Climatic variability and climate risk in agriculture in the Mediterranean area

Climatic variability and climate risk in agriculture in the Mediterranean area

Pierpaolo DuceCNR-IBIMET, Sassari, ITALY

Antonio Arca, Donatella SpanoDESA, University of Sassari, ITALY

Simona Canu, Andrea MotroniSAR - SARDEGNA, Sassari, ITALY

Gabriele Antolini, Franco ZinoniARPA-SM, Bologna, ITALY

WORKSHOP ON CLIMATIC ANALYSIS AND MAPPING FOR AGRICULTURE14-17 June 2005, Bologna, Italy

Climatic Variations – Background

IPCC Working Group II, 2001


IPCC Working Group II, 2001

17

Temperature and Precipitation – Italy - 1867-1995

Yearly and seasonal trends (Brunetti et al., 2000)

b ± b

T (°C/100 y)

P (mm/100 y)

North 0.4 ± 0.1 - 47 ± Year South

0.7 ± 0.1

- 104 ± 12


Winter

0.7 ± 0.1 8 ± 7 0.9 ± 0.1

- 16 ± 7

North

South

Summer

0.2 ± 0.1 7 ± 6 0.5 ± 0.1

- 17 ± 4

NorthSouth

-

Objectives

to develop a methodology forto develop a methodology for assessing climatic risk based on assessing climatic risk based on bioclimatic indexes bioclimatic indexes

to evaluate the potential effects ofto evaluate the potential effects of climatic variations on agricultural climatic variations on agricultural production production

CLIMATIC VARIABILITY AND CLIMATE RISKIN AGRICULTURE IN THE MEDITERRANEAN

AREA

Objectives

to develop a methodology forto develop a methodology for assessing climatic risk based on assessing climatic risk based on bioclimatic indexes bioclimatic indexes

to evaluate the potential effects ofto evaluate the potential effects of climatic variations on agricultural climatic variations on agricultural production production


AREA

to obtain maps of climatic risk forto obtain maps of climatic risk for agriculture agriculture based on past andbased on past and future climatic variability future climatic variability

Objectives


AREA

1) Data CollectionData Collection soil, land cover, climate, soil, land cover, climate, climatic scenarios A2 and B2climatic scenarios A2 and B2

2)2) Land Capability for Agriculture (LCA)Land Capability for Agriculture (LCA) classifications (based on pedology, classifications (based on pedology, climateclimate and land cover) and land cover)

3)3) Assessment of current and future Assessment of current and future climaticclimatic risk for agricultural areas and crops risk for agricultural areas and crops

ActivitiesActivities

CLIMATIC VARIABILITY AND CLIMATE RISK

DataData

Geology, pedology, morphology, etc.Geology, pedology, morphology, etc. Climate Climate (1961-2000 Sardinia, 1951-2000 Emilia-(1961-2000 Sardinia, 1951-2000 Emilia-Romagna)Romagna) temperature and rainfall series - temperature and rainfall series - completecomplete Climate Climate (1961-2000 Sardinia, 1951-2000 Emilia-(1961-2000 Sardinia, 1951-2000 Emilia-Romagna)Romagna) temperature and rainfall series - temperature and rainfall series - incompleteincomplete Land Cover MapLand Cover Map

GISGISArcGISArcGIS


MethodsLCA Classifications

Modification of the Soil Map of Sardinia and Emilia-Romagna Pedological LCA Classification Bioclimatic index calculation – Cluster Analysis (weather stations) Climatic LCA Classification Climatic data mapping (10 km x 10 km grid)Climatic data mapping (10 km x 10 km grid) Bioclimatic index calculation over the same gridBioclimatic index calculation over the same grid Climatic LCAClimatic LCA Classification for each cell of the gridClassification for each cell of the grid Overlay Pedological LCA – Climatic LCA Pedo-climatic LCA Classification


Modification of the Soil Map of Sardinia and Emilia-Romagna Pedological LCA Classification Bioclimatic index calculation – Cluster Analysis (weather stations) Climatic LCA Classification Climatic data mapping (10 km x 10 km grid) Bioclimatic index calculation over the same grid Climatic LCA Classification for each cell of the grid Overlay Pedological LCA – Climatic LCA Pedo-climatic LCA Classification


Modification of the Soil Map of Sardinia and Emilia-Romagna Pedological LCA Classification Bioclimatic index calculation – Cluster Analysis (weather stations) Climatic LCA Classification Climatic data mapping (10 km x 10 km grid)Climatic data mapping (10 km x 10 km grid) Bioclimatic index calculation over the same gridBioclimatic index calculation over the same grid Climatic LCAClimatic LCA Classification for each cell of the Classification for each cell of the gridgrid Overlay Pedological LCA – Climatic LCA Pedo-climatic LCA Classification


Modification of the Soil Map of Sardinia and Emilia-Romagna Pedological LCA Classification Bioclimatic index calculation – Cluster Analysis (weather stations) Climatic LCA Classification Climatic data mapping (10 km x 10 km grid) Bioclimatic index calculation over the same grid Climatic LCA Classification for each cell of the grid Overlay Pedological LCA – Climatic LCAOverlay Pedological LCA – Climatic LCA Pedo-climatic LCAPedo-climatic LCA ClassificationClassification

Pedological LCA classificationLCA classification mapmap Climatic LCA classificationClimatic LCA classification mapmap Pedo-climaticPedo-climatic LCALCA classificationclassification mapmap

Climatic Risk AssessmentClimatic Risk Assessment

Climatic Risk Index ClassificationClimatic Risk Index Classification

Analysis of spatial and temporal Analysis of spatial and temporal variability Bioclimatic Indexesvariability Bioclimatic Indexes


PEDOLOGICALLCA MAPSARDINIA

8 classesClass 1: no or very minorlimitations to agriculture

. . . . . . .Class 8: no agriculture use

Class 1-4: Land suitablefor agriculture

23.7%

Class 5-8: Land notsuitable for agriculture

75.4%

PEDOLOGICAL LCA MAP - EMILIA-ROMAGNA

Bioclimatic Index Calculations HEAT UNITHEAT UNIT

CUMULATIVE DEGREE-DAYSCUMULATIVE DEGREE-DAYS

°D°D lower quartilelower quartile

WATER LIMITATIONS MAXIMUM POTENTIAL SOIL MOISTURE DEFICIT

MaxPSMDmedian

CLIMATIC LCA MAP

365

1m

iT

To

365

1i

i

MAX

ETo iP

Bioclimatic Index Calculations HEAT UNITHEAT UNIT

CUMULATIVE DEGREE-DAYSCUMULATIVE DEGREE-DAYS

°D°D lower quartilelower quartile

WATER LIMITATIONSWATER LIMITATIONS MAXIMUM POTENTIAL SOIL MOISTURE DEFICITMAXIMUM POTENTIAL SOIL MOISTURE DEFICIT

MaxPSMDMaxPSMDmedianmedian

CLIMATIC LCA MAP

365

1m

iT

To

365

1i

i

MAX

ETo iP

asinara

villanova monteleonetempio

is cannonerisdesulo

ala' dei sardisos canales (diga)

col. penale sarcidano

santa sofia

genna-silanavallicciola

cuglieri

nurri f. c.

mandas f. c.

jerzu

meanasardo

lanuseiozieri

bidighinzunuoromacomervillavovatulooschiri

mogoro (diga)

carloforte

calagonone

villacidro f.c.

algheroarmungiasanta lucia

sanluri o.n.c.

escalaplano capo frascaoroseipalmas suergiucapo bellavistacorongiu

bosa

muravera

decimomannurifornitore

tirso

capo carbonara

iglesiaspiscinamanna

ottava

castiadascampuomu

olbiabudoni (c.ra)

sassari (serra secca) s. giovanni coghinas

s. giusta

elmasuta

3000

3500

4000

4500

5000

5500

6000

6500

7000

7500-1000 -900 -800 -700 -600 -500 -400 -300 -200 -100 0

MaxPSMD (mm )

D

CLIMATIC LCA MAP

Bioclimatic Index Analysis

utaelmas

s. giusta

s. giovanni coghinassassari (serra secca)

budoni (c.ra)olbia

campuomucastiadas

ottava

piscinamannaiglesias

capo carbonara

rifornitoretirso

decimomannu

muravera

bosacorongiucapo bellavistapalmas suergiu

orosei capo frascaescalaplano

sanluri o.n.c.santa lucia

armungia alghero

villacidro f.c.

calagonone

carloforte

mogoro (diga)

oschiri villavovatulomacomernuoro

bidighinzu

ozierilanusei

meanasardo

jerzu

mandas f. c.

nurri f. c.

cuglieri

vallicciolagenna-silana

santa sofia

col. penale sarcidanosos canales (diga)

ala' dei sardidesulo

is cannoneris

tempiovillanova monteleone

asinara

3000

3500

4000

4500

5000

5500

6000

6500

7000

7500-1000 -900 -800 -700 -600 -500 -400 -300 -200 -100 0

MaxPSMD (mm )

D

2.1 12.2

3.1

3.2

4.1

4.2

5.17.1 6.1

7.2

6.2

5.2

CLIMATIC LCA MAP

Climatic LCA Classification

Max Potential Soil Moisture Deficit 1961-1990


Climatic Land Capability 1971-2000


Prime Classes

Non Prime Classes

Prime Classes

Non Prime Classes

PEDO-CLIMATIC LCA MAP

Pedo-climatic LCA Classification

Pedo-climaticLCA class

PedologicalLCA classes

ClimaticLCA classes

most suitable

moderately suitable

less suitable

not suitable

1 to 4

4-6, 4-8, 6

6-7, 6-8

8

1, 21, 22, 31

1, 21, 22, 31

Prime + 32, 41, 42

-

most suitable (23.7%)

moderately suitable (27.7%)

less suitable (17.4%)

not suitable (31.2%)

PEDO-CLIMATICLCA MAP

(1961-2000)(1961-2000)

Pedo-Climatic Land Capability 1961-2000

most suitable

moderately suitable

least suitable

not suitable

Classes

PEDO-CLIMATIC LCA MAP (1971-2000)(1971-2000)

most suitable

mod. suitable

less suitable

not suitable

82

79

61

8074

77

7863

847675

8672626981clima

668887 83

6467 89

736590 7068

71 85

3000

3500

4000

4500

5000

5500

6000

6500

7000

7500-1000 -900 -800 -700 -600 -500 -400 -300 -200 -100 0

MaxPSMD (mm)

°D

D1D2D3D4

D5

D6

Cell #1

-160-340-440-540-640

Climate Variability AnalysisCLIMATIC RISK MAP

Cell # MaxPSMDmedian

D1 D2 D3 D4 D5 D6

1 -565 0 3 6 3 15 3 2 -646 0 0 2 8 5 15 3 -615 0 2 3 6 5 14 4 -625 0 2 2 7 5 14 5 -623 0 2 2 6 6 14 6 -600 0 2 5 4 10 9 7 -639 0 0 2 8 5 15 8 -581 0 2 6 3 12 7 9 -498 0 7 4 10 7 2

10 -547 0 3 7 4 11 5 11 -630 0 0 3 8 5 14 12 -400 3 8 8 8 3 0 13 -409 2 9 7 9 3 0 14 -562 0 3 6 4 11 6 15 -619 0 2 2 7 7 12

Climate Variability AnalysisCLIMATIC RISK MAP

Risk Index = 6

1

*D

D

f coeff

Class D1 D2 D3 D4 D5 D6

coefficient 0 0.05 0.5 0.75 0.9 1

Cell # D1 D2 D3 D4 D5 D6 1 0.00 0.10 0.20 0.10 0.50 0.10 2 0.00 0.00 0.07 0.27 0.17 0.50 3 0.00 0.07 0.10 0.20 0.17 0.47 4 0.00 0.07 0.07 0.23 0.17 0.47 5 0.00 0.07 0.07 0.20 0.20 0.47

f

Climate Variability Analysisand Climate Risk Assessment

CLIMATIC RISK MAP

Risk Class Risk Index

Null 0 - 0.25 Low 0.25 - 0.50 Moderate 0.50 - 0.75 High 0.75 - 1.00

Climate Risk Assessment

CLIMATIC RISK MAP

Climatic Risk1961-1990


null null

low low

moderate moderate

high high

GDD: 51-80, 61-90, 71-0071-00

Climatic LCA: 51-80, 61-90, 71-0071-00

FUTURE CLIMATE FUTURE CLIMATE SCENARIOSSCENARIOS

Data obtained from CNR – IBIMET, FlorenceData obtained from CNR – IBIMET, Florence Sub-project 1: High resolution future climate scenarios Climate Model developed by Climate Model developed by Hadley Centre (Met. Office, UK) HADCM3 Model (AOGCM) Climate scenarios A2 and B2 Period 2005-2099

A2

B2

Growing Degree Days 1971-2000 Growing Degree Days2070-2099 (Scenario B2)

GDD

GDD


Max Potential Soil Moisture Deficit2070-2099 (Scenario A2)


Climatic Land Capability 2070-2099 (Scenario A2)

Prime Classes

Non Prime Classes

Prime Classes

Non Prime Classes


(1961-2000)(1961-2000)





Pedo-Climatic Land Capability 1961-2000

most suitable

moderately suitable

least suitable

not suitable

Classes


(2070-2099 – (2070-2099 – A2)A2)





Pedo-Climatic Land Capability 2070-2099 (Scenario A2)

most suitable

moderately suitable

least suitable

not suitable

Classes


(2070-2099 – (2070-2099 – B2)B2)





Pedo-Climatic Land Capability 2070-2099 (Scenario B2)

most suitable

moderately suitable

least suitable

not suitable

Classes

Pedo-climatic LCA classes

Surface area relative to the total area(%)

1961-2000 Scenario A2 Scenario B2

most suitable 23.7 10.5 14.0

moderately suitable 27.7 19.3 19.7

least suitable 17.4 38.4 35.4

not suitable 31.2 31.8 30.9

ConclusionsConclusions

TTo determine climatic risk for o determine climatic risk for agriculture, climatic variability agriculture, climatic variability should be included in the LCA should be included in the LCA methodology methodology The methodology can be easily applied to actual and future climate



To determine climatic risk for To determine climatic risk for agriculture, climatic variability agriculture, climatic variability should be included in the LCA should be included in the LCA methodology methodology The methodology can be easily applied to actual and future climate



By adjusting bioclimatic indexes, the methodology can be applied to different climatic regions Limitations of the results mainlyLimitations of the results mainly depend on spatial resolution of depend on spatial resolution of inputinput data and approximations derived data and approximations derived fromfrom empirical analysis empirical analysis



By adjusting bioclimatic indexes, the methodology can be applied to different climatic regions Limitations of the results mainlyLimitations of the results mainly depend on spatial resolution of depend on spatial resolution of inputinput data and approximations derived data and approximations derived fromfrom empirical analysis empirical analysis


THANKSTHANKS


Climatic Risk2070-2099 (Scenario B2)

null

low

moderate

high

null

low

moderate

high

Documents

Climatic variability and climate risk in agriculture in the Mediterranean area