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Statistical Analysis of Severe Drought Events in Central Aegean Sea, Greece

Explore the detection and statistical analysis of severe drought events in the Central Aegean Sea using standardized precipitation and reconnaissance drought indices. Learn about the methodology, results, and conclusions derived from the study.

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Statistical Analysis of Severe Drought Events in Central Aegean Sea, Greece

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  1. Detection and Statistical Analysis of Severe Drought Events Using Standardized Precipitation Index and Reconnaissance Drought Index,Case Study: Central Aegean Sea, GreeceAnastasiadis Stavros*, Demetris F. Lekkas, Konstantinos MammasAnalysis and Simulation of Environmental Systems Research GroupDepartment of Statistics – Actuarial and Financial Mathematics,University of Aegean

  2. Overview • Regional Drought Assessment • Why is needed? • Method - Drought indices • SPI & RDI • Central Aegean – Data Collections • Results • Conclusions

  3. Drought • Complex – slow developing phenomenon • Spatial and Temporal characteristics • European Drought Center defines “drought means a sustained and regionally extensive occurrence of below average natural water availability” • Last 30 years in Europe • Drought events : 1976 - 1989 – 1991 – 2003 • Since 1991: Average annual economic cost 5.3 € billion • 2003 drought : 8.7€ billion (associated with heat wave) (European Communities,2007) • Meteorological Drought • Many definitions • Regional Characteristics • Usually combination : Degree of dryness and Duration of dry period • A viable meteorological drought definition depends on the study-research purposes

  4. Method • Selection of Drought Index • SPI (Precipitation, Gamma distribution) • (2010) WMO selection as key drought indicator • RDI (Precipitation/PET, lognormal) • (2004) MEDROPLAN • Thornwaite method – Based on temperature • Goodness of fit: Anderson Darling test • Fitting data with MLE estimator • Drought Characteristics • Duration (Length of dry period – indicator below threshold) • Severity (Sum of the negative deviations for a specific drought event) • Intensity (Severity / Duration )

  5. Case Study • Stations • Larisa • Milos • Mytilini • Naxos • Hellenic National Meteorological Service • Time Period : 1955-2010 • Time Step : daily aggregated to Annual • Variables : • Precipitation • Temperature

  6. Precipitation

  7. Temperature

  8. Goodness of fit

  9. Intensity 0.95 (Spi) 0.97 (Rdi) 2000-2010 Intensity 1.13 (Spi) 1.14 (Rdi) 2 2 7 7 1989 2010 1999 (Rdi) 2006

  10. 2000-2010 Intensity 0.93 (Spi) 0.88 (Rdi) Intensity 0.49 (Spi) 0.28 (Rdi) 4 (RDI) Intensity 1.28 (Spi) 1.38 (Rdi) 2 4 3 5 2004 2006 2007 2008 1964 1970

  11. Summary Performance

  12. Common Consecutive Dry Periods in all Stations

  13. Summaring Results Extreme Drought Years • 1989 & 2006 • Related Probability 4.4 % Three Common Periods, with similar or different characteristics (severity) • 1959-1960 • 1989-1990 • 2004-2005 Increases in the duration of Dry Periods and Extreme Events • Since 1985

  14. Fitting distributions ? Is it really necessary for drought assessment ? Identification of the same Extreme Events Identification of the same drought events • Four drought indices : • Spi • Rdi • Unesco Aridity (Standardized) • (NO distribution involved) • Rainfall / Temperature (Standardized) • (NO distribution involved) 2010 Dry conditions companied with Heat Wave 1999 Extreme Event identified only by RDI

  15. Conclusions • Spi world wide applications/ recognition • Temperature should always be included • Impacts are usually more severe when droughts and heat waves are happening at the same time • Question • Does SPI (or of any index) value (e.g. -2) indicate severe drought? Shouldn’t be related to impacts? • Definitions must incorporate both physical and social measures

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