Analyzing time series of SPI, SPEI and SPTI drought indices by using artificial neural network SOFM method and numerical comparison in chaharmahal va bakhtiari

Document Type : Research Article


1 Assistant Professor, Faculty of New Sciences & Technologies, University of Tehran

2 University of Tehran


Analysis and comparison of drought indices are several of the studies needed to monitor and evaluate drought by multiple indicators. Drought evaluation is typically performed using climatic and hydrological parameters.
So far, several indices have been introduced to the analysis of this phenomenon. This paper in order to monitor drought in Chaharmahal and Bakhtiari province is compared to the Performance of three drought indicators, SPEI, SPI and SPTI. The basis of the comparison of indices is the use of the SOFM neural network, which by use of the results of the topology of this network, is resulted that the drought indices are in one category or not? Subsequently, the frequency analysis of drought classes and all types of drought analysis have been done. The results show that both numerical and SOFM methods can analyze and evaluate the outputs of drought indices, accurately. Also, according to the obtained results, the most severe period of drought had been occurred during the period between 1988 and 1990 in all three drought indices. On the other hand, the most severe drought was happened in this study in September 2003 based on the SPEI index at Behesht Abad Station with a value of -5.9. From other results of this paper can also be referred to the high sensitivity of the SPEI than two other drought indices in calculations.


Main Subjects

[1] Aswathanarayana U. Water resources management and the environment. CRC Press; 2001 Jan 1.
[2] Wilhite DA. Drought as a natural hazard: concepts and definitions.
[3] Watkins A. Planning for drought. InNew Mexico water planning conference proceedings. New Mexico water resources research institute report 2003 (No. 326).
[4] Schneider SH, Hare FK. Encyclopedia of climate and weather. New York: Oxford university press; 1996 Apr 25.
[5] Dracup JA, Lee KS, Paulson Jr EG. On the definition of droughts. Water resources research. 1980 Apr;16(2):297-302.
[6] Vicente-Serrano SM, López-Moreno JI. Hydrological response to different time scales of climatological drought: an evaluation of the Standardized Precipitation Index in a mountainous Mediterranean basin.
[7] Hao Z, Singh VP. Drought characterization from a multivariate perspective: A review. Journal of Hydrology. 2015 Aug 1;527:668-78.
[8] Zargar A, Sadiq R, Naser B, Khan FI. A review of drought indices. Environmental Reviews. 2011 Sep 13;19(NA):333-49.
[9] McKee TB, Doesken NJ, Kleist J. The relationship of drought frequency and duration to time scales. InProceedings of the 8th Conference on Applied Climatology 1993 Jan 17 (Vol. 17, No. 22, pp. 179-183). Boston, MA: American Meteorological Society.
[10] Vicente-Serrano SM, Beguería S, López-Moreno JI. A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. Journal of climate. 2010 Apr;23(7):1696-718.
[11] Ali Z, Hussain I, Faisal M, Nazir HM, Abd-el Moemen M, Hussain T, Shamsuddin S. A novel multi-scalar drought index for monitoring drought: the standardized precipitation temperature index. Water resources management. 2017 Dec 1;31(15):4957-69.
[12] Palmer WC (1965) ‘Meteorological drought.’ Research Paper No.45 (U.S. Department of Commerce, Weather Bureau: Washington, D.C.)
[13] Van Rooy MP. A rainfall anomaly index independent of time and space. Notos. 1965;14(43):6.
[14] Palmer WC. Keeping track of crop moisture conditions, nationwide: The new crop moisture index.
[15] Bhalme HN, Mooley DA. Large-scale droughts/floods and monsoon circulation. Monthly Weather Review. 1980 Aug;108(8):1197-211.
[16] Shafer BA. Developmnet of a surface water supply index (SWSI) to assess the severity of drought conditions in snowpack runoff areas. InProceedings of the 50th Annual Western Snow Conference, Colorado State University, Fort Collins, 1982 1982.
[17] Keyantash JA, Dracup JA. An aggregate drought index: Assessing drought severity based on fluctuations in the hydrologic cycle and surface water storage. Water Resources Research. 2004 Sep;40(9).
[18] Karamouz M, Rasouli K, Nazif S. Development of a hybrid index for drought prediction: case study. Journal of Hydrologic Engineering. 2009 Feb 18;14(6):617-27.
[19] Kao SC, Govindaraju RS. A copula-based joint deficit index for droughts. Journal of Hydrology. 2010 Jan 15;380(1-2):121-34.
[20] Hao Z, AghaKouchak A. A nonparametric multivariate multi-index drought monitoring framework. Journal of Hydrometeorology. 2014 Feb;15(1):89-101.
[21] Sohrabi MM, Ryu JH, Abatzoglou J, Tracy J. Development of soil moisture drought index to characterize droughts. Journal of Hydrologic Engineering. 2015 Mar 23;20(11):04015025.
[22] Tsakiris G, Loukas A, Pangalou D, Vangelis H, Tigkas D, Rossi G, Cancelliere A. Drought characterization. Drought management guidelines technical annex. 2007:85-102.
[23] Svoboda MD, Fuchs BA, Poulsen CC, Nothwehr JR. The drought risk atlas: enhancing decision support for drought risk management in the United States. Journal of Hydrology. 2015 Jul 1;526:274-86.
[24] Smakhtin VU, Schipper EL. Droughts: The impact of semantics and perceptions. Water Policy. 2008 Apr 1;10(2):131-43.
[25] Niemeyer S. New drought indices. Options Méditerranéennes. Série A: Séminaires Méditerranéens. 2008 Jun 12;80:267-74.
[26] Wilhite DA. Preparing for drought: A guidebook for developing countries. Diane Publishing; 1994.
[27] Sheffield J, Wood EF, Roderick ML. Little change in global drought over the past 60 years. Nature. 2012 Nov;491(7424):435.
[28] Beguería S, Vicente‐Serrano SM, Reig F, Latorre B. Standardized precipitation evapotranspiration index (SPEI) revisited: parameter fitting, evapotranspiration models, tools, datasets and drought monitoring. International Journal of Climatology. 2014 Aug;34(10):3001-23.
[29] Vicente-Serrano SM, Van der Schrier G, Beguería S, Azorin-Molina C, Lopez-Moreno JI. Contribution of precipitation and reference evapotranspiration to drought indices under different climates. Journal of Hydrology. 2015 Jul 1;526:42-54.
[30] Cavazos T. Using self-organizing maps to investigate extreme climate events: An application to wintertime precipitation in the Balkans. Journal of climate. 2000 May;13(10):1718-32.
[31] Chang FJ, Chang LC, Kao HS, Wu GR. Assessing the effort of meteorological variables for evaporation estimation by self-organizing map neural network. Journal of Hydrology. 2010 Apr 15;384(1-2):118-29.
[32] Farsadnia F, Kamrood MR, Nia AM, Modarres R, Bray MT, Han D, Sadatinejad J. Identification of homogeneous regions for regionalization of watersheds by two-level self-organizing feature maps. Journal of Hydrology. 2014 Feb 13;509:387-97.
[33] Dai A. Increasing drought under global warming in observations and models. Nature climate change. 2013 Jan;3(1):52.
Volume 6, Issue 3
September 2019
Pages 837-847
  • Receive Date: 21 April 2019
  • Revise Date: 06 August 2019
  • Accept Date: 06 August 2019
  • First Publish Date: 23 September 2019