Abstract
In a changing climate, drought indices as well as drought definitions need to be revisited because some statistical properties, such as the long-term mean, of climate series may change over time. This study aims to develop a Non-stationary Standardized Precipitation Evapotranspiration Index (NSPEI) for reliable and robust quantification of drought characteristics in a changing climate. The proposed indicator is based on a non-stationary log-logistic probability distribution, assuming the location parameter of the distribution is a multivariable function of time and climate indices, as covariates. The optimal non-stationary model was obtained using a forward selection method in the framework of the Generalized Additive Models in Location, Scale, and Shape (GAMLSS) algorithm. The Non-stationary and Stationary forms of SPEI (i.e., NSPEI and SSPEI) were calculated using the monthly precipitation and temperature data of 32 weather stations in Iran for the common period of 1964–2014. The results showed that almost at all the stations studied, the non-stationary log-logistic distributions outperformed the stationary ones. The AICs of the non-stationary models for 97% of the stations were lower than those of the stationary models. The non-stationary models at 90% of the stations were statistically significant at the 5% significance level. While SSPEI identified the long-term and continuous drought and wet events, NSPEI revealed the short-term and frequent drought/wet periods at almost all the stations of interest. Finally, it was revealed that NSPEI, compared to SSPEI, was a more reliable and robust indicator of drought duration and drought termination in vegetation cover during the severest drought period (the 2008 drought). Therefore, it was suggested as a suitable drought index to quantify drought impacts on vegetation cover in Iran.
Similar content being viewed by others
Availability of Data and Materials
Readers can contact authors for availability of data and materials.
References
Abramowitz M, Stegun IA (1965) Handbook of mathematical functions with formulas, graphs, and mathematical tables. Dover, Dover Books on Advanced Mathematics, New York
Alizadeh-Choobari O, Adibi P, Irannejad P (2018) Impact of the El Niño-Southern Oscillation on the climate of Iran using ERA-Interim data. Clim Dyn 51:2897–2911
Bazrafshan J (2017) Effect of air temperature on historical trend of long-term droughts in different climates of Iran. Water Resour Manag 31:4683–4698
Bazrafshan J, Hejabi S (2018) A non-stationary reconnaissance drought index (NRDI) for drought monitoring in a changing climate. Water Resour Manag 32:2611–2624
Bazrafshan J, Hejabi S, Eslamian S (2017) Drought modeling examples. In S., E., F., E. (Eds.), Handbook of Drought and Water Scarcity Francis and Taylor, CRC Press, USA, pp. 167–188
Burnham KP, Anderson DR (2002) Model selection and multimodel inference: A practical information-theoretical approach, 2nd edn. Springer, New York
Cheng L, AghaKouchak A (2014) Nonstationary precipitation intensity-duration-frequency curves for infrastructure design in a changing climate. Sci Rep 4:7093
De Planhol X (2012) Famines. In Encyclopedia Iranica, IX/2, pp. 203–206
Dezfuli AK, Karamouz M, Araghinejad S (2010) On the relationship of regional meteorological drought with SOI and NAO over southwest Iran. Theoret Appl Climatol 100:57–66
Ghaleb F, Mario M, Sandra AN (2015) Regional landsat-based drought monitoring from 1982 to 2014. Climate 3:563–577
Ghasemi AR, Khalili D (2006) The influence of the Arctic Oscillation on winter temperatures in Iran. Theoret Appl Climatol 85:149–164
Ghasemi AR, Khalili D (2008) The effect of the North Sea-Caspian pattern (NCP) on winter temperatures in Iran. Theoret Appl Climatol 92:59–74
Golian S, Mazdiyasni O, AghaKouchak A (2015) Trends in meteorological and agricultural droughts in Iran. Theoret Appl Climatol 119:679–688
Hamed KH, Rao AR (1998) A modified Mann-Kendall trend test for autocorrelated data. J Hydrol 204:182–196
Hosking JRM (1990) L-Moments: Analysis and estimation of distributions using linear combinations of order statistics. J R Stat Soc Ser B Methodol 52(1):105–124
IPCC (2014) Climate change 2014: Synthesis report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, R.K. Pachauri and L.A. Meyer (eds.)]. IPCC, Geneva, Switzerland, 151 pp
Kang L, Jiang S (2019) Bivariate frequency analysis of hydrological drought using a nonstationary standardized streamflow index in the Yangtze River. J Hydrol Eng 24:05018031
Kendall MG (1970) Rank correlation methods. Griffin, London
Khalili A (1997) Synthesis proceeding of integrated water plan of Iran. Jamab Consulting Engineering Co., Climate Section, The Ministry of Energy, Tehran, Iran
Khalili A, Rahimi J (2018) Climate. In: Roozitalab MH, Siadat H, Farshad A (eds) The Soils of Iran. Springer International Publishing, Cham, pp 19–33
Kogan FN (1995) Application of vegetation index and brightness temperature for drought detection. Adv Space Res 15:91–100
Kwon H-H, Lall U (2016) A copula-based nonstationary frequency analysis for the 2012–2015 drought in California. Water Resour Res 52:5662–5675
Li JZ, Wang YX, Li SF, Hu R (2015) A Nonstationary Standardized Precipitation Index incorporating climate indices as covariates. J Geophys Res Atmos 120:12,082–012,095
Mann HB (1945) Nonparametric tests against trend. Econometrica 13:245–259
Mavromatis T (2007) Drought index evaluation for assessing future wheat production in Greece. Int J Climatol 27:911–924
McKee TB, Doeskin NJ, Kleist J (1993) The relationship of drought frequency and duration to time scales. Proceedings of the eighth conference on applied climatology. American Meteorological Society, Anaheim, CA, pp. 179–184
Mishra AK, Singh VP (2010) A review of drought concepts. J Hydrol 391:202–216
Moradi HR (2004) North atlantic oscilation index and its effect on climate of Iran. Geogr Res Q 36:17–30
Nazemosadat MJ, Cordery I (2000) On the relationships between ENSO and autumn rainfall in Iran. Int J Climatol 20:47–61
Nazemosadat MJ, Ghasemi AR (2004) Quantifying the ENSO-Related Shifts in the Intensity and Probability of Drought and Wet Periods in Iran. J Clim 17:4005–4018
Palmer WC (1965) Meteorological drought. Research Paper No. 45, US Weather Bureau, Washington, DC
Paulo AA, Pereira LS (2006) Drought concepts and characterization. Water Int 31:37–49
Pinzon JE, Tucker CJ (2014) A non-stationary 1981–2012 AVHRR NDVI3g time series. Remote Sensing 6:6929–6960
Rahimzadeh Bajgiran P, Darvishsefat AA, Khalili A, Makhdoum MF (2008) Using AVHRR-based vegetation indices for drought monitoring in the Northwest of Iran. J Arid Environ 72:1086–1096
Rashid MM, Beecham S (2019) Development of a non-stationary Standardized Precipitation Index and its application to a South Australian climate. Sci Total Environ 657:882–892
Raziei T, Saghafian B, Paulo AA, Pereira LS, Bordi I (2008) Spatial patterns and temporal variability of drought in Western Iran. Water Resour Manag 23:439
Rigby RA, Stasinopoulos DM (2005) Generalized additive models for location, scale and shape. J Roy Stat Soc: Ser C (appl Stat) 54:507–554
Russo S, Dosio A, Sterl A, Barbosa P, Vogt J (2013) Projection of occurrence of extreme dry-wet years and seasons in Europe with stationary and nonstationary Standardized Precipitation Indices. J Geophys Res Atmos 118:7628–7639
Sen Z (2015) Chapter Four - Regional drought analysis and modeling, applied drought modeling, prediction, and mitigation. Elsevier, Boston, pp 205–274
Serinaldi F, Kilsby CG (2015) Stationarity is undead: Uncertainty dominates the distribution of extremes. Adv Water Resour 77:17–36
Shamsipour AA, AlaviPanah SK, Mohammadi H, Azizi A, Khoshakhlagh F (2008) An analysis of drought events for central plains of Iran through an employment of NOAA-AVHRR data. Desert 13:105–115
Stasinopoulos DM, Rigby RA, Akantziliotou C (2008) Instructions on how to use the GAMLSS package in R, 2nd edn. STORM Research Centre, London Metropolitan University, London
Thornthwaite CW (1948) An approach toward a rational classification of climate. Geogr Rev 38:55–94
Tsakiris G, Pangalou D, Vangelis H (2007) Regional drought assessment based on the reconnaissance drought index (RDI). Water Resour Manag 21:821–833
Tsakiris G, Vangelis H (2005) Establishing a drought index incorporating evapotranspiration. Eur Water 3–11
Van Loon AF (2015) Hydrological drought explained. Wiley Interdiscip Rev Water 2:359–392
Vangelis H, Tigkas D, Tsakiris G (2013) The effect of PET method on Reconnaissance Drought Index (RDI) calculation. J Arid Environ 88:130–140
Vicente-Serrano SM, Beguería S, López-Moreno JI (2010) A multiscalar drought index sensitive to global warming: The standardized precipitation evapotranspiration index. J Clim 23:1696–1718
Wang Y, Duan L, Liu T, Li J, Feng P (2020) A Non-stationary Standardized Streamflow Index for hydrological drought using climate and human-induced indices as covariates. Sci Total Environ 699:134278
Wang Y, Li J, Feng P, Hu R (2015) A time-dependent drought index for non-stationary precipitation series. Water Resour Manag 29:5631–5647
Wilhite DA (2000) Drought: A global assessment. Routledge, London
Wilhite DA, Glantz MH (1985) Understanding: the drought phenomenon: the role of definitions. Water Int 10:111–120
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
Zarch MAA, Sivakumar B, Sharma A (2015) Droughts in a warming climate: A global assessment of Standardized precipitation index (SPI) and Reconnaissance drought index (RDI). J Hydrol 526:183–195
Zarei AR, Mahmoudi MR (2020) Assessment of the effect of PET calculation method on the Standardized Precipitation Evapotranspiration Index (SPEI). Arab J Geosci 13
Acknowledgements
The authors would like to thank the Iran National Science Foundation (INSF) for funding this research under Grant Number 96010915. We also acknowledge I.R. of Iran Meteorological Organization for providing some data used in this study.
Funding
This study was funded by Iran National Science Foundation (Grant Number 96010915).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Ethical Approval
Not applicable.
Consent to Participate
Not applicable.
Consent to Publish
Not applicable.
Competing Interests
The authors declare that they have no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Bazrafshan, J., Cheraghalizadeh, M. & Shahgholian, K. Development of a Non-stationary Standardized Precipitation Evapotranspiration Index (NSPEI) for Drought Monitoring in a Changing Climate. Water Resour Manage 36, 3523–3543 (2022). https://doi.org/10.1007/s11269-022-03209-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11269-022-03209-x