Joint GWP CEE/DMCSEE training: The Romanian experiences in planning and management of drought by Elena Mateescu

1. 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

2. 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

3. 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

4. 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

5. June – August 2000
June 2003
November 2011
August 2012
SPI index - 3
1. Climatic drought indicators

6. 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

7. 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

10. 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

11. 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

12. 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.

13. 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)

14. 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)

15. 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

16. Type of messages:
- Phenology
- Metadata
- Soil moisture
Soil moisture data

17. Agromet web-software application / 80 agromet indices

18. 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

19. 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

20. 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

21. 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.

22. 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

23. 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

24. OrientGate 3 Thematic Centers and 6 specific Pilot Studies

25. 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).

26. 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 / 10.9C
1981 - 2010 / 11.4C, +0.5C
CARACAL 1961-1990 / 10.9ºC 1981-2010 / 11.4ºC, +0.5ºC ► 2007: 12.9C (+1.9C) ► 1969: 10.0 C (-0.9C)
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: 8.5C (+1.7C)
► 1985: 5.6 C (-1.2C)

27. Warmest years in Caracal,
over 1961 – 2010 period
(1961-1990 / 10.9C)
Annual air temperature
Deviation
1. 2007
12.9C
1.9C
2. 1994, 2000
12.6C
1.7C
3. 2008, 2009
12.2C
1.3 C
4. 1990, 2002
12.0C
1.1C
5. 2001
11.9C
1.0C
6. 1966, 1999
11.8C
0.9C
7. 1961, 1989
11.7C
0.8C
8. 1983, 1992
11.6C
0.7C
9. 2004
11.5C
0.6C
10. 1968, 1975, 2006, 2010
11.4C
0.5C
11. 2003
11.3C
0.4C
2000-2010 / 10 warmest years
Warmest years in Tg. Secuiesc,
over 1961 – 2010 period
(1961-1990 / 6.8C)
Annual air temperature
Deviation
1. 1994,
8.6C
1.8C
2. 2007
8.5C
1.7C
3. 2009
8.2C
1.4C
4. 2008
8.1C
1.3C
5. 1999
7.8C
1.0C
6. 1966, 1989, 1990,
2000, 2002
7.7C
0.9C
7. 2006
7.5C
0.7C
8. 2001, 2004
7.4C
0.6C
9. 1975
7.3C
0.5C
10. 1971, 1972, 1968,
1977, 1983
7.2C
0.4C
11. 1998, 2005
7.1C
0.3C
2000-2010 / 9 warmest years

28. y = 1,5858x + 12,426
0
50
100
150
200
250
Intensity of scorching heat trend in summer period - CARACAL / 1961-2013
Tmax≥32C
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≥32C
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

29. 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

30. 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)

31. 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)

32. 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

33. -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
+0,5C
-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

34. Scenariul RCP 8.5
Scenariul RCP 2.6
Climate change scenarios / 2021-2050 vs.1971-2000 CMIP5 experiments – summer season

35. 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)

36. 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

37. 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
September 10
September 20
September 30
October 10
October 20
November 1
Base
2020s
2050s
WUE (kg.m-3)
Recommendations to improve effective use of water by crops (WUE) / change in sowing date

38. 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

39. 4000
4200
4400
4600
4800
5000
5200
5400
Current
climate
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

40. 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

41. 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.

42. •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

43. - 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.

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

45. 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)

46. 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

47. 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

48. Soil moisture / 3 October 2014 http://www.meteoromania.ro/anm/?lang=ro_ro
DROUGHT

49. Thank you for your attention!
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