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