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A. Motroni, S. Canu Climate indicators for assessing sensitive areas to drought and desertification in Sardinia (Italy) “CLIMATIC ANALYSIS AND MAPPING.

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Presentation on theme: "A. Motroni, S. Canu Climate indicators for assessing sensitive areas to drought and desertification in Sardinia (Italy) “CLIMATIC ANALYSIS AND MAPPING."— Presentation transcript:

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

2 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: ) 2001 Map of Environmentally Sensitive Areas to desertification (scale 1: ) 2004 In 2000 the Agrometeorological Service of Sardinia started to develop a Geographic Information System for assessing and monitoring Environmentally Sensitive Areas to Desertification “CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

3 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 VQI Vegetation Quality Index SQI Soil Quality Index CQI Climate Quality Index MQI Management Quality Index ESAI “CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

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

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

6 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) Definition of “desertification” United Nations Convention to Combat Desertification (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

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 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 0.50

0.65 DESERTIFICATION 0.03 > P/ETo > 0.75 NO DESERTIFICATION “CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005

10 Carta P/ETo 4,6% semi-arid 29,8% dry sub-humid 7,5% humid 58,1% moist sub-humid Reference period

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

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

13 Bagnouls-Gaussen Index 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 Number of days/year with 2T>P (climatic mean)

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

15 “CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005 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. Aridity Index Simplified Water Balance

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

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

18 “CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005 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.

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

20 “CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005 SPI calculation rain gauges - time period: time scales:1, 3, 6, 12, 24, 48 months Short-term drought Long-term drought soil moisture conditions ground water, stream flow, reservoir storage - 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. affect affect

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

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

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

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

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

26 “CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June % - 11% meteorological stations

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

30 “CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005 Results Negative SPI trends are found for almost all stations Negative SPI trends are found for almost all stations Short time scale (3, 6 months) SPI maps show wider areas with negative 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 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 Extreme drought events are mostly concentrated in the last two decades Extreme drought events are mostly concentrated in the last two decades of More controversial is the situation in other areas (central-eastern part of the region, for example)

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

32 “CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE” – Bologna June 2005 Conclusions Drought study and monitoring should be included in any complex model 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 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 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 trends derived from long-time scales (24, 48 months) SPI can be useful tools for assessing drought-bound areas

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


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