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Relationship Between Hydrologic and Metrological Droughts Using the Streamflow Drought Indices and Standardized Precipitation Indices in the Dez Watershed of Iran

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Abstract

This research utilizes DrinC software and some codes developed in MATLAB software for calculating the drought indices and determination of trend of climatologic and hydrologic time series data using different nonparametric Mann–Kendall trend tests. The time series data used in this research include the minimum, mean and maximum monthly temperatures, monthly precipitation, and monthly flow discharge (from 1981 to 2012). These data are pertinent to the Dez watershed climatic and hydrometric stations in southwest Iran. Results of this research show that precipitation has no significant trend, but flow discharge has a decreasing trend. The trends of mean, maximum, and minimum temperatures are increasing in summer and autumn but decreasing in spring. In winter, the trend of minimum temperature is increasing, while the trend of mean and maximum temperatures is decreasing. Standardized precipitation index (SPI) and streamflow drought index (SDI) show that the number and intensity of short-term droughts (with 3 months time scale) are more than the number and intensity of long-term droughts (with 6, 9, and 12 month time scales). Correlation coefficient between SPI and SDI increases as the time scale is increased too.

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References

  1. Xu K, Milliman JD, Xu H (2010) Temporal trend of precipitation and runoff in major Chinese rivers since 1951. Glob Planet Chang 73(3–4):219–232. https://doi.org/10.1016/j.gloplacha.2010.07.002

    Article  Google Scholar 

  2. Khalili K, Tahoudi MN, Mirabbasi R, Ahmadi F (2016) Investigation of spatial and temporal variability of precipitation in Iran over the last half century. Stoch Environ Res Risk Assess 30(4): 1205–1221. https://doi.org/10.1007/s00477-015-1095-4

    Article  Google Scholar 

  3. Addisu S, Selassie YG, Fissha G, Gedif B (2015) Time series trend analysis of temperature and rainfall in lake Tana Sub-basin, Ethiopia. Environ Syst Res 4(1):25. https://doi.org/10.1186/s40068-015-0051-0

    Article  Google Scholar 

  4. Masih I, Uhlenbrook S, Maskey S, Smakhtin V (2011) Streamflow trends and climate linkages in the Zagros Mountains. Iran Clim Chang 104(2):317–338. https://doi.org/10.1007/s10584-009-9793-x

    Article  Google Scholar 

  5. Abghari H, Tabari H, Talaee PH (2013) River flow trends in the west of Iran during the past 40 years: impact of precipitation variability. Glob Planet Chang 101:52–60. https://doi.org/10.1016/j.gloplacha.2012.12.003

    Article  Google Scholar 

  6. Zamani R, Mirabbasi R, Abdollahi S, Jhajharia D (2017) Streamflow trend analysis by considering autocorrelation structure, long term persistence, and Hurst coefficient in a semi-arid region of Iran. Theor Appl Climatol 129(1–2):33–45. https://doi.org/10.1007/s00704-016-1747-4

    Article  Google Scholar 

  7. Mann HB (1945) Nonparametric tests against trend. Econometrica 13(3):245–259. https://doi.org/10.2307/1907187

    Article  MathSciNet  MATH  Google Scholar 

  8. Sen PK (1968) Estimates of the regression coefficient based on Kendall’s tau. J Am Stat Assoc 63(324):1379–1389. https://doi.org/10.1080/01621459.1968.10480934

    Article  MathSciNet  MATH  Google Scholar 

  9. 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(9):1807–1829. https://doi.org/10.1002/hyp.1095

    Article  Google Scholar 

  10. Taxak AK, Murumkar AR, Arya DS (2014) Long term spatial and temporal rainfall trends and homogeneity analysis in Wainganga basin, Central India. Weather Clim Extremes 4:50–61. https://doi.org/10.1016/j.wace.2014.04.005

    Article  Google Scholar 

  11. Kumar V, Jain SK (2011) Trends in rainfall amount and number of rainy days in river basins of India (1951–2004). Hydrol Res 42(4):290–306. https://doi.org/10.2166/nh.2011.067

    Article  Google Scholar 

  12. Subash N, Singh SS, Priya N (2011) Variability of rainfall and effective onset and length of the monsoon season over a sub-humid climatic environment. Atmos Res 99(3–4):479–487. https://doi.org/10.1016/j.atmosres.2010.11.020

    Article  Google Scholar 

  13. Sayemuzzaman M, Jha MK (2014) Seasonal and annual precipitation time series trend analysis in North Carolina, United States. Atmos Res 137:183–194. https://doi.org/10.1016/j.atmosres.2013.10.012

    Article  Google Scholar 

  14. Croitoru AE, Piticar A, Dragotă CS, Burada DC (2013) Recent changes in reference evapotranspiration in Romania. Glob Planet Chang 111:127–136. https://doi.org/10.1016/j.gloplacha.2013.09.004

    Article  Google Scholar 

  15. Gocic M, Trajkovic S (2013) Analysis of changes in meteorological variables using Mann-Kendall and Sen’s slope estimator statistical tests in Serbia. Glob Planet Chang 100:172–182. https://doi.org/10.1016/j.gloplacha.2012.10.014

    Article  Google Scholar 

  16. de la Casa AC, Nasello OB (2012) Low frequency oscillation of rainfall in Córdoba, Argentina, and its relation with solar cycles and cosmic rays. Atmos Res 113:140–146. https://doi.org/10.1016/j.atmosres.2012.05.003

    Article  Google Scholar 

  17. Adib A, Kalaee MMK, Shoushtari MM, Khalili K (2017) Using of gene expression programming and climatic data for forecasting flow discharge by considering trend, normality, and stationarity analysis. Arab J Geosci 10(9): 208. https://doi.org/10.1007/s12517-017-2995-z

    Article  Google Scholar 

  18. Somee BS, Ezani A, Tabari H (2012) Spatiotemporal trends and change point of precipitation in Iran. Atmos Res 113:1–12. https://doi.org/10.1016/j.atmosres.2012.04.016

    Article  Google Scholar 

  19. Tabari H, Somee BS, Zadeh MR (2011) Testing for long-term trends in climatic variables in Iran. Atmos Res 100(1):132–140. https://doi.org/10.1016/j.atmosres.2011.01.005

    Article  Google Scholar 

  20. Ay M, Kişi Ö (2015) Investigation of trend analysis of monthly total precipitation by an innovative method. Theor Appl Climatol 120(3–4):617–629. https://doi.org/10.1007/s00704-014-1198-8

    Article  Google Scholar 

  21. Caloiero T (2017) Trend of monthly temperature and daily extreme temperature during 1951–2012 in New Zealand. Theor Appl Climatol 129(1–2):111–127. https://doi.org/10.1007/s00704-016-1764-3

    Article  Google Scholar 

  22. Gocic M, Trajkovic S (2014) Spatiotemporal characteristics of drought in Serbia. J Hydrol 510:110–123. https://doi.org/10.1016/j.jhydrol.2013.12.030

    Article  Google Scholar 

  23. Du J, Fang J, Xu W, Shi P (2013) Analysis of dry/wet conditions using the standardized precipitation index and its potential usefulness for drought/flood monitoring in Hunan Province, China. Stoch Environ Res Risk Assess 27(2):377–387. https://doi.org/10.1007/s00477-012-0589-6

    Article  Google Scholar 

  24. Zhang Q, Xu CY, 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(1–2):89–99. https://doi.org/10.1007/s00704-008-0095-4

    Article  Google Scholar 

  25. Tabari H, Nikbakht J, Talaee PH (2013) Hydrological drought assessment in northwestern Iran based on streamflow drought index (SDI). Water Resour Manag 27(1):137–151. https://doi.org/10.1007/s11269-012-0173-3

    Article  Google Scholar 

  26. Hao Z, AghaKouchak A (2013) Multivariate Standardized Drought Index: a parametric multi-index model. Adv Water Resour 57:12–18. https://doi.org/10.1016/j.advwatres.2013.03.009

    Article  Google Scholar 

  27. Marofi S, Soleymani S, Salarijazi M, Marofi H (2012) Watershed-wide trend analysis of temperature characteristics in Karun- Dez watershed, southwestern Iran. Theor Appl Climatol 110(1–2):311–320. https://doi.org/10.1007/s00704-012-0662-

    Article  Google Scholar 

  28. Hosseinizadeh A, SeyedKaboli H, Zareie H, Akhondali A, Farjad B (2015) Impact of climate change on the severity, duration, and frequency of drought in a semi-arid agricultural basin. Geoenv Disasters 2(1):23. https://doi.org/10.1186/s40677-015-0031-8

    Article  Google 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(1–2):171–183. https://doi.org/10.1016/j.jhydrol.2009.06.012

    Article  Google Scholar 

  30. Hamed KH, Rao AR (1998) A modified Mann–Kendall trend test for autocorrelated data. J Hydrol 204(1–4):182–196. https://doi.org/10.1016/S0022-1694(97)00125-X

    Article  Google Scholar 

  31. Guttman NB (1999) Accepting the standardized precipitation index: a calculation algorithm. JAWRA J Am Water Resour Assoc 35(2):311–322. https://doi.org/10.1111/j.1752-1688.1999.tb03592.x

    Article  Google Scholar 

  32. Sönmez FK, Kömüscü A, Erkan A, Turgu E (2005) An analysis of spatial and temporal dimension of drought vulnerability in Turkey using the standardized precipitation index. Nat Hazards 35(2):243–264. https://doi.org/10.1007/s11069-004-5704-7

    Article  Google Scholar 

  33. Angelidis P, Maris F, Kotsovinos N, Hrissanthou V (2012) Computation of drought index SPI with alternative distribution functions. Water Resour Manag 26(9):2453–2473. https://doi.org/10.1007/s11269-012-0026-0

    Article  Google Scholar 

  34. Nalbantis I, Tsakiris G (2009) Assessment of hydrological drought revisited. Water Resour Manag 23(5):881–897. https://doi.org/10.1007/s11269-008-9305-1

    Article  Google Scholar 

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Acknowledgements

The authors of this manuscript would like to thank Dr. Reza Zamani and the managers and staffs of civil engineering department and engineering faculty of Shahid Chamran University of Ahvaz for providing the facilities of this study.

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Authors and Affiliations

  1. Civil Engineering Department, Engineering Faculty, Shahid Chamran University, Ahvaz, Iran

    Arash Adib & Fatemeh Tavancheh

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  1. Arash Adib
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Correspondence to Arash Adib.

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Adib, A., Tavancheh, F. Relationship Between Hydrologic and Metrological Droughts Using the Streamflow Drought Indices and Standardized Precipitation Indices in the Dez Watershed of Iran. Int J Civ Eng 17, 1171–1181 (2019). https://doi.org/10.1007/s40999-018-0376-y

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  • DOI: https://doi.org/10.1007/s40999-018-0376-y

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