1. Agrometeorological Service of Sardinia
Climate indicators for assessing sensitive areas to drought and desertification in Sardinia (Italy)
A. Motroni, S. Canu
Agrometeorological Service of Sardinia
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

2. Sensitive Areas to Desertification
In 2000 the Agrometeorological Service of Sardinia started to develop a
Geographic Information System for assessing and monitoring Environmentally
Sensitive Areas to Desertification
Applied methodologies: Desertification Prone Areas (Pimenta et al., 1997) Environmentally Sensitive Areas (ESAs) to desertification (MEDALUS Project (UE) Kosmas et al., 1997) Results: Map of vulnerable areas to desertification (scale 1: ) Map of Environmentally Sensitive Areas to desertification (scale 1: ) 2004
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

3. Vegetation Quality Index Management Quality Index
Parent material
Soil texture
Rock fragment
Soil depth
Drainage
Slope gradient
Rainfall
Aridity index
Aspect
Fire risk
Erosion protection
Drought resistance
Plant cover
Land use intensity
Policy
SQI
Soil Quality Index
CQI
Climate Quality Index
ESAI
VQI
Vegetation Quality Index
MQI
Management Quality Index
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

4. ESAs CQI Climate Quality Index Rainfall Aridity index Aspect
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

5. Objective:
to show some aridity and drought indexes useful for assessing areas sensitive to desertification processes
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

6. Definition of “desertification”
UNCCD(1):“Land degradation in arid, semi-arid and dry/sub-humid areas, resulting from various factors, including climatic variations and human impacts” (UNEP, 1994)
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(1): United Nations Convention to Combat Desertification
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

7. …, i.e. desertification is a complex phenomenon strictly dependent on climate
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

8. Causes of desertification:
Extreme climatic events: drought/floods
Pressures on the territory: overgrazing, uncontrolled urbanization/country areas abandonment…
Excessive exploitation of water resources
Fires and deforestation
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

9. The bioclimatic index FAO-UNEP (1997), P/ETo.
Atmospheric conditions characterizing a desert climate lead to severe water deficit, i.e. potential evapotranspiration (ETo) values higher than precipitation values. Such conditions are calculated by several indices, the most used one is
The bioclimatic index FAO-UNEP (1997), P/ETo.
Considering this index, the sensible areas to desertification can be classified as follow:
a) arid and semi arid P/ETo<0.50
b) dry/sub-humid <P/ETo<0.65
c) humid and hyper-humid P/ETo>0.65
DESERTIFICATION > P/ETo > NO DESERTIFICATION
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

10. Carta P/ETo 4,6% semi-arid 29,8% dry sub-humid 58,1% moist sub-humid
Reference period
Carta P/ETo
4,6% semi-arid
29,8% dry sub-humid
58,1% moist sub-humid
7,5% humid
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

11. Bagnouls-Gaussen Index (meteorological deficit)
Aridity indexes:
Bagnouls-Gaussen Index
(meteorological deficit)
Simplified Water Balance Index
(hydrological deficit)
Drought index
Standardized Precipitation Index
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

12. Aridity indexes - Input data
Climatic data
About 200 stations
Reference time period:
Daily maximum and minimum temperature
Daily precipitation
Interpolation techniques
temperature -> multi-linear regression with residuals Kriging
precipitation->Kriging/Co-kriging
Agrometeorological data
Daily ETo (Hargraves-Samani)
Daily ETa
Pedological data
AWC data based on
soil type, texture, soil depth, chemical composition
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

13. In this way, the soil component
Bagnouls-Gaussen Index
Number of days/year
with 2T>P
(climatic mean)
Originally, ESAs methodology
considered the Bagnouls-Gaussen
aridity index:
where
BGI = Bagnouls-Gaussen Index
Ti = Temperature of the i month (°C)
Pi = Total monthly precipitation of the month i (mm)
K = Frequency of the condition 2Ti-Pi>0 for the i month (%)
In this way, the soil component
is not considered!
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

14. Simplified Water Balance
ETa = f x ETo
w soil water content
t time
S water surplus
P precipitation
ETa actual evapotranspiration
evapotranspiration coefficient
soil water content in a given day
wi = current soil moisture for the i day
wi-1 = soil moisture in the previous day
P = precipitation
ETo = potential evapotranspiration
f = evapotranspiration coefficient
f i-1 = wi-1/w*= evapotranspiration coefficient
for the day i-1
w* = Available Water Capacity (AWC)
soil available water content (AWC)
(Reed et al., 1997)
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

15. Simplified Water Balance
Aridity Index
Simplified Water Balance
For each year, aridity index values have been estimated computing the number of days in which soil humidity values were below different thresholds of AWC (0%, 10%,25%, 50%, 75%).
The 50% threshold was used for calculating the aridity index in order to avoid over and underestimates of the index and to obtain a good spatial variability.
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

16. (Simplified Water Balance)
BGI vs. Simplified Water Balance
(Simplified Water Balance)
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

17. What has been the trend of drought in Sardinia for the last 50 years?
The concept of aridity is already included in the
definition of desertification (P/ETo)
from a static to a dynamic analysis
ESAs methodology should be integrated
with an analysis of drought events
What has been the trend of drought in Sardinia for the last 50 years?
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

18. The Standardized Precipitation Index, SPI (McKee et al., 1993)
Standardized Precipitation Index (SPI) is a probability index that considers only precipitation.
The SPI is computed for several time scales, ranging from 1 month to 48 months, to capture the various scales of both short-term and long-term drought.
These time scales reflect the impact of drought on the availability of the
different water resources.
Positive SPI values indicate greater than median precipitation, while negative values
indicate less than median precipitation. A drought event occurs any time the SPI is
continuously negative and reaches an intensity where the SPI is -1.0 or less. The event
ends when the SPI becomes positive.
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

19. SPI Advantages: Low input data requirement (monthly P)
Availability of precipitation data
Good territorial distribution of rain gauges
Easy way to represent drought trends
Short and long-term drought events
are considered
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

20. soil moisture conditions
SPI calculation
- Procedure to calculate the SPI is very simple. It is calculated by taking the difference of the
precipitation from the mean for a particular time scale, and then dividing it by the standard
deviation.  
- 102 rain gauges
- time period:
- time scales:1, 3, 6, 12, 24, 48 months
Short-term drought
Long-term drought
affect
affect
ground water,
stream flow,
reservoir storage
soil moisture conditions
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

21. SPI - Geographic distribution
of meteorological
stations
- Best and longer data series
- Homogeneous distribution
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

22. SPI classes classification
The index is negative for drought, and positive for wet conditions. (<-2 / >+2)
As the dry or wet conditions become more severe, the index becomes
more negative or positive
SPI value
Class
>2 or greater
Extremely wet
1.50 to 1.99
Very wet
1.00 to 1.49
Moderately wet
-0.99 to 0.99
Near normal
-1.49 to -1.00
Moderately dry
-1.99 to -1.50
Severely dry
-2.00 and less
Extremely dry
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

23. Negative trend 3, 12, 24, 48 month SPI
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

24. Positive trend 3, 12, 24, 48 month SPI
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

25. In order to estimate SPI trends, angular coefficients for each station and for each time scale were calculated and spatial interpolated (Spline techniques)
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

26. 102 meteorological stations
89% -
102 meteorological stations
11% +
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

27. Extreme drought events

28. 3,12, 24, 48 month SPI trend maps
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

29. Mean rainfall total
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

30. Negative SPI trends are found for almost all stations
Results
Negative SPI trends are found for almost all stations
Extreme drought events are mostly concentrated in the last two decades of
Short time scale (3, 6 months) SPI maps show wider areas with negative
trends than long time scale (12, 24, 48 months) ones
24 and 48 month SPI trend maps indicate
- Sardinian areas already characterized by drier conditions
(semi-arid and dry sub-humid) show a negative trend of precipitation in
Only in some areas (north-east and south-west of Sardinia)
precipitation trends are close to remain the same or smoothly increase
probably due to rain regimes
More controversial is the situation in other areas
(central-eastern part of the region, for example)
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

31. Next steps
to rebalance ESAs desertification methodology with the SPI drought index
to calculate an on-line SPI index (short term drought) for drought alert
taking into account also the “controversial” period
to relate SPI calculation results with atmosphere circulation models
and rain regimes
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

32. Conclusions
Drought study and monitoring should be included in any complex model
of desertification phenomena
In an already defined climatic area, drought indexes give a better
representation of weather effects on desertification than aridity indexes,
because
- climate variability is considered
- their relation to vegetation biomass  fire risk, erosion resistance, etc.
SPI is a very useful and easy-to-apply drought index for determining
possible climatic areas and weather conditions which can lead to
desertification processes
trends derived from long-time scales (24, 48 months) SPI can be useful
tools for assessing drought-bound areas
“CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

33. Environmentally Sensitive Areas to desertification
Scale
of the study
1:100’000
Grazie !