Skip to main content

Advertisement

Log in

Vulnerability of Bulgarian agriculture to drought and climate variability with focus on rainfed maize systems

  • Original Paper
  • Published:
Natural Hazards Aims and scope Submit manuscript

Abstract

Bulgarian agriculture is affected by droughts and, likely, by climate change. Thus, aiming at assessing its vulnerability, this study includes a general characterization of climate variability in eight selected locations, both in northern and southern Bulgaria. Trend tests were applied to monthly precipitation, maximum and minimum temperature and to the Standardized Precipitation Index with two-month time step (SPI-2) relative to the period of 1951–2004. Negative trends were identified for precipitation and SPI-2 at various locations, mainly in the Thrace Plain, indicating that dryness is likely to be increasing in Bulgaria. The vulnerability of rainfed maize systems to drought was studied using the previously calibrated WinISAREG model and the Stewart’s yield model to compute both the relative yield decrease (RYD) due to water stress and the corresponding net irrigation required to overcome those losses. Results identified a strong relation between SPI-2 for July–August (SPI-2July–Aug) and RYD. Results also show that yield losses are higher when the soils have a smaller soil water holding capacity. For the various regions under study, thresholds for RYD were defined considering the related economic impacts and the influence of soil characteristics on the vulnerability of the rainfed maize systems. Finally, to support drought risk management, SPI-2July–Aug thresholds were developed to be used as indicators of the economic risk of rainfed maize for various climate regions and soil groups in Bulgaria.

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

Access this article

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

Instant access to the full article PDF.

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

Similar content being viewed by others

References

  • Alexandrov V (1999) Vulnerability and adaptation of agronomic systems in Bulgaria. Clim Res 12:161–173

    Article  Google Scholar 

  • Alexandrov V (ed) (2011) Methods for monitoring and estimation of drought vulnerability in Bulgaria. National Institute of Meteorology and Hydrology and Bulgarian Academy of Sciences, Sofia, 216 (in Bulgarian)

  • Alexandrov VA, Hoogenboom G (2000) The impact of climate variability and change on crop yield in Bulgaria. Agric For Meteorol 104:315–327

    Article  Google Scholar 

  • Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration—guidelines for computing crop water requirements. Irrigation and drainage paper 56, FAO, Rome

  • Boneva K (2012) Study on soil characteristics related to calibration and use of “crop-water-yield” simulation models. In: Z Popova (ed) Risk assessment of drought in agriculture and irrigation management through simulation models. “N. Poushkarov” Institute of Soil Science, Sofia, pp 141–165 (in Bulgarian)

  • Bordi I, Sutera A (2004) Drought variability and its climatic implications. Glob Plan Chang 40:115–127

    Article  Google Scholar 

  • Bordi I, Fraedrich K, Sutera A (2009) Observed drought and wetness trends in Europe: an update. Hydrol Earth Syst Sci 13:1519–1530

    Article  Google Scholar 

  • Çakir R (2004) Effect of water stress at different development stages on vegetative and reproductive growth of corn. Field Crops Res 89:1–16

    Article  Google Scholar 

  • Conde C, Liverman D, Flores M, Ferrer R, Araújo R, Betancourt E, Villarreall G, Gay C (1997) Vulnerability of rainfed maize crops in Mexico to climate change. Clim Res 9:17–23

    Article  Google Scholar 

  • Doorenbos J, Kassam AH (1979) Yield response to water. Irrigation and drainage paper 33, FAO, Rome

  • Doorenbos J, Pruitt WO (1977) Crop water requirements. Irrigation and drainage paper 24. FAO, Rome

  • Dow K (2010) News coverage of drought impacts and vulnerability in the US Carolinas, 1998–2007. Nat Hazards 54:497–518

    Article  Google Scholar 

  • Eneva S (1997) Irrigation and irrigation effect on field crops. Problems of crop production science and practice in Bulgaria. Agricultural University of Plovdiv (in Bulgarian)

  • Fraser ED, Simelton E, Termansen M, Gosling SN, South A (2013) “Vulnerability hotspots”: integrating socio-economic and hydrological models to identify where cereal production may decline in the future due to climate change induced drought. Agric For Meteorol 170:195–205

    Article  Google Scholar 

  • Gregoric G (ed) (2012) Drought management centre for South-East Europe—DMCSEE. Summary of project results, Slovenian Environmental Agency, Ljubljana. http://www.met.hu/doc/DMCSEE/DMCSEE_final_publication.pdf

  • Guttman NB (1998) Comparing the Palmer drought index and the standardised precipitation index. J Am Water Res As 34:113–121

    Article  Google Scholar 

  • Hamed KH, Rao RA (1998) A modified Mann Kendall test for autocorrelated data. J Hydrol 204:182–196

    Article  Google Scholar 

  • Helsel DR, Hirsch RM (1992) Statistical methods in water resources. Elsevier, Amsterdam

    Google Scholar 

  • Hlavinka P, Trnka M, Semeradova D, Dubrovsky M, Zalud Z, Mozny M (2009) Effect of drought on yield variability of key crops in Czech Republic. Agric For Meteorol 149:431–442

    Article  Google Scholar 

  • Hoffman MT, Carrick PJ, Gillson L, West AG (2009) Drought, climate change and vegetation response in the succulent karoo, South Africa. S Afr J Sci 105:54–60

    Article  Google Scholar 

  • Huth R, Pokorná L (2004) Parametric versus non-parametric estimates of climatic trends. Theor Appl Climatol 77:107–112

    Article  Google Scholar 

  • Ivanova M, Popova Z (2011) Model validation and crop coefficients for maize irrigation scheduling based on field experiments in Sofia. In: “100 years soil science in Bulgaria”, Trans Nat Conf, Sofia, pp 542–548 (in Bulgarian)

  • Kang Y, Khan S, Ma X (2009) Climate change impacts on crop yield, crop water productivity and food security—a review. Prog Nat Sci 19:1665–1674

    Article  Google Scholar 

  • Keyantash J, Dracup JA (2002) The quantification of drought: an evaluation of drought indices. Bull Am Meteorol Soc 83:1167–1180

    Google Scholar 

  • Koinov V, Kabakchiev I, Boneva K (1998) Atlas of the soils in Bulgaria. Zemizdat, Sofia

    Google Scholar 

  • Koleva E, Alexandrov V (2008) Drought in Bulgarian low regions during the 20th century. Theor Appl Climatol 92:113–120

    Article  Google Scholar 

  • Krysanova V, Vetter T, Hattermann F (2008) Detection of change in drought frequency in the Elbe basin: comparison of three methods. Hydrol Sci J 53:519–537

    Article  Google Scholar 

  • Lana X, Serra C, Burgueño A (2001) Patterns of monthly rainfall shortage and excess in terms of the standardized precipitation index for Catalonia (NE Spain). Int J Climatol 21:1669–1691

    Article  Google Scholar 

  • Li W, Fu R, Juarez RIN, Fernandes K (2008) Observed change of the standardized precipitation index, its potential cause and implications to future climate change in the Amazon region. Phil Trans R Soc B 363:1767–1772

    Article  Google Scholar 

  • Liu Y, Teixeira JL, Zhang HJ, Pereira LS (1998) Model validation and crop coefficients for irrigation scheduling in the North China Plain. Agric Water Manag 36:233–246

    Article  Google Scholar 

  • Liu X, Wang Y, Peng J, Braimoh AK, Yin H (2013) Assessing vulnerability to drought based on exposure, sensitivity and adaptive capacity: a case study in middle Inner Mongolia of China. Chin Geogr Sci 23:13–25

    Article  Google Scholar 

  • Lloyd-Hughes B, Saunders MA (2002) A drought climatology for Europe. Int J Climatol 22:1571–1592

    Article  Google Scholar 

  • Martins DS, Raziei T, Paulo AA, Pereira LS (2012) Spatial and temporal variability of precipitation and drought in Portugal. Nat Hazards Earth Syst Sci 12:1493–1500

    Article  Google Scholar 

  • McKee TB, Doesken NJ, Kleist J (1993) The relationship of drought frequency and duration to time scales. In: Proceedings of 8th conference on applied climatology, American Meteorological Society, Boston, pp 179–184

  • McKee TB, Doesken NJ, Kleist J (1995) Drought monitoring with multiple time scales. In: Proceedings of 9th conference on applied climatology, American Meteorological Society, Boston, pp 233–236

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

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Moreira EE, Coelho CA, Paulo AA, Pereira LS, Mexia JT (2008) SPI-based drought category prediction using loglinear models. J Hydrol 354:116–130

    Article  Google Scholar 

  • Moreira EE, Mexia JT, Pereira LS (2012) Are drought occurrence and severity aggravating? A study on SPI drought class transitions using log-linear models and ANOVA-like inference. Hydrol Earth Syst Sci 16:3011–3028

    Article  Google Scholar 

  • National Drought Mitigation Center (NDMC) (2014) Drought basics. National Drought Mitigation Center. http://drought.unl.edu/DroughtBasics/WhatisDrought.aspx. Accessed 10 Feb 2014

  • Olesen JE, Trnka M, Kersebaum KC, Skjelvåg AO, Seguin B, Peltonen-Sainio P, Rossi F, Kozyra J, Micale F (2011) Impacts and adaptation of European crop production systems to climate change. Eur J Agron 34:96–112

    Article  Google Scholar 

  • Paulo AA, Pereira LS (2008) Stochastic prediction of drought class transitions. Water Resour Manag 22:1277–1296

    Article  Google Scholar 

  • Paulo AA, Pereira LS, Matias PG (2003) Analysis of local and regional droughts in southern Portugal using the theory of runs and the Standardized Precipitation Index. In: Rossi G, Cancelliere A, Pereira LS, Oweis T, Shatanawi M, Zairi A (eds) Tools for drought mitigation in Mediterranean Regions. Kluwer, Dordrecht, pp 55–78

    Chapter  Google Scholar 

  • Paulo AA, Rosa R, Pereira LS (2012) Climate trends and drought indices based on precipitation and evapotranspiration in Portugal. Nat Hazards Earth Syst Sci 12:1481–1491

    Article  Google Scholar 

  • Pereira LS, Teodoro PR, Rodrigues PN, Teixeira JL (2003) Irrigation scheduling simulation: the model ISAREG. In: Rossi G, Cancelliere A, Pereira LS, Oweis T, Shatanawi M, Zairi A (eds) Tools for drought mitigation in Mediterranean Regions. Kluwer, Dordrecht, pp 161–180

    Chapter  Google Scholar 

  • Pereira LS, Cordery I, Iacovides I (2009) Coping with water scarcity. Addressing the challenges. Springer, Dordrech

    Book  Google Scholar 

  • Popova Z (ed) (2012) Risk assessment of drought in agriculture and irrigation management through simulation models. “N. Poushkarov” Institute of Soil Science, Sofia, 242 p (in Bulgarian)

  • Popova Z, Kercheva M (2005) Ceres model application for increasing preparedness to climate variability in agricultural planning—risk analyses. Phys Chem Earth, Parts A/B/C 30:117–124

    Article  Google Scholar 

  • Popova Z, Pereira LS (2008) Irrigation scheduling for furrow irrigated maize under climate uncertainties in the Thrace plain, Bulgaria. Biosyst Eng 99:587–597

    Article  Google Scholar 

  • Popova Z, Pereira LS (2011) Modelling for maize irrigation scheduling using long term experimental data from Plovdiv region, Bulgaria. Agric Water Manag 98:675–683

    Article  Google Scholar 

  • Popova Z, Kercheva M, Pereira LS (2006a) Validation of the FAO methodology for computing ETo with limited data. Application to South Bulgaria. Irrig Drain 55:201–215

    Article  Google Scholar 

  • Popova Z, Eneva S, Pereira LS (2006b) Model validation, crop coefficients and yield response factors for irrigation scheduling based on long-term experiments. Biosyst Eng 95:139–149

    Article  Google Scholar 

  • Popova Z, Ivanova M, Pereira LS, Alexandrov V, Doneva K, Alexandrova P, Kercheva M (2012) Assessing drought vulnerability of Bulgarian agriculture through model simulations. J Environ Sci Eng B 1:1017–1036

    Google Scholar 

  • Rafailov R (1995) Annual reports of ISS N. Poushkarov, Sofia (in Bulgarian)

  • Rafailov R (1998) Annual reports of ISS N. Poushkarov, Sofia (in Bulgarian)

  • Raziei T, Saghafian B, Paulo AA, Pereira LS, Bordi I (2009) Spatial patterns and temporal variability of drought in Western Iran. Water Res Manag 29:439–455

    Article  Google Scholar 

  • Rodrigues GC, Paredes P, Gonçalves JM, Alves I, Pereira LS (2013) Comparing sprinkler and drip irrigation systems for full and deficit irrigated maize using multicriteria analysis and simulation modeling: ranking for water saving vs. farm economic returns. Agric Water Manag 126:85–96

    Article  Google Scholar 

  • Santos JF, Pulido-Calvo I, Portela MM (2010) Spatial and temporal variability of droughts in Portugal. Water Resour Res. doi:10.1029/2009WR008071

    Google Scholar 

  • Sen PK (1968) Estimates of the regression coefficient based on Kendall’s tau. J Am Stat As 63:1379–1389

    Article  Google Scholar 

  • Simelton E, Fraser ED, Termansen M, Forster PM, Dougill AJ (2009) Typologies of crop-drought vulnerability: an empirical analysis of the socio-economic factors that influence the sensitivity and resilience to drought of three major food crops in China (1961–2001). Environ Sci Policy 12:438–452

    Article  Google Scholar 

  • Slavov N, Koleva E, Alexandrov V (2004) The climate of drought in Bulgaria. In: Knight GG, Raev I, Staneva M (eds) Drougth in Bulgaria: a contemporary analog for climate change. Ashgate Publishing Limited, Aldershot, pp 39–52

    Google Scholar 

  • Sönmez FK, Koemuescue AU, Erkan A, Turgu E (2005) An analysis of spatial and temporal dimension of drought vulnerability in Turkey using the standardized precipitation index. Nat Hazards 35:243–264

    Article  Google Scholar 

  • Sousa PM, Trigo MR, Aizpura P, Nieto R, Gimeno L, Garcia-Herrera R (2011) Trends and extremes of droughts indices throughout the 20th century in the Mediterranean. Nat Hazards Earth Syst Sci 11:33–51

    Article  Google Scholar 

  • Stewart JL, Hanks RJ, Danielson RE, Jackson EB, Pruitt WO, Franklin WT, Riley JP, Hagan RM (1977) Optimizing crop production through control of water and salinity levels in the soil. Utah water research laboratory report PRWG151-1. Utah State University, Logan

  • Stoyanov P (2008) Agroecological potential of maize cultivated on typical soils in the conditions of Bulgaria. Habilitation thesis, “N. Poushkarov” Institute of Soil Science, Sofia, (in Bulgarian)

  • Varlev I (2008) Potential, efficiency and risk under maize cultivation in Bulgaria. Academy of Agriculture, Sofia, 128 p (in Bulgarian)

  • Varlev I, Popova Z (1999) Water-evapotranspiration-yield. Irrig and Drain Inst, Sofia, 144 p (in Bulgarian)

  • Varlev I, Kolev N, Kirkova I (1994) Yield-water relationships and their changes during individual climatic years. In: Proceedings of 17th European Regional Conference of ICID, Varna, pp 351–360

  • Vicente Serrano SM, González-Hidalgo JC, Luis MD, Raventós J (2004) Drought patterns in the Mediterranean area: the Valencia region (eastern Spain). Clim Res 26:5–12

    Article  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 

  • Wang Z, He F, Fang W, Liao Y (2013) Assessment of physical vulnerability to agricultural drought in China. Nat Hazards 67:645–657

    Article  Google Scholar 

  • Wilhelmi OV, Wilhite DA (2002) Assessing vulnerability to agricultural drought: a Nebraska case study. Nat Hazards 25:37–58

    Article  Google Scholar 

  • Wu H, Wilhite DA (2004) An operational agricultural drought risk assessment model for Nebraska, USA. Nat Hazards 33:1–21

    Article  Google Scholar 

  • Xu W, Ren X, Johnston T, Yin Y, Klein K, Smith A (2012) Spatial and temporal variation in vulnerability of crop production to drought in southern Alberta. Can Geogr 56:474–491

    Article  Google Scholar 

  • Zhang J (2004) Risk assessment of drought disaster in the maize-growing region of Songliao Plain. China Agric Ecosyst Environ 102:133–153

    Article  Google Scholar 

  • Zhang Q, Xu CY, Zhang Z (2009) Observed changes of drought/wetness episodes in the Pearl River basin, China, using the standardized precipitation index and aridity index. Theor Appl Climatol 98:89–99

    Article  Google Scholar 

Download references

Acknowledgments

Authors gratefully acknowledge the financial support of Drought Management Centre for South East Europe Project, South East Europe Transnational Cooperation Programme co-funded by the European Union and FCT-Portugal funded project PTDC/GEO-MET/3476/2012.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to L. S. Pereira.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Popova, Z., Ivanova, M., Martins, D. et al. Vulnerability of Bulgarian agriculture to drought and climate variability with focus on rainfed maize systems. Nat Hazards 74, 865–886 (2014). https://doi.org/10.1007/s11069-014-1215-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11069-014-1215-3

Keywords

Navigation