Presentation on the TAGMI tool by Jennie Barron at CPWF's final grant event at IFAD headquarters in Rome on October 28-29, 2014.

1. New approach in decision support for technology
outscaling in smallholder farming systems:
The TAGMI ‘proof of concept’
Dr Jennie Barron
(jennie.barron@sei-international.org)
Stockholm Environment Institute (SEI)
Challenge Programme Water and Food
Volta Basin V1 project and Limpopo Basin L1 project

2. Session outline :
- Briefing of TAGMI concept and product
- Q&A
- TAGMI testing

3. Targeting AGwater Management Interventions:
PURPOSE :
• provide a decision support tool for AWM outscaling
PROCESS:
• Merging different type of knowledge through Bayes
network approach
• Show strength of prediction (uncertainty)
PRACTISE
• 3 AWM technologies for Volta and Limpopo
• User modifying input data and relations
www.seimapping.org/tagmi

4. Pooling knowledge in a consultative research process
• Reviews,
literature
search
• Consultations
(PGIS), MSc
theses
• Meetings,
presentations,
dialogue
• Consultations National
public,
(private) ,
NGOs
LBDC, VBDC
, CPWF
MERGED
KNOWLEDGE
In TAGMI model
Existing
academic
knowledge
Farmers ,
local
community

5. STEP 1: Process of consultation : incorporate various sources
of knowledge
Consultation 2011 Consultation 2012 Synthesis
Reg
researc
h
5%
Nat
researc
Farmer
Farmer
81%
/
Comm
unity …
CBO
1%
Extensi
on
5%
Public
Service
s
L2o%cal
govt
6%
NGO
1%
Farmer
2%
CBO
5%
Public
Services
Local govt 9%
17%
NGO
5%
Nat govt
6%
Reg
mgmnt
2%
Nat
research
52%
Intl
research
2%
CBO
Pu3b%lic
Service
s
7%
Local
govt
19% NGO
12%
Nat
govt
11%
h
34%
Reg
mgmnt
8%
Intl
researc
h
1%
CBO
2%
Public
Services
4%
Local
govt
27%
Reg
research
2%
research
26%
NGO
23%
Nat
Nat govt
12%
Reg
mgmnt
3%
Intl
research
1%

6. STEP 2: Decide: What is relevant technologies?
What is ‘success’?
AWM intervention Initial
Consultation (2011)
PGIS in depth
(2011,2012)
TAGMI representation
(2013)_
Soil and water conservation /DRS/CES
Planting pits (incl zai)
Bunding /ridges/contour bunds/ploughing
Tied ridges
BF
BF
GH
GH
GH,BF GH,BF
Cover crop
Tree planting
Mulching
GH
GH BF
Shallow groundwater use
Shallow wells
Wastewater re-use
GH
GH. BF GH ,BF
Motorised water pumps ()small scale irrigation)
Treadle pumps
Drip irrigation
Punched bag
Micro irrigation
Supplemental irrigation (rice)
GH, BF
BF
BF
GH
BF
GH,BF
GH, BF
GH,BF
Earth dams
Underground (in stream) dams
Small dams /reservoirs
Ferro cement tanks
Roof waterharvesting
Large scale irrigation scheme
GH. BF
GH. BF
GH,BF
GH,BF GH,BF
3 AWM interventions
chosen for TAGMI

7. STEP 3: Merge interdisciplinary factors with Bayes approach

8. STEP 3: Merge interdisciplinary factors with Bayes approach

9. STEP 3: Merge interdisciplinary factors with Bayes approach

10. STEP 4: Develop web based interface in open source
and accessible data layers

11. http://www.seimapping.org/tagmi/index.php

12. Example: Data input and impact

13. RESULTS: Current TAGMI predictions Volta
SWC
Small scale
irrigation
Small
reservoirs

14. RESULTS: Testing climate change impact on potential
Volta basin: Potential out-scaling under CC
Current
--20%

15. Indica
tor of
succe
ss
Indicator
of success
Can we calibrate/validate?
CPWF L2:
Requires functional
institutional structures
CPWF L2:
Requires adequate ‘resources’
- Money, manpower, skills,
equipment, etc.
CPWF L3:
Improving market access
CPWF L3:
Poor soil management/ fertility

16. Can we calibrate / validate ?
TAGMI predictions
match actual adoption
rates for about 75% of
the provinces

17. LESSONS FOR RESEARCH
• There is opportunity for out-scaling of SWC , smallholder
irrigation and small reservoirs but prediction strength is low
• Data on social-human layers are critical, but rarely
available
• High agreement between factors affecting out-scaling
across technologies, countries and basins
• The importance and benefit of investments in “Best
Practice In Implementation” (‘Due diligence’ ) to achieve
successful outscaling

18. TAGMI taken to practise: ‘doing research for development’
• CPWF in Volta and Limpopo developed ‘proof of concept’
• Generic approach: easily done for other technologies and
scales
• Spin-off in new Bayes model for shallow groundwater irrigation
N Ghana; AWM opportunities in Niger; livestock –fodder
system improvements Volta-Niger
• What does it take to embed into decision support process?

19. www.seimapping.org/TAGMI
Stockholm Environment Institute in partnership with
WATERNET, University of Witwatersrand, International Water Management Institute (IWMI),
University of Ouagadougou, Institut National de l’Environnement et de Récherche Agricole (INERA),
Kwame Nkrumah University of Science and Technology (KNUST),
Savanna Agricultural Research Institute (CSIR-SARI),
We thank all contributors:
absent colleagues
farmers, boundary partners and participants in consultations and events
VBDC and V1 colleagues, and LBDC and L1 colleagues
funders

20. Thank you!