This presentation was held by N.Sultana & K.J. Peters at the interntional seminar 'Livestock Resources for Food Security in the Light of Climate Change' co-hosted by SIANI and SLU Global in Uppsala on the 11th of March 2016.

1. Water use in Global Dairy Farming
Systems and lessons for breeding
policies for dairy production
Results of a research project in
collaboration with IFCN-Dairy
N.Sultana, K. J.Peters
Humboldt Universität zu Berlin
k.peters@agrar.hu-berlin.de

2. Importance of water in animal agriculture
Agriculture: uses 85% of the present global freshwater consumption,
of which
29% by Livestock (Mekonnen and Hoekstra, 2012)
75% for Irrigation (Shilklomanov, 2000)

3. 2. Increase food production, agricultural pollution
1. Human population. 65 % increase (3.7 mrd) by 2050 (Wallace, 2000)
Future challenges
Importance of water in animal agriculture
4. Climate change impact on rainfall distribution pattern
• 19 to 35% decrease in water availability for agriculture
• Increase water scarcity for human population from 7% to 67%
3. Urbanization and industrial, increase in water use and pollution

4. WSI = Water Scarcity Index (Pfister et al. 2009. Assessing the environmental impacts of
freshwater consumption in LCA. Environ. Sci. Technol. 43 (11), 40984104)
Water Stress Index
0 <= 0.2
0.2 <= 0.4
0.6<= 0.7
0.7 <= 0.1
Low
Moderate
Severe
Extreme
National Water Scarcity Index (WSI)
Water scarcity measured :
Total annual freshwater
withdrawals / hydrological
availability.
WSI indicates the portion of
CWU depriving other users of
freshwater.
Holistic view of current water scarcity by region

5. 1. Around 1.2 mrd people live in areas of physical scarcity
and 500 million people are close to it
2. Another 1.6 mrd people face economic water shortage
(where countries lack the necessary infrastructure to take
water from rivers and aquifers)
3. Though planet water does not change
freshwater is distributed unevenly and
too much of it is wasted, polluted and unsustainably
managed.
Sources: Human Development Report 2006. UNDP, 2006 Coping with water scarcity. Challenge of the twenty-first century. UN-
Water, FAO, 2007.
Effects of current water scarcity

6. Holistic view of water scarcity problem by regions
Source: IWMI = International Water Management Institute, 2007.
Economic water scarcity:
• <25% of water withdrawn from rivers for human purposes but not enough water infrastructure to
make water available for use
Physical water scarcity:
• >75% of river flows are withdrawn for agriculture, industry and domestic purposes.
Water scarcity
measures:
freshwater available
for human requirements
implies that dry areas are not
Necessarily water scarce).

7. Water availability and dairying
Dairy production highly depenend on water in its various forms
Important to know the water demand of a dairy system
USA
EthiopiaArgentina
China
Bangladesh
India
India

8. Milk production 2011
in mill tons ECM
EU-27
153
84
34
30
10
21
42
138
32
11
Milk volumes cows & buffalo milk –standardized to 4% fat and 3,3% protein
Status of current milk production
Milk production in mill. tonnes
Milk production 2011 = IFCN ( International Farm Comparison Network)
Milk delivered to processor
Milk not delivered to processor

9. Water footprint definition
• A water footprint is measured in terms of the volume
of water consumed, evaporated and polluted.
• Three corresponding categories (Water Footprint Network)
Blue Water Footprint: The amount of surface water and
groundwater required (evaporated or used directly) to make a product.
Green Water Footprint: The amount of rainwater required
(evaporated or used directly) to make a product.
Grey Water Footprint: The amount of freshwater required to mix
and dilute pollutants enough to maintain water quality according to
certain standards as a result of making a product.

10. Consumptive Water Use
• Measures Green and blue water
• removed from a local hydrological system
• without return to a water system (e.g. water used in
manufacturing and agriculture)
• Indirectly includes grey water
Water footprint methods
Is a incomplete Water Foot print

11. Water footprint methods
The Water Footprint Network (WFN) method
– accounts for the virtual water and is an indicator of direct
and indirect Water Use Volume (green, blue, grey)
However
– Simple combination of hypothetical pollution volume (grey)
with water consumption (blue) is not meaningful
– Inclusion of green water in the WF is misleading, since it does
not fully affect the water cycle and is rather an indicator of
land use
Pfister, St. and Ridoutt, B.R. 2013, Environmental Science & Technology 48 (1):4-4

12. Water footprint methods
The LCA - Water use impact
(ISO 14046,2010, standard approach)
– Accounts for blue water
grey water
and its water scarcity related impacts of
pollutants expressed as
water equivalent along the whole LC (H2Oe)
Pfister, St. and Ridoutt, B.R. 2013, Environmental Science & Technology 48 (1):4-4

13. • Types of water consideration (e.g. rainfall, stored water in surface
and ground, polluted water)
• Concept of water use in farming systems
• Defining goals and interpretation problem
2. Lack of consistent approach
e.g. Classical or volumetric Impact assessment based
approach
International Standard Method which is under Development
(ISO, 14046, 2013)
Methodological challenges in water research
Materials and methods

14. 1. Application of consumptive water use (CWU) and its
drivers
2. Application of Water use impact
3. Evaluating differences between Consumptive water use
and Water use impact (WF)
Application of different WF methods in diverse
dairy systems

15. Steps in our study to measure water use
3. Comparison of Water use assessment method
IFCN: International Farm Comparison Network method. TIPI-CAL: Technology Impact and Policy Impact Calculation
Represent the most common farming
system within the regions
Average management & performance
& high proportion of milk in the region
1. Selection of typical farm
within the IFCN-Dairy Net
Typical farm data are collected at farm level
2. System boundary

16. Drinking and
servicing
water
Concentrate,
by-products
and roughage
Fuel,
Electricity
Fertilizer,
pesticides
External inputs Internal farm inputs
Total feed
and
fodder
Water for
feed
mixing
Buildings and
dairy
implements
Co-
products:
beef
and
manure
Heifers
Dairy cows
Functional
unit: 1 kg
energy
corrected
milk (ECM)
Farm grown
feed (main
product and
by-products)
2. System boundary (Cradle –to Farm Gate)
ECM = Energy Corrected Milk which is standardized by 4% fat and 3.3% protein
Materials and methods

17. Application of Consumptive Water use (CWU) method
(as in Hemme et al, 2010)
60 typical farms from 60 dairy regions of 49 countries and
6 selected dairy systems
Application and comparison of CWU (WFN, 2010) and LCA-based
water use impact (WF) (after Ridoutt and Pfister, 2010)
12 typical farming systems from 12 geographical regions
Comparison of Water use assessment methods
Materials and methods

18. 0
1000
2000
3000
4000
5000
6000
NO-20
CH-23
FI-25
AT-22
DE-31S
DE-95N
DE-85E
NL-76
BE-40N
LU-51
FR-39MC
FR-50W
ES-50NW
IT-154
UK-146NW
IE-48
DK-128
SE-55
PL-15
CZ-425
RS-2
UA-150
BY-1
BY-608
RU-1063
CA-58
US-80WI
US-350WI
US-66NY
AU-275WA
NZ-348
MX-15
AR-170
UY-119
PY-45
CL-47
BR-20S
BR-120PR
PE-7
TN-4
DZ-6
MA-3N
EG-2
UG-3
NG-5
CM-35
ZA-422
AM-10A
IL-67
JO-75
IR-90
IN-2W
IN-13W
IN-2S
PK-5
BD-2
ID-3NG
ID-3JA
CN-17BE
CN-6IM
CWU(L/kgECM)
S. America Africa Asia
C. and E.
Europe
Western EuropeRegions
*Typical
farms
N.America
Oceania
CWU for feed CWU for other inputs
Mean
(St. Dev.)
1771 (±1035) 62 (±45)
Min (Max.) 706 (5400) 31 (304)
Application of Consumptive Water use (CWU) method
in dairy farms
= CWU for feed
= CWU for other inputs

19. Relation between consumptive water use and milk
yield (kg ECM/cow/year)
y = -0.1168x + 1849.7
R² = 0.68
0
500
1000
1500
2000
0 5000 10000 15000
CWU(LH20/kgECM)
Milk yield
Europe
y = -0.2038x + 3777.1
R² = 0.31
0
1000
2000
3000
4000
5000
6000
0 10000 20000
CWU(LH20/kgECM)
Milk yield
Asia and Africa
y = -0.1601x + 2466.4
R² = 0.65
0
500
1000
1500
2000
2500
3000
0 5000 10000 15000
CWU(LH20/kgECM)
Milk yield
USA and Oceania
Major results

20. Production system Intensive Grazing Small-scale
Variable Unit DE-95N US-350WI NZ-348 BR-20SC EG-2 BD-2
Breed HF HF HF CB EB Local
Farm land ha 90 270 130 18 0 0
Grazing hrs./day 0 0 12 12 0 0
Climate Mild with
no dry
season
Humid,
severe
winter
Mild, no
dry
season
Mild with dry
winter
Desert
area
Monsoon
Rainfall mm/m2 850 860 1250 1300 250 1800
T. (Mean) (°C) 12 15 15 27 32 28
Consumptive water use in selected dairy systems
Background information
HF = Holstein Friesian; CB = Crossbred; EB: Egyptial Buffaloes

21. 75%
80%
85%
90%
95%
100%
DE-95N
US-350WI
NZ-348
BR-20SC
EG-2
BD-2
Intensive Grazing Small-scale
0
500
1000
1500
2000
2500
3000
3500
4000
DE-95N
US-350WI
NZ-348
BR-20SC
EG-2
BD-2
CWU(LH20/kgECM)
Feed production & mixing Drnking
Servicing Farm manufacturing inputs
Capital goods
Intensive Grazing Small-scale
Consumptive water use in selected dairy systems
CWU = Consumptive water use
FEED
Pasture
based
Concentrate,
by-product +
crop residues
Maize +
concentrate
based
Major results
Drinking

22. Conclusion on consumptive water use
• The world average CWU 1833 L/kg ECM (range: 739 to 5622),
with large inter- and intra-regional differences
• Feed is the highest single input to CWU 96-99% water
• Lower CWU associated with high productivity and farm based
feeding systems
• Rather high CWU in pasture based systems
• Highest CWU associated with low productivity and higher
concentrate feeding

23. Comparison of CWU and LCA-based water use
impact (WF)
1. Volume of water use based on volumetric approach (CWU)
2. Water use impact assessment including water scarcity with
Life cycle assessment (LCA) approach

24. Blue and grey water volumes
0
250
500
750
1000
US-350WI
DE-95N
CN-17BE
JO-75
NZ-348
BR-25SE
AR-170
ZA-422
EG-5
IN-2S
MX-15
BD-2
LH2O/kgECM
Intensive Grazing Small-scale
Blue water
Grey water
Major Results

25. Major Results
H2Oe = Water equivalent; WSI = Water Scarcity Index
WF (H2Oe) =
Water use impact (WF) based on LCA method
a) Blue & grey water volumes
considering water scarcity
0
200
400
600
800
1000
1200
1400
1600
US-350WI
DE-95N
CN-17BE
JO-75
NZ-348
BR-25SE
AR-170
ZA-422
EG-5
IN-2S
MX-15
BD-2
LH2Oe/kgECM
Intensive Grazing Small-scale
0,00
0,20
0,40
0,60
0,80
1,00
US-350WI
DE-95N
CN-17BE
JO-75
NZ-348
BR-25SE
AR-170
ZA-422
EG-5
IN-2S
MX-15
BD-2
m³/m³
National WSI Local WSI
Intensive Grazing Small-scale
b) Water scarcity of production area

26. Consumptive water use
• The world average CWU 1833 L/kg ECM with huge variability (ranging from
739 to 5622)
• Feed is the main contributer more than 96% of total CWU
• Lower CWU associated with high productivity and farm based feeding systems
Water use impact (WF)
• Lower WF associated with pasture based system where water scarcity is low
• Higher WF associated with land less system based on external concentrate
supply, and where water scarcity is higher
Planning of dairy production system should include assessment of
water foot print and water returns
Home messages

27. Method perspective
• The summation of water volumes is not a comprehensive tool for assessing
water productivity
• Water use impact assessment considering degradative water use and water
scarcity is a more appropriate tool for assessing impact of water use
Reasons of WF variation
• Due to interaction effects among the regional water scarcity where production
occurs, with amount of degraded water, feeding system and feed efficiency
Dairying in areas with high concentrate feed input in water scarce region
is a hotspot of adding to water problem
Home messages (cont.)

28. Translation of these findings into dairy planning
1. Assessment of water availability and water scarcity
2. Assessment of the appropriate feeding system for a
dairy production system
pasture, forage, crop-residues,
agro-industrial by-products, LCA
grain concentrate
LCA WF
Lower
larger
3. Assessment of appropriate
performance and production efficiency level
4. Define breeding policy

29. Thank you so far!
and now we need to decide if we
can spare time to consider
breeding option for smallholders
in Ethiopia

30. The case of Dairying in Ethiopia
Diverse dairy production systems:
1. Commercial Peri-urban dairy systems partly with own Value
Chain (liquid milk and processed products)
2. Semi-commercial Peri-urban and Rural mixed farming
systems with linkage to milk collection systems (liquid milk ,
but also butter and trad. cheese)
3. Extensive Rural mixed farming systems (Trad. Butter and trad.
cheese)
4. 99.2 % of the 27 mill. cows are indigenous breeds with a low
milk yield, few selected indigenous dairy breeds
129 thousand are cross (0.61 %) and exotic breeds (0.11%);
32 thousand cows with small holders.

31. Commercial Peri-urban dairy systems
Purebred and grade dairy cows, medium high yield
Modern dairy production and processing technics
Agro-industrial by-products and concentrates
Mais silage, Hay
AI service with own technicians

32. Semi-commercial systems
crossbred cows of different grade, medium yield
Crop-residues, grazing, hay and agro-industrial by-
products
AI service only in well organized Dairy coops,
otherwise village bull service

33. Extensive small scale mixed farming systems
-Indigenous cows or low grade crossbreds, low yield
-Crop-residues, hay, grazing, small amount of by-
products
-AI service not available,
-only NM with available bulls

34. Agro-ecological breeding policy
,Yilma zelalem,,G.B., Emannuelle aYilmand S., Ameha. 2011.
A Review of the Ethiopian Dairy Sector. Ed. Rudolf Fombad, Food and Agriculture Organization of the United Nations,
Sub Regional Office for Eastern Africa (FAO/SFE), Addis Ababa, Ethiopia, pp 81.
The NEXT STAGE IN DAIRY DEVELOPMENTFOR ETHIOPIA, Dairy Value Chains, End Markets and Food Security, USAID/ Land
O+Lakes, 2010
• Absence of effective breeding policies and programs to
assure optimum performance levels and efficiencies
• AI service has been inefficient for different reasons in
rural areas
• Bilateral projects through EDDP link up to World Wide
Sires, for AI use in commercial peri-urban dairies,
through private enterprises (ALPPIS)
• Chance of forming Dairy Farmer and Cattle Breeder
Associations

35. Agro-ecological breeding policy
Yilma zelalem,,G.B., Emannuelle aYilmand S., Ameha. 2011.
A Review of the Ethiopian Dairy Sector. Ed. Rudolf Fombad, Food and Agriculture Organization of the United Nations,
Sub Regional Office for Eastern Africa (FAO/SFE), Addis Ababa, Ethiopia, pp 81.
The NEXT STAGE IN DAIRY DEVELOPMENTFOR ETHIOPIA, Dairy Value Chains, End Markets and Food Security, USAID/ Land
O+Lakes, 2010
Attempts to improve dairy merit of national herd include:
• Importation of purebred dairy cows
• Production and distribution of Crossbred cows on
Government farms
• Importation of crossbred cows from Kenya
• AI-Center with Purebred, crossbreds and local bulls
• Distribution of imported semen form high yielding
breeds
• Distribution of crossbred bulls

36. Agro-ecological breeding policy
Options:
1. The intensive commercial dairy sector (ICDS)
exotic semen through private sector AI
services and
purchase of breeding bulls from within the ICDS
3. Less intensive semi commercial and rural dairies
obtain crossbred bulls of various grade and
sources
(appropriateness and supply sustainability?)
Yilma zelalem,,G.B., Emannuelle aYilmand S., Ameha. 2011.FAO,
Sub Regional Office for Eastern Africa (FAO/SFE), Addis Ababa, Ethiopia, pp 81.

37. Agro-ecological breeding policy
Supply of breeding bulls for the rural sector
– Link up with existing community actions
– Crossbred bulls (?) from commercial dairy farmers in
and around Addis Ababa, Asella Livestock Farm,
Wolaita Jersey Bull Ranch and DDE
– 75 % crossbreed bulls distributed to individual
farmers through various agencies
– Farmers established breeding bull stations
Constraint: Replacement of bulls was and is linked to a
functional supply chain (sustainability?)

38. A new scheme for Breeding bull provision
Suggestion of a young sire programme to provide
crossbred bulls for rural smallholder dairy
farmers
1. Concept for application acrosss the highland
dairy shed
2. Action domain
Rural administrative Community with
established farmer interaction

39. Evaluation of bulls on the basis of their ancestors’
performances, eg. bull mothers
- future option also on maternal / paternal halfsisters
A new scheme for Breeding bull provision
Definition: Young sire programme
Features:
- short generation intervals (minimum 3-4 years)
- low accuracies
→ relatively high genetic response per year
- simple, least expensive breeding scheme

40. - comprises about 200 farmers
- formation of village service co-operatives
(e.g. purchase of agricultural inputs, milk
collecting, marketing)
- implementation of village bull service
A new scheme for Breeding bull provision
Rural administrative community e.g. Selale

41. • Crossbred cow population in a PA
–200 small holder
- 2 crossbred cows per farm → 400 crossbred cows
4. A new scheme for Breeding bull provision
Determination of number of replacement bulls
for rural community
• Number of replacment bulls needed per year
- Mating ratio: 1 : 40 → 10 bulls for service in
Useful life of a bull: 3 years → 4 bulls

42. 5. Model calculation for a Young sire scheme
Establishment of local open nuclei based on
cow performance
- Second step:
→ start of a farmer based recording system with
community verification
Identification of superior cows to breed bull calves:
- First step (no recording)
→farmer identification of best performaning cows
(e.g. milk yield history, field day comparison)

43. 5. Model calculation for a Young sire scheme
Establishment of local open nuclei based on
cow performance
Minimum nucleus size within a PA:
- 14-28 superior cows (7-14% of cow population)
→ no scope for performance selection

44. 5. Model calculation for a Young sire scheme
Establishment of local open nuclei based on
cow performance
Selection intensities for different nucleus sizes
Nucleus size
50 100 150
Expected proportion of bulls
selected, % 28-56 14-28 9-19
Selection intensity i 1.16-0.69 1.60-1.16 1.80-1.42

45. 6. Conclusions
• Agro-ecological planning including water
conditions essential for securing efficiency
• Rural smallholder need increased dairy
performance for efficient use of resources/water
• Community based breeding scheme best suited
to secure operational sustainability
• Young Sire program with open nucleus breeding
scheme could lead to sutainable performance
with best efficiency

46. 6. Conclusions
• It pre-supposes an active participation of the
farmers and respective vocational training,
• Calls for extended scientific engagement of
higher learning institutes interested in R 4 D and
aquainted with participartory research methods
Excellent field lab for College /
University students