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WORKSHOP “CROP YILED FORECASTING IN SOUTH EAST EUROPE”

SJOPJE, 30-31 MAY 2013Faculty of Agricultural Sciences and Food

AGROMETEOROLOGICAL ACTIVITY IN ROMANIA AND EXPERIEN CES IN THE CONTEXT OF CLIMATE CHANGE

Dr. Elena Mateescu National Meterological Administration

MINISTRY OF ENVIRONMENT AND CLIMATE CHANGE

NATIONAL METEOROLOGICAL ADMINISTRATION

OUTLINE►AGROCLIMATIC CONDITION IN ROMANIA IN THE CONTEXT OF

CLIMATE CHANGE

►AGROMETEOROLOGICAL OPERATIONAL ACTIVITY

- AGROMETEOROLOGICAL NETWORK

- DISSEMINATION PROCESS OF AGROMETEOROLOGICAL PRODUCTS

►AGROMETEOROLOGICAL RESEARCH ACTIVITY - NATIONAL AND EUROPEAN RESEARCH PROJECTS

►FUTURE STEPS

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8.4

8.5

8.6

8.7

8.8

8.9

9

9.1

9.2

9.3

0C

1961-1970 1971-1980 1981-1990 1991-2000 2001-2010

Decennial evolution of mean multiannual air tempera ture - RomaniaMean air temperature (0C)

1961-1970 8.9 /+0.40C

1971-1980 8.7 /+0.60C

1981-1990 8.7 /+0.60C

1991-2000 8.8 /+0.50C

2001-2010 9.3

2001-2010 / + 0.4…+0.6°°°°C

Mean annual air temperature trend in Romania, over 1901-2010 period

7.0

7.5

8.0

8.5

9.0

9.5

10.0

10.5

11.0

11.5

12.019

01

1906

1911

1916

1921

1926

1931

1936

1941

1946

1951

1956

1961

1966

1971

1976

1981

1986

1991

1996

2001

2006

Anii

Tem

p. (

grad

e C

elsi

us)

► In ROMANIA, the mean annual airtemperature rose by 0,6°C in the last 100years. The evolution by decades of themean multiannual air temperature overthe 1961-2010 period show that the airtemperature rose by 0,4...0,6°C in the2001-2010 interval in comparison withevery decade. The increasing trend isobvious especialy begining with 1971.

Annual air temperature trend in Romania,over 1901-2010 period

REASON FOR CONCERNS???AGROCLIMATIC CONDITION IN ROMANIA IN THE CONTEXT OF CLIMATE CHANGE

Annual rainfall trend in Romania, over 1901-2010 per iod

Annual rainfall amounts (mm) trend in Romania, over 1901-2010 period

y = 0.0045x + 635.65

400.0

500.0

600.0

700.0

800.0

900.0

1000.0

1901

1905

1909

1913

1917

1921

1925

1929

1933

1937

1941

1945

1949

1953

1957

1961

1965

1969

1973

1977

1981

1985

1989

1993

1997

2001

2005

2009

Series1 Linear (Series1)

As regards precipitation, the 1901-2010 period highlighted a general decreasing trend in the annual precipitation amounts especially after 1961 year and a parallel enhance of the

precipitation deficit in the South, South-East and East of the country.

1945-1946 2006-2007 2011-2012

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DECADEXX-TH CENTURY

EXTREMELY DROUGHTY YEARS EXTREMELY RAINY YEARS

1901-1910 1907-1908 1910

1911-1920 1917-1918 1911, 1912, 1915, 1919

1921-1930 1923-1924, 1927-1928 1929

1931-1940 1934-1935 1937, 1939, 1940

1941-1950 1945-1946, 1947-1948, 1949-1950 1941, 1944, 1947

1951-1960 1952-1953 1954, 1955, 1957, 1960

1961-1970 1962-1963, 1964-1965 1969, 1970

1971-1980 1973-1974, 1975-1976 1972, 1974, 1975, 1976

1981-1990 1982-1983, 1985-1986, 1987-1988 1981, 1990

1991-2000 1992-1993, 1997-1998, 1999-2000 1991, 1997

XXI-ST CENTURY

2001-2010 2000-2001, 2001-2002, 2002-2003,

2006-2007, 2008-2009

2005, 2006, 2008, 2010

2011-2020 2011-2012

Since 1901 until now, Romania has seen in every decade one to four extremely droughty/rainy years, an increasing number of droughts being

more and more apparent after 1981

Droughty/rainy years in Romania

(1901-2010)

31 July / Maize 31 August / Maize

Soil moisture classes

<300 mc/ha Extreme pedological drought

300 – 600 mc/ha Severe pedological drought

600 – 900 mc/ha Moderate pedological drought

900 – 1200 mc/ha Satisfactory supply

Soil moisture reserve in Romania

(1971-2000)

The southern, south-eastern and eastern part of Rom ania are the most vulnerable areas to extreme and severe pedolog ical drought.

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31 July / Maize 31 August / Maize

Estimations of the soil moisture reserve in Romania, in the context of

predictable climate change

In the conditions in which the climatic scenarios estimate a decrease of the annual precipitation amounts (10-20%), it is expected that the intensity of pedological

drought phenomena increased in the most vulnerable areas already known today, respectively the south, south-east and east of Romania. In the areas limited by the

red line, the pedological drought will reach the highest intensity values (extreme/Co-300 m3/ha and severe/600-900 m3/ha).

Internet – free access of seasonal forecasts and agromet information(http://www.meteoromania.ro/anm/?lang=ro_ro)

- Seasonal forecasts-Agrometeorological

forecasts - Soil moisture information

AGROMETEOROLOGICAL OPERATIONAL ACTIVITY

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AGROMETEOROLOGICAL RESEARCH ACTIVITY

- NATIONAL AND EUROPEAN RESEARCH PROJECTS

1. National Programme of Research, Development and Innovation (PNCDI-II, and PNII-ID-PCCE and PCCA-2), 2007-2015:

- GRIMPCLIM: Ways to mitigate climatic change impacts on wheat crops in SouthernRomania (2007-2010)

- CLIMPACTPOMI: Evaluating the climatic change impacts on Romania’s agro-climaticpotential in order to zone fruit-growing yields (2007-2010).

2. Sectoral Plan of the Ministry of Agriculture and Rural Dev elopment – ADER 2020(2011-2014)

- ADER 1.1.1: Geo-referential indicators system at different spatial and temporal scales toassess the vulnerability and adaptation of agro-ecosystems to global changes

- ADER 3.3.1: Monitoring and assessment system of the indicators regarding the agreementwith the EU Agro-environmental Directives specific to semi-subsistence farms

- ADER 5.1.1: creating of geo-referential data bases regarding the regional climate risks forthe main agricultural and horticultural crops

- ADER 8.1.1: Evaluating the risk of contamination with micotoxines at winter wheat crops inRomania

PROGRAMS AND NATIONAL RESEARCH PROJECTS

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1. RESEARCH ACTIVITIES RELATED TO CLIMATE CHANGE SCENARIOS

⇒ FP6 / CECILIA - Central and Eastern European Climate Change Impact and Vulnerability Assessment (2006-2009)

2. RESEARCH RELATED TO CLIMATE CHANGE ADAPTATION: assessin gvulnerabilities and risks and translating them to implemen tation actions at theregional and local levels

⇒ INTERREG IVC / WATERCoRe - Water scarcity and drought - Co-ordinated activitiesin European Regions (2010-2013)

⇒ PROJECT CE DGE / MIDMURES - Mitigation Drought in Vulnerable Area of theMures Basin (2011-2012)

⇒ SEE Transnational Cooperation Programme / ORIENTGATE: a structured networkfor integration of climate knowledge into policy and territorial planning (2012-2014)

⇒ SEE Transnational Cooperation Programme /CC-WARE: Mitigating Vulnerability ofWater Resources under climate Change (2012-2014)

EUROPEAN RESEARCH PROJECTS

WG4Pilot study 2: Climate change

adaptation measures in Romanian agriculture field

NMA - coordinator of pilot studyEPA Covasna - partner

SEE / OrientGate ProjectA structured network for integration of climate kno wlegde into policy

and territorial planning

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Project activities will be carried out under seven work packages (WPs):

WP1: Transnational project and financial management

WP2: Communication activities

WP3: Mapping and harmonising data and downscaling

WP4 Thematic Centre 1: Forestry and Agriculture

- Pilot Study 1: Adapted forest management at LTER Zobelboden, Austria

- Pilot Study 2: Climate change adaptation measures in Romanian agriculture

WP5 Thematic Centre 2: Drought, Water and Coasts

- Pilot Study 3: Climate change adaptation in the new water regime

in Puglia region, Italy

- Pilot Study 4: Effects of climate change on wetland ecosystems in

Attica region, Greece

- Pilot Study 5: Water resources and hydroelectric use, Trento, Italy

WP6 Thematic Centre 3: Urban Adaptation and Health

- Pilot Study 6: Vulnerability assessment in two Hungarian municipalities — 13th

district of Budapest and Veszprem

WP7 Regional Planning Cross-Sectoral Study

The ORIENTGATE project aims to implement concerted and coordinated climate adaptation actions across South Eastern Europe (SEE).

A set of indicators which will be tested in different pilot areas of 3 Thematiccentres (TC):- TC1- Forestry and Agriculture (pilot studies in Austria and Romania);- TC2- Drought, Water and Coasts (pilot studies in Italy and Greece);- TC2- Urban Adaptation and Health (pilot study in Hungary).The calculation of indicators will be executed side by side using the observedmeteorological data and data time series generated on the basis of climateprojections. The sets of indicators are grouped by every sector (agriculture,forests, hydrology and health).

Spatial distribution of all the meteorological stations from the project

partners involved in WP3 activities

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Index Name Index Name

FD Frost Days SDII Simple Daily Intensity Index

TD Tropical Days R5mm n° of days with RR ≥ 5mm

CTD Consecutive Tropical Days CDD Consecutive Dry Days

GSL Growing Season Length CWD Consecutive Wet Days

GDD Growing Degree Days R99pTOTPrecipitation due to extremely wet

days (> 99th percentile)

WSDI Warm Spell Duration Index PRCPTOT Total precipitation in wet days

CSDI Cold Spell Duration Index WD Warm/Dry

PaDI Palfai Drought Index SPI3 Standardized Precipitation Index

PET Potential EvapoTranspiration SPEI3Standardized Precipitation-

Evapotranspiration Index

AI Aridity Index

Agriculture

Pilot study 2 – description and methods of implementation

Summary

� 2 sites in Covasna and Caracal, with different agroclimatic conditions

� Different cropping systems (winter wheat, maize, sunflower and potato)

� CERES-Wheat and CERES-Maize models, in combination with the RegCMs climatic predictions at a very fine resolution over 2021-2050 and 2071-2100

� The DSS for Agrotechnology Transfer (DSSAT) in order to evaluate the potential impact of weather patterns on the productivity of selected crops

� Three different technological sequences will be analyzed by alternative simulations of crop management practices: application of irrigation, using different soil classes, changes in sowing date, etc.

Implementation

� NMA (PP10): will be responsible for implementing Pilot 2 (Task 1-3)

� EPA Covasna (PP9): will participate to the implementation process (Task 1-3).

� Local Municipality from Covasna and Caracal will provide technical support for the implementation of results in order to develop drought-risk management tools and adaptation measures (Task 1 and 3).

� LP/CMCC will collaborate with NMA in implementing of the Pilot 2 (Task 2).

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The area of pilot study 2

⇒ Covasna county is located inthe south-eastern part of theTransilvania region, in avulnerable area to extremeevents (drought/floods).

⇒ Caracal county is located in thesouth part of the Oltenia region, in avulnerable area to extremeconditions (drought/water scarcity).

Long-term observations and agro-climatic data

� Drought indicators:

� climatic indicators: SPI, Aridity index

� agrometerological indicators: soil moisture

� satellite-derived products: Normalized Difference Water Index (NDWI), Leaf area Index (LAI); Fraction of Absorbed Photosynthetic Solar Radiation (fAPAR)

SPI / November 2011 Soil Moisture Reserve / November 2011

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Projected changes in monthly means of air temperature and precipitation for decades 2021-2050 and 2071-2100 / CARACAL

01020304050607080

I II III IV V VI VII VIII IX X XI XII

1961-1990

2021-2050

2021-2050 /-15,8% - VII

01020304050607080

I II III IV V VI VII VIII IX X XI XII

1961-1990

2071-2100

2071-2100 /-35.9% - VII

-5

0

5

10

15

20

25

I II III IV V VI VII VIII IX X XI XII

1961-19902021-2050

2021-2050 /+0,4°C – VI, VII, VIII, IX

-5

0

5

10

15

20

25

I II III IV V VI VII VIII IX X XI XII

1961-19902071-2100

0

C

2071-2100 /+0,8°C- VIII

RESULTS – based on regional climate model (RCM) outputs developed in the Ensembles project (8 RCMs)

Growing season duration / winter wheat and maize cr opsRegCMs/ 2021-2050 and 2071-2100/ SRES A1B scenario

230 240 250 260 270 280

Currentclimate

2021-2050

2071-2100

Craiova

Bechet

Bailesti

Calafat

Caracal

Winter wheat growing season duration

100 105 110 115 120 125 130 135 140 145 150

Current climate

2021-2050

2071-2100

DS (days )

Maize growing season duration

CraiovaBechetBailestiCalafatCaracal

Oltenia Plain1961 – 1990 / 261 – 274 days2021 - 2050 / 251 – 264 days / -9...-13 days2071 - 2100 / 245 – 259 days / -15...-22 days

CARACAL1961 – 1990 / 270 days2021 - 2050 / 257 days / -13 days2071 - 2100 / 251 days / -19 days

Oltenia Plain1961 – 1990 / 133 – 145 days2021 - 2050 / 121 – 133 days / -7...-16 days2071 - 2100 / 167 – 125 days / -14...-25 days

CARACAL1961 – 1990 / 142 days2021 - 2050 / 127 days / -15 days2071 - 2100 / 117 days / -25 days

Shortening vegetation season with 9-22 days for win ter wheat, and 7 to 25 days for the maize crop

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Winter wheat and maize grain yield /RegCMs/2020-2050 and 2071-2100/A1B scenario

10001500200025003000350040004500500055006000

Current climate 2021-2050 2071-2100

CaracalCalafatBailestiCraiovaBechet

Average winter wheat grain yieldkg/ha

100015002000250030003500400045005000550060006500

Current climate 2021-2050 2071-2100

Average maize grain yield

CaracalCalafatBailestiCraiovaBechet

kg/ha

Oltenia Plain 1961-1990 / 4380 - 4840 kg/ha2021-2050 / 4598 - 5225 kh/ha / 2.5…8.0%2071-2100 / 5052 - 5469 kg/ha / 10,2…17,5%

Oltenia Plain1961-1990 / 5094 - 5420 kg/ha2021-2050 / 4256 - 4898 kg/ha / -6,7…-17,0%2071-2100 / 3125 - 4298 kg/ha / -18.6…-39.1%

CARACAL1961-1990 / 4452 kg/ha2021-2050 / 4731 kg/ha / 6.3%2071-2100 / 5147 kg/ha / 15.6%

CARACAL1961-1990 / 5094 kg/ha2021-2050 / 4358 kg/ha / -14.4%2071-2100 / 3235 kg/ha / -36.5%

1. Increasing wheat production with 2.5 ... 17.5%; 2. Reducing maize production with 6,7 ... 39,1%;

3. Winter wheat can benefit from the interaction bet ween increased CO 2 concentrations and higher air temperatures, while maize is vulnerable t o climate change, mainly in the case of a

scenario predicting hot and droughty conditions.

MANAGEMENT RECOMMENDATIONS AND OPTIONS TO IMPROVE THE CROP SYSTEMS AND YIELDS IN ROMANIA , IN THE CON TEXT

OF REGIONAL CLIMATE CHANGE SCENARIOS OVER 2020-2050

1. Recommendations and options to improve the genoty pe varieties and yields

2. Recommendations to improve effective use of water (WUE) by crops

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Winter wheat - altered genetic coefficients (P1V and P1D) for genotype selection

P1 V / FUNDULEA 4-MEDSpecific. Current climate

P1V=6.0ScenarioP1V=6.0

2020-2050P1V=5.0

450 ppmP1V=4.0 P1V=3.0 P1V=2.0

GY (kg.ha-1) 4650 5727 4675 4687 4691 4693

PRC (mm) 424 379 357 357 357 357

ET (mm) 505 392 314 314 314 314

Maturity (days) 192 175 155 155 155 155

SD (days) 279 262 242 242 242 242

WUE (kg.m-3) 0.9 1.5 1.5 1.5 1.5 1.5

Specific. Climatic Scenario SD(days)

GY(kg.ha -1)

ET(mm)

PRC(mm)

WUE(kg.m -3)

P1V=6.0

P1V=6.0P1V=5.0P1V=4.0P1V=3.0P1V=2.0

Current climate

2020-2050 (450ppm)2020-2050 (450ppm)2020-2050 (450ppm)2020-2050 (450ppm)2020-2050 (450ppm)

279

-17-37-37-37-37

4650

23.2%0.5%0.8%0.9%0.9%

505

-22.4%-37.8%-37.8%-37.8%-37.8%

424

-10.6%-15.8%-15.8%-15.8%-15.8%

0.9

58.7%61.7%62.1%62.2%62.3%

Winter wheat grain yield /2020-2050/450 ppmP1 V / Fundulea 4-MED

100015002000250030003500400045005000550060006500

Currentclimate

P1V=6 P1V=5 P1V=4 P1V=3 P1V=2

kg/h

a

The most suitable genotype - winter wheat varieties with high vernalization

requirement / P1V=6.0

Specific. Current climate P1D=4

Scenario

P1D=4

2020-2050

P1D=3.5

450 ppm

P1D=3.0 P1D=2.5 P1D=2 P1D=1

GY (kg/ha) 4307 5713 5734 5689 5612 5459 5187

PRC (mm) 437 408 379 379 364 353 367

ET (mm) 519 405 392 370 354 337 309

Maturity (days) 196 180 175 168 165 159 153

SD (days) 283 267 262 255 252 246 240

WUE (kg/mc) 0.8 1.4 1.5 1.5 1.6 1.6 1.7

P1 D / FUNDULEA 4-MED

Specific. Climatic scenario SD(days)

GY(kg.ha -1)

ET(mm)

PRC(mm)

WUE(kg.m -3)

P1D=4.0

P1D=4.0P1D=3.5P1D=3.0P1D=2.5P1D=2.0P1D=1.0

Current climate

2020-2050 (450ppm)2020-2050 (450ppm)2020-2050 (450ppm)2020-2050 (450ppm)2020-2050 (450ppm)2020-2050 (450ppm)

283

-16-21-28-31-37-43

4307

+32.6%+33.1%+32.1%+30.3%+26.7%+20.4%

519

-22.0%-24.5%-28.7%-31.8%-35.1%-40.5%

437

-6.6%-13.3%-13.3%-16.7%-19.2%-16.0%

0.8

70.0%76.3%85.3%91.0%95.2%

102.3%

Winter wheat grain yield /2020-2050/450ppmP1 D / Fundulea 4-MED

100015002000250030003500400045005000550060006500

Currentclimate

P1D=4 P1D=3.5 P1D=3.0 P1D=2.5 P1D=2 P1D=1

kg/h

a

The most suitable genotype - winter wheat varieties with moderate

photoperiod requirement / P1D=3.5

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Winter wheat grain yield /2020-2050/450ppmAltereted genetic coefficients (P1V and P1D)

/ Fundulea 4-MED

4200

4400

4600

4800

5000

5200

5400

Currentclimate

Var 1 Var 2 Var 3 Var 4 Var 5

kg/h

aSpecific. Current

climate P1V=6.0

ScenarioVAR 1

P1V=3.0/P1D=3.0

2020-2050VAR 2

P1V=4.0/P1D=3.5

450 ppmVAR 3

P1V=6.0/P1D=2.5VAR 4

P1V=4.0/P1D=2.0VAR 5

P1V=6.0/P1D=1.0

GY (kg.ha-1) 4650 5017 5321 5334 5180 5076

SD (days) 279 245 258 252 242 240

Winter wheat growing season2020-2050/450 ppm

225 230 235 240 245 250 255 260 265

Current climate

Var 1

Var 2

Var 3

Var 4

Var 5

days

The most suitable combinations - winter wheat varieties with high vernalization and moderate photoperiod requirements / P1V =6.0/P1D=2.5

Altered genetic coefficients - P1 V / P1 D

FUNDULEA 4-MED

Rainfed Winter Wheat Water Use Efficiency

1.11.15

1.21.25

1.31.35

1.41.45

1.51.55

1.61.65

1.71.75

1.8

CurrentClimate

2020s 2050s

WU

E (k

g.m

-3)

Soil 1Soil 2Soil 3Soil 4

Rainfed Maize Water Use Efficiency(different soil type and texture)

1.61.71.81.9

22.12.22.32.42.52.6

Currentclimate

2020s 2050s

WU

E (kg

.m-3

)

Soil 1Soil 2Soil 3Soil 4Soil 5

Soil classes WUE (kg.m-3)Base

WUE(kg.m-3)2020s

WUE (kg.m-3)2050s

Soil 1: Cambic chern.-clay loam 1.26 1.39 1.68

Soil 2: Cambic chern.-clay 1.22 1.38 1.67

Soil 3: Cambic chern.-sandy loam 1.23 1.41 1.68

Soil 4: Brown reddish-fine loamysand

1.25 1.40 1.68

Soil classes WUE (kg.m-3)Base

WUE(kg.m-3)2020s

WUE (kg.m-3)2050s

Soil 1: Cambic chern.-clay loam 2.08 2.10 2.25

Soil 2: Cambic chern.-sandy clay 2.08 2.06 2.44

Soil 3: Cambic chern.-sandy loam 2.16 2.06 1.84

Soil 4: Brown reddish – clay 2.25 2.23 1.94

Soil 5: Brown reddish – fine loam 2.28 2.23 2.06

Winter wheat WUE shows an increasing trend for all soil classes, but there are not differences between the four soil

classes

The highest increase of maize WUE, up to 8.2 -17.3% in 2050, can be expected for the medium Cambic Chernozems soils ( sandy clay

and clay loam)

Winter wheat and Maize - Using different soil classe s /Calarasi

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Rainfed & Irrigated Maize WUE(change in sowing date)

1.61.71.81.92.02.12.22.32.42.52.62.72.8

Currentclimate

2020s 2050s

WU

E (k

g.m

-3)

April 24/Irrig.April 1/Irrig.April 24/RainfedApril 1/Rainfed

Rainfed Winter Wheat WUE (change in sowing date)

0.60.70.80.9

11.11.21.31.41.51.61.71.81.9

2

Base 2020s 2050sW

UE

(kg

.m-3

)

Nov. 5Oct.25Oct.12Sept.30Sept.20 Sept.10

In the case of winter wheat, water is used more efficiently with the later sowing date, October 25 and November 5, respectively.

The predicted WUE of maize crop increases by 6.1-18.2% in both scenarios (2020s and

2050s), with an earlier sowing date (April 1) in comparison with current dates (April 24).

Winter wheat and Maize – change in sowing date / CalarasiSowing date WUE

(kg.m-3)Base

WUE (kg.m-3)2020s

WUE (kg.m-3)

2050s

November 5 1.41 1.51 1.85

October 25 1.35 1.45 1.8

October 12 1.26 1.39 1.68

September 30 1.16 1.31 1.58

September 20 1.07 1.23 1.6

September 10 0.98 1.15 1.51

Rainfed Irrigated

Sowing date

Scenario GY(kg.ha-1)

ET(mm)

WUE(kg.m-3)

GY(kg.ha-1)

ET(mm)

WUE(kg.m-3)

April 24 Base2020s2050s

7196-32.9%-81.5%

346-14.4%-30.3%

2.08+1.0%+8.2%

10198-3.9%-9.8%

510-5.5%-12.2%

2.0+8.0%+19.0%

April 1 Base2020s2050s

8158-0.5%

+18.1%

348-9.2%

+24.7%

2.34+9.8%+9.0%

10251-7.3%

+10.5%

518+12.7%+24.3%

1.98+6.1%+18.2%

Winter wheat - application of irrigation /Calarasi

Rainfed Irrigated

Specific. Scenario GY(kg.ha-1)

ET(mm)

WUE(kg.m -3)

GY(kg.ha-1)

ET(mm)

WUE(kg.m -3)

Without CO 2 Base2020s2050s

4945-1.5%+12%

391-3.6%-5.9%

1.26+2.4%

+19.8%

5833-1.2%

-

452-4.0%-9.7%

1.29+3.1%

+10.9%

With CO 2 2020s2050s

+5.6%+20.9%

-3.8%-8.7%

+10.3%+33.3%

+3.9%+13.0%

-6.2%-14.2%

+10.9%+31.8%

Rainfed Winter Wheat Water Use Efficiency

11.11.21.31.41.51.61.71.81.9

2

CurrentClimate

2020s 2050s

WU

E (kg

.m-3

)

without CO2

with CO2

Irrigated Winter Wheat Water Use Efficiency

11.11.21.31.41.51.61.71.81.9

2

CurrentClimate

2020s 2050s

WU

E (kg

.m-3

)

without CO2

with CO2

Winter wheat crop uses the available soil water mo re efficiently in both scenarios, particularly in t he case of 2050 scenario, Taking into account the CO2 effect on both rainfed and irrigated winter wheat, the WUE increas es

significantly by 10-11% in 2020 and by 32-33% in 20 50, compared with the current conditions, due mainl y to the increased CO2 assimilation rate

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15

Rainfed Irrigated

Specific. Scenario GY(kg.ha-1)

ET(mm)

WUE(kg.m -3)

GY(kg.ha-1)

ET(mm)

WUE(kg.m -3)

Without CO 2 Base2020s2050s

7196-32.9%-81.5%

346-14.4%-30.3%

2.08-21.6%-73.5%

10198-3.9%-9.8%

510-5.5%

-12.2%

2.0+1.5%+2.5%

With CO 2 2020s2050s

-13.7%-20.8%

-14.4%-26.9%

+0.1%+8.2%

-2.9%-8.6%

-10.2%-23.1%

+8.0%+19.0%

Rainfed Maize Water Use Efficiency

0

0.5

1

1.5

2

2.5

3

Currentclimate

2020s 2050s

WU

E (kg

.m-3

)

without CO2

with CO2

Irrigated Maize Water Use Efficiency

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Currentclimate

2020s 2050sW

UE

(kg

.m-3

)

without CO2

with CO2

By application irrigation, the water use efficiency increases for both scenarios by 1.5-2.5% (without CO2) up to 8-19% (with CO2), compared with the

current climate

In the rainfed conditions, without taking into acco unt the CO2 effect, WUE decreases significantly by 22% in

2020 up to 74% in 2050

Maize - application of irrigation / Calarasi

CONCLUSIONS► Climate change estimations made by regional climatic model s highlighted that the futureclimate evolutions may have important effects upon crops an d they are conditioned by aninteraction between the following factors: current climat e changes on a local scale, severityof climate scenario-forecasted parameters, how the increa sed CO2 concentrations influencephotosynthesis, and the genetic type of crops (C 3 or C 4).

► Management recommendations and options to improve t he crop systems and yields in the context of regional climate change scenarios a re:⇒ Using different genotype varieties ⇒ Using different soil classes⇒ Change in sowing date⇒ Application of irrigation

► Climate is one of the most important factors determining the productivity of agriculturalproduction systems.

► Future climate projections show that the Romanian agricult ural areas may be affected in anegative way by a number of climate changes that are predicte d by regional climate models.Adapting to climate change through a better crop system mana gement will benefit mainlyfrom the knowledge given by our responses to severe climate e vents, when plans to adaptto and mitigate predictable climate change risks are implem ented.

10/22/2013

16

FUTURE STEPSNEEDS ACTIONS

1. Agro climatic observation,

monitoring and forecasting

1. Extension and modernization of the existing network of agrometeorological

stations and the development of the equipment to ensure reliable ongoing

data at national/ regional/local level

2. Improvement of the collection, management, and use of observational

data and other relevant information on the current and historical climate

and its impact for agriculture;

3. Development of the climate prediction products (seasonal forecasts/three

months);

4. The design of climate information and predictions into early warning and

disaster prevention system (based on various climate forecasts indices –

heat index, drought indices, climatological indices etc).

2. Create systematic archives of

information - extreme maximum

air temperature, heat waves,

droughty years , etc) and available

research studies

1. A comprehensive inventory of available studies, adaptation measures and

policies related to the impacts of drought on agriculture and water

management

2. Review of known impact projections and regional effects with focus on

adaptation measures to drought in agriculture and water management

sectors.

3. Enhancement of cooperation,

transfer of technology, know-how

and practices

1. The exchange of knowledge and experience, and the actual transfer of good

practices to local and regional authorities, including a database of relevant

case studies with a particular emphasis to the impact on different sectors;

2. Regional training of stakeholders for adopting the best available practices

for drought and climate change adaptation based on available information

and studies.

4. Climate modeling and

scenarios

1. Identify gaps in the development of regional climate scenarios and

enhance capacity/experience in the use of different models – training

activities, education and training fellowships, participation in scientific

assessment under IPCC and research under WMO, EU/FP7

programmes, INTERREG, SEE, COST Actions, etc;

2. Improve the availability and applicability of CC modeling for use by

decision makers and farmers (provide data and outputs of the

response of water resources to possible climate change scenarios,

promote the use of GIS technology, etc)

5. New research

projects/programmes

1. New research projects focusing on different themes:

- Knowledge for Climate: information focused on the impact of climate

change on crop and forest yield, pests and diseases, and the

development of a database on droughts and risk mapping at regional

level;

- Decision support systems: supporting policy development, project

development and transfer of information in the science-policy

interface;

2. Integrated research program, including cross-sectoral synthesis in

order to develop knowledge’s regarding the effects of climate change

on regional development in the short, medium and long term

(within/among sectors, spatial/temporal scales, technology, socio-

economic conditions, etc);

FUTURE STEPS

10/22/2013

17

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