Skip to main content

Advertisement

SpringerLink
Log in

Three-dimensional risk analysis of hydro-meteorological drought using multivariate nonlinear index

  • Original Paper
  • Published:
Theoretical and Applied Climatology Aims and scope Submit manuscript

Abstract

Applying combined nonlinear indices is a useful approach in assessing drought condition. This study investigates a combined multivariate index (Joint Deficit Hydro-meteorological Index: JDHMI) in monitoring hydro-meteorological drought to determine whether the index could simultaneously reflect the complicated nonlinear behavior of precipitation and runoff in a watershed. The JDMI (JDHI) index is obtained on the basis of the joint marginal distribution of SPImod1,…, SPImod12 (SRImod1,…, SRImod12) using the empirical copula. The JDHMI then is computed by combining the JDMI and JDHI indices using a suitable theoretical copula. Furthermore, drought characteristics (severity-duration-magnitude) are extracted from the JDHMI and trivariate conditional return periods that are obtained from three-dimensional copulas in four different scenarios. Results of this study indicate that (1) multivariate copulas effectively reflect the complicated and nonlinear relationship between drought variables; (2) comparison between univariate and multivariate drought indices indicated that the JDHMI is slightly more sensitive to the historical events; and (3) spatial distribution of drought hazard is illustrated using conditional return period obtained in four different scenarios in Bandar-Sedij and Kole-Mehran watershed. Additionally, the conditional probabilities provide effective information for forecasting drought conditions. In this regards, on the basis of several specific values of S-D-M, it is estimated that the central and eastern parts of the region will experience frequent hydro-meteorological drought over next 18 years. Finally, due to the climatic changing in the recent years, findings of this study could be useful in reducing drought effects on the natural resources and also help decision-makers in developing water resources.

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
Fig. 10
Fig. 11

Similar content being viewed by others

References

  • Bazrafshan O, Mahmudzadeh F, Bazrafshan J (2017) Evaluation of temporal trends of the drought indices SPI and SPEI in the Southern Coast of Iran. Desert Management 4(8):54–69

    Google Scholar 

  • Bazrafshan O, Zamani H, Shekari M (2019) A copula-based index for drought analysis in arid and semi-arid regions of Iran. Nat Resour Model 33:e12237

    Google Scholar 

  • Bazrafshan, O., Zamani, H., Shekari, M., & Singh, V. P. (2020). Regional risk analysis and derivation of copula-based drought for severity-duration curve in arid and semi-arid regions. Theor Appl Climatol, 1-17

  • Borji M, Malekian A, Salajegheh A, Ghadimi M (2016) Multi-time-scale analysis of hydrological drought forecasting using support vector regression (SVR) and artificial neural networks (ANN). Arab J Geosci 9(19):725

    Article  Google Scholar 

  • Byun HR, Wilhite DA (1999) Objective quantification of drought severity and duration. J Clim 12(9):2747–2759

    Article  Google Scholar 

  • Chen, X., Li, F. W., Li, J. Z., & Feng, P. (2019). Three-dimensional identification of hydrological drought and multivariate drought risk probability assessment in the Luanhe River basin, China. Theor Appl Climatol, 1-22

  • Choubin B, Khalighi-Sigaroodi S, Malekian A, Ahmad S, Attarod P (2014) Drought forecasting in a semi-arid watershed using climate signals: a neuro-fuzzy modeling approach. J Mt Sci 11(6):1593–1605

    Article  Google Scholar 

  • Choubin B, Malekian A, Golshan M (2016) Application of several data-driven techniques to predict a standardized precipitation index. Atmósfera 29(2):121–128

    Article  Google Scholar 

  • Cohen J (1968) Weighted kappa: nominal scale agreement provision for scaled disagreement or partial credit. Psychol Bull 70(4):213–220

    Article  Google Scholar 

  • Dracup JA, Lee KS, Paulson EG Jr (1980) On the statistical characteristics of drought events. Water Resour Res 16(2):289–296

    Article  Google Scholar 

  • Eghtedar Nezhad M, Bazrafshan O, Bazrafshan J (2018) Spatio-temporal variations of meteorological drought using standardized precipitation evapotranspiration index in Iran. J Agric Meteorol 5(2):35–46

  • Eslamian S (ed) (2014) Handbook of engineering hydrology: modeling, climate change, and variability. CRC Press, London

    Google Scholar 

  • Farid R. 2006. Bivariate frequency analysis of regional drought characteristics Ph.D. thesis, University of Waterloo. Canada

  • Genest C, Rivest LP (1993) Statistical inference procedures for bivariate Archimedean copulas. J Am Stat Assoc 88(423):1034–1043

    Article  Google Scholar 

  • Genest C, Rémillard B, Beaudoin D (2009) Goodness-of-fit tests for copulas: a review and a power study. Insurance: Mathematics and economics 44(2):199–213

    Google Scholar 

  • Hao Z, AghaKouchak A (2013) Multivariate standardized drought index: a parametric multi-index model. Adv Water Resour 57:12–18

    Article  Google Scholar 

  • Hao Z, Singh VP (2012) Entropy‐copula method for single‐site monthly streamflow simulation. Water Resour Res 48(6)

  • Hao Z, Singh VP (2015) Drought characterization from a multivariate perspective: a review. J Hydrol 527:668–678

    Article  Google Scholar 

  • Hofert M, Mächler M (2011) Nested Archimedean copulas meet R: the nacopula package. J Stat Softw 39(9):1–20

    Article  Google Scholar 

  • Hui-Mean F, Yusof F, Yusop Z, Suhaila J (2019) Trivariate copula in drought analysis: a case study in peninsular Malaysia. Theor Appl Climatol:1–15

  • Kao SC, Govindaraju RS (2010a) A copulabased joint deficit index for droughts. J Hydrol 380:121–134

    Article  Google Scholar 

  • Kao SC, Govindaraju RS (2010b) Reply to comment by TP Hutchinson on “Trivariate statistical analysis of extreme rainfall events via the Plackett family of copulas”. Water Resour Res 46(4)

  • Kazemzadeh M, Malekian A (2016) Spatial characteristics and temporal trends of meteorological and hydrological droughts in northwestern Iran. Nat Hazards 80(1):191–210

    Article  Google Scholar 

  • Liu Y, Zhu Y, Ren L, Yong B, Singh VP, Yuan F, Jiang S, Yang X (2019) On the mechanisms of two composite methods for construction of multivariate drought indices. Sci Total Environ 647:981–991

    Article  Google Scholar 

  • McKee TE (2003) Rough sets bankruptcy prediction models versus auditor signalling rates. J Forecast 22(8):569–586

    Article  Google Scholar 

  • McKee, T. B., Doesken, N. J., & Kleist, J. (1993). The relationship of drought frequency and duration to time scales. In Proceedings of the 8th Conference on Applied Climatology, 17(22), 179–184

  • Mirabbasi R, Anagnostou EN, Fakheri-Fard A, Dinpashoh Y, Eslamian S (2013) Analysis of meteorological drought in Northwest Iran using the Joint Deficit Index. J Hydrol 492:35–48

    Article  Google Scholar 

  • Mishra AK, Singh VP (2010) A review of drought concepts. J Hydrol 391:202–216

    Article  Google Scholar 

  • Moradi M, Bazrafshan O, Bahreman A, Esmaelpour Y (2018) Assessment of the relations between the trends of climatic factors and river flow in southern coastal watersheds, Iran. Watershed Management Researches Journal 31(2):79–92

    Google Scholar 

  • Nalbantis I, Tsakiris G (2009) Assessment of hydrological drought revisited. Water Resour Manag 23(5):881–897

    Article  Google Scholar 

  • Naresh Kumar M, Murthy CS, Sesha Sai MVR, Roy PS (2009) On the use of standardized precipitation index (SPI) for drought intensity assessment. Meteorological Applications 16(3):381–389

    Article  Google Scholar 

  • Nasrollahi M, Khosravi H, Moghaddamnia A, Malekian A, Shahid S (2018) Assessment of drought risk index using drought hazard and vulnerability indices. Arab J Geosci 11(20):606

    Article  Google Scholar 

  • Nelsen RB (2006) An introduction to copulas. Springer, New York, 269 pp

    Google Scholar 

  • Obasi GOP (1994) WMO’s role in the international decade for natural disaster reduction. Bull Am Meteorol Soc 75(9):1655–1661

    Article  Google Scholar 

  • Quiring SM (2009) Developing objective operational definitions for monitoring drought. J Appl Meteorol Climatol 48(6):1217–1229

    Article  Google Scholar 

  • Salvadori G, De Michele C (2004) Frequency analysis via copulas: theoretical aspects and applications to hydrological events. Water Resour Res 40(12)

  • Saravi MM, Safdari AA, Malekian A (2009) Intensity-duration-frequency and spatial analysis of droughts using the Standardized Precipitation Index. Hydrology & Earth System Sciences Discussions 6(2)

  • Shiau JT (2006) Fitting drought duration and severity with two-dimensional copulas. Water Resour Manag 20(5):795–815

    Article  Google Scholar 

  • Shukla S, Wood AW (2008) Use of a standardized runoff index for characterizing hydrologic drought. Geophys Res Lett 35:L02405

    Article  Google Scholar 

  • Sklar A (1959) Distribution functions of n dimensions and margins, vol 8. Publications of the Institute of Statistics of the University of Paris, Paris, pp 229–231

    Google Scholar 

  • Trinh T, Ishida K, Kavvas ML, Ercan A, Carr K (2017) Assessment of 21st century drought conditions at Shasta dam based on dynamically projected water supply conditions by a regional climate model coupled with a physically-based hydrology model. Science Total Environ 586:197–205

    Article  Google Scholar 

  • Wilhite DA, Svoboda MD, Hayes MJ (2006) Understanding the complex impacts of drought: a key to enhancing drought mitigation and preparedness. Water Resour Manag 21:763–774

    Article  Google Scholar 

  • Wong G, Lambert MF, Metcalfe AV (2008) Trivariate copulas for characterization of droughts. Anziam J 49:306–323

    Article  Google Scholar 

  • Yang J, Chang J, Wang Y, Li Y, Hu H, Chen Y, Huang Q, Yao J (2018) Comprehensive drought characteristics analysis based on a nonlinear multivariate drought index. J Hydrol 557:651–667

    Article  Google Scholar 

  • Zamani H, Bazrafshan O (2020) Modeling monthly rainfall data using zero-adjusted models in the semi-arid, arid and extra-arid regions. Meteorog Atmos Phys 132(2):239–253

    Article  Google Scholar 

  • Zargar A, Sadiq R, Naser B, Khan FI (2011) A review of drought indices. Environ. Rev. 19(NA):333–349

    Article  Google Scholar 

Download references

Acknowledgements

The authors truly appreciate the Research Deputy, University of Hormozgan for their collaboration and I.R Iran Meteorological Organization (IRIMO) for related data.

Author information

Authors and Affiliations

  1. Department of Natural Resources Engineering, Faculty of Agriculture and Natural Resources, University of Hormozgan, P.O. BOX: 3995, Bandar-Abbas, Iran

    Zahra Azhdari & Ommolbanin Bazrafshan

  2. Department of Mathematics and Statistics, Faculty of Science, University of Hormozgan, P.O. BOX: 3995, Bandar-Abbas, Iran

    Marzieh Shekari & Hossein Zamani

Authors
  1. Zahra Azhdari
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ommolbanin Bazrafshan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Marzieh Shekari
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hossein Zamani
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Ommolbanin Bazrafshan or Hossein Zamani.

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

Azhdari, Z., Bazrafshan, O., Shekari, M. et al. Three-dimensional risk analysis of hydro-meteorological drought using multivariate nonlinear index. Theor Appl Climatol 142, 1311–1327 (2020). https://doi.org/10.1007/s00704-020-03365-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00704-020-03365-3

Keywords

Search

Navigation