A Case Study in the Moga district of Punjab, India

Water Footprints of Milk

Production

Upali Amarasinghe, Vladimir Smakhtin, Bharat Sharma and Nishadi Eriyagama

of International Water Management Institute

Carlo Galli and Manfred Noll

of

Nestle

Outline

1. Background and objectives

2. Components of milk water footprints

3. Impact of Moga water footprints

4. Reducing water footprints

Increasing physical water scarcity

Degree of development (%)

No data 0 - 25 25 - 60 > 60

2000 2025 2050

1. Background

1.2 Moga in a brief

Indian states

Punjab districts

Moga blocks

1.3 Moga in a brief

• 11th largest district in Punjab

• Have an arid climate - Annual rainfall 438 mm,

temperature 7 - 48°C

• Population is 895,000.

• 80% live in rural areas and livelihoods depends on

agriculture

• Average land holding size is 13 acres

1.4 Why Moga?

-35

-30

-25

-20

-15

-10

-5

0

1998 2000 2002 2004 2006 2008 2010

Dep

th (m

eter

s)

Depth to groundwater (m) in few villages before and after irrigating rice in the Kharif season

1.5 Why Moga?

• Groundwater is the major source of irrigation

and is overexploited everywhere

• At risk are sustainable agriculture production,

industrial expansion, domestic water supply

etc.

• Moga is one of Nestlé's Milk districts and

feed production depends on groundwater

1.6 Objectives

• Assess water

footprints (WFP) of

milk, wheat and rice

production in Moga

• Assess impacts of

total WFPs and

• Find ways of reducing

WFPs

2.1 Components of water footprints

WFP = the consumptive water use (Evapo-transpiration)

Water Footprints

Direct water use Indirect water useDirect water use Indirect water useDirect water use

Green water

footprints

Irrigation water

footprints

Gray water

footprints

Internal water

footprints

External water

footprints

2.2. Components of WFPs of milk and crops

WFP Direct water use + Indirect water use Green = na + CWU from soil moisture

in fodder and other feed crops

Irrigation = Drinking/servicing of animals

+ CWU from irrigation in fodder and other feed crops

=MilkWFP

{

Grey = na + Water pollution through input use or in by products

Green = CWU from soil moisture in crop production

+ na

Irrigation = CWU from irrigation water in crop production

+ na =1Crop

WFP

{ Grey = Water pollution from

input use or in byproducts

+ na

2.3 Data and methodology

• Estimated WFPs (m3/ton) using primary data

– collected from a sample survey in Moga

– Sample size of 300 farmers

• Combined with secondary data of total

production to estimate total WFP (million

m3/year)

• Used production surpluses and value to assess

impacts of total WFP

2.4 Water footprints of milk, wheat and rice (m3/ton)

Water footprints

• Rice - 1,870 m3/ton

• Milk- 940 m3/ton

• Wheat- 554 m3/ton

• Contribution from external water

footprints to milk production is

37%

Commodity Water Footprint (m3/ton)

Green Irrigation Grey

Canal Groundwater

Milk 58 - 882 (94%) 143

Wheat 17 42 495 (90%) 74

Rice 346 50 984 (71%) 195

-

400

800

1,200

1,600

2,000

Rice(Internal)

Wheat(Internal)

Milk(Internal)

Milk(External)

WF

P (m

3 /ton)

Green Irrigation (canal water)Irrigation (groundwater) Irrigation (non beneficial)Grey

Crop water requirements

Crop water requirements

• rice - 671mm

• Wheat – 268

• Fodder crops – 727 mm

Effective rainfall and net irrigation requirement

167

8132

504

260

595

0

200

400

600

800

Rice Wheat Fodder crops

Eff

rf &

NE

T (m

m)

Effective rainfall Net evapotranspiration

Water footprints of milk

• Green fodder - 196 m3/ton

• Dry fodder – 184 m3/ton

• Concentrates – internal – 218 m3/ton

• Concentrates – External - 327 m3/ton

• Drinking/bathing – 15 m3/ton

21%

20%

23%

34%

2%

Green

Dry

Concentrates

Concentrates -externalDrinking/servicing

Composition of milk water footprints

3.1 Impacts- Groundwater footprints

• Internal groundwater footprint

– contributes to 78% of total

– of the exports (of 84 mcm) is more than natural recharge limits (1200 mcm/yr)

– Needs to be reduced for sustainable agricultural production

Commodity Internal water footprint

(million cubic meters /year)

Virtual water in production

surpluses (million cubic

meters/year)

Total Irrigation Groundwater Total Groundwater

Milk 127 113 113 72 64

Wheat 464 450 415 412 368

Rice 1,198 898 854 1,194 852

Total 1,789 1,461 1,382 1,678 1,284

3.2 Impacts – Virtual water contribution

• Value of output per unit of net

irrigated area

– US$ 4,221/ha in Milk only

– US$ 3433/ha in milk-wheat

– US$ 3081/ha in milk-wheat-rice

• High dependency of milk only outputs

from virtual water

0.0

0.1

0.2

0.4

0.5

0.6

Irrig

atio

nW

FP

Gro

und

wat

er

Irrig

atio

nW

FP

Gro

und

wat

er

Irrig

atio

nW

FP

Gro

und

wat

er

Rice, wheat andmilk production

system

Wheat and milkproduction

system

Milk onlyproduction

system

Vla

ue ($

/m3)

-

1

2

3

4

5

Val

ue (U

S$

1000

/ha)

Rice Wheat Milk-internal

milk-external Value ($/ha)

4.1 Reducing water footprints: Agriculture diversification

Observations

• Virtual groundwater content and

exports of rice is large

• Milk only or wheat-milk production

systems have higher value of output

• Dairy intensive production systems

with less rice area offer the most

benefits

• An ideal scenario is a combination of

– Less rice area

– More dairy animals

– Same wheat area

– More fodder area

4.2. Impact of Agriculture diversification Scenario Crop area - % of total Number of lactating

animals per 6 ha land

Kharif Rabi Crossbred cows

Buffaloes

Rice Fodder Wheat Fodder

Base 90 10 90 10 1 3

A1 0 10 90 10 1 3

A2 0 31 90 10 8 3

A3 62 20 90 10 5 3

A4 62.5 19.9 90 10 1 7

1,752

3,294

3,609 3,575

3,124

1,382

541

711

1,200 1200

Base A1 A2 A3 A4 Base A1 A2 A3 A4

Scenarios Scenarios

Val

ue ($

/ha)

Tot

al W

FP

(mcm

)

Value of output ($/ha) Groundwater WFP (mcm)

• Scenario A3 is the

optimum under current

level of productivities.

• Value of output is

US$480/ ha more than the base scenario

4.3. Policy recommendations for reducing WFP

1. Diversify agriculture to dairy intensive production systems, especially for small holders

� Wheat-milk or Milk only is preferred

� Value of output will increase, but

� Virtual water imports also will increase.� Increase virtual trade opportunities, possibly, for rainfed areas

2. Reduce rice area, increase number of lactating cross-bred cows, and increase fodder area

� 62% rice area, 20% fodder area in Kharif� 90% wheat area and 10% fodder area in Rabi

� 5 cross-bred cows and 3 buffaloes (Total of 8 lactating animals/ 6 ha)

4.4 Policy recommendations for reducing water withdrawals

Interventions already in place in Moga

1. Strictly adhering to delayed rice

planting till June 10th

• Reduce ET by 9%

• Reduce withdrawals by 141 million

m3

2. Laser land leveling in all irrigated

areas

– Only 17% of area is laser leveled at

present

– Irrigation depth on laser level land

is 124 mm

0

400

800

1200

1600

2000

10-J

un11

-Jun

12-J

un13

-Jun

14-J

un15

-Jun

16-J

un17

-Jun

18-J

un20

-Jun

26-J

un10

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11-J

un12

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13-J

un14

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15-J

un16

-Jun

17-J

un18

-Jun

20-J

un26

-Jun

With out laser levelling With laser levelling

Net

or

irrig

atio

n w

ithdr

aw

als

(mm

)

Irrigation withdrawals - net irrigation requirement

Net Irrigation requirement

Acknowledgement:

• NESTLE India for providing financial support

• Moga and Punjab Agriculture department for data collection

support

• Carlo Galli, Manfred Noll, Babarjit Bhullar of Nestle for

logistical support

• Nestle Moga staff for sample survey data collection support