latif M, Roeckner E (1999) Increased El Nino Frequency in a climate model forced by future greenhouse warming. Nature 398:694–697CrossRefGoogle Scholar
  63. Vidakovic M (1991) Conifers: morphology and variation. Translated from Croatian by Maja Soljan. Graficki Zavod Hrvatske, CroatiaGoogle Scholar
  64. Villanueva-Diaz J, Stahle DW, Luckman BH, Cerano-Paredes J, Therrell MD, Cleaveland MK, Cornejo-Oviedo E (2007) Winter-spring precipitation reconstructions from tree rings for northeast Mexico. Clim Change 83:117–131CrossRefGoogle Scholar
  65. Voelker SL (2011) Age-dependent changes in environmental influences on tree growth and their implications for forest responses to climate change. Size- and age-related changes in tree structure and function. In: Meinzer FC, Lachenbruch B, Dawson TE, (eds) Tree physiol, vol 4, pp 455–479Google Scholar
  66. Wang H, Shao X, Jiang Y, Fang X, Wu S (2013) The impacts of climate change on the radial growth of Pinus koraiensis along elevations of Changbai Mountain in northeastern China. For Ecol Manag 289:333–340CrossRefGoogle Scholar
  67. Watson E, Luckman H (2005) An exploration of the controls of n pre-instrumental streamflow using multiple tree-ring proxies. Dendrochronology 22:225–234CrossRefGoogle Scholar
  68. Webb RH, Hereford R, McCabe GJ (2004) The state of the Colorado River Ecosystem in Grand Canyon; chapter 3, the state of the Colorado River Ecosystem in Grand Canyon, a report of the Grand Canyon Monitoring and Research Center 1991–2004, pp 59–69Google Scholar
  69. Wilmking M, Juday GP, Barber VA, Zald HSJ (2004) Recent climate warming forces contrasting growth responses of white spruce at treeline in Alaska through temperature thresholds. Glob Change Biol 10:1724–1736CrossRefGoogle Scholar
  70. Wilson R, Elling W (2004) Temporal instability in tree-growth/climate response in the Lower Bavarian Forest region: implications for dendroclimatic reconstruction. Trees 18:19–28CrossRefGoogle Scholar
  71. Woodhouse CA, Meko DM, MacDonald GM, Stahle DW, Cooke ER (2010) A 1200-year perspective of 21st century drought in southwestern North America. Proc Natl Acad Sci USA 107:21283–21288CrossRefGoogle Scholar
  72. Wu X, Lin Z, Sun L (1988) A preliminary study of the climatic change of the Hengudan Mountains area since 1600 A.D. Adv Atmos Sci 5:437–443CrossRefGoogle Scholar
  73. Zarean H, Yazdanpanah H, Movahedi S, Jalilvand H, Momeni M, Yarali N (2014) Chronological study of Quercus Persica growth ring response to climatic variables of precipitation and temperature in Zagros forests (a case study of Dena Region). J Appl Environ Biol Sci 4(4):247–255Google Scholar
  74. Zareiee AR (2014) Evaluation of changes in different climates of Iran, using De Martonne index and Mann-Kendall trend test. Nat Hazards Earth Syst Sci 2:2245–2261CrossRefGoogle Scholar
  75. Zhang WT, Jiang Y, Dong MY, Kang MY, Yang HC (2012) Relationship between the radial growth of Picea meyeri and climate along elevations of he Luyashan Mountain in North-Central China. For Ecol Manag 265:142–149CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.Department of Range and Watershed Management, Faculty of Natural ResourcesUniversity of GuilanRashtIran
  2. 2.Department of Range Management, Faculty of Natural ResourcesTarbiat Modares UniversityTehranIran
  3. 3.Department of Forestry, Faculty of Natural ResourcesUniversity of GuilanRashtIran

Personalised recommendations