climate change in bulgaria: assessing trends of ...

Abstract ID:37124

CLIMATE CHANGE IN BULGARIA: ASSESSING TRENDS OF DROUGHTS AGGRAVATION, MAIZE CROPPING RISK AND IRRIGATION REQUIREMENTS Z. Popova*, М. Ivanova*, L.S.Pereira**, V.Alexandrov***, M. Kercheva*, K. Doneva*, D. Martins* *N. Poushkarov Institute of Soil Science, Agrotechnology and Plant Protection-ISSAPPNP, 7 Shosse Bankya Str., 1080 Sofia, Bulgaria ([email protected]; [email protected]); **CEER-Biosystems Engineering, Institute of Agronomy, Technical University of Lisbon, Tapada de Ajuda, 1349-017 Lisboa, Portugal; *** National Institute of Meteorology and Hydrology- NIMH, 66 Tsarigradsko chaussee Blvd., 1784 Sofia

This study aims at assessing maize cropping risk due to observed trends for drought aggravation for the maize crop season which is associated with climate change trends relative to precipitation, air temperature and reference evapotranspiration (ETo-PM) at selected weather stations

Trends of drought aggravation Relative to ETo for maize crop season (V-IX), a significant trend was observed for 1970-2004 (Fig.1).

50

2 1 0

0 May

Jun

Jul

Aug

Sep

May

Jun

Jul

Aug

Sep

150

50

1 0 May

Jun

Jul

Aug

Sep

Mi

Mi

Mo

May

Jun

Jul

Aug

Sep

Se

Se

Ex

0 Year

20 10 Se

Mo

Mi

Mi

Mo

Dry

f) 40

20 10

Se

Ex

Wet

Mo

Mi

Mi

Mo

Se

Ex

10 Se

Mo

Mi

Mi

Mo

Dry

Se

Wet

Pleven Silistra

Varna Sofia

Sandans ki

Plovdi v

Stara Zagora

Northern Location

0.02 0.05

0.02

0.01

0.05

February

0.06

0.05

0.03 0.04

0.03

0.03

0.08

0.05 0.02 0.04 0.04 0.03 0.03

0.05 0.00 0.03 0.05 0.05 0.04

0.05 0.01 0.04 0.06 0.04 0.02

0.05 0.00 0.03 0.04 0.03 0.01

0.09 0.02 0.04 0.05 0.04 0.05

0.01 0.01

0.01

0.00

0.00

0.01

0.01

0.01

0.00

0.00

0.00

-0.02

-0.01

0.00

0.02

0.00 0.01 -0.01 0.04 -0.01 0.01 0.02 0.02

0.03

0.02

0.04

0.00 -0.01 0.02 0.01 0.04 0.04 0.00 0.03 0.01 0.01 0.00 0.02 0.02 0.02 0.01 0.02

0.02 0.03 0.05 0.02 0.00 0.02 0.03 0.00

-0.01 -0.02 0.02 0.00 -0.02 -0.01 0.03 -0.01

0.04 0.02 0.05 0.03 0.03 0.04 0.05 0.04

0.00 0.00 0.02 0.00 0.02 0.02 0.04 0.02

-0.01 -0.01 0.03 0.01 0.01 0.02 0.03 0.02

0.03 0.04 0.06 0.02 0.03 0.02 0.04 0.04

0.00

0.00

-0.02 0.01

0.01

0.02

0.02

0.00 0.03 0.01 November -0.02 -0.03 0.04 December -0.02 -0.01 0.04 Year 0.00 0.01 0.01

-0.02 0.02 -0.04 0.01

0.02

0.01

0.03

-0.02

-0.04

-0.01

-0.04 0.00

-0.02

-0.02

-0.02

-0.01 0.03

0.01

0.01

0.02

0.03

-0.2

0.02

-0.25

-0.39

February

-0.56

0.74

-0.04

0.04

0.05

0.03

-0.09

-0.32

March

-0.23

0.39

0.46

0.06

0.11

0.05

-0.14

0.00

April

-0.05

0.94

0.27

0.02

0.02

0.01

-0.20

-0.39

December

May

-0.09

0.67

-0.21

0.03

0.16

0.04

-0.55

-0.58

June

-0.48

0.25

0.05

0.02

-0.52

0.06

-0.92

-0.39

July

0.30

0.36

-0.08

0.21

-0.51

0.12

-0.31

-0.44

August

-0.05

0.15

0.18

0.04

0.27

0.02

0.06

0.11

Year Minima January February March April May June July August Septembe r October

0.02

0.17

0.01

-0.20

0.27

October

-0.11

0.71

0.14

0.03

-0.05

0.01

-0.43

-0.29

-0.40

0.23

0.09

-0.01

-0.23

0.00

-0.45

-0.43

-0.02

0.83

0.12

-0.02

-0.01

-0.02

0.10

-0.09

-1.27

0.35

1.14

0.02

-0.95

0.03

-3.52

-3.3

Novembe r Decembe r Year

0.02

March 0.07 0.03 0.06 April 0.01 0.00 0.02 May 0.03 0.02 0.04 June 0.03 0.03 0.03 July 0.02 0.02 0.03 August 0.01 -0.01 0.02 Septembe -0.02 -0.01 r 0.02 October 0.00 -0.01 0.00

-0.19

0.44

Stara Zagor a

0.02

0.25

0.49

Sandansk Plovdi i v

0.04 -0.01

-0.17

0.50

Silistra Varna Sofia

Maxima January

January

Septembe r

Southern Location

November 0.00 -0.03 -0.03 0.01 0.02 0.00

0.02

-0.01 0.02

Table 1. Precipitation trend (mm year-1) Table 2. Temperature trend (oC year-1)

RYD (%)

19 50 19 55 19 60 19 65 19 70 19 75 19 80 19 85 19 90 19 95 20 00 20 05

RYD (%)

NIRs (mm)

NIRs (mm)

2004

2001

1998

1995

1992

1989

NIRs maize (mm)

RYD raimfed maize (%)

05

1.00

1.50

2.00

Threshold 2012 Threshold 1995-2005

RYD 0 -2.00 -1.50 -1.00 -0.50 0.00

2.50

c)

SPI (2) for "July - Aug"

y = -21.6x + 35.7 R2 = 0.79

73

NIRs maize (mm)

00

20

20

95

19

90

85

19

80

19

19

75

2004

1998

1995

1950 1953 1956 1959 1962 1965 1968 1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 1986

1983

1980

1977

1974

1971

1968

1965

1962

1959

1956

1953

Drought vulnerability mapping

0.50

1.00

1.50

2.00

2.50



67

y = -84.3x + 148.4 R2 = 0.75 295 270


NIR 0 -2.50 -2.00 -1.50 -1.00 -0.50 0.00 0.50 1.00 1.50 2.00 2.50

d)



g)

i)

SPI-2Jul-Aug

0.5 0 -0.5 -1 -1.5 -2 Lom

14

Y = 1200x-1

12

Y=

10

600 lv ha-1

1000x-1

800 lv ha-1 1000 lv ha-1

Y = 800x-1

1200 lv ha-1

8

Y = 600x-1

1400 lv ha-1

6 4

350 0 300

0

200

400

600

100

1.00

90

0.90

80

0.80

70

y=

97.6x-1.0

0.70

60

y = 84.5x-1.0

0.60

50

y = 74.7x-1.0

0.50

40

y = 60.7x-1.0

0.40

30

0.30

20

0.20

10

0.10 0.00 0

250

а)

200

300

400

500

600

700

100

Grain price, lv t-1

Fig. 9 Relationships between yield threshold values and grain price G (BGN t-1) at different levels of production expenses РЕ (BGN ha-1) when yield is expressed in absolute terms Y (t ha-1) (a) or in relative terms, as relative yield decrease RYD (%) (b) or a fraction y=Y/Ymax=1-RYD.

50

90 100 0 100 0 10 20 30 40 50 60 70 80 90 100 80 90 PNIRs (%) 90 Pleven Silistra Sofia Plovdiv Sandanski Varna b) 70 80 80 Fig. 57060Probability curves of occurrence for net irrigation requirements (NIRs,70 mm): a) at Pleven as influenced by soil total available water 50 60 TAW (mm m-1) and b) for six locations and soils of medium TAW 60 100 100 40 100 50 100 90 90 50 90 90 80 80 30 40 80 12 % risky years (6/51) for Pleven 80 70 70 40 10 % risky years (5/51) for Silistra 70 70 20 60 60 30 20 % risky years(10/51) for Sofia 60 60 12 % risky years (6/51) for Pleven 30 50 50 29 % risky years (15/51) for Plovdiv 12 % risky years (6/51) for Pleven 50 50 10 % risky years (5/51) for Silistra 10 40 40 63 % risky years(32/51) for Sandanski 20 % risky years (5/51) for Silistra 18 % risky years (9/51) for Pleven 10 12 % risky years (6/51) for Pleven 20 % risky years(10/51) for Sofia 40 40 20 14 % risky years(7/51) for Varna 35 % risky years (18/51) for Silistra 10 30 18 % risky years (9/51) for Pleven 20 % risky years(10/51) for Sofia 12 % risky years (5/51) (6/51) for Silistra Pleven 30 29 % risky years (15/51) for Plovdiv 20 % risky years(10/51) for Sofia 39 % risky years(20/51) for Sofia 0 35 % risky years (18/51) for Silistra 10 % risky years (5/51) for Silistra 30 30 10 29%%risky riskyyears(32/51) years (15/51)forforSandanski Plovdiv 20 2920%%risky (15/51) for 5939%%risky (30/51) for 20 riskyyears years(10/51) forPlovdiv Sofia riskyyears years(20/51) forPlovdiv Sofia 63 0 10 20 30 40 50 60 80 90 100 10 63 % risky years(32/51) for Sandanski 20 82 % risky years(42/51) for Sandanski 29 % risky years (15/51) for Plovdiv 70 59 % risky years (30/51) for Plovdiv63 % risky years(32/51) for Sandanski 20 10 14 % risky years(7/51) for Varna 14 % risky years(7/51) for Varna 10 riskyyears(42/51) years(25/51)forforSandanski Varna 63 % risky years(32/51) for Sandanski 8249%%risky P (%) 10 14 % risky years(7/51) for Varna 14 % risky years(7/51) for Varna 10 RYD 0 49 % risky years(25/51) for Varna 0 0 0 0 0 50 6020 30 7040 Sofia 50 80 60 70 90 80 90 100 100 0 0 10 0Pleven 20 RYD 3010 Threshold 40 5020 60 7030 80 9040 100 Plovdiv/Silistra RYD 10Threshold RYD Threshold 500 10 60 20 30 70 40PRYD Sofia 50 80 60 70 90 80 90 100 100 (%) 0 10 0Pleven 20 3010 40 5020 60 7030 80 9040 100 Silistra PRYD (%) P (%) RYD PRYD Varna (%) Plovdiv Sandanski P (%) P (%) Pleven RYD Threshold Pleven TAW=136-157mm m-1 Plovdiv TAW=136mm m-1 Pleven RYD Threshold Pleven TAW=136-157mm m-1 Plovdiv TAW=136mm m-1

Silistra/Plovdiv/Sandanski RYD RYD Threshold late hybrid Silistra TAW=136-157mm m-1 Sandanski TAW=136mm m-1 Silistra/Plovdiv/Sandanski RYD Threshold late hybrid Silistra TAW=136-157mm m-1 Sandanski TAW=136mm m-1

Pleven RYD Threshold Pleven RYD Threshold Plovdiv Pleven Plovdiv

Sofia RYD Threshold semi-early hybrids Sofia TAW=136mm m-1 Varna 136-157mm m-1 Sofia RYD Threshold semi-early hybrids Sofia TAW=136mm m-1 Varna 136-157mm m-1

RYD

Pleven RYD Threshold Pleven Plovdiv Pleven RYD Threshold Pleven Plovdiv

Plovdiv/Silistra RYD Threshold Silistra Plovdiv/Silistra RYD Threshold Sandanski Silistra Sandanski

Silistra/Plovdiv/Sandanski RYD Threshold late hybrid Silistra Sandanski Silistra/Plovdiv/Sandanski RYD Threshold late hybrid Silistra Sandanski

Sofia RYD Threshold semi-early hybrids Sofia Varna 136-157mm m-1 Sofia RYD Threshold semi-early hybrids Sofia Varna 136-157mm m-1

Sofia RYD Threshold Sofia RYD Threshold Varna Sofia Varna

Fig.6 Comparison of relative yield decrease (RYD, %) probability curves of occurrence at six locations and two soil of: a) medium (136157 mm m-1) and b) large (180 mm m-1) TAW, rainfed maize, 19512004.

AGU Chapman Conference on California Drought: Causes, Impacts, and Policy; 20-22 April 2015, Irvine, California

Sofia

Sandanski

Plovdiv

Stara Zagora

Conclusions:

1 0.5 0 -0.5 300

-1

250

200 -1.5 150

-2 100 50

Lom

Pleven

Silistra

Varna

Sofia

Sandanski

Plovdiv

0 Lom

b)

Pleven

Northern Silistra Locations

Varna

Sofia

Northern Locations

116 mm m-1

Fig.12 Spatial distribution of: seasonal SPI2 “July-Aug” a)-c); Relative yield decrease for rainfed maize (RYD, %) d)-f) and Net irrigation requirements (NIR, mm) g)-i) for the year of: a), d) and g) extreme (2000); b), e) and h) average (1970) and c), f) and i) moderate (1981) irrigation demand

Southern Locations

Sandanski

Stara Zagora

Plovdiv Stara Zagora Southern Locations

Southern Locations

800

150 100

Varna

Grain price, lv t-1 b)

200

100

Silistra

1.5

0

800

Pleven

Northern Locations

PRODUCTION EXPENCES 800 lv ha-1

Y = 1400x-1

2

Ex

SPI-2Jul-Aug Classes

h)

Pleve n

Year

d)

400

Climate variability and trends Lom

TAW=180mm m-1 NIRs threshold for TAW=180 mm m-1

450

20

Fig. 4 Frequency (%) of SPI-2July–Aug drought/ wet classes (Extreme-Ex; SevereSe; Moderate-Mo and Mild-Mi) comparing current (1979–2004) and past (1951–1978) observation periods at: a) Lom, b) Pleven, c) Silistra, d) Varna, e) Sofia, f) StaraZagora, g) Sandanski, h) Plovdiv

Trend analyses of precipitation shows negative trends for The Thrace plain. Maximum temperature (Table 2) shows significant trends for increase in June and July at various locations. All stations have a positive trend for Tmax on a year basis, with a mean increase of 0.024 ⁰C yr-1.

TAW=157 mm m-1 NIRs threshold for TAW=157 mm m-1

30

Wet


g)

16

500

Ex

0.50

235

The SPI-2July-Aug threshold, when computed for the values of RYD that do not produce economic losses, may be used as indicators of dryness that affects yields. These values are represented in Fig. 11 for all locations and soil groups including, when the change in economic condition was considered (Fig. 11b).

Fig. 8 Trendline of net irrigation requirements NIRs, mm, maize at: a) Sofia; b) Plovdiv; c) Pleven; d) Silistra; soils of medium water holding capacity (136-157 mm·m-1), 1951-2004 vs. 1970-2004

PNIRs (%)1,4 3 5 7 9 11121416182022242527293133353638404244464749515355575960626466687071737577798182848688909294959799

0 Se


a)

a)


40

Dry

Lom

1950

30

50

Southern Locations

1950 1953 1956 1959 1962 1965 1968 1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004

150

50

50

Ex

Northern Locations

Precipitation (mm)

Wet

40

Wet

30

200

100

Ex

0

Fig. 3 On right, monthly precipitation for the wet, average and dry years; on left, reference evapotranspiration for the low, average and high climatic demand conditions at: a) Pleven, b) Silisrtra, c) Sofia and b) Plovdiv, MaySeptember, 1951-2004

Mo

50

Ex

Frequency

3

Frequency

Plovdiv

e)

100

0

Mo


4 2

Se

Dry

6 5

Mi

0 Ex

7

Mi

Cv, % 50 42 30

h)

NIRs

3

Mo


d)

Frequency

4

Se

Dry

60 50 40 30 20 10 0

100

Frequency

Sofia

5

Wet


c)

6

Ex

150

SPI-2Jul-Aug

150

Ex

Cv, % 46 40 30

Fig. 10 Relationships between SPI2July-Aug and relative yield decrease of rainfed maize RYD or Net irrigation requirements NIR for: a) and c) Plovdiv and b) and d) Pleven;TAW=180 mm m-1)

y = 2.26x + 131

y = 1-RYD threshold value, fraction

Dry 7

Se

200

Year

1975

Mo

1977

Mi

250

1970

Mi

Cv, % 55 47 35

y = -93.8x + 189.9 R2 = 0.89

270

0 -2.50 -2.00 -1.50 -1.00 -0.50 0.00 0.50 1.00 1.50 2.00 2.50

Relationships between yield threshold values (t ha-1) and grain price (lv t-1) are derived at different levels of production expenses (lv ha-1) (Fig. 9a). In relative terms, RYD (%) or 1-RYD, relationships are universal and results could be compared for the agro-climatic regions and the different levels of expenses (Fig. 9).

300

1955

Mo

250

0

1973

Se

300

400 350 300 250 200 150 100 50 0

RYD threshold value, %

0 Ex

Sep

10

1984

Aug

20

60

Year

350

1976

Jul

150

Thresholds upgrade to actual economic conditions

1971

10

y = 3.52x + 112

50

400

30

Late (H708, 2L602, BC622) Average Cv, Yield, Cv, Cv, -1 kg ha % % % 59 2292 72 50 52 2906 59 44 4250 41 34 41

Black sea

1

1978

20

200

500

1972

40

Continental

Varna

1.5

Wet

2004

40

250

b)

100

450 50

Year

400

Ex


b)

30

Se

1981

Jun

Mo

Dry

0 May

Mi

1954

Sep

Mi

67

b)

(%)(%) RYD RYD

Aug

Mo

1953

Jul

Se

1964

Jun

Wet

50

0 May

Ex

1989

1 0

Ex

Silistra

300

0

c)

1992

50

2

Se

y = -23.6x + 47.2 R2 = 0.91

0 -2.00 -1.50 -1.00 -0.50 0.00

50

350

Mediterranean

Lom

SPI2 “July-Aug”

Linear (1970-2004)

y = -2.61x + 5360.3

Pleven

y = 3.44x + 108

Year

Linear (1951-2004)

Cv, % 69 59 43

Sandanski Transitional

Using the SPI-2 index as water stress indicator and for water management

100

aa)

yields depending on climate and soil

1956

3

100

0

Irrigation requirements and

2001

Frequency

Silistra

4

50

Year

1996

a)

100

Mo


6 5

Mi

Dry

Sep

150

Mi

150

200

d)

a)

1994

Aug

Mo

200 100

100 0

1987

Jul

10

250

300

y = -0.50x + 1165.5

1961

Jun

400

y = 2.53x + 65

Average Yield, -1 kg ha 3723 4299

Danube Plain

y = 1.49x - 186

350

300

Average Yield, -1 kg ha 3894 4550 5915

5483

0

AVG on 3 years

400 300 200

1965

7

May

y = 0.33x + 118 RMSE=57.0 mm

y = 0.46x + 108 RMSE=54.6 mm

600 500

1988

Sep

500

Fig.2 Precipitation total for peak demand period “June-August” (mm) (o) at a) Sofia; b) Plovdiv; c) Pleven and d) Varna; comparison of trendlines for 1951-2004 and 1970-2004

1993

Aug

Year

(%) (%) RYD RYD RYD (%)

Jul

Se

Frequency

Jun

y = -1.82x + 224 RMSE=76.2 mm y = -1.82x + 224 RMSE=76.2 mm

Plovdiv Stara Zagora Transitional continental

semi early Average Cv, Yield, -1 kg ha % 4421 42 4920 37 5896 29

TAW -1 mm m 116 136-157 180 173

y = 0.61x + 38

Sofia Continental

Sandanski

The WinISAREG model (Pereira et al., 2003) is an irrigation scheduling tool for computing the soil water balance and evaluating the respective impacts on crop yields. The model adopts the water balance approach of Doorenbos & Pruitt (1977) and the methodology to compute crop evapotranspiration and irrigation requirements (Allen et al. 1998). Yield impacts of water stress are assessed with Stewart’ model (1-Ya/Ymax) =Ky (1ETa/ETmax). Both models were previously validated for maize hybrids of different sensitivity to water stress on soils of small, medium and large TAW in various locations (Popova et al., 2006a; 2006b; Popova, 2008; Popova and Pereira, 2011; Ivanova and Popova, 2012).

Year

400

350

600

Year Year

1958

0 May

y = 0.08x + 180 RMSE=77.2 mm y = 0.08x + 180 RMSE=77.2 mm

400

0 Ex

0

Year

100 90 80 70 60 50 40 30 20 10 0

Thracian Lowland

a)

Year

b)

Precipitation (mm)

(mm) (mm) Precipitation Precipitation

0

1

20

North Bulgaria

Sofia field

RYD rainfed maize (%)

b)

1950 1950 1953 1953 1956 1956 1959 1959 1962 1962 1965 1965 1968 1968 1971 1971 1974 1974 1977 1977 1980 1980 1983 1983 1986 1986 1989 1989 1992 1992 1995 1995 1998 1998 2001 2001 2004 2004

600 600 500 500 400 400 300 300 200 200 100 100 0 0

NIRs (mm)

2

0 100

Yield threshold value, t ha-1

10

50

100 200

100

NIRs (mm)

3

20

200 300

0

(%) (%) RYD RYD

4

Frequency

Frequency

Pleven

100

300 400

Probability curves of occurrence of net irrigation requirement (NIRs, mm) and relative yield decrease under rainfed conditions RYD, built for each location and soil using the validated ISAREG and Stewart’s models over the period 1951-2004 (Figs. 5 ; 6 ).

Precipitation (mm)

5

400 500

Climate region Maize hybrid

d)

Year

NIRs (mm)

200

1.06-31.08.

30

1992

50

300



y = 0.73x + 35

Fig. 7 Trendline of relative yield decrease RYD,%, for rainfed maize at: a) Sofia; b) Plovdiv; c) Pleven; d) Silistra; late hybrids (H708, 2L-602 and ВС622), soils of medium water TAW (136157 mm·m-1)1951-2004 vs. 1970-2004

NIRs (mm)

400

500 600

c)

19501950 19531953 19561956 19591959 19621962 19651965 19681968 19711971 19741974 19771977 19801980 19831983 19861986 19891989 19921992 19951995 19981998 20012001 20042004

(mm)(mm) Precipitation Precipitation

Precipitation (mm)

y = -2.61x + 231 RMSE=78.0 mm

y = -0.50x + 195 RMSE=74.0 mm

500

c) c)

30

1989

Year

Relative to seasonal precipitation (V-IX), a significant inter-seasonal variability combined with a negative trend were observed for the recent 35 years (Fig.2). 600

Monthly precipitation and reference evapotranspiration (ETo) relative to 19512004 at selected locations are presented in Fig. 3. Precipitation represents wet, average and dry years, i.e. when the probability for being exceeded is, respectively, 10, 50 and 90 %. ETo was computed with the PM-ETo equation (Allen et al. 1998) using only temperature data as described by Popova et al. (2006a). ETo refers to low, average and high climatic demand conditions, when values are exceeded with a probability of 90, 50 and 10 %, respectively.

6

1986

1983

1980

1977

1974

1971

1968

1965

1962

1959

1956

1953

1950

а)

2001

y = 1.05x - 1501 R2 = 0.1378 RMSE=28.3

19

600

70

y = 0.06x + 452.5 R2 = 0.0013 RMSE=27.6

700

500

Climate data and indexes

South Bulgaria

Year

y = 0.89x + 29

65

ETo-PM (mm)

800

https://www.researchgate.net/profile/Zornitsa_Popova

40

Li near (1970-2004)

y = 0.37x +49

b)

100 90 80 70 60 50 40 30 20 10 0

19

Li near (1951-2004)

Year

19

AVG on 3 years

Year

Fig.1 Seasonal ETo-PM “May-September” (mm) (o) at: a) Sofia; b) Plovdiv; c) Pleven and d) Varna; comparison of trendlines relative to 1951-2004 and 1970-2004.

a)

40

y = 2.57x + 578 R2 = 0.58 RMSE=22.4 mm

d)

0

150

600

1950 1953 1956 1959 1962 1965 1968 1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004

Year 1.05-30.09.

a)

500

1950 1953 1956 1959 1962 1965 1968 1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 c)

700

60

y = 2.30x + 650 R2 = 0.33 RMSE=33.5 mm

600

y = 1.60x + 568 R2 = 0.52 RMSE=24.1 mm

19

700

100 90 80 70 60 50 40 30 20 10 0

y = 0.66x + 18

19

800

600

7

Year

100 90 80 70 60 50 40 30 20 10 0

55

b)

y = 0.55x + 676 RMSE=38.1 mm

ETo-PM (mm)

ETo-PM (mm)

1950 1953 1956 1959 1962 1965 1968 1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004

Year

800

600

500

1950 1953 1956 1959 1962 1965 1968 1971 1974 1977 1980 1983 1986 1989 1992 1995 1998 2001 2004 а)

y = 2.59x + 646 R2 = 0.48 RMSE=27.4 mm

RYD (%)

600

700

RYD (%)

700

500

Results and findings:

ETO-PM (mm)

Trend analysis show that both RYD and NIR increase for the last 30 years.

y = 0.46x + 682 RMSE=34.9 mm

y = 1.05x + 556 R2 = 0.14 RMSE=28.3 mm

500

Simulations are performed for a Transitional Continental (Plovdiv, Stara Zagora), a Moderate Continental (Sofia, Pleven, Silistra, Lom), a Transitional Mediterranean (Sandanski) and a North Black Sea (Varna) climate.

Soil water balance and yield modelling

Variability of rainfed maize grain yield

800

ETo-PM (mm)

ETo-PM (mm)

800

Materials and methods:

Map of Bulgaria with experimental fields of ISSAPPNP and meteorological stations of NIMH.

Yield and irrigation requirements

19

Extreme weather events, as drought, lead to substantial increase in agricultural risk and unstable farm incomes. The necessity to develop methodologies and simulation tools for better analysing/forecasting/managing the risk of agricultural drought is evident after the extremely dry 2000, 2007 and 2012.

136-157 mm m-1

173-180 mm m-1

Fig. 11 Threshold values of SPI2 “July-Aug” indicative of economic risk for rainfed maize in various regions and soil groups having small (116 mm m-1), medium (136-157 mm m-1) and large (173-180 mm m-1) TAW. Economical conditions of: a) 1990-2005 and b) the very dry 2012.

This study, relative to rainfed and irrigated maize crop, was applied to eight Bulgarian climate regions and three soil groups, and the period 1951-2004: ٠Relative to climate change, significant negative trends for precipitation during Peak Demand Season “June-Aug” were identified in The Thrace region, which are combined with the respective positive trends for ETo June-Aug (Figs. 1 and 2) . ٠An analysis relative to the present weather conditions shows a trend for aggravation of drought not only in The Thrace but also in the northern locations and Sofia field, thus confirming that agricultural lands in Bulgaria experience an increased vulnerability to water stress (Figs. 4, 7 and 8) . ٠Rainfed maize is associated with great yield variability (29%