Assessment of short- and long-term memory in trends of major climatic variables over Iran: 1966–2015

  • Ameneh MianabadiEmail author
  • Pooya Shirazi
  • Bijan Ghahraman
  • A. M. J. Coenders-Gerrits
  • Amin Alizadeh
  • Kamran Davary
Original Paper


In arid and semi-arid regions, water scarcity is the crucial issue for crop production. Identifying the spatial and temporal trends in aridity, especially during the crop-growing season, is important for farmers to manage their agricultural practices. This will become especially relevant when considering climate change projections. To reliably determine the actual trends, the influence of short- and long-term memory should be removed from the trend analysis. The objective of this study is to investigate the effect of short- and long-term memory on estimates of trends in two aridity indicators—the inverted De Martonne (ϕ IDM ) and Budyko (ϕ B ) indices. The analysis is done using precipitation and temperature data over Iran for a 50-year period (1966–2015) at three temporal scales: annual, wheat-growing season (October–June), and maize-growing season (May–November). For this purpose, the original and the modified Mann–Kendall tests (i.e., modified by three methods of trend free pre-whitening (TFPT), effective sample size (ESS), and long-term persistence (LTP)) are used to investigate the temporal trends in aridity indices, precipitation, and temperature by taking into account the effect of short- and long-term memory. Precipitation and temperature data were provided by the Islamic Republic of Iran Meteorological Organization (IRIMO). The temporal trend analysis showed that aridity increased from 1966 to 2015 at the annual and wheat-growing season scales, which is due to a decreasing trend in precipitation and an increasing trend in mean temperature at these two timescales. The trend in aridity indices was decreasing in the maize-growing season, since precipitation has an increasing trend for most parts of Iran in that season. The increasing trend in aridity indices is significant in Western Iran, which can be related to the significantly more negative trend in precipitation in the West. This increasing trend in aridity could result in an increasing crop water requirement and a significant reduction in the crop production and water use efficiency. Furthermore, the modified Mann–Kendall tests indicated that unlike temperature series, precipitation, ϕ IDM , and ϕ B series are not affected by short- and long-term memory. Our results can help decision makers and water resource managers to adopt appropriate policy strategies for sustainable development in the field of irrigated agriculture and water resources management.



The authors would like to thank the Islamic Republic of Iran Meteorological Organization (IRIMO) for providing the precipitation and temperature data. Furthermore, we appreciate the help of Hossein Tabari, Edo Abraham, Farshad Fathian, and the anonymous reviewers for their useful comments and suggestions for improving the manuscript.

Funding information

This research was partly funded by NWO Earth and Life Sciences (ALW), veni-project 863.15.022, the Netherlands.


  1. Ahmadi H (2008) Applied geomorphology. Tehran, Iran (in Persian)Google Scholar
  2. Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration—guidelines for computing crop water requirements—FAO irrigation and drainage paper 56Google Scholar
  3. Ashraf B, Yazdani R, Mousavi-Baygi M, Bannayan M (2013) Investigation of temporal and spatial climate variability and aridity of Iran. Theor Appl Climatol 118:35–46. CrossRefGoogle Scholar
  4. Aydin M (1995) Water key ingredient in Turkish farming. Forum Appl Res Public Policy 10:68–70Google Scholar
  5. Baltas E (2007) Spatial distribution of climatic indices in northern Greece. Meteo 14:69–78. Google Scholar
  6. Bannayan M, Sanjani S (2011) Weather conditions associated with irrigated crops in an arid and semi arid environment. Agric For Meteorol 151:1589–1598. CrossRefGoogle Scholar
  7. Bannayan M, Sanjani S, Alizadeh A, Lotfabadi SS, Mohamadian A (2010) Association between climate indices, aridity index, and rainfed crop yield in northeast of Iran. F Crop Res 118:105–114. CrossRefGoogle Scholar
  8. Budyko MI (1974) Climate and life. Academic Press, OrlandoGoogle Scholar
  9. Croitoru A, Piticar A, Imbroane AM, Burada DC (2013) Spatiotemporal distribution of aridity indices based on temperature and precipitation in the extra-Carpathian regions of Romania. Theor Appl Climatol 112:597–607. CrossRefGoogle Scholar
  10. de Martonne E (1925) Traité de Géographie Physique. 3 tomes. ParisGoogle Scholar
  11. Delju AH, Ceylan A, Piguet E, Rebetez M (2013) Observed climate variability and change in Urmia Lake Basin, Iran. Theor Appl Climatol 111:285–296. CrossRefGoogle Scholar
  12. Dinpashoh Y, Mirabbasi R, Asce SM, et al (2014) Effect of short-term and long-term persistence on identification of temporal trends. 617–625. doi:
  13. Eyshi Rezaie E, Bannayan M (2012) Rainfed wheat yields under climate change in northeastern Iran. Meteorol Appl 19:346–354. CrossRefGoogle Scholar
  14. Fathian F, Dehghan Z, Bazrkar MH, Eslamian S (2014) Trends in hydrologic and climatic variables affected by four variations of Mann-Kendall approach in Urmia Lake basin, Iran. Hydrol Sci J 6667:140617041244008. Google Scholar
  15. Ghahraman B (2006) Time trend in the mean annual temperature of Iran. Turkish. J Agric For 30:439–448Google Scholar
  16. Ghahraman B (2013) Effect of short- and long-term memory on trend significancy of mean annual flow by Mann-Kendall test. Int J Eng Trans A Basics 26:1155–1168. Google Scholar
  17. Ghahraman B, Taghvaeian S (2008) Investigation of annual rainfall trends in Iran. J Agric Sci Technol 10:93–97Google Scholar
  18. Hamed KH (2008) Trend detection in hydrologic data: the Mann-Kendall trend test under the scaling hypothesis. J Hydrol 349:350–363. CrossRefGoogle Scholar
  19. Hamed KH, Rao RA (1998) A modified Mann-Kendall trend test for autocorrelated data. J Hydrol 204:182–196. CrossRefGoogle Scholar
  20. Hargreaves GH, Samani ZA (1985) Reference crop evapotranspiration from temperature. Appl Eng Agric 1:96–99CrossRefGoogle Scholar
  21. Heathcote R (1983) The arid lands: their use and abuse. Longman, New YorkGoogle Scholar
  22. Hulme M (1996) Recent climatic change in the world’s drylands. Geophys Res Lett 23:61–64CrossRefGoogle Scholar
  23. Hurst HE (1951) Long-term storage capacity of reservoirs. Trans Am Soc Civ Eng 116:770–799Google Scholar
  24. IPCC (2013) Climate change 2013: the physical science basis. Contribution of Working Group I to the Fifth Assessment.Stockholm, ZwedenGoogle Scholar
  25. Kendall MG (1975) Rank correlation methods. Charles Griffin, LondonGoogle Scholar
  26. Kharel Kafle H, Hendrik JB (2009) Climatic trends in Israel 1970 – 2002 : warmer and increasing aridity inland. Clim Chang 96:63–77. CrossRefGoogle Scholar
  27. Knapp CL, Stoffel TL, Whitaker SD (1980) Insulation solar radiation manual. Solar Energy Research Institute, GoldenGoogle Scholar
  28. Koutsoyiannis D, Montanari A (2007) Statistical analysis of hydroclimatic time series: uncertainty and insights. Water Resour Res 43:1–9. CrossRefGoogle Scholar
  29. Kumar S, Merwade V, Kam J, Thurner K (2009) Streamflow trends in Indiana: effects of long term persistence, precipitation and subsurface drains. J Hydrol 374:171–183. CrossRefGoogle Scholar
  30. Li ZL, Xu ZX, Li JY, Li ZJ (2008) Shift trend and step changes for runoff time series in the Shiyang River basin, northwest China. Hydrol Process 22:4639–4646. CrossRefGoogle Scholar
  31. Mann HB (1945) Nonparametric tests against trend. Econometrica 13:245–259CrossRefGoogle Scholar
  32. Mckee TB, Doesken NJ, Kleist J (1993) The relationship of drought frequency and duration to time scales. In: Eighth Conference on Applied Climatology, Am Meteorol Soc,. pp 179–186Google Scholar
  33. McKee T, Doesken N, Kleist J (1995) Drought monitoring with multiple time scales. In: Ninth Conference on Applied Climatology, Am Meteorol Soc,. pp 233–236Google Scholar
  34. Mekonnen MM, Hoekstra AY (2016) Four billion people facing severe water scarcity. Sci Adv 2:1–7CrossRefGoogle Scholar
  35. Moral FJ, Paniagua LL, Rebollo FJ, Garcia-Martin A (2016) Spatial analysis of the annual and seasonal aridity trends in Extremadura, southwestern Spain. Theor Appl Climatol 130:1–16. Google Scholar
  36. Muhire I, Ahmed F (2016) Spatiotemporal trends in mean temperatures and aridity index over Rwanda. Theor Appl Climatol 123:399–414. CrossRefGoogle Scholar
  37. Nazemosadat MJ, Cordery I (2000) On the relationships between Enso and autumn rainfall in Iran. Int J Climatol 20:47–61CrossRefGoogle Scholar
  38. Nikkath N, Selvaraj S (2016) Trend analysis and estimation of hurst exponent for aerosol time series of chennai. Int J Dev Res 6:8178–8182Google Scholar
  39. Paltineanu C, Tanasescu N, Chitu E, Mihailescu IF (2007) Relationships between the de Martonne aridity index and water requirements of some representative crops : a case study from Romania. Int Agrophysics 21:81–93Google Scholar
  40. Rai RK, Upadhyay A, Ojha CSP (2010) Temporal variability of climatic parameters of Yamuna River basin : spatial analysis of persistence, trend and periodicity. Open Hydrol J 4:184–210CrossRefGoogle Scholar
  41. Salas JD (1980) Applied modeling of hydrologic time series. Water Resources Publication, LittletonGoogle Scholar
  42. Sanjani S, Bannayan M, Kamyabnejad M (2011) Detection of recentclimate change using daily temperature extremes in Khorasan Province, Iran. Clim Res 49:247–254. CrossRefGoogle Scholar
  43. Sayari N, Bannayan M, Alizadeh A, Farid A (2013) Using drought indices to assess climate change impacts on drought conditions in the northeast of Iran (case study: Kashafrood basin). Meteorol Appl 20:115–127. CrossRefGoogle Scholar
  44. Sen PK (1968) Asymptotically efficient tests by the method of n rankings. J R Stat Soc 30:312–317Google Scholar
  45. Shabani B, Mousavi Baygi M, Jabari Noghabi M, Ghareman B (2013) Modeling and prediction of monthly max & min temperatures of Mashhad plain using time series models. J Water Soil 27:896–906 (in Persian)Google Scholar
  46. Shifteh Some’e B, Ezani A, Tabari H (2012) Spatiotemporal trends of aridity index in arid and semi-arid regions of Iran. Theor Appl Climatol 111:149–160. CrossRefGoogle Scholar
  47. Tabari H, Aghajanloo M (2013) Temporal pattern of aridity index in Iran with considering precipitation and evapotranspiration trends. Int J Climatol 33:396–409. CrossRefGoogle Scholar
  48. Tabari H, Hosseinzadeh Talaee P (2011a) Analysis of trends in temperature data in arid and semi-arid regions of Iran. Glob Planet Chang 79:1–10. CrossRefGoogle Scholar
  49. Tabari H, Hosseinzadeh Talaee P (2011b) Temporal variability of precipitation over Iran : 1966 – 2005. J Hydrol 396:313–320. CrossRefGoogle Scholar
  50. Tabari H, Hosseinzadeh Talaee P, Ezani A, Shifteh Some’e B (2011a) Shift changes and monotonic trends in autocorrelated temperature series over Iran. Theor Appl Climatol 109:95–108. CrossRefGoogle Scholar
  51. Tabari H, Shifteh Somee B, Rezaeian Zadeh M (2011b) Testing for long-term trends in climatic variables in Iran. Atmos Res 100:132–140. CrossRefGoogle Scholar
  52. 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. CrossRefGoogle Scholar
  53. Theil H (1950) A rank-invariant method of linear and polynomial regression analysis. Part 3. Springer Netherlands, DordrechtGoogle Scholar
  54. Türkes M (2003) Spatial and temporal variations in precipitation and aridity index series of Turkey. Mediterr Clim 181–213Google Scholar
  55. Türkes M, Sümer UM (2004) Spatial and temporal patterns of trends and variability in diurnal temperature ranges of Turkey. Theor Appl Climatol 77:195–227. CrossRefGoogle Scholar
  56. UNEP (1992) World atlas of desertification. Edward Arnold, LondonGoogle Scholar
  57. UNFCCC (2007) Climate change: impacts, vulnerabilities and adaptation in developing countriesGoogle Scholar
  58. von Storch H (1995) Misuses of statistical analysis in climate. In: Analysis of Climate Variability: Applications of Statistical Techniques. pp 11–26Google Scholar
  59. Yue S, Hashino M (2003) Temperature trends in Japan : 1900 – 1996. Environment 27:15–27. Google Scholar
  60. Yue S, Pilon P, Phinney B, Cavadias G (2002) The influence of autocorrelation on the ability to detect trend in hydrological series. Hydrol Process 16:1807–1829. CrossRefGoogle Scholar
  61. Zambakas J (1992) General climatology. Department of Geology, National & Kapodistrian University of Athens, AthensGoogle Scholar
  62. Zhang Q, Xu C, Zhang Z (2009) Observed changes of drought / wetness episodes in the Pearl River basin, China, using the standardized precipitation index and aridity index. Theor Appl Climatol 98:89–99. CrossRefGoogle Scholar
  63. Zhang B, Kang S, Li F, Tong L, Du T (2010) Variation in vineyard evapotranspiration in an arid region of northwest China. Agric Water Manag 97:1898–1904. CrossRefGoogle Scholar
  64. Zhao G, Hörmann G, Fohrer N, Zhang Z, Zhai J (2010) Streamflow trends and climate variability impacts in Poyang Lake basin, China. Water Resour Manag 24:689–706. CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Austria, part of Springer Nature 2018

Authors and Affiliations

  • Ameneh Mianabadi
    • 1
    Email author
  • Pooya Shirazi
    • 1
  • Bijan Ghahraman
    • 1
  • A. M. J. Coenders-Gerrits
    • 2
  • Amin Alizadeh
    • 1
  • Kamran Davary
    • 1
  1. 1.Water Engineering DepartmentFerdowsi University of MashhadMashhadIran
  2. 2.Water Resources SectionDelft University of TechnologyDelftNetherlands

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