Transcript Διαφάνεια 1

UNIVERSITY OF THESSALY
LABORATORY OF AGROMETEOROLOGY
An Overview of
Environmental Hazards
Related to Crops in Greece
By:
Nicolas R. Dalezios
UNIVERSITY OF THESSALY
FROST
LABORATORY
IN
OF
AGROMETEOROLOGY
GREECE
EVENTS, CLIMATOLOGY, DAMAGES,
FORECASTING-RISK ASSESSMENT
An Overview of Environmental Hazards Related to Crops in Greece
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FROST EVENTS
• Advection frosts
• Radiation frosts
• A combination of both
• THE MOST DAMAGING FROSTS ARE THE
ADVECTIVE FOLLOWED BY RADIATION FROSTS
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CLIMATOLOGY OF FROST
Trewatha’s world map (1954) shows the average length of frost-free
period. Greece is divided in three zones
• Zone 2
Occasional winter frosts. (Islands, Southern Greece)
• Zone 3
Frost-free season > 240 days. (Central & parts of
Northern Greece)
• Zone 4
180 days < Frost-free season < 240 days (Northern
Greece)
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LABORATORY
AGRICULTURAL DAMAGES
OF
(in thousands euros)
WHEATHER
PHENOMENON
TOTAL (2001-2004)
WIND STORM
47,100
RAINFALL
177,850
HEAT WAVE
3,239
FROST
539,400
FLOOD
27,452
HAIL
179,005
SNOW
3,883
TOTAL
977,929
FROST CONTRIBUTION (%)
55
An Overview of Environmental Hazards Related to Crops in Greece
AGROMETEOROLOGY
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CROP DAMAGES & CONTRIBUTION TO
TOTAL FROST INJURIES
CROP
CATEGORY
DESCRIPTION
CONTRIBUTION
(%)
CITRUS
ORANGES, GRAPE
FRUITS
30-50
STONE FRUITS
PEACHES
20-30
VEGETABLES
INDUSTRIAL PLANTS
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15-20
COTTON
15-20
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FROST PROTECTION
• MAINLY PASSIVE METHODS ARE USED (cost-effective and more
beneficial than active protection methods)
• Wind machines protect < 10% of the citrus crop in Greece
• Sprinklers (over-plant and under-plant) protect < 20% of the citrus
crop
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FROST FORECASTING – RISK ASSESSMENT
CASE STUDY: Frost risk mapping for the agricultural region of Central
Greece
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LABORATORY
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AGROMETEOROLOGY
HAIL
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CLIMATOLOGY OF HAIL IN GREECE
1
WEST
0,9
CENTRAL
NORTH
0,8
Number of Hail Days
EAST
0,7
SOUTH
0,6
0,5
0,4
0,3
0,2
0,1
0
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
DEC
Number of observed hail days for different areas in Greece.
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HAIL DAMAGES
60
50
40
30
20
10
0
2000
2001
2002
2003
2004
Total annual compensations given to farmers from hail losses
(prices are in million €)
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40
35
30
%
25
20
15
10
5
0
2000
2001
2002
2003
2004
Hail loss percent from total compensations given to farmers
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100,0
90,0
80,0
70,0
%
60,0
50,0
40,0
30,0
20,0
10,0
0,0
JAN
FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
Monthly distribution hail losses Percent of compensations
Example: The year 2004.
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Peaches
Corn
Vineyards
Cotton
Vineyards
Tomatoes
Cherries
0
< 0.4 M €
<1 M€
<2 M€
<5 M€
< 10 M €
> 10 M €
Compensations given per prefecture for the year 2004
and main agricultural products hit by hail
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HAIL PROTECTION
THE NATIONAL HAIL SUPRESSION PROGRAMME (NHSP)
Area
The three protected agricultural areas of NHSP.
An Overview of Environmental Hazards Related to Crops in Greece
Total Compensations
(in M €)
Difference
%
Average
Period
71-83
Average
Period
84-88
A1, Pella Hmathia
1.31
0.55
-58
A2, Serres
0.34
0.15
-56
A3, Karditsa
0.96
0.18
-81
TOTAL
916,4
309,2
-66
Differences in compensations given
before and during the NHSP
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DROUGHT
• Regional phenomena, referred to as "non events", since their
basic cause is the lack of precipitation events in a region over a
period of time.
• Four drought categories: meteorological or climatological,
hydrological, agricultural, and socioeconomic (American
Meteorological Society, 1997).
• Drought responsive parameters: rainfall, soil moisture,
potential evapotranspiration, vegetation condition, groundwater and surface-water levels.
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Drought indices
• Describe the magnitude, duration, severity, and spatial extent
of drought.
• Based on meteorological and hydrological variables, such as
precipitation, streamflows, soil moisture, reservoir storage, and
groundwater levels.
• Conventional drought indices based on ground measurements
(e.g. PDSI, SPI, RDI, Rainfall Deciles, CMI, SWSI).
• Satellite drought indices based on remote sensed data (e.g.
NDVI, VCI, TCI, VHI).
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District climatic characteristics of Greece
1.
2.
3.
4.
5.
Western coast and the islands of the Ionian Sea:
significant precipitation, small annual temperature range.
West coast of southern continental Greece and the
islands of the Aegean Sea: low winter temperatures, high
summer temperatures and low precipitation.
Northern and Central continent: long duration storms,
short drought periods, low negative temperatures during
winter and large annual temperature range.
Crete and southern Greece: with small annual
precipitation and droughts long duration.
Pindous Mountain range: high annual precipitation and
strong gradients of precipitation and temperature with
elevation.
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Drought in Greece
• Drought severity increased from the northern to the southern
and from the western to the eastern regions (Dalezios et al.,
2000;Loukas et al., 2002).
Isoseverity map of droughts in
Greece, from Z-index values, for
three-month duration and five-year
return period.
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Case Study
• Use of RDI and SPI in Naxos island, Mornos and Nestos
basin (Tsakiris and Vangelis, 2005; Tsakiris et al., 2006).
Normalised yearly RDI for Naxos meteorological station
for the period 1955/56 – 1991/92.
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Nestos watershed: maximum water deficit at
Hryssoupoli station during the years 1988-1994.
Severe drought, in 1986-1994 (Achladia station)
and 1988-1996 (Ptelea station). maximum drought
intensity for the year 1984-85 (Potami station).
Mornos case study: maximum water deficit and the
most severe drought at Pentagi station during the years
1987-1995. The maximum annual drought intensity year
2000-2001.
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Wheat and Drought
• Drought: major environmental factor limiting for wheat
growth during the early part of its life cycle.
Plant Protection from drought
•
•
•
•
•
Rational regime of irrigation.
Alternative plant production.
Selection of tolerant plant genotypes.
Pumping of groundwater.
Construction of off-stream reservoirs to store surface water
sinks for collection of precipitation water.
• Uses of desalinisation plants.
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EXCESS RAIN
• The duration and frequency of extreme rainfall rates are important
climatological features to be considered in meteorology, agriculture,
hydrology and civil engineering.
• Heavy precipitation events in the world wide have caused great
damage to crop production.
• A warmer climate will be one in which the hydrological cycle will in
general be more intense, leading to more heavy rain events (IPCC,
1996).
• Enhanced hydrologic cycle is responsible for the increasing flood
damage.
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Precipitation-related measures
used for study of floods
•
•
•
•
•
•
•
•
Total precipitation
Number of wet days per station
Number of extreme precipitation days (>2 inches) per station
Number of 2-day heavy precipitation events per station
Number of 3-day heavy precipitation events per station
Number of 5-day heavy precipitation events per station
Number of 7-day heavy precipitation events per station
Percentage of an area with much above-normal cold season (October–
April) precipitation
• Percentage of an area with the number of wet days much above normal
• Percentage of an area with much above-normal proportion of total annual
precipitation from 1-day extreme events.
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Damages of Extreme Precipitation
• Anoxic conditions by excessively wet soils (Kozdrόj and van
Elsas, 2000).
• Increased risk of plant disease and insect infestation (Ashraf
and Habib-ur-Rehman, 1999).
• Large losses of crop yield and production.
Damages after extreme precipitation
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Excess Rain damages in Greece
Rainfall
Floods
Windstorms
Extreme
temperature
Hail
Frost
Total map damages in Greece for all agriculture disaster categories in thousands € from 1986 to 2003.
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Excess rain and Cotton
 Large damages are caused mainly in cotton and especially in
end-grow season at September.
 Effects in economy, quality and productivity of cotton in
Greece and especially in Thessaly plain where cotton
production is significant.
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FOREST FIRES
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Types of Forest Fires
• Ground fires.
• Surface fires.
• Crown fires.
Meteorological parameters such as rainfall, high
temperature, low relative humidity and wind velocity have
serious effect in the initiation and spread of forest fires.
Other factors affecting:
• the variety and amount of fuel (vegetation and dead
organic material),
• the fuel moisture and
• the topography (altitude, slope).
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Causes of Forest Fires
Causes of forest fires in Greece for the period
1985-1997 (Dalezios, 2006).
In Greece, the causes of
wildfires are classified into
three categories:
•
Wildfires caused by
natural causes.
•
Wildfires caused by
human activities.
•
Wildfires caused by
dubious-unknown
reasons.
An Overview of Environmental Hazards Related to Crops in Greece
CATEGORY OF CAUSE
Contribution in
Percent (%)
1. Negligence
1.1 Cigarettes stubs or matches
14,0
1.2 Burning of stubble
21,1
1.3 Military shooting exercises
0,6
1.4 Trains and electrical lines
0,4
1.5 Sparks from machinery
2,7
1.6 Overheating
2,5
1.7 Bees smoking
0,6
1.8 Campers
1,5
1.9 Burn of wastes and other
causes
5
1. Sum of causes due to
negligence
48,4
2. Arsons
27,2
3. Natural causes
2,1
4. Dubious or unknown causes
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Burned Area in Greece
Burned Area per type of forest coverage
70000
60000
Forest areas (full cover)
Forest areas (partial cover)
Burned area (ha)
50000
Pastures
40000
30000
20000
10000
19
95
19
85
19
87
19
89
19
91
19
93
19
73
19
75
19
77
19
79
19
81
19
83
19
63
19
65
19
67
19
69
19
71
19
55
19
57
19
59
19
61
0
Year
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Wildfire Statistics for Greece
Basic statistics of forest fires in Greece for the period 1955-1996 (Dalezios, 2006)
Year
MEAN NUMBER OF FIRES PER YEAR
991
MAXIMUM NUMBER OF FIRES
2,406
1993
MINIMUM NUMBER OF FIRES
304
1959
MEAN BURNED AREA (ha)
28,193
MAXIMUM BURNED AREA (ha)
110,501
1988
MINIMUM BURNED AREA (ha)
2,221
1959
Need for protection (prevention and suppression),
monitoring, forecasting and risk assessment.
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Monitoring and Mapping
K-study in Penteli, Greece (Domenikiotis et al. (2002).
•
Technique based on satellite derived NDVI.
•
NOAA/AVHRR and Landsat TM data.
(a)
(b)
Images formed by NOAA/AVHRR data before (a) and after (b) the forest fire in
Penteli, Greece. Bright areas in the first image indicate the presence of vegetation
and the gray areas correspond to suburbs of Athens and the sea
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Monitoring and Mapping
Burned areas: dark red, Vegetation areas: green (Landsat TM
images).
Concluding, NOAA/AVHRR data can be used for operational
monitoring and assessment of damaged area in near real-time
with high degree of accuracy. Landsat TM is much more
accurate (Domenikiotis et al. (2002).
(a)
(b)
Landsat TM color composites images (7,4,1) before (a) and after (b) the forest
fire in Penteli, Greece. This band compilation highlights the burned area.
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Forecasting and Risk Assessment
K-study in Pelio, Greece (Spanos et al. 2002).
•
Use of three meteorological parameters and
Angström’s index for risk assessment.
•
NDVI for detection of the burned areas.
Meteorological parameters and Angström’s index during the initiation
of fire.
Station/Parameter
Volos
Velestino
Zagora
Air Temperature (C)
28.3
29
27
Relative Humidity (%)
30.3
33
45
Wind speed (ms-1)
2.6
0.3
0.8
Angström’s index
1.4
1.5
2.3
The study highlighted the importance of local
meteorological conditions in the fire risk assessment.
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GRAPES PEST AND DISEASES
1.
2.
3.
4.
5.
6.
7.
8.
9.
Hadromycosis-Bertisillioseis / Verticillium dahliae, Verticillium
albo-atrum
Bacillar necrosis / Xylophilus ampelinus
Botrytis (ash decay) vine / Botryotinia fuckeliana
Esca or Polisporiash / Phellinus igniarius, Stereum hirsutum (esca,
black measles, apoplexy)
Necrosis of arms / Eutypa lata
Mildew of vine (downy mildew) / Plasmopara viticola
Decays of fruits from penikilla / Prnicillium digitatum, Penicillium
italicum, Penicillium expansum
Fomopsi or exkoriosi of vine / Phomopsis viticola
Oidio of vine / Uncinula necator
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Geographical distribution of indemnification for damages of
mildew in Greece (source ELGA).
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Protection measurements
•
•
•
•
•
The care of soil and the fertilization
Corridors and areas released exempted of pests
Cares of leafage
Direct means of plant health protection (combating)
Estimate of danger and observation of enemy or pathogenic
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The use of models for protection of diseases
• PERO Model
simulates the infection cycle development according to
agrometeorological conditions, allowing the best
timing for fungicide treatment.
• PLASMO model
Simulates the inflection cycle development and
diseased leaf area
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Ν . A g h ia lo s 2 0 0 0
1800
1600
o ilsp o t s/ h e ct are
1400
1200
1000
800
600
400
200
26
/8
19
/8
12
/8
5/
8
29
/7
22
/7
15
/7
8/
7
1/
7
24
/6
17
/6
10
/6
3/
6
27
/5
20
/5
13
/5
6/
5
29
/4
0
d at e s
n e w o ils p o ts
la te n t o ils p o ts
vis ib le o ils p o ts
to ta l o ils p o ts
PERO Model Application Results
for the area of N. Aghialos in Greece for the year 2000
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