Detection and Statistical Analysis of Severe Drought Events Using Standardized Precipitation Index and Reconnaissance Drought Index,
Case Study: Central Aegean Sea, Greece
Anastasiadis Stavros*, Demetris F. Lekkas, Konstantinos Mammas
Analysis and Simulation of Environmental Systems Research Group Department of Statistics – Actuarial and Financial Mathematics,University of Aegean
• Regional Drought Assessment – Why is needed?
• Method - Drought indices – SPI & RDI
• Central Aegean – Data Collections• Results • Conclusions
Overview
• 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)
( E u r o p e a n C o m m u n i ti e s , 2 0 0 7 )
• 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
Drought
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 )
Case Study Stations• Larisa• Milos• Mytilini• Naxos
Hellenic National Meteorological Service
Time Period : 1955-2010
Time Step : daily aggregated to Annual
Variables : • Precipitation • Temperature
Precipitation
Temperature
SPI A-D test, a=0.05 , Annual Precipitation Dataset
Distribution Larisa Milos Mytilini Naxos
Rank Statistic Rank Statistic Rank Statistic Rank Statistic
Gamma 1 0.22 1 0.19 2 0.62 2 0.32
Normal 2 0.43 2 0.44 1 0.24 1 0.22
RDI A-D test, a=0.05 , Annual Precipitation/PET dataset
Distribution Larisa Milos Mytilini Naxos
Rank Statistic Rank Statistic Rank Statistic Rank Statistic
LogNormal 1 0.30 1 0.23 2 0.89 1 0.29
Normal 2 0.37 2 0.31 1 0.24 2 0.32
Goodness of fit
Spi 1955-2010 2000-2010
Near Normal (N) 13 2Severe (S) 10 3
Extreme (Ex) 3 2 1989-2006-2010
sum 26 7Consecutive Years Length Structure
1959-1960 2 N-N 1972-1973 2 S-N 1989-1995 7 Ex-S-N-S-S-N-S 2004-2010 7 S-N-Ex-S-N-S-Ex
Rdi 1955-2010 2000-2010 Near Normal (N) 13 2
Severe (S) 9 3
Extreme (Ex) 4 2 1989-1999 2006-2010
sum 26 7Consecutive Years Length Structure
1959-1960 2 N-N 1972-1973 2 S-N 1989-1995 7 Ex-S-N-S-S-N-S 2004-2010 7 S-N-Ex-S-N-S-Ex
Kendall SlopeSpi-12 Larisa sig 0.0233sen -0.0194Z -2.22687 Significant Downward Rdi-12 Larisa sig 0.026sen -0.019Z -2.2263 Significant Downward
2000-2010
22 7 7
1989 1999 (Rdi)
2006 2010
Intensity 0.95 (Spi)0.97 (Rdi) Intensity
1.13 (Spi)1.14 (Rdi)
Spi 1955-2010 2000-2010 Near Normal (N) 15 1
Severe (S) 7 1
Extreme (Ex) 4 3 1964-2004-2006-2007
sum 26 5Consecutive Years Length Structure
1958-1960 3 N-S-N 1989-1992 4 S-N-N-S 1998-1999 2 N-N 2004-2008 5 Ex-N-Ex-Ex-S
Rdi 1955-2010 2000-2010 Near Normal (N) 16 3
Severe (S) 6 0
Extreme (Ex) 6 4 1964-1970-2004-2006-2004-2008
sum 28 7Consecutive Years Length Structure
1958-1960 3 N-N-N 1989-1992 4 S-N-N-S 1998-2001 4 N-S-N-N 2004-2008 5 Ex-N-Ex-Ex-Ex
Kendall SlopeSpi-12 Milos sig 0.6871sen -0.0045Z -0.4028 Not Significant Downward Rdi-12 Milos sig 0.502sen 0.0057Z -0.6714 Not Significant Downward
3 4 2
4(RDI)
5
2004 2006 2007 2008
2000-2010
1964 1970
Intensity 0.93 (Spi)0.88 (Rdi)
Intensity 0.49 (Spi)0.28 (Rdi) Intensity
1.28 (Spi)1.38 (Rdi)
Summary Performance
Extreme Drought Events Spi & Rdi Larisa Milos Mytilini Naxos
1957 Rdi 1958 Spi & Rdi1964 Spi & Rdi Spi & Rdi
1970 Rdi 1977 Spi & Rdi
1989 Spi & Rdi Spi & Rdi Spi & Rdi
1990 Spi & Rdi1992 Spi & Rdi
1999 Rdi 2000 Spi & Rdi2004 Spi & Rdi
2006 Spi & Rdi Spi & Rdi Spi & Rdi
2006 2007 Spi & Rdi 2008 Spi & Rdi 2010 Spi & Rdi
Common Consecutive Dry Periods in all Stations
SPI
Larisa Milos Mytilini Naxos Common Periods
RDI
Larisa Milos Mytilini Naxos Common Periods
1959-1960 1958-1960 1956-1959 1958-1960 1959-1960 1959-
1960 1958-1960 1956-1959 1958-1960 1959-1960
1963-1967 1963-1967 1972-1973 1972-
1973
1982-1983 1982-1983 1985-1986 1986-1987 1985-1986 1986-1987
1989-1995 1989-1992 1989-1993 1989-1993 1989-1992 1989-
1995 1989-1992 1989-1993 1989-1990 1989-1990
1998-1999 1999-2000 2000-2001 1998-2001 1999-2000 2000-2001
2004-2010 2004-2008 2003-2010 2004-2005 2004-2005 2004-
2010 2004-2008 2003-2010 2004-2005 2004-2005
Legend
Consecutive Years 7 6 5 4 3 2
Colours
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
Fitting distributions ? Is it really necessary for drought assessment ?
Identification of the same drought events Identification of the same Extreme 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
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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