Landscape Level Hydrological Modeling and Farm Scale Modeling in the Volta River Basin

Landscape level hydrological modeling

&
Farm-scale modeling
Fred Kizito, Katrien Descheemaeker, Sabine Douxchamps

3 / 7 / 2012

Landscape level hydrological modeling


3 / 7 / 2012

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

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


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

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

6

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

7

Water Balance Components for
Golinga
1200

Calibration

Validation

800

600

400

200

0
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014

Rainfall (mm) and Discharge (mm)

1000

Simulated

Warm-up

Rainfall (mm)

Surface Water Discharge (mm)

Percolation (mm)

Groundwater Discharge (mm)

Evapotranspiration (mm)

8

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


Farm-scale modeling


3 / 7 / 2012

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

NPK
NPK
NPK

Giller et al. 2010


Options

NUANCES-FARMSIM: farm-scale modeling approach

Tittonell et al. (2007) Fld Crops Res. 100, 348-368; Rufino et al. (2007) Livestock Sci. 112, 273-287; Chikowo et al. (2008) Ag. Syst.
97, 151-166; Tittonell et al. (2009) Ag. Syst. 101, 1-19; van Wijk et al. (2009) Ag. Syst. 102, 89-101; Tittonell et al. (2010) E. J Agron.
32, 10-21.

APSIM (Agricultural Production Systems sIMulator)


Constraint analysis
Example of feedbase in villages around Golinga reservoir

In-house
feeding

Grazing

Feed gap

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


Adapted from McDonald (2010)

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



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



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



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



Scenario Analysis
Discussion support tool  Learning tool



Simulation experiment


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

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


concentrates


fertilizer

Tradeoff analysis

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

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


Merci pour votre attention!
Thanks for your attention!


Landscape Level Hydrological Modeling and Farm Scale Modeling in the Volta River Basin

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