climate implications for agricultural production within the murray valley of nsw

Climate implications for Agricultural Production within the Murray Valley

of NSW

Michael Cashen – Climatologist, [email protected]

John Smith – District Agronomist, [email protected]

So what’s the talk about?

The three P’s

Climate indicators Deniliquin and MDB

Relevant research quantifying uncertainty

Impacts on farming systems

Future implications for farm businesses and

Deniliquin

The three P’s of climate change

PeripheralPolicy Physical

Policy responses- Climate Change

Emission Trading Scheme (ETS), Carbon Pollution Reduction

Scheme (CPRS) and Carbon Tax.

Water policy review (MDBA- draft basin plan)

Exceptional circumstance policy review

Peripheral responses-Climate Change

Niche marketing and preferential buying

Food miles Carbon footprint (life cycle analysis) Carbon neutral

Our focus today- Physical

(science and biophysical impacts on Ag)


The three P’s





Deniliquin

Rainfall in Deniliquin (1889-2009)

Data source: SILO Data Drill

Deniliquin yearly rainfall 1889-2009

0

100

200

300

400

500

600

700

800

900

1889

1896

1903

1910

1917

1924

1931

1938

1945

1952

1959

1966

1973

1980

1987

1994

2001

2008

Year

mm

/ye

ar

Total yearly rainfall

11 per. Mov. Avg. (Total yearly rainfall )

Iconic droughts 1900-1909, 1936-45 and 1997-2009

Seasonal analysis rainfall (1889-2009)

Deniliquin seasonal rainfall trends (1889-2009) 11 yr moving average

0

20

40

60

80

100

120

140

160

1889

1895

1901

1907

1913

1919

1925

1931

1937

1943

1949

1955

1961

1967

1973

1979

1985

1991

1997

2003

2009

Year

mm

/sea

son Autumn MAM (11yr moving average)

Spring SON (11 year moving average)

Summer DJF (11 year moving average)

Winter JJA (11 year moving average)


Autumn rainfall-Deniliquin


0

20

40

60

80

100

120

140

1889

1895

1901

1907

1913

1919

1925

1931

1937

1943

1949

1955

1961

1967

1973

1979

1985

1991

1997

2003

2009

Year

mm

/sea

son

Autumn MAM (11yr moving average)


Murray Darling Basin- temperatures

Murray Darling Basin- annual rainfall

Iconic droughts 1900-1909, 1936-45 and 1997-2009

MDB- Winter and Spring rainfall

Murray Darling Basin -Cool Season Rainfall JJASON (1900-2009)

0

50

100

150

200

250

300

350

400

450

1900

1905

1910

1915

1920

1925

1930

1935

1940

1945

1950

1955

1960

1965

1970

1975

1980

1985

1990

1995

2000

2005

Year

mm

/JJA

SO

N p

erio

d

JJASON

5 per. Mov. Avg. (JJASON)

Data source: BoM

Drivers of winter/spring variability ENSO/IOD Ummenhofer et al 2010

4 Sites Seasonal

rainfall trends

Horsham seasonal rainfall trend (1889-2009)-data drill

0

20

40

60

80

100

120

140

160

180

200

1889

1894

1899

1904

1909

1914

1919

1924

1929

1934

1939

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1949

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1959

1964

1969

1974

1979

1984

1989

1994

1999

2004

2009

Year

mm

/sea

son Autumn MAM

Spring SON

Summer DJF

Winter JJA

Moree seasonal rainfall trend 1889-2009 (11yr moving average)- data drill

0

50

100

150

200

250

300

1889

1894

1899

1904

1909

1914

1919

1924

1929

1934

1939

1944

1949

1954

1959

1964

1969

1974

1979

1984

1989

1994

1999

2004

2009

Year

mm

/se

as

on Autumn MAM

Spring SON

Summer DJF

Winter JJA

MDB seasonal rainfall (1900-2009) 11 yr moving average

0

20

40

60

80

100

120

140

160

180

200

19

00

19

06

19

12

19

18

19

24

19

30

19

36

19

42

19

48

19

54

19

60

19

66

19

72

19

78

19

84

19

90

19

96

20

02

20

08

Year

mm

Autumn 11 yr moving average

Winter 11 yr moving average

Spring 11 yr moving average

Summer 11 year moving average

Autumn rainfall-Deniliquin


0

20

40

60

80

100

120

140

1889

1895

1901

1907

1913

1919

1925

1931

1937

1943

1949

1955

1961

1967

1973

1979

1985

1991

1997

2003

2009

Year

mm

/sea

son

Autumn MAM (11yr moving average)


Impact on Deniliquin

Source: S Gannon Westpac 2010

83%


The three P’s





Deniliquin

The Subtropical Ridge

STR Changes and temperature

STR Impacts

Quantifying uncertainty


The three P’s





Deniliquin

Rainfall and Plant water use-Deniliquin

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec

month

mm

/mth

Mean 61-90 Mean 91-08 Etc estimate - Wheat

Reduced PAW

Reduced PAW in winter crop growing seasonStored soil moisture 61-90 = 69.2mmStored soil moisture 91-08 = 40.7mm (-28.5mm)

Reduced PAW in winter crop growing season

GCM predictions

Rainfall and Plant water use-Deniliquin

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec

month

mm

/mth

Mean 61-90 Mean 91-08 CC 2030 50p A1B scenario CC 2070 50p A1F1 scenario Etc estimate

Reduced PAW

Implications for reduced water

0 0 83% 94% 101% 110% 113% 114% 117% 119% 122% 123%

0 0 5% 14% 26% 31% 31% 35% 36% 37% 38% 38%

Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May

1976/77 - 1998/99

1999/00 - 2010/11

Rice

Winter Cropping

Sowing Harvest

Spring Irrigation Pre season Irrigation

PI - Microspore

Changes in water priorities– Less water available when decisions need to be

made• Winter crops for yield potential• Calculated risk on water availability for rice

Implications for industry – rice (Gaydon et al., 2010)

Declines in irrigation water supply -ve impact Potential increases in water demand (?) -

increased ET but quicker growth Low-temperature damage may be reduced (?)

Significant improvements in water productivity difficult under existing systems –

less water = less rice

Rice farming system changes

Adaptation– Drill sowing - Farm layouts– Aerobic rice - New Varieties– AWD - Irrigation methods

Implications for industry – grains (Howden et al., 2010)

Enhanced growth with elevated CO2

– Increased photosynthetic rates and WUE Reduced frost risk Accelerated plant development with increased

temp. – Reduced yield without variety adaptation– More rapid depletion of soil moisture

Rainfall is a key determinant of yield – considerable risk of lower rainfall = lower yield

Implications for industry – grains (Howden et al., 2010)

Pests and disease - variable but for us– Stripe rust

• increase with milder winter temps, quicker life cycle

– Viral Diseases (Barley Yellow Dwarf) • increase with warmer winter temps, more

aphid activity– Take all

• decrease, favoured by wet soil conditions

Take home message- Temps are up- Autumn rainfall down- STR intensification driving autumn decline (temp)- GCM uncertainty around autumn (under estimate?)- Impacting on water availability

- Less water less production


The three P’s





Deniliquin

Future implications for farms

Scale (Diversification)

Return on water and land asset base (Review)

Equity level (Key to survival)

Flexible systems (annual –turn on or off)

References

Gaydon DS, Beecher HG, Reinke R, Crimp S and Howden SM (2010) ‘Rice’. In Adapting Agriculture to Climate Change. CSIRO Publishing Howden SM, Gifford RG and Meinke H (2010) ‘Grains’. In Adapting Agriculture to Climate Change. CSIRO Publishing

Timbal B (2010) ‘Understanding the anthropogenic nature of observed rainfall decline across south-eastern Australia. Centre for Australian

Weather and Climate Research, Technical Report No. 026

Ummenhofer CC, Alexander SG, Briggs PR, England MH, McIntosh PC, Meyers GA, Pook MJ, Raupach MR, Risbey JS (2010). Indian and Pacific Ocean Influences on Southeast Australian Drought and Soil Moisture. Journal of Climate. Published on line in (http://journals.ametsoc.org) DOI 10.1175/2010JCLI3475.1

http://journals.ametsoc.org/

http://journals.ametsoc.org/

Additional slides

El Nino Southern Oscillation

Image source: Bureau of Meteorology

Indian Ocean Dipole

Image source: www.oceansatlas.org

The years of ENSO/IOD

(Ummenhofer et al 2010)

Impact of ENSO/IOD events MDB

Statistical impact of ENSO/IOD events on JJASON rainfall MDB 1900-2006

050

100150200250300350400450

El N

ino

an

d n

ega

tive

dip

ole

(1)

El N

ino

an

d n

eut

ral

dip

ole

(11

)

El N

ino

an

d p

osi

tive

dip

ole

(6)

Neu

tra

l EN

SO

an

dn

eg

ativ

e d

ipo

le (

8)

Neu

tra

l EN

SO

an

dn

eu

tral

dip

ole

(41

)

Neu

tra

l EN

SO

an

dp

osi

tive

dip

ole

(11

)

La

Nin

a a

nd

ne

ga

tive

dip

ole

(7)

La

Nin

a a

nd

ne

utr

ald

ipo

le (

21)

La

Nin

a a

nd

po

sitiv

ed

ipo

le (

1)

phenomina

mm

win

ter/

spri

ng

q1

min

median

max

q3

Figures inside brackets indicated number of events (1900-2006)

Note: variation in impact between case study sites

http://www.climatechangeinaustralia.gov.au/technical_report.php

climate implications for agricultural production within the murray valley of nsw

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