Skip to main content

Advertisement

SpringerLink
Log in

Modeling and Monitoring of Drought for forecasting it, to Reduce Natural hazards Atmosphere in western and north western part of Iran, Iran

  • Published:
Air Quality, Atmosphere & Health Aims and scope Submit manuscript

Abstract

The phenomenon of drought has a lot of damage every year in different parts of human life. The drought is not specific to the region, and it affects different parts of the world. One of these areas is Northwest of Iran, which suffered from this phenomenon in recent years. The purpose of this study is to model, analyze, and predict the drought in Northwest of Iran. To do this, climatic parameters (precipitation, temperature, sunshine, minimum relative humidity, and wind speed) of 21 stations were used in the period of 32 years (1987–2018). For modeling of the TIBI fuzzy index, first, four indicators (SET, SPI, SEB, and MCZI) were been fuzzy in MATLAB software. Then, the indices were compared and the Topsis model was used for prioritizing areas involved with drought. Results showed that the new fuzzy index of T.I.B.I. for classifying drought reflected four above indicators with high accuracy. Of these five climatic parameters used in this study, the temperature parameter had the most effect on the fluctuation of drought severity. The severity of the drought was more based on a 12-month scale modeling than 6 months. The longest drought persistence in the study area occurred in Urmia Station in the 12-month period from July 2003 to December 2004. The highest percentage of drought occurrence was at Urmia station on a 12-month scale and the lowest was in Sanandaj station on a 6-month scale.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Notes

  1. Adaptive Neuro-Fuzzy Inference System

References

  • Adib A, Georgian AZ (2016) Drought monitoring and monitoring using drought indices. Iran Irrigation Water Eng 8:173–185 [In Persian]

    Google Scholar 

  • Ahmadzadeh G, Majid L, Kourosh M (2010) Comparison of artificial intelligence systems (ANN and ANFIS) in estimating the rate of transpiration of reference plants in very dry regions of Iran. J Water Soil 2:679–689 [In Persian]

    Google Scholar 

  • Alirreza N, Pål G, Helen K, Anders L, Per L (2019) Use of TEOM monitors for continuous long-term sampling of ambient particles for analysis of constituents and biological effects. Air Qual Atmosphere Health 12:161–171. https://doi.org/10.1007/s11869-018-0638-5

    Article  CAS  Google Scholar 

  • Alizadeh S, Mohammadi H, Kordvani P (2017) Modeling the dispersion of drought caused by climate change in Iran using dynamic system. Land Expansion 9:169–188 [In Persian]

    Google Scholar 

  • Ansari H, Davari K, Sanaeenejad SH (2010) Drought monitoring using SEPI standardized rainfall and sedimentation index, developed on the basis of fuzzy logic. Journal of Soil and Water (Agricultural Sciences and Technology) 1:38–52

    Google Scholar 

  • Armando L, Santos MS (2015) Use of two indicators for the socio-environmental risk analysis of northern Mexico under three climate change scenarios. Air Qual Atmos Health 8:331–345. https://doi.org/10.1007/s11869-014-0286-3

    Article  Google Scholar 

  • Bandyopadhyay N, Bhuiyan C, Saha AK (2019) Drought mitigation: critical analysis and proposal for a new drought policy with special reference to Gujarat (India). Progress Disaster Sci 22:10–49. https://doi.org/10.1016/j.pdisas.2019.100049

    Article  Google Scholar 

  • Bayazidi M (2018) Drought evaluation of synoptic stations in the west of Iran using the Herbst method and comparative neuro-fuzzy model. Iran Water Resources Research 14:278–284 [In Persian]

    Google Scholar 

  • Cammalleri C, Micale F, Vogt J (2015) On the value of combining different modelled soil moisture products for European drought monitoring. J Hydrol 525:547–558. https://doi.org/10.1016/j.jhydrol.2015.04.021

    Article  Google Scholar 

  • Damavandi AA, Rahimi M, Yazdani MR, Norouzi AA (2016) Field monitoring of agricultural drought through time series of NDVI and LST indicators. MODIS data (case study: Markazi province). Geographic Inf Res (Sepehr) 25:115–126 [In Persian]

    Google Scholar 

  • Ekhtiari khajeh S, Dinpazhoh Y (2018) Application of the Effective Drought Index (EDI) for studying dry periods (Tabriz, Bandar Anzali and Zahedan stations). Irrigation Sci Engi 1:133–145

    Google Scholar 

  • Fanni Z, Khalilalahi HA, Sajjadi J, Falsleman M (2016) Analysis of the causes and consequences of drought in South Khorasan Province and Birjand. J Plann Space Des 20:175–200 [In Persian]

    Google Scholar 

  • Fathi-Zadeh H, Gholami-nia A, Mobin M, Soodyzizadeh H (2017) Investigating the relationship between meteorological drought and solar variables in some Iranian standards. Environ Hazards 17:63–87 [In Persian]

    Google Scholar 

  • Gholam Ali M, Younes K, Esmaeil H, Fatemeh T (2011) Assessment of geostatistical methods for spatial analysis of SPI and EDI drought indices. World Appl Sci J 15:474–482

    Google Scholar 

  • Haddadi H, Heidari H (2015) Detection of the effect of precipitation fluctuations on surface water flood in Lake Urmia catchment basin. Geogr Environ Plann 57:247–262 [In Persian]

    Google Scholar 

  • Hao Z, Hao F, Singh V, Xia Y, Xinyishen O (2016) A theoretical drought classification method for the multivariate drought index based on distribution properties of standardized drought indices. Adv Water Resour 14:240–247

    Google Scholar 

  • Harry W, Nevil Q, Michael H (2019) Remote sensing for drought monitoring & impact assessment: Progress, past challenges and future opportunities. Remote Sens Environ 232:111–291. https://doi.org/10.1016/j.rse.2019.111291

    Article  Google Scholar 

  • Huanga S, Huanga Q, Changa J, Zhua Y, Lengb G (2016) Drought structure based on a nonparametric multivariate standardized drought index across the Yellow River basin China. J Hydrol 530:127–136

    Google Scholar 

  • Huiqian Y, Qiang Z, Chong-Yu X, Juan D, Peng S, Pan H (2019) Modified palmer drought severity index: model improvement and application. Environ Int 130:104–951. https://doi.org/10.1016/j.envint.2019.104951

    Article  Google Scholar 

  • Jafar Nejad A, Kia S.M (2010) Fuzzy Logic in MATLAB. Kian Rayaneh Sabz publication 4: 157–180

  • Jafari H, Bakhtiari F, Dostkamian M (2018) Analysis of the spatial association of droughts with the watershed water flow of Ghezel Ozan basin. Geography and Development 15:79–94

    Google Scholar 

  • Jan Darmian I, Shakiba A, Nasseri H (2015) Study of drought status and its relationship with quantitative and qualitative changes in groundwater in Sarab plain, international conference on development, focusing on agriculture. Environment and Tourism, Iran, Tabriz 7:16–17 [In Persian]

    Google Scholar 

  • Jinum M, Jeonbin K (2017) Evaluatin historical drought charactristics simulated in Cordexast Asia against observations. Int J Climatol 25:32–43

    Google Scholar 

  • Jonilda K, Georgios G, Yiannis P, Theodoros C, Philippe T, Chrysanthos S, Christos P, Jos L (2019) Evaluation of EU air quality standards through modeling and the FAIRMODE benchmarking methodology. Air Quality, Atmosphere & Health 12:73–86. https://doi.org/10.1007/s11869-018-0631-z

    Article  CAS  Google Scholar 

  • Junfang Z, Jingwen X, Xingmei X, Houquan L (2016) Drought monitoring based on TIGGE and distributed hydrological model in Huaihe River Basin, China. Sci Total Environ 553:358–365. https://doi.org/10.1016/j.scitotenv.2016.02.115

    Article  CAS  Google Scholar 

  • Keshtkarisani S (2015) Drought study in West Azarbaijan province with Spi and Gis Index, International Conference on Agricultural. Environment and Tourism, Iran, Tabriz 4:16–19

    Google Scholar 

  • Kinga W, Anita UL, Marta S (2019) Air quality at two stations (Gdynia and Rumia) located in the region of gulf of Gdansk during periods of intensive smog in Poland. Air Quality, Atmosphere & Health 12:879–890. https://doi.org/10.1007/s11869-019-00708-6

    Article  CAS  Google Scholar 

  • Kis A, Rita P, Judit B (2017) Multi- model analysis of regional dry and wet condition for the Carpatian region. Int J Climatol 17:4543–4560

    Google Scholar 

  • Konarkuhi A, SoleimanJahi H, Falahi S, Riahimadvar H, Meshkat Z (2010) Using the new intelligent fuzzy-neural recognition inventory system (ANFIS) to predict the human cannibalization potential of human papilloma virus. Journal of Arak University of Science and Technology 13:95–105 [In Persian]

    Google Scholar 

  • Liu M, Xianli X, Sun Y, Lexander A, Kelin W (2017) Decreasing spatial variability of drought in south West China during 1959-2013. Int J Climatol 21:4610–4619

    Google Scholar 

  • Makvandi R, Maghsoudlo-Kamali B, Mohammadfam I (2012) Utilization of TOPSIS multivariate decision making model for assessing the environmental consequences of oil refineries (case study: Khuzestan extra heavy oil refinery). Environ Stud 3:77–86 [In Persian]

    Google Scholar 

  • Martha A, Carmelo C, Christopher H, Jason O, Xiwu Z, William K (2013) Using a diagnostic soil-plant-atmosphere model for monitoring drought at field to continental scales. Procedia Environ Sci 19:47–56. https://doi.org/10.1016/j.proenv.2013.06.006

    Article  Google Scholar 

  • Mirzaee F, IraqiNezhad S, Big-Haddad A (2015) Development of WEAP integrated water model model for drought condition modeling. J Eng Watershed Manag 7:85–97 [In Persian]

    Google Scholar 

  • Modaresirad A, Ghahramani B, Khalili D, Ghahramani Z, Ahmadiardakani S (2017) Integrated meteorological and hydrological drought model: a management tool for proactive water resources planning of semi-arid regions. Adv Water Resour 54:336–353

    Google Scholar 

  • Montaseri M, Amirataee B (2015) Stochastic estimation of drought prevalence (case study: northwest of Iran). Journal of Civil and Environmental Engineering 3:12–26 [In Persian]

    Google Scholar 

  • Montaseri M, Norjo A, Bahmanesh J, Akbari M (2018) Wet season and meteorological drought in southern basins of Lake Urmia. Ecoehydrology 1:189–202

    Google Scholar 

  • Moradi H, Tayyi M, Ghasemian D, Chesghi J, Bahari R (2008) Simulation and analysis of the relationship between water and climate droughts using probabilistic models of Babol plain. Iran Watershed Association 2(5):71–74 [In Persian]

    Google Scholar 

  • Mulchsfaki Y (2006) Geographic information system and multi-criteria decision analysis, translated by Akbar Parizgar. Ata Ghafari flooded. Tehran. Publishing Side 4:551–563 [In Persian]

    Google Scholar 

  • Nazmfar H, Amina A (2014) Measurement of spatial inequality in using educational indices using Topsis method (case study: Khorestan Province). Two Chapters of Educational Planning Studies 3:115–134 [In Persian]

    Google Scholar 

  • Nourani V, Amir M (2017) Application of a hybrid association rules/decision tree model for drought monitoring. Glob Planet Chang 159:37–45. https://doi.org/10.1016/j.gloplacha.2017.10.008

    Article  Google Scholar 

  • Olusola A, Jiahua W (2019) Appraising regional multi-category and multi-scalar drought monitoring using standardized moisture anomaly index (SZI): a water-energy balance approach. J Hydrol 579:124–139. https://doi.org/10.1016/j.jhydrol.2019.124139

    Article  Google Scholar 

  • Parsa-Mehr AH, Khosravani Z (2017) Determination of drought determination using multi-criteria decision making based on TOPSIS. Research on Pasture and Desert of Iran 24:16–29

    Google Scholar 

  • Perovi R, Alidadi H, Javid A, Najafpour AS (2015) Modeling the effect of drought on total hardness and solids of groundwater in Mashhad plain. J Environ Health Res 1:85–94 [In Persian]

    Google Scholar 

  • Qamasi M, MalekMohammadi M, Montaseri H (2016) Drought prediction with SPI and EDI index using ANFIS modeling method in Kohgiluyeh and Boyerahmad province. Agricultural Meteorology Journal 1:36–47

    Google Scholar 

  • Quesada B, Giuliano M, Asarre D, Rangecoft S, Vanloon A (2017) Hydrological change: toward a consistent approach to assess changes on both floods and droughts. Adv Water Resour 5:31–35

    Google Scholar 

  • Runping S, Anqi H, BolunLi JG (2019) Construction of a drought monitoring model using deep learning based on multi-source remote sensing data. Int J Appl Earth Obs Geoinf 79:48–57. https://doi.org/10.1016/j.jag.2019.03.006

    Article  Google Scholar 

  • Salahi B, Mojtabapour F (2016) Spatial analysis of climate drought in northwest of Iran using spatial correlations statistics. Journal of Environmental Spatial Spatial Analysis 3:1–20 [In Persian]

    Google Scholar 

  • Salajeghe A, Fathabadi A (2009) Investigating the possibility of estimating the suspended load of Karaj River using fuzzy logic and neural network. Journal of Rangeland and Watershed Management (Iranian Journal of Natural Resources) 2:271–282

    Google Scholar 

  • Samidianfard S, Asadi I (2018) Projection of SPI drought index by multiple regression and supportive vector regression methods. Water and Soil Conservation 6:1–16

    Google Scholar 

  • Shamsniya A, Pirmoradian N, Amiri N (2008) Drought modeling in Fars Province using time series analysis. Geography and Planning 28:165–189

    Google Scholar 

  • Shokri-kouchak S, Behnia AS (2013) Monitoring and drought stress in Khuzestan province using Markov chain SPI index. Journal of Science and Environmental Sciences 5:41–52 [In Persian]

    Google Scholar 

  • Sobhani B, Safarianzengir V (2018) Investigating and predicting the risk of monthly rainfed exposure to horticultural and agricultural products in the northern strip of Iran (Golestan, Gilan and Mazandaran provinces). J environ spat anal 5:125–144[in Persian]

  • Sobhani B, GhafariGilandeh A, Golvost A (2015) Drought monitoring in Ardebil province using the developed SEPI index based on fuzzy logic. Journal of Applied Geosciences Research 15:51–72 [In Persian]

    Google Scholar 

  • Spinoni J, Naumann G, Vogt J, Barbosa P (2015) The biggest drought events in Europe from 1950–2012. journal of hydrology: Regional 3:509–524

    Google Scholar 

  • Torabipodeh H, Shahinejad B, Dehghani R (2018) Drought estimation using smart networks. Hydrogeomorphology. 14:179–197

    Google Scholar 

  • Touma D, Ashfaq M, Nayak M, Kao S-C, Diffenbaugh N (2015) A multi-model and multi-index evaluation of drought characteristics in the 21st century. J Hydrol 526:196–207

    Google Scholar 

  • Wenzhe J, Chao T, Qing C, Kimberly N, Lixin W (2019a) A new multi-sensor integrated index for drought monitoring. Agric For Meteorol 268:74–85. https://doi.org/10.1016/j.agrformet.2019.01.008

    Article  Google Scholar 

  • Wenzhe J, Lixin W, Kimberly N, Qing C (2019b) A new station-enabled multi-sensor integrated index for drought monitoring. J Hydrol 574:169–180. https://doi.org/10.1016/j.jhydrol.2019.04.037

    Article  Google Scholar 

  • Xiao L, Ping G, Qian T, Jingfeng X, Yifan L, Yikuan T (2019) Drought risk evaluation model with interval number ranking and its application. Science of The Total Environmen 685:1042–1057. https://doi.org/10.1016/j.scitotenv.2019.06.260

    Article  CAS  Google Scholar 

  • Yarahmadi D (2014) Hydroclimatic analysis of water level fluctuations in Lake Urmia. Journal of Natural Geography 46:77–92

    Google Scholar 

  • Yunjun Y, Shunlin L, Qiming Q, Kaicun W, Shaohua Z (2011) Monitoring global land surface drought based on a hybrid evapotranspiration model. Int J Appl Earth Obs Geoinf 13:447–457. https://doi.org/10.1016/j.jag.2010.09.009

    Article  Google Scholar 

  • Zahiri AS, Sharifan H, Arakashi F, Rahimian M (2014) Evaluation of drought and drought phenomena in Khorasan province using indices of PNPI, SPI, NITZCHE. Irrigation and drainage journal of Iran 2:865–845 [In Persian]

    Google Scholar 

  • Zeinali B, SafarianZengir V (2017) Drought monitoring in Urmia Lake Basin using fuzzy index. Journal of environmental risks 6: 37-62. [in Persian]. https://doi.org/10.22111/jneh.2017.3075

  • Zeinali B, Asghari S, SafarianZengir V (2017) Drought monitoring and assessment of its prediction in Lake Urmia Basin using SEPT and ANFIS model. Environmental Impact Analysis Spatial Analysis Journal 4:73–96 [In Persian] http://jsaeh.khu.ac.ir/article-1-2695-fa.html

    Google Scholar 

  • Zelekei T, Giorgi T, Diro F, Zaitchik B (2017) Trend and periodicity of drought over Ethiopia. Int J Climatol 65:4733–4748

    Google Scholar 

  • Zengchao H, Fanghua H, Vijay S, Wei O, Hongguang C (2017) An integrated package for drought monitoring, prediction and analysis to aid drought modeling and assessment. Environ Model Softw 91:199–209. https://doi.org/10.1016/j.envsoft.2017.02.008

    Article  Google Scholar 

  • Zexi S, Qiang Z, Vijay S, Peng S, Changqing S, Huiqian Y (2019) Agricultural drought monitoring across Inner Mongolia, China: model development, spatiotemporal patterns and impacts. J Hydrol 571:793–804. https://doi.org/10.1016/j.jhydrol.2019.02.028

    Article  Google Scholar 

  • Zolfaghari H, Nouri Z (2016) Application of drought index (CPEL) in determining proper variables for drought analysis in Iran. Journal of Spatial Analysis of Environmental Hazards 3:99–114 [In Persian]

    Google Scholar 

Download references

Acknowledgments

The authors would like to thank the I.R. of Iran Meteorological Organization (IRIMO) for providing the meteorological data for this study. We also would like to thank Prof. Majid Rezaei Banafsheh for writing support.

Funding

The authors were supported by Tabriz University.

Author information

Authors and Affiliations

  1. Department of Physical Geography, Climatology, Faculty of Literature and Humanities, University of Mohaghegh Ardabili, Ardabil, Iran

    Vahid SafarianZengir

  2. Department of Physical Geography, Climatology, Faculty of Literature and Humanities, University of Mohaghegh Ardabili, Ardabil, Iran

    Behroz Sobhani

  3. Department of Geomorphology, University of Mohaghegh Ardabili, Ardabil, Iran

    Sayad. Asghari

Authors
  1. Vahid SafarianZengir
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Behroz Sobhani
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sayad. Asghari
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Behroz Sobhani.

Ethics declarations

Conflict of interest

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

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

SafarianZengir, V., Sobhani, B. & Asghari, S. Modeling and Monitoring of Drought for forecasting it, to Reduce Natural hazards Atmosphere in western and north western part of Iran, Iran. Air Qual Atmos Health 13, 119–130 (2020). https://doi.org/10.1007/s11869-019-00776-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11869-019-00776-8

Keywords

Search

Navigation