Using the SPI relative to 67 years data sets, a Markov chains approach has been utilized for several locations in Alentejo, southern Portugal, to characterize the stochasticity of droughts, which allowed predicting the transition from a class of severity to another up to 3 months ahead. Markov models were applied using both the homogeneous and non-homogeneous formulations. The results of the application of the Markov models are presented and discussed, showing in particular the usefulness of adopting a non-homogeneous formulation, which allows to differentiate predictions in relation to the initial month considered, thus understanding the probable evolution of a drought as influenced by the climate and, in particular, the seasonality of rainfall. However, these results, which are promising in view of drought management, require further developments and to be associated with other predictive tools of stochastic or physical nature. Possible approaches on using predictions of drought class transitions in view of drought risk management are also discussed.
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Agresti A (1990) Categorical data analysis. Wiley, New York (561p)
Anderson TW, Goodman LA (1957) Statistical inference about Markov chains. Ann Math Stat 28:89–110
Bickenbach F, Bode E (2003) Evaluating the Markov Property in studies of economic convergence. Int Reg Sci Rev 26(3):363–392
Bishop YMM, Fienberg SE, Holland PW (1975) Discrete multivariate analysis: theory and practice. MIT Press, Cambridge, M.A.
Bonaccorso B, Bordi I, Cancelliere A, Rossi G, Sutera A (2003) Spatial variability of drought: an analysis of the SPI in Sicily. Water Resour Manag 17(4):273–296
Çinlar E (1975) Introduction to stochastic processes. Prentice-Hall, New Jersey (402p)
Cordery I, McCall M (2000) A model for forecasting drought from teleconnections. Water Resour Res 36:763–768
Easterling WE (1989) Coping with drought hazard: recent progress and research priorities. In: Siccardi F, Bras RL (eds) Natural Disasters in European Mediterranean Countries, US National Science Foundation and National Research Council of Italy, Perugia, pp 231–270
Helsel DR, Hirsch RM (1992) Statistical methods in water resources. Elsevier, Amsterdam (522p)
Isaacson DL, Madsen R (1976) Markov chains: Theory and applications. John Wiley, New York (267p)
Lohani VK, Loganathan GV (1997) An early warning system for drought management using the Palmer drought index. J Am Water Resour Assoc 33(6):1375–1386
Lohani VK, Loganathan GV, Mostaghimi S (1998) Long-term analysis and short-term forecasting of dry spells by the Palmer drought severity index. Nord Hydrol 29(1):21–40
McKee TB, Doesken NJ, Kleist J (1993) The relationship of drought frequency and duration to time scales. In: 8th Conference on Applied Climatology. American Meteorological Society, Boston, MA, pp 179–184
McKee TB, Doesken NJ, Kleist J (1995) Drought monitoring with multiple time scales. In: 9th Conference on Applied Climatology, American Meteorological Society, Boston, MA, pp 233–236
NDMC home page (2004) http://www.drought.unl.edu/
Nelder JA (1974) Loglinear models for contingency tables: a generalization of classical least squares. Appl Stat 23:323–329
Ochola WO, Kerkides P (2003) A Markov chain simulation model for predicting critical wet and dry spells in Kenia: Analysing rainfall events in the Kano plains. Irrig Drain 52(4):327–342
Paulo AA, Pereira LS (2002) Analysis of the regional droughts in Southern Portugal using the standardized precipitation index. In: Maiga AH, Pereira LS, Musy A (eds) Sustainable water resources management: Health and productivity in hot climates. (Proc. Inter-regional Conference Envirowater 2002, Ouagadougou, Nov. 2002). EIER, Ouagadougou, pp 83–93
Paulo AA, Pereira LS (2006) Drought concepts and characterization. Comparing drought indices applied at local and regional scales. Water Int 31(1):37–49
Paulo AA, Pereira LS, Matias PG (2002) Analysis of the regional droughts in southern Portugal using the theory of runs and the Standardised Precipitation Index. In: Drought Mitigation and Prevention of Land Desertification (Proc. Intern. Conf., Bled, Slovenia), Slov. Nat. Com. on Irrig. and Drain., Ljubljana, CD-ROM paper 64
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, The Netherlands, pp 55–78
Paulo AA, Ferreira E, Coelho C, Pereira LS (2005) Drought class transition analysis through Markov and Loglinear models, an approach to early warning. Agric Water Manag 77:59–81
Rossi G (2003) Requisites for a drought watch system. In: Rossi G, Cancellieri A, Pereira LS, Oweis T, Shatanawi M, Zairi A (eds) Tools for drought mitigation Mediterranean Regions. Kluwer, Dordrecht, The Netherlands, pp 147–157
Sivakumar MVK, Wilhite DA (2002) Drought preparedness and drought management. In: Drought mitigation and prevention of land desertification (Proc. Intern. Conf., Bled, Slovenia), UNESCO and Slov. Nat. Com. ICID, Ljubljana, CD-ROM, paper 2
Steinemann A (2003) Drought indicators and triggers: a stochastic approach to evaluation. J Am Water Resour Assoc 39(5):1217–1233
Tsakiris G, Vangelis H (2004) Towards a drought watch system based on spatial SPI. Water Resour Manag 18(1):1–12
Vicente-Serrano SM (2006) Differences in spatial patterns of drought on different time scales: an analysis of the Iberian Peninsula. Water Resour Manag 20(1):37–60
Vogt JV, Somma F (eds) (2000) Drought and drought mitigation in Europe. Kluwer, Dordrecht, The Netherlands (336p)
Wilhite DA, Easterling WE, Wood DA (eds) (1987) Planning for drought. Toward a reduction of societal vulnerability. Westview, Boulder, CO (597 p)
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Paulo, A.A., Pereira, L.S. Prediction of SPI Drought Class Transitions Using Markov Chains. Water Resour Manage 21, 1813–1827 (2007). https://doi.org/10.1007/s11269-006-9129-9
- Markov chains
- standardized precipitation index
- stochastic modeling
- early warning
- drought management