Skip to main content

Drought indices for the Zagreb-Grič Observatory with an overview of drought damage in agriculture in Croatia

Abstract

The Standardized Precipitation Index (SPI) for different time scales of n = 1, 2, 3, 6, 9, 12, and 24 months and the monthly Palmer Drought Severity Index (PDSI) were calculated for the Zagreb-Grič Observatory, located in North-Western Croatia, for the period 1862–2012. The PDSI exhibits a stronger long-term negative trend than the SPI due to the influence of the global warming, which corresponds with the global scale results published in the 4th IPCC (Intergovernmental Panel on Climate Change) report. The SPI for a 9-month scale was compared with the PDSI for a monthly scale because the correlation between them is the highest in comparison with other SPI time scales. The Chapman percentile classification regarding dryness/wetness severity was used instead of the “originally” proposed classes. Thirty-year moving averages indicate that long-term variation in dryness/wetness severity is more clearly emphasised for the PDSI than for the SPI, showing the last 30-year period to be the driest on record. Autoregressive function analysis indicates that the SPI for a 1-month scale has serialy independent values, while the SPI for the 9-month scale and the monthly PDSI are close to a Markov process. A significant correlation was established between the SPI and PDSI indices and crop damages in Croatia.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Notes

  1. Details on the climate of Croatia are available in two climate atlases for the periods 1931–1960, 1961–1990, and 1971–2000, respectively, published by the DHMZ. The recent one covers the last two periods (Zaninović et al. 2008), and it is available at the DHMZ.

  2. The index also indicates wetness, when it has a positive sign, but it is not included in its name.

  3. Original Palmer (1965) PDSI calibration was used in this paper.

  4. In this study, precipitation totals are used.

  5. The months at the beginning of the period 1862–2012 for time scales higher than 1 month are the exceptions.

  6. Much higher resolution images similar to those shown in Fig. 11 were available to the authors.

References

  • Alley WM (1984) The Palmer severity index: limitations and assumptions. J Clim Appl Meteorol 23:1100–1109

    Article  Google Scholar 

  • Blauhut V, Gudmundsson L, Stahl K (2015) Towards pan-European drought risk maps: quantifying the link between drought indices and reported drought impacts. Environ Res Lett 10:14008. https://doi.org/10.1088/1748-9326/10/1/014008

    Article  Google Scholar 

  • Box GEP, Jenkins GM (1976) Time series analysis: Forecasting and control. Holden Day, San Francisco

  • Christensen JH, Hewitson B, Busuioc A, Chen A, Gao X, Held I, Jones R, Kolli RK, Kwon WT, Laprise R, Rueda VM, Mearns L, Menéndez CG, Räisänen J, Rinke A, Sarr A, Whetton P (2007) Regional climate projections. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Climate change. The physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge

    Google Scholar 

  • Cindrić K, Telišman Prtenjak M, Herceg Bulić I, Mihajlović D, Pasarić Z (2016) Analysis of the extraordinary 2011/2012 drought in Croatia. Theor Appl Climatol 123:503–522

    Article  Google Scholar 

  • Conrad V, Pollak LW (1950) Methods in climatology. Harvard University Press, Cambridge

    Book  Google Scholar 

  • Croatian Bureau of Statistic (2013) Statistical Yearbook of the Republic of Croatia 2013. Zagreb

  • Davis JM, Rappoport PN (1974) The use of time series analysis techniques in forecasting meteorological drought. Mon Weather Rev 102:176–180

    Article  Google Scholar 

  • Eagleman JR (1967) Pan evaporation, potential and actual evapotranspiration. J Appl Meteorol 6:482–488

    Article  Google Scholar 

  • Guttman NB (1989) Comparing the Palmer drought index and the standardized precipitation index. J Am Water Resour Assoc 34:113–121

    Article  Google Scholar 

  • Guttman NB (1999) Accepting the standardized precipitation index: a calculation algorithm. J Am Water Resour Assoc 35:311–322

    Article  Google Scholar 

  • Katz RW, Skaggs RH (1981) On the use of autoregressive-moving average processes to model meteorological time series. Mon Weather Rev 109:479–484

    Article  Google Scholar 

  • McKee TB, Doeksen NJ, Kleist J (1993) The relationship of drought frequency and duration of time scales. Proceedings of the 8-th Conference on Applied Climatology. American Meteorological Society, Anaheim, CA, Boston MA; 179–184, 17–22 January.

  • Mihajlović D (2006) Monitoring the 2003–2004 meteorological drought over Pannonian part of Croatia. Int J Climatol 26:2213–2225

    Article  Google Scholar 

  • Ministry of Agriculture (2005) National Project of Irrigation and Land and Water Management (in Croatian). Zagreb

  • Mishra AK, Desai VR (2005) Drought forecasting using stochastic models. Stoch Env Res Risk A 19:326–339

    Article  Google Scholar 

  • Palmer WC (1965) Meteorological drought. U.S. Department of Commerce Research Paper No. 45, Washington

  • Pandžić K, Likso T (2010) Homogeneity of average annual air temperature time series for Croatia. Int J Climatol 30:1215–1225

    Article  Google Scholar 

  • Pandžić K, Šimunić I, Tomić F, Husnjak S, Likso T, Petošić D (2006) Comparison of three mathematical models for the estimation of 10-day drain discharge. Theor Appl Climatol 85:107–115

    Article  Google Scholar 

  • Pandžić K, Trninić D, Likso T, Bošnjak T (2009) Long-term variations in water balance components for Croatia. Theor Appl Climatol 95:39–51

    Article  Google Scholar 

  • Paulo A, Martin D, Pereira LS (2016) Influence of precipitation changes on the SPI and related drought severity. An analysis using long-term data series. Water Resour Manag 30:15–5757. https://doi.org/10.1007/s11269-016-1388-5

    Article  Google Scholar 

  • Penzar B (1976) Drought severity Palmer’s indices for Zagreb and their statistical forecast (in Croatian). Papers and Presentations (Zagreb) 13:1–58

    Google Scholar 

  • Stagge JH, Kohn I, Tallaksen LM, Stahl K (2015) Modeling drought impact occurrence based on meteorological drought indices in Europe. J Hydrol 530:37–50

  • Sušnik A, Pogačar T, Gregorič G, Roškar J, Ceglar A (2010) Establishment of agricultural drought monitoring at different spatial scales in Southeastern Europe. Acta Agric Slov 95:231–243

    Article  Google Scholar 

  • Tadesse T, Senay G, Demisse GB (2011) Evaluation of Eta products for drought monitoring in Ethiopia. In: Nebraska Water Resources Center Annual Technical Report, University of Nebraska, Nebraska

  • Thornthwaite CW (1948) An approach toward a rational classification of climate. Geogr Rev 38:55–94

    Article  Google Scholar 

  • Trenberth KE, Jones PD, Ambenje P, Bojariu R, Easterling D, Tank AK, Parker D, Rahimzadeh F, Renwick JA, Rusticucci M, Soden B, Zhai P (2007) Observations: surface and atmospheric climate change. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Climate change. The physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge

    Google Scholar 

  • Vicente-Serrano SM (2006) Differences in spatial patterns of drought on different time scales: an analysis of the Iberian Peninsula. Water Resour Manag 20:37–60

    Article  Google Scholar 

  • 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

    Article  Google Scholar 

  • Wells N, Goddard S, Hayes MJ (2004) A self-calibrating Palmer Drought Severity Index. J Clim 17:2335–2351

    Article  Google Scholar 

  • Wilks DS (2006) Statistical methods in the atmospheric sciences. Elsevier Inc., London

    Google Scholar 

  • Zaninović K (ed) (2008) Climate Atlas of Croatia. Meteorological and Hydrological Service, Zagreb

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Krešo Pandžić.

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

Verify currency and authenticity via CrossMark

Cite this article

Pandžić, K., Likso, T., Curić, O. et al. Drought indices for the Zagreb-Grič Observatory with an overview of drought damage in agriculture in Croatia. Theor Appl Climatol 142, 555–567 (2020). https://doi.org/10.1007/s00704-020-03330-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00704-020-03330-0