Study Objectives:
Modeling hydrological dynamics to quantify water fluxes for achieving optimal crop-livestock productivity
- Assess sub-basin scale water balance thresholds at target sites
- Develop water allocations framework in target sites
- Recommend best-fit integrated rainwater management strategies that maximize productivity
3. Study objectives
Modeling hydrological dynamics to quantify water
fluxes for achieving optimal crop-livestock
productivity
o Assess sub-basin scale water balance thresholds at target
sites
o Develop water allocations framework in target sites
o Recommend best-fit integrated rainwater management
strategies that maximize productivity
Andes • Ganges • Limpopo • Mekong • Nile • Volta
4. Study sites
Landscape hydrological modeling:
o Conduct sub-basin water balance thresholds
o Develop a water allocations framework in target sites
o Assess water productivity in specific crop-livestock systems
Andes • Ganges • Limpopo • Mekong • Nile • Volta
5. Methods
• Baseline characterization has been conducted in
target sites at the household level
• Tools:
and
• SWAT hydrological modeling is physically based
– Weather, soil properties, topography, vegetation,
and land management practices data sets
• DEM:
– Used at 90 m resolution
– Watershed delineation; Stream network
Andes • Ganges • Limpopo • Mekong • Nile • Volta
6. Crop water use trends in Golinga
Data Source: Ministry of Food and Agriculture, Ghana
Production estimates and Regional Crop Acreage data for 1992 to 2010
- Complemented and verified with V2 Household survey data
Andes • Ganges • Limpopo • Mekong • Nile • Volta
6
7. Water, crops and livestock
distribution for Golinga
Source: Ramankutty et al, 2000
Processed from Global Croplands database;
Complemented with Ghana MoFA Data
and V2 Household data
Source: Processed from FAO
Geo-portal data
-Not checked against V2 HH data
Andes • Ganges • Limpopo • Mekong • Nile • Volta
7
9. Conclusion
Milestones:
• Cropping density and livestock distribution ascertained for all study
sites; Water balance thresholds calculated for all study sites
• Currently developing crop-livestock water productivity maps for all
target sites
• Landscape outputs from water allocations and water balance will
complement farm-level flows analysis
Conclusion
• Hydrological analysis indicated that reservoirs play a critical role in
maintaining storage and reducing surface runoff losses at subbasin scale
Andes • Ganges • Limpopo • Mekong • Nile • Volta
11. Objectives
Identify and evaluate promising interventions for
improved farm productivity
•
•
•
•
•
•
•
Extrapolating field results in space and time
Aggregate field level outputs to farm level
Scenario analysis: exploring options
Risk analysis
Tradeoff analysis (tradeoffs in resource allocation)
Identifying issues for further (field) research
Discussion and decision support tool: informing the
innovation platform
Andes • Ganges • Limpopo • Mekong • Nile • Volta
15. Constraint analysis
Example of feedbase in villages around Golinga reservoir
In-house
feeding
Grazing
Feed gap
Andes • Ganges • Limpopo • Mekong • Nile • Volta
16. Scenario Analysis
Baseline situation
• 1.5 ha farm
• household of 8 people
• crops: millet, sorghum and cowpea intercropped
• no crop residue stored for cattle
• 3 breeding cows, sells at 4-5 years, herd of 8-10
Andes • Ganges • Limpopo • Mekong • Nile • Volta
Adapted from McDonald (2010)
17. Scenario Analysis
Baseline
Animals sold (10y)
5-6
Animals on hand
12-13
Forage deficit
7000
Wet season labour
+50
Cattle revenue
34000
Gross Margin*
515000
Cash balance
-3000
* - including home consumption
Andes • Ganges • Limpopo • Mekong • Nile • Volta
Adapted from McDonald (2010)
18. Scenario Analysis
Baseline
Animals sold (10y)
Manure
(4 t/ha)
5-6
6-7
Animals on hand
12-13
13
Forage deficit
7000
6000
Wet season labour
+50
+20
Cattle revenue
34000
37000
Gross Margin
515000
637000
Cash balance
-3000
109000
Andes • Ganges • Limpopo • Mekong • Nile • Volta
Adapted from McDonald (2010)
19. Scenario Analysis
Baseline
Animals sold (10y)
Manure
(4 t/ha)
Crop residue
harvesting
5-6
6-7
7-8
Animals on hand
12-13
13
13
Forage deficit
7000
6000
3000
Wet season labour
+50
+20
+10
Cattle revenue
34000
37000
41000
Gross Margin
515000
637000
671000
Cash balance
-3000
109000
140000
Andes • Ganges • Limpopo • Mekong • Nile • Volta
Adapted from McDonald (2010)
20. Scenario Analysis
Baseline
Calves sold (10y)
Manure
(4 t/ha)
Crop
residue
harvesting
Sell cow, buy
10 sheep &
fatten
5-6
6-7
7-8
6-7
Cattle on hand
12-13
13
13
9-10
Forage deficit
7000
6000
3000
4400
Wet season labour
+50
+20
+10
+50
Livestock revenue
34000
37000
41000
96000
Gross Margin
515000
637000
671000
739000
Cash balance
-3000
109000
140000
205000
Andes • Ganges • Limpopo • Mekong • Nile • Volta
Adapted from McDonald (2010)
23. Simulation experiment
Lessons:
- Fertilizer increases average yield, but also production risk
- Information on risk is useful for insurance providers (partner in the IPs?)
Andes •
- Water and Ganges • Limpopo • Mekong • Nile • are interlinked
nutrient use efficiency Volta
24. Tradeoff analysis
Understanding resource allocation decisions
Resources are finite; directing them to one objective
will penalize other objectives
•
•
•
Labor: weeding vs. marketing produce
Cash: fertilizers vs. hiring labor for weeding
Crop residues: soil organic matter vs. livestock feeding
Andes • Ganges • Limpopo • Mekong • Nile • Volta
30. concentrates
fertilizer
Tradeoff analysis
Lessons:
- Tradeoff analysis helps us in systems understanding
- LinkedAndes • Ganges • Limpopo • Mekongsocio-institutional settings (e.g. market) and farmers’
with understanding of • Nile • Volta
objectives, this can be used to design well-adapted interventions
31. Conclusions
Farm systems models are useful tools
for research to
- Understand complex farm dynamics, including farmer
decision making
- Identify topics for further (field) research
for development through
- Assisting in the development of adapted interventions
- Generation of information for discussion support (in IPs)
! Need for high quality input data
Andes • Ganges • Limpopo • Mekong • Nile • Volta
32. Merci pour votre attention!
Thanks for your attention!
Andes • Ganges • Limpopo • Mekong • Nile • Volta