Simple Short-Term Probabilistic Drought Prediction Using Mediterranean Teleconnection Information

Mohammad Mehdi Bateni (), Javad Behmanesh, Javad Bazrafshan, Hossein Rezaie and Carlo Michele
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Mohammad Mehdi Bateni: Urmia University
Javad Behmanesh: Urmia University
Javad Bazrafshan: University of Tehran
Hossein Rezaie: Urmia University
Carlo Michele: Politecnico di Milano

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2018, vol. 32, issue 13, No 12, 4345-4358

Abstract: Abstract Timely forecasts of the onset or possible evolution of droughts is an important contribution to mitigate their manifold negative effects; therefore, in this paper, we propose a mathematically-simple drought forecasting framework gaining Mediterranean Sea temperature information (SST-M) to predict droughts. Agro-metrological drought index addressing seasonality and autocorrelation (AMDI-SA) was used in a Markov model in Urmia lake basin, North West of Iran. Markov chain is adopted to model drought for joint occurrence of different classes of drought severity and sea surface temperature of Mediterranean Sea, which is called 2D Markov chain model. The proposed model, which benefits suitability of Markov chain models for modeling droughts, showed improvement results in prediction scores relative to classic Markov chain model not including SST-M information, additionally.

Keywords: Drought forecasting; Teleconnection; Markov model; Mediterranean sea; Model evaluation; Skill score (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s11269-018-2056-8

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