Joint DMCSEE / GWP CEE capacity building training

From monitoring to end users

The Romanian experiences in planning and

management of drought – current status

and perspectives

Elena Mateescu – National Meteorological Administration, Romania

4th DMCSEE International Steering Committee

and

3rd Global Water partnership IDMP-CEE workshop

Budapest, Hungary

2 – 4 October 2014

AGROMETEOROLOGICAL

NETWORK

- 7 Regional Meteorological Centres

- 159 weather meteorological stations, 126 being automatic (MAWS)

- 55 weather stations integrating a special program of agrometeorological

measurements – soil moisture and phenological data (winter wheat, maize,

sunflower, rape, fruit trees and vineyards.

National Meteorological Observation Network of Romania

METEOROLOGICAL

NETWORK

Drought monitoring system in Romania - description

1. Agrometeorological and climatic drought indices – heat

stress (HS), soil moisture (SM), SPI, SPEI, PDSI, etc /

operationally activity

2. Drought related-indices derived from remote sensing

data / operationally and research activity

- LAI / Leaf Area Index

- NDVI / Normalized Differences Vegetation Index

- NDWI / Normalized Difference Water Index

- NDDI / Normalized Difference Drought Index

- fAPAR / Fraction of Absorbed Photosynthetically Active

Radiation Index

3. Drought indices - research activity

- DVI / Drought Vulnerability Index

- DROGHT-ADAPT – web platform

1. Agrometeorological drought indicators

Scorching heat intensity Soil moisture

Frequency of dry months / 1970-2012 / Maize crop

0

1

2

3

4

5

6

7

8

1970 1975 1980 1985 1990 1995 2000 2005 2010

nr. luni

BECHET BOTOSANI BUZAU CONSTANTA GALATI GRIVITA ORADEA TG.JIU SATU MARE TIMISOARA VASLUI TG.MURES tendinta

Frequency of dry months on the maize crop over the 1970-2011 period , 22 agromet stations from South of Romania

June – August 2000

June 2003 November 2011 August 2012

SPI index - 3

1. Climatic drought indicators

Spatial distribution of the Palmer Drought Severity annual index (1961-2010)

Trends of 6 – month SPEI values (Standardized Precipitation Evapotranspiration Index) over the 1961-2010 period. Growth

trends are indicated in red and the lowering ones in blue.

SPEI

PDSI / annual

values

Spatial distribution of the Palmer Drought Severity index for the warm season months (May-August over the 1961-2010 period). The negative values indicate

the tendency of aridity and the positive ones show exceeding rainfalls. Hatched zones shows statistically significant trends at a 90% confidence level

(according with Mann Kendall test)

PDSI / seasonal values

Date Soil moisture

(mc/ha)

% CAu (Soil water supply

capacity)

Classes

20.07.2013 883 55 %CAu Satisfactory supply

31.07.2013 695 43 %CAu Moderate pedological

drought

10.08.2013 548 34 %CAu Strong pedological drought

20.08.2013 667 42 %CAu Moderate pedological

drought

MODIS – LAI (1 km) evolution in the Olt and Covasna agricultural areas for 20 July to 20 August 2013

2. Drought related-indices derived from remote sensing data

MODIS NDWI and NDDI over Covasna county on 21.07 -13.08.2013

Date Soil moisture (mc/ha) % CAu (Soil water supply capacity) Classes

10.07.2013 1216 76 %CAu Close to the optimal supply

20.07.2013 883 55 %CAu Satisfactory supply

31.07.2013 695 43 %CAu Moderate pedological drought

10.08.2013 548 34 %CAu Strong pedological drought

20.08.2013 667 42 %CAu Moderate pedological drought

21.07 – 28.07.2013 29.07 – 5.08.2013 6.08 – 13.08.2013

NDVI and NDWI evolution from MODIS and the amount of precipitation

registered at Caracal weather station (wheat crop)

May – September 2013

Through comparing it with the precipitation recorded at Caracal

weather station, a minimum NDVI value was noticed at the beginning of

May, due to the lack of precipitation. Further, due to the precipitation

recorded in May and June, the NDVI values returned to normal (> 0.6). A

NDVI decrease trend can be noticed over the interval when wheat was

harvested (July). The same trend can be seen in the course of NDWI.

NDWI correlates well with the moisture measured at the stations and in

the test area. The maximum values of NDWI (~0.4) correspond to medium

vegetation water content and to medium vegetation fraction cover.

NDVI and NDWI evolution from MODIS and the soil moisture measured at Caracal

weather station (sun flower)

NDVI and NDWI evolution from MODIS and the amount of precipitation registered

at Caracal weather station (sun flower)

- The decrease of both NDVI and

NDWI for the sun flower and maize

crops in August through

September 2013 is explained by

the decreasing of the soil water

moisture reserve and rainfall

deficit.

- The satellite remote sensing

techniques play an important role

in crop identification; disease and

water stress detection, because

they provide spatially explicit

information and access to remote

locations. The use of multispectral

satellite data may ensure an

improvement of the classical

methods destined to determine the

agrometeorological parameters of

interest.

- The vegetation indices are among

the most commonly used satellite

data products for the evaluation,

monitoring, and measurement of

vegetation cover, condition,

biophysical processes, and

change. The main advantages

consist in the possibility to obtain

spatial information with a

resolution varying from kilometers

to meters and to update those data

at time intervals that may vary

from hours to seasons.

NDVI and NDWI evolution from MODIS and the amount of precipitation registered

at Caracal weather station (corn)

FUTURE STEPS of agromet operational activity:

- EU Funding Period for 2007-2013 and 2014-2020 periods / Operational

Sectoral Programme for Environment (POS-MEDIU)

-NMA project: The development of the national system of monitoring and

warning of extreme weather phenomena for the protection of life and

property materials.

- In 2007-2013 period will be implemented the activities related of

modernization of meteo and agrometerological networks:

1. Meteorological network – 31 weather meteo stations (MWAS) in

order to complete the automatic meteo network and dedicated

software for processing data in automatic flow.

2. Agrometeorlogical network:

- Modernization of agromet network / 25 soil moisture portable systems /

new systems implemented within 5 November 2014

- Windows Server /CISC x86 6-core

- National data base platform / type SQL Server 2008

- Modernization of applications in operational activity – dedicated software

for agrometeorological data and indicators (national level)

Agromonitoring system /

conceptual scheme

2 components:

1. Local level / agromet

station - metadata

2. National level – web

application

3. Validation of data at

regional level by 7

responsible with agromet

activity using a web

interface

Type of messages:

- Phenology

- Metadata

- Soil moisture

Soil moisture data

Agromet web-software application / 80 agromet indices

Drought vulnerability scales

DVI Vulnerability Scales Color scale

0.00 – 0.49 No or less vulnerability

0.50 – 0.99 Low vulnerability

1.00 – 1.49 Medium vulnerability

1.50 – 1.99 High vulnerability

2.00 – 2.49 Very high vulnerability

2.50 – 3.00 Extreme vulnerability

W i

DVI =

KN where:

DVI = Drought Vulnerability Index

N = Number of indicators under consideration

W I = Weights of drought vulnerability indicators, where I = 1, 2….N

k = Upper limit of vulnerability weights (e.g. scale = 0-k, where k is highest value of W I

3. Drought vulnerability index (DVI) based on climatic variables Integrated Drought Management Programme in Central and Eastern European Countries /

WMO-GWP Initiative .

- Activity 5.4. Drought Risk Management Scheme: a decision support system

Milestone no. 2.2. Framing methodology for vulnerability to drought assessment based on

available GIS information including population map, type of economic

Vulnerability

level

Scales

Heat stress (HS) SPEI Soil Moisture (SM)

No

vulnerability

0 No stress <10 0 No deficit <-.0.99 0 No deficit 100%AWC

Low

Vulnerability

1 Low

stress

11-30 1 Low deficit -1.99 to -1 1 Low

deficit

65-100%AWC

High

vulnerability

2 Moderate

stress

31 -50 2 Moderate

dry

-2.99 to -2 2 Moderate

deficit

35-65%AWC

Extreme

vulnerability

3 Strong

stress

>51 3 Very Dry <-.3 3 Strong

deficit

0-35%AWC

Drought vulnerability component scale

Heat stress - HS SPEI Soil Moisture - SM

Drought Vulnerability Index for maize crop during the critical period for water plant needs (August)

The most critical areas recorded in the south, south-east and west regions

CONSIDERATIONS on Drought Vulnerability Index (DVI)

- This approach is based on the combination of several climatic indicators

over long periods of time (>30 years 1961-2010). Also, these indicators based on

climatic variables have major influences on plant vegetative processes. The climate

variables such as air temperature, precipitation and evapotranspiration associated

with soil data have a great influence on the aridization processes. The soil type and crop

data are also important. In term of meteorological definition, a drought period is defined

by a significant deficit in the rainfall regime. The heat waves produce thermal stress to

plants even if water is not limited especially during the summer period. Pedological

drought refers to a significant deficit in the soil moisture. For agriculture, drought is

defined by parameters affecting crops growth and yield. All these type of drought affect

agricultural production loss varying function of their intensity and duration.

- The next phase of this research is to explore the drivers of vulnerability and identify

the adaptation pathways of agriculture to climate variability and change. In this regard,

this analysis enabled us to identify the most vulnerable regions for maize crop in

Romania using different climatic indicators and expert analisys (based on

screening approach method). Results obtained suggest a major focus on areas of the

greatest needs in terms of vulnerability to drought events. Vulnerability has been

expressed as a function of exposure and intensity at different level in time and space.

The approach is useful in evaluating the vulnerability of crop systems to drought

and may help the decision makers to formulate more specific and targeted climate

adaptation policies to reduce production losses in agriculture.

Results of the Romanian research in adaptation measures to drought in agriculture

Project SEE /C/0001/2.2./X: A structured network for integration of climate knowlegde into policy and territorial planning – OrientGate (2012-2014)

WG4: TC 1 / Forestry and Agriculture Pilot study 2: Climate change adaptation measures

in Romanian agriculture field

Responsible: National Meteorolgical Administration

EPA Covasna - partner

OrientGate project area

The ORIENTGATE project aims to: - Foster the integration of climate change in territorial planning and development

- Coordinate climate change adaptation efforts in South Eastern Europe

- Connect climate change policy planners and decision makers with the communities

that produce climate knowledge

The Partnership:

- 33 partners (Ministries, NHMS, Regional Public Authorities, Municipalities and Environmental Agency)

- Led by the Euro-Mediterranean Centre on Climate Change (CMCC) Italy

OrientGate

3 Thematic Centers and 6 specific Pilot Studies

The study area of Pilot Study 2

Olt county/ Caracal area is located in the

south part of the Oltenia region, in a

vulnerable area to extreme conditions

(drought/water scarcity).

Covasna county / Tg. Secuiesc area is

located in the south-eastern part of the

Transilvania region, in a vulnerable area to

extreme events (drought/floods).

Observed changes of the climatic condition

in the Pilot Study 2 area – Caracal and Covasna sites,

in the context of CC

Summary

Different cropping systems (winter wheat and maize);

RegCMs climatic predictions at a very fine resolution over 2021-2050 and 2071-2100;

Different technological sequences were analyzed by alternative simulations of crop management practices: changes in sowing date, altered genetic coefficients (P1V and P1D) for genotype selection, irrigation needs, etc.

Implementation

NMA (PP10): is responsible for implementing Pilot 2 (Task 1-3)

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

PILOT STUDY 2

AGROCLIMATIC CONDITION IN THE CONTEXT OF CC

y = 0,0214x + 10,63

9,0

9,5

10,0

10,5

11,0

11,5

12,0

12,5

13,0

13,5

14,0

C Mean annual air temperature trend in Caracal / 1961 - 2010

1961 - 1990 / 10.9C

1981 - 2010 / 11.4C, +0.5C

CARACAL

1961-1990 / 10.9ºC

1981-2010 / 11.4ºC, +0.5ºC

► 2007: 12.9C (+1.9C)

► 1969: 10.0 C (-0.9C)

y = 0,0216x + 6,4807

4,0

4,5

5,0

5,5

6,0

6,5

7,0

7,5

8,0

8,5

9,0

Mean annual air temperature trend in Tg. Secuiesc /1961-2010 C

Tg. Secuiesc / COVASNA

1961-1990 / 6.8ºC

1981-2010 / 7.2ºC, +0.4ºC

► 2007: 8.5C (+1.7C)

► 1985: 5.6 C (-1.2C)

Warmest years in Caracal, over 1961 – 2010 period

(1961-1990 / 10.9C)

Annual air temperature

Deviation

1. 2007 12.9C 1.9C

2. 1994, 2000 12.6C 1.7C

3. 2008, 2009 12.2C 1.3 C

4. 1990, 2002 12.0C 1.1C

5. 2001 11.9C 1.0C

6. 1966, 1999 11.8C 0.9C

7. 1961, 1989 11.7C 0.8C

8. 1983, 1992 11.6C 0.7C

9. 2004 11.5C 0.6C

10. 1968, 1975, 2006, 2010 11.4C 0.5C

11. 2003 11.3C 0.4C

2000-2010 /

10 warmest years

Warmest years in Tg. Secuiesc, over 1961 – 2010 period

(1961-1990 / 6.8C)

Annual air temperature

Deviation

1. 1994, 8.6C 1.8C

2. 2007 8.5C 1.7C

3. 2009 8.2C 1.4C

4. 2008 8.1C 1.3C

5. 1999 7.8C 1.0C

6. 1966, 1989, 1990, 2000, 2002

7.7C 0.9C

7. 2006 7.5C 0.7C

8. 2001, 2004 7.4C 0.6C

9. 1975 7.3C 0.5C

10. 1971, 1972, 1968, 1977, 1983

7.2C 0.4C

11. 1998, 2005 7.1C 0.3C

2000-2010 /

9 warmest years

y = 1,5858x + 12,426 0

50

100

150

200

250

Intensity of scorching heat trend in summer period - CARACAL / 1961-2013 Tmax≥32C

HEAT STRSS /1961-2013

y = 0,3066x - 3,4962

0

10

20

30

40

50

60

70

Intensity of scorching heat trend in summer period -Tg. Secuiesc / 1961-2013

Tmax≥32C

CARACAL 1. 2012 / 224 Units 2. 2013 / 195 Units 3. 2000 / 189 Units 4. 2007 / 159 Units

5. 1987, 1993 / 121 Units

1961-1990 / 36 Units 1981-2010 / 76 Units

Tg. Secuiesc / COVASNA 1. 2012 / 61 Units 2. 2013 / 40 Units 3. 2007 / 39 Units 4. 1987 / 24 Units 5. 2000 / 21 Units

1961-1990 / 2 Units 1981-2010 / 7 Units

Interval Monthly rainfall amounts (mm)

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

1961-1990 38,7 38,9 40,0 47,9 63,1 73,2 60,4 46,3 32,1 32,4 47,7 45,2

1981 - 2013 31,9 29,6 36,9 43,9 51,6 60,2 51,8 41,0 38,5 39,3 41,0 40,5

Deviation -6,8 -9,3 -3,1 -4,0 -11,5 -13,0 -8,6 -5,3 6,3 6,9 -6,7 -4,7

0,0

10,0

20,0

30,0

40,0

50,0

60,0

70,0

80,0

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

1961-1990

1981-2010

Evolution of the mean monthly rainfall (mm) in Caracal over 1981-2010 period, compared with the baseline climate period (1961-1990)

Mean monthly rainfall trend over 1981-2013, compared

with the baseline climate period/ Caracal

Interval Monthly rainfall amounts (mm)

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

1961-1990 20,7 18,8 19,8 44,9 64,4 79,8 79,2 68,8 39,3 27,4 20,1 17,5

1981 - 2013 17,0 18,5 22,6 44,7 69,0 82,6 74,3 67,4 42,0 31,8 20,7 22,6

Deviation -3,7 -0,3 2,8 -0,2 4,6 2,8 -4,9 -1,4 2,7 4,4 0,6 5,1

Mean monthly rainfall trend over 1981-2013, compared

with the baseline climate period/ Tg. Secuiesc

0,0

10,0

20,0

30,0

40,0

50,0

60,0

70,0

80,0

90,0

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

1961-1990

1981-2010

Evolution of the mean monthly rainfall (mm) in Tg. Secuiesc over 1981-2010 period, compared with

the baseline climate period (1961-1990)

CARACAL / 1961 – 2010

2 years / 4.0% - excessively droughty years (<350.0 mm/year)

9 years / 18,0% - dry years (351.0 – 450.0 mm/year)

25 years / 50,0% - moderate dry years (451.0 – 600.0 mm/year)

TOTAl dry years - 36 years / 72,0%)

6 years / 12,0% - optimal years (601.0 – 700.0 mm/year)

8 years / 16,0% - excessive rainy years (701.0 – 800.0 mm/year)

The frequency of droughty/rainy years (1961-2010)

2006-2007

2011-2012

Tg. Secuiesc / 1961 – 2010

14 years / 28,0% - dry years (351.0 – 450.0 mm/year)

28 years / 56,0% - moderate dry years (451.0 – 600.0 mm/year)

TOTAl dry years - 42 years / 84,0%)

6 years / 12,0% - optimal years (601.0 – 700.0 mm/year)

2 years / 4,0% - excessive rainy years (701.0 – 800.0 mm/year)

DECADE XX-TH CENTURY

EXTREMELY DROUGHTY YEARS EXTREMELY RAINY YEARS

1961-1970 1961-1962, 1967-1968 / 2 years 1968-1969, 1969-1970 / 2 years

1971-1980 1973-1974, 1975-1976 / 2 years 1972-1973, 1978-1979 / 2 years

1981-1990 1982-1983, 1984-1985, 1986-1987, 1989-1990 / 4

years

-

1991-2000 1992-1993, 1994-1995, 1995-1996, 1999-2000 / 4

years

1990-1991 / 1 year

XXI-ST CENTURY

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

2006-2007, 2008-2009 / 5 years

2004-2005, 2005-2006, 2009-2010 /

3 years

2011-2020 2011-2012, ……….. ……….

Droughty and rainy years /1961-2020

DECADE XX-TH CENTURY

EXTREMELY DROUGHTY YEARS EXTREMELY RAINY YEARS

1961-1970 1961-1962, 1962-1963, 1963-1964 / 3 years 1969-1970 / 1 year

1971-1980 1973-1974, 1975-1976 / 2 years 1972-1973, 1974-1975, 1978-1979

/ 3 years

1981-1990 1984-1985, 1985-1986, 1986-1987,

1989-1990 / 4 years

-

1991-2000 1991-1923, 1993-1994, 1997-1998 / 3 years 1990-1991 / 1 year

XXI-ST CENTURY

2001-2010 2000-2001, 2002-2003, 2005-2006,

2006-2007 / 4 years

2009-2010 / 1 year

2011-2020 2011-2012, ………. …………….

Caracal

Tg. Secuiesc

-5

0

5

10

15

20

25

30

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

1961-1990

2021-2050

C Projected changes in monthly means of air temperature for

decade 2021-2050 / CARACAL Air Temperature Rainfall

I 0,2 -1,9

II 0,3 9,3

III 0,4 3,4

IV 0,6 3,5

V 0,7 -2.8

VI 0,8 -0,8

VII 1,3 -10,3

VIII 1,1 -2,3

IX 0,5 -8,4

X 0,3 -6,6

XI 0,3 -15,1

XII 0,0 -10,8

AN +0,5C -4.5%

Projected changes of the monthly air temperature and rainfall for decade 2020-2050 CARACAL

RegCMs / SRES A1B scenarios

0

10

20

30

40

50

60

70

80

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

1961-1990

2021-2050

mm

Scenariul RCP 8.5 Scenariul RCP 2.6

Climate change scenarios / 2021-2050 vs.1971-2000 CMIP5 experiments – summer season

Recommendations and options to

improve:

- water use efficiency (WUE) and

- the genotype varieties and yields

A case study for CARACAL and

COVASNA agricultural areas (RegCM3/2020-2050 and 2071-2100/SRES-A1B)

270

257

251

240 250 260 270 280

1961-1990

2021-2050

2071-2100

days

Growing season duration / winter wheat and maize crops

RegCMs/ 2021-2050 and 2071-2100/ SRES A1B scenario

Shortening vegetation season with 13-19 days for winter wheat, and 15 to 25 days for the maize crop

142

127

117

0 20 40 60 80 100 120 140 160

1961-1990

2021-2050

2071-2100

days

Maize growing season duration / CARACAL

Winter wheat growing season duration / CARACAL No. days of SD / Winter wheat

Diff.

1961-1990 270

2021-2050 257 -13

2071-2100 251 -19

No. days of SD / Maize

Diff.

1961-1990 142

2021-2050 127 -15

2071-2100 117 -25

Sowing date WUE

(kg.m-3)

Base

WUE

(kg.m-3)

2020s

WUE

(kg.m-3)

2050s

November 1 1.35 1.52 1.88

October 20 1.30 1.41 1.78

October 10 1.20 1.38 1.62

September 30 1.10 1.26 1.50

September 20 1.09 1.18 1.38

September 10 0.96 1.10 1.25

Water is used more efficiently by the winter wheat crop with the later sowing date (October 20 and November 1) in comparison with earlier dates of September / CARACAL

0

0,2

0,4

0,6

0,8

1

1,2

1,4

1,6

1,8

2

Se

pte

mb

er

10

Se

pte

mb

er

20

Se

pte

mb

er

30

Oc

tob

er

10

Oc

tob

er

20

No

vem

be

r 1

Base

2020s

2050s

WU

E (

kg

.m-3

)

Recommendations to improve effective use of water by crops (WUE) / change in sowing date

0

2

4

6

8

10

12

14

16

18

Current climate 2020s 2050s

apr.01

apr.11

apr.21

Sowing date WUE

(kg.m-3)

Base

WUE

(kg.m-3)

2020s

WUE

(kg.m-3)

2050s

April 1 4.45 12.5 16.5

April 11 3.5 9.9 12.3

April 20 2.05 5.1 8.7

Water is used more efficiently by the maize crop with an earlier sowing date (April 1 and 11) in comparison with later

date (April 20) / CARACAL

Recommendations to improve effective use of water by crops (WUE) / change in sowing date

4000

4200

4400

4600

4800

5000

5200

5400

Currentclimate

Var 1 Var 2 Var 3 Var 4 Var 5

kg

/ha

Winter wheat grain yield /2021-2050/450ppm Altereted genetic coefficients (P1V and P1D)

/ Fundulea 29

Winter wheat - altered genetic coefficients (P1V and P1D)/ Fundulea 29

Specific. Current climate P1V=6.0

Scenario VAR 1

P1V=3.0/P1D=3.0

2020-2050 VAR 2

P1V=4.0/P1D=3.5

/ 450 ppm VAR 3

P1V=6.0/P1D=2.5

VAR 4

P1V=4.0/P1D=2.0

VAR 5

P1V=6.0/P1D=1.0

GY (kg/ha) 4452

5014

5238

5118

5022

4989

SD (days) 270

258

255

252

243

241

The most suitable combinations - winter

wheat varieties with moderate

vernalization and photoperiod

requirements / P1V =4.0/P1D=3.5

Adaptation measures to drought in the context of CC:

changing of the sowing date

ORIENTGATE

Study Pilot 2:

Olt County / Caracal area

Covasna County / Tg. Secuiesc

area

2021-2050

Winter wheat: later sowing date

Caracal area: October 20 and

November 1

Tg. Secuiesc area: September 10

and October 5

Maize: earlier sowing date

Caracal area: April 1 and 11

Tg. Secuies area: March 20 and

April 1

Technical Working Group Meeting – SEE OrientGate Project

1-2 April 2014, Romania

1st April 2014, scientific working group meeting /

Bucharest

The first day of the meeting was dedicated to scientific debates.

The meeting included a discussion of current status of project, a presentation of

preliminary results of Pilot Study 2, and an overview of future steps to identify the most

suitable options for reducing the impacts of climate change (especially drought) as the

best adaptation measures on agriculture in the selected pilot area;

65 participants attended the event namely representatives from the Romanian Academy

of Agricultural and Forestry Sciences “Gheorghe Ionescu-Sisesti”, the Romanian

Academy, the Ministry of Environment and Climate Change, the Ministry of Agriculture and

Rural Development, the Agricultural Research-Development Station Caracal and

specialists working in the areas of agriculture, geography, water resources management,

environment and plant protection;

Also participated the representatives from the Federal Ministry of Agriculture, Forestry,

Environment and Water Management, Forest Department in Austria (BMLFUW) which is

the coordinator of the TC 1 and from the Environmental Protection Agency of Covasna

which is the partner in the project;

8 scientific papers presented during the 1st day of the Technical Working Group Meeting.

• Presenting the current status and the results of the Orientgate Project in the

Romanian media, RTV Television Broadcast.

Technical Working Group Meeting – SEE OrientGate Project

2 April 2014, Caracal, Romania

2 April 2014 - Field trip to the Agricultural Research-Development Station

Caracal to visit the experimental plots developed under Pilot Study 2

- OrientGate publications / Book including all 6 case studies and leaflets

- Pilot Study 2 / 200 Brochure; 100 Books on adaptation to drought in

Romanian agriculture (English/Romanian version)

Local Municipality from Caracal and Covasna will be the main end-users of the project results in order to develop drought-risk management tool

and adaptation measures and farmers to put in practice the recommendations.

OrientGate web-page: http://www.orientgateproject.org/

Warnings at national level and now-casting forecasts at

local level

- Seasonal forecasts (1-3 months)

- Regional forecasts (2 weeks) - Agromet forecats /weekly - Soil moisture maps /daily

- Notes on the drought evolution

TODAY / Internet – free access of meteorological forecasts and agromet information

(http://www.meteoromania.ro/anm/?lang=ro_ro)

FUTURE PERSPECTIVES ON DROUGHT MONITORING IN ROMANIA

Decision-making support system for the integrated management of

drought in agriculture / DROUHT - ADAPT Web Platform for drought

monitoring and forecast

COMPONENTS Historical climate data (e.g.

maps in GIS environment for

each variables (temperature,

precipitation, soil moisture,

etc.) and extreme data of

weather stations/

representative for agriculture

Drought Action

Plan / prevention

measures on

specific phases of

intervention

Agromet station /

climatic data, soil and

phenological data

Vulnerability Drought

Index (DVI)

Technical

recommendations for

agricultural crop

calendar / at regional

evel

Warnings and forecats – 1. Meteorological forecasts / daily

for the next 7 days; and warnings of drought events and other extreme phenomena (heat stress, extreme

rainfall s, heat waves, etc) 2. Agromet forecasts /daily for the

next 7 days 3. Seasonal forecasts (1-3 months)

1. Optimum

2. Pre-alert

3. Alert

4. Emerency

Phase Optimum Pre-alert Alert Emergency

Actions Planification Monitoring and Control

Intervention

Tye of measures

Strategic Tactical Emergency

Agromet station Jan. Febr. Marc. May Jun. Jul. Aug. Sept. Oct. Nov. Dec.

Alexandria

Barlad

Timisoara

Craiova

Drought monitoring and warnings / on-line system

Agromet station

Drought Risk level Scenario (Estimation / update every 2 weeks or 1

month)

Alexandria Very low

Barlad Medium

Timisoara High

Craiova Extreme

Soil moisture / 3 October 2014

http://www.meteoromania.ro/anm/?lang=ro_ro

DROUGHT

Thank you for your attention!

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