Irrigation - Intensification - Illumination · Irrigation - Intensification - Illumination...

Irrigation - Intensification - Illumination

Exploring Limits and Trade-Offs in Agricultural Intensification

Alexander Herzig, John Dymond, Anne-Gaelle Ausseil

Outline

Objective

Ecosystem Services & Models

Identifying Trade-offs with LUMASS

Agricultural Intensification in the Ruamahanga

Black CreekWhite Rock

Objectives

Assessing the impact of agricultural intensification on the provisioning of ecosystem services in theRuamahanga catchment.

Identification of trade-offs between environmental andagricultural objectives of land management.

Guiding questions

Do we make the best use of our natural resources?

Is there environmental headroom for agricultural intensification?

Ecosystem service Process Indicator Model / Data

Global climate regulation

Carbon fixationCarbon sequestration[t CO

2eq. / ha / yr] CenW (Kirschbaum 1999)

Greenhosue gas emission

Methane and nitrous oxide emissions[t CO

2eq. / ha / yr]

New Zealand greenhouse gas inventory emission factors (MfE 2010)

Erosion control Soil erosion Soil erosion[t sediment / km2 / yr]

NZeem(R)(Dymond et al. 2010)

Water-flow regulation Water cycling Water yield [mm/yr] WATYIELD(Fahey et al. 2010)

Clean water provision Nutrient cycling Nitrate leached[kg N / ha / yr]

Overseer(R) (MAF et al. 2011), literature figures (Lilburne et al. 2010)

Food and fibre Plant and animal growth

Wool, meat, milk, crop, grapes, timber production[kg / ha / yr]

Statistics NZ, Baker & Associates (2009)

Agricultural performance Indicator Model / Data

Farm profitability Operating surplus[Mio. $]

ANZ (2012, 2014), Baker & Associates (2009), Beef & Lamb (2014), Lewis & Bryant (n.d.), Laurie (2014)

(modified from Ausseil et al. 2013)

Land-Use Productivity max Revenue+ =Land-Use Env. Indicator min Env. Imapct+ =Water Spec. Efficiency max Efficiency+ =Habitat Suitability max Biodiversity+ =

Resource Criteria Outcome+ =

Multi-objective Spatial Optimisation

+ =ABCD

?

+ =

Land-Use Productivity Revenue

ABCD

?$$$

$$$

$$$

$$$

A $$ $$$ $ $$

B $ $ $$$ $$

C $$$ $$ $$ $

D $$ $$ $ $$$

Land-Use Performance with Respect to Productivity

AAAAABBD

AABBBCCCCCDD

Atotal allocation:

AAAAAAABBBBBCCCCCDDD

proximity to stationary objects

nutrient cap depending on proximity to surface water

housing suitability depending on proximity to industry

business suitability depending proximity to transport (road / rail)

habitat suitability depending on proximity to settlement, road, river, lake, forest, etc.

quantity per zone

ha dairy per region

m3 water per irrigation zone

no-go area

Allocation Constraints Where?How much?

aaaaabbd

aabbbcccccdd

quantity per zone the overall nitrate leaching must not be greater

then XXX kg N a-1 the maximum nitrate leaching in zone X1 must

not be greater than XXX kg N a-1 the overall net revenue from dairy must be

greater than $XXX the total habitat value in zone X3 must be at least

XXXX units

Desired PerformanceTolerated ImpactPerformance Constraints

Spatial Optimisation with LUMASS

LUMASS

EnvironmentalModels

Socio-EconomicExpectations

Spatial Constraints

Exploring Limits Identifying trade-offs Discovering Potentials

Optimal Land-Use

Ruamahanga CatchmentLand Use 2011

Ruamahanga CatchmentIrrigable Areas

Black Creek

White Rock

Agricultural Intensification Scenarios

S1 – land-use intensification

S2 – intensive dairy expansion

S3 – dairy, arable, viticulture expansion

S5 – surplus maximisation

dairy → irrigated dairyarable → irrigated arable<x> → <x>

min nitrate leachingmilk solids >= S1 + 30%

min nitrate leachingmilk solids >= S1 + 30%crop yield >= S1 + 30%grapes >= yr2011 + {25%,8%} (Ruamahanga)

viticulture → viticulture scrub → scrubnative bush → native bush<x> → <y>

sheep beef → irrigated dairydeer

max operating surplus GHG <= yr2011N leach <= yr2011meat >= 30% yr2011wool >= 30% yr2011wood >= 30% yr2011<x> >= yr2011

S4 – dairy, arable, viticulture expansions. S3

land-use conversion constraints

→ irrigated dairy→ irrigated arable→ viticulture

sheep beefdeer

Black CreekLand Use - 2011

AreaCarbon

CropYieldErosion

GHGGrapes

MeatMilkSolids

NleachOpSurpl

WaterYldWood

Wool

0

2

4

6

8

10

12

14

16

0 0

15

0

2

0 0

14

5

3

0 0 0Re

lativ

e P

erf

orm

an

ce C

ha

ng

e [%

]

AreaCarbon

CropYieldErosion

GHGGrapes

MeatMilkSolids

NleachOpSurpl

WaterYldWood

Wool

0

10

20

30

40

50

60

70

80

90

100

110

0 0

33

0

26

0 0

97

46

28

0 0 0Re

lativ

e P

erf

orm

an

ce C

ha

ng

e [%

]

Ruamahanga

Black Creek

Black CreekLand Use IntensificationBC-S1



Land Use - 2011 Land Use Intensification

Black CreekIntensive Dairy ExpansionBC-S2b

AreaCarbon

CropYieldErosion

GHGGrapes

MeatMilkSolids

NleachOpSurpl

WaterYldWood

Wool

-20

0

20

40

60

80

100

120

140

160

0 0

33

0

34

0 -15

156

58

43

0 0 -16

Rel

ativ

e P

erfo

rman

ce C

hang

e [%

]

AreaCarbon

CropYieldErosion

GHGGrapes

MeatMilkSolids

NleachOpSurpl

WaterYldWood

Wool

-202468

1012141618202224

0 0

15

0

3

0 -1

22

7

5

0 0 -1

Rel

ativ

e P

erfo

rman

ce C

hang

e [%

]

Ruamahanga

Black Creek

sheepbeef → irrigated dairydeer



min nitrate leachingmilk solids >= S1 + 30%

objective & performance constraints

Land Use - 2011 Intensive Dairy Expansion

Potential nitrate leaching [kg N/ha/yr] for irrigated dairy

farming

Optimal and potential locations of land use change to increase milk solids

production by 30% while minimising nitrate leaching.

Optimal and potential locations of land use change to increase milk solids

production by 30% while minimising nitrate leaching.

Potential production of milk solids [kg milk solids/ha/yr] for irrigated

dairy farming

Black CreekDairy, Cropping, ViticultureExpansion (constrained) BC-S3b

AreaCarbon

CropYieldErosion

GHGGrapes

MeatMilkSolids

NleachOpSurpl

WaterYldWood

Wool

-2

2

6

10

14

18

22

26

30

34

0 0

32

03

25

-1

22

7 6

0 0 -1

Rel

ativ

e P

erfo

rman

ce C

hang

e [%

]

AreaCarbon

CropYieldErosion

GHGGrapes

MeatMilkSolids

NleachOpSurpl

WaterYldWood

Wool

-30

-10

10

30

50

70

90

110

130

150

0 0

72

0

31

108

-20

156

59 60

0 0 -19

Rel

ativ

e P

erfo

rman

ce C

hang

e [%

]

Ruamahanga

Black Creek



min nitrate leachingmilk solids >= S1 + 30%crop yield >= S1 + 30%grapes >= yr2011 + 25% (Rua.)

sheep → irrigated dairybeef → irrigated arabledeer → viticulture


ARA IrARA BEF DAI IrDAI DEE FOR SHP SNB VIT0

5

10

15

20

25

30

35

40

45

1 0 1

32

0 0

9 10

40

6

1 2 1

27

9

0

9 10

39

7

2011 Expansion

Op

era

tion

al S

urp

lus

[Mio

. $]


2

4

6

8

10

10 0

4

0 0 0

12

1

0

2

0 0

9

0 0

12

3

2011 Expansion

Op

era

tion

al S

urp

lus

[Mio

. $]

Ruamahanga

Black Creek

Black CreekDairy, Cropping, ViticultureExpansion (constrained) BC-S3b






Land Use - 2011 Dairy, Cropping, Viticulture Expansion(constrained)

Black CreekDairy, Cropping, ViticultureExpansion (unconstrained) BC-S4b

AreaCarbon

CropYieldErosion

GHGGrapes

MeatMilkSolids

NleachOpSurpl

WaterYldWood

Wool

-30

-10

10

30

50

70

90

110

130

150

-6 2

72

-11

31

108

-20

156

27

59

-9 -3 -19

Rel

ativ

e P

erfo

rman

ce C

hang

e [%

]

AreaCarbon

CropYieldErosion

GHGGrapes

MeatMilkSolids

NleachOpSurpl

WaterYldWood

Wool

-2

2

6

10

14

18

22

26

30

34

0 0

32

03

25

-1

22

3

6

0 0 -1

Rel

ativ

e P

erfo

rman

ce C

hang

e [%

]

Ruamahanga

Black Creek





Land Use - 2011 Dairy, Cropping, Viticulture Expansion(unconstrained)

Black CreekSurplus maximisation(unconstrained) BC-S5

AreaCarbon

CropYieldErosion

GHGGrapes

MeatMilkSolids

NleachOpSurpl

WaterYldWood

Wool

-10

0

10

20

30

40

50

60

70

0

9

20

-1 -1

23

-5

20

0

8

-1

57

-5

Rel

ativ

e P

erfo

rman

ce C

hang

e [%

]

AreaCarbon

CropYieldErosion

GHGGrapes

MeatMilkSolids

NleachOpSurpl

WaterYldWood

Wool

-80

-60

-40

-20

0

20

40

60

80

100

120

140

0

1,129

45

-44 -7

101

-70

142

0

83

-18

2,892

-70

Rel

ativ

e P

erfo

rman

ce C

hang

e [%

]

max operating surplusGHG <= yr2011N leach <= yr2011meat >= 30% yr2011wool >= 30% yr2011wood >= 30% yr2011<x> >= yr2011





5

10

15

20

25

30

35

40

45

1 0 1

32

0 0

9 10

40

6

1 1 1

27

8

0

14

9

38

7

2011 Expansion

Op

era

tion

al S

urp

lus

[Mio

. $]


2

4

6

8

10

10 0

4

0 0 0

12

1

0

1

0 0

8

0

5

01

3

2011 Expansion

Op

era

tion

al S

urp

lus

[Mio

. $]

Ruamahanga

Black Creek

Black CreekSurplus maximisation(unconstrained) BC-S5





Land Use - 2011Max. Surplus, maintain EnvironmentalPerformance of Ruamahanga Catchm.

(unconstrained)

Area Carbon CropYield Erosion GHG Grapes Meat MilkSolids Nleach OpSurpl WaterYld Wood Wool-8

-4

0

4

8

12

16

20

24

28

32

0

9

20

-1 -1

23

-5

20

0

8

-1

57

-5

Intensification Dairy Expansion Dairy, Crop, Vit. Exp (cons.)

Dairy, Crop., Vit. Exp. (uncons.) Max. Surplus, keep footprint

Re

lativ

e P

erf

orm

an

ce C

ha

ng

e [%

]

Impact of Land Use Scenarios for the Black CreekIrrigable Area on Ecosystem Services Provision inthe Ruamahanga Catchment

Ruamahanga CatchmentIrrigable Area – White Rock

White RockLand Use - 2011

White RockLand Use IntensificationWR-S1

AreaCarbon

CropYieldErosion

GHGGrapes

MeatMilkSolids

NleachOpSurpl

WaterYldWood

Wool

0

1

2

3

4

5

6

7

0 0

4

0

1

0 0

7

2

1

0 0 0Re

lativ

e P

erf

orm

an

ce C

ha

ng

e [%

]

AreaCarbon

CropYieldErosion

GHGGrapes

MeatMilkSolids

NleachOpSurpl

WaterYldWood

Wool

0

10

20

30

40

50

60

70

80

90

0 0

33

0

19

0 0

83

36

16

0 0 0Re

lativ

e P

erf

orm

an

ce C

ha

ng

e [%

]

Ruamahanga

White Rock



White Rock

AreaCarbon

CropYieldErosion

GHGGrapes

MeatMilkSolids

NleachOpSurpl

WaterYldWood

Wool

-20

0

20

40

60

80

100

120

140

0 0

62

0

23 22

-13

138

48

32

0 0 -13

Re

lativ

e P

erf

orm

an

ce C

ha

ng

e [%

]

AreaCarbon

CropYieldErosion

GHGGrapes

MeatMilkSolids

NleachOpSurpl

WaterYldWood

Wool

-2

0

2

4

6

8

10

12

0 0

8

0

1

8

-1

11

32

0 0 -1

Re

lativ

e P

erf

orm

an

ce C

ha

ng

e [%

]

Ruamahanga

White Rock

Dairy, Cropping, ViticultureExpansion (constrained) WR-S3b






Land Use - 2011 Dairy, Cropping, Viticulture Expansion

White RockSurplus maximisation(unconstrained) BC-S5

AreaCarbon

CropYieldErosion

GHGGrapes

MeatMilkSolids

NleachOpSurpl

WaterYldWood

Wool

-4

-2

0

2

4

6

8

10

12

14

16

18

20

0

2

14

0 0

75

-4

14

0

7

0

14

-3

Re

lativ

e P

erf

orm

an

ce C

ha

ng

e [%

]

AreaCarbon

CropYieldErosion

GHGGrapes

MeatMilkSolids

NleachOpSurpl

WaterYldWood

Wool

-80-60-40-20

020406080

100120140160180

0

2,965

115

-15 -8

206

-70

179

0

96

-10

3,564

-70

Re

lativ

e P

erf

orm

an

ce C

ha

ng

e [%

]

Ruamahanga

White Rock





Land Use - 2011Max. surplus, maintain environmentalperformance of Ruamahanga catchm.

(unconstrained)

Area Carbon CropYield Erosion GHG Grapes Meat MilkSolids Nleach OpSurpl WaterYld Wood Wool-6

-4

-2

0

2

4

6

8

10

12

14

16

18

20

0

2

14

0 0

75

-4

14

0

7

0

14

-3

Intensification Dairy, Crop. Vit. Exp (cons.) Max. Surplus, Keep Footprint

Re

lativ

e P

erf

orm

an

ce C

ha

ng

e [%

]

Impact of Land Use Scenarios for the White RockIrrigable Area on Ecosystem Services Provision inthe Ruamahanga Catchment

Conclusions

➢ Agricultural intensification and expansion (S1-S3) increased the environmental footprint.

➢ The greater the expected production increase the greater the modelled environmental footprint.

➢ Relaxing the constraints on possible land-use conversions (S4) reduced the environmental footprint.

➢ The biggest increase in operating surplus, except for meat and wool, was modelled for scenario S5.

➢ The current land-use configuration does not use the full potential of the landscape to provide ecosystem services.

➢ The effect of agricultural intensification (S1-S5) in the Black Creek indicative irrigable area has a greater impact on the provisioning of ecosystem services in the Ruamahanga catchment than the effect of agricultural intensification in the White Rock indicative irrigable area.

Conclusions

➢ the integration of performance indicators from different models

➢ the integration of stakeholder objectives and expectations

➢ the exploration of landscape limits and potentials

➢ the identification of trade-offs between conflicting objectives

➢ evidence-based spatial decision-making and policy development

LUMASS supports

[email protected]

Irrigation - Intensification - Illumination · Irrigation - Intensification - Illumination...

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