1. Calculating Programme Financial Scenarios The FarmTree®Tool turns farm projections into basin scenarios
Agroforestry needs Cash Flow Planning => Farm & Landscape CFP
Water Productivity Master Class 3: From Farms to Basins MetaMeta, Wageningen, 7 June, 2017
Frank van Schoubroeck,

2. Presentation Outline: from farm to basin planning
The FarmTree®Tool – and possible synergy with basin planning
Actor
Activity
Outcome
Project designers define investments in landscape components
Landscape Planning
Cash flow & economic indicators
Environmental & social indicators
Farmer / entrepreneurs prepare cash flow plans
Farm Planning
Farm enterprise cash flow and Human Resource planning
Farmers weigh management options
Plot Planning
Agronomic & economic performance at plot level
Local Data Pool
Water models?
Local Experts gather data
Tree models
Crop models
Inputs models
HR models

3. 1. Three Research Questions
1 - How do we capture cash flows at farm level?
2 - How do we capture cash flows at landscape level?
3 - How do large numbers of farmers get teased into farm planning?

4. => The FarmTree®Tool can help
2 Question
1 - How do we capture cash flows at farm level?
Investments & writing-off; short & long cycles
Varying water availability & uses
Price fluctuations
Mix of crop, tree and animal production
=> The FarmTree®Tool can help

5. …………………………………………………………..
2 FarmTree®Tool - Model
…………………………………………………………..
Model ..………...
Results Filter ...
Input
General data; individual choices & risks => Model => indicators over 5-50 years
Output

6. 3 – Example Developing Farm Scenarios:
ICRAF Project - to introduce Rainwater Harvesting in Kenya

7. 3a Baseline
(imaginary) 1 ha subsistence farm:
0.7 ha maize + NPK
0.3 ha beans
Experienced farmer
Farm Gate of wholesale price
4 full-time 500/day

8. 3a Baseline Result
Farm production is steady-state at KES 1.8 m; result at KES 0.8 m
Net Present Value KES 8m
See a summary graph (20Y):

9. 3b Baseline + Farm Pond
1 ha Farm Pond Enterprise with inputs:
Investment: 250m3 pond; pump, NPK, Pest Control allows for:
0.3 ha tomato, onion and kayes
0.6 ha trees Melia+Grevillea (maize intercrop)
10 bee hives chickens
Unexperienced farmer (learning in 4 y)
4 full-time 500/day
Farm gate of wholesale market price); 15% interest

10. 3b Baseline + Farm Pond: Result
Lowest cash flow point is KES -730k; payback Year 3
Annual result at KES 4 m (Y6)
Net Present Value KES 24k (setup); KES 38k (Y5)
Internal Rate of Return 53% (Y5); 76% (Y10)
See a summary graph (20Y) :

11. 3b Non-monetary Indicator Projection
Example: Carbon flow over 50 years.
We can also project: production of Calories, Vit A/C, Protein; shade, erosion, water use, etc.

12. 4a Senegal, youth farmer training, December 2015
Khar Ndiaye:
“The FarmTree®Tool shows that our agriculture is different from that of our parents”
March, 2017: the French Embassey declares trainee Idrissa Traore, Bakel, as “best young entrepreneur” in Senegal
But what about … basin level planning?

13. 2 - How do we capture cash flows at basin level?
6a From farm to basin …
2 - How do we capture cash flows at basin level?

14. Wood lots Food Grain Fields Horticulture Sylvo-pastoralism
6b Water Mgmt Projects address various landscape elements with short and longer term results
Wood lots
Food Grain Fields
Horticulture
Sylvo-pastoralism

15. => Black figures from Y6 onwards
6c Example: 125,000 ha Tanzania Adaptation Project => Financial Projection Protocol
Project Base Scenario
=> Black figures from Y6 onwards

16. Results of Interventions
6c Project Financial Projection Protocol
Project Base Scenario
=> Accounting Structure
Interventions
Risks
Baseline
Investments
Project Results
Economic Indicators
Results of Interventions
Year 1-15

17. 3 - How do large numbers of farmers get access to planning?
6d Project Financial Projection Protocol
Scenario: Agriculture prices -50%
=> red figures even after 15 years
3 - How do large numbers of farmers get access to planning?

18. 7. Our Ambition: Farmers explore management options through a Farm Game

19. Geodata bring in real limitation and uncertainty:
“GeoFarmGame” for strategizing water investments?
Farm
Game
Tree, Crop, Inputs Data
Market Data
Geo-Data stream
Landscape
Multiple Farm Scenarios
Historical
Geo-Data
Projecting Scenarios
Carrying out ‘best bet’ Farming Practice
Monitoring & Evaluation vis-à-vis projection
Imagining farming scenarios
Farm-Level Learning Cycle
Carrying out ‘best bet’ Landscape Investment
Imagining Landscape scenarios
Landscape- Level Learning Cycle
Historical +

20. The FarmTreeServices™ Team
Frank van Schoubroeck, The Netherlands
Mike Kothuis, The Netherlands - Gaming
Adamou Salissou, Niger/west-Africa,
Peter Paap, The Netherlands
Judith Sinja, Kenya