decision support for technology uptake in smallholder farming systems: the example of tagmi
DESCRIPTION
Presented by Jennie Barron (University of York, UK) at the Livestock Systems and Environment (LSE) Seminar, ILRI, Nairobi, 8 May 2014TRANSCRIPT
5/9/2014
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Decision support for technology uptake in smallholder farming systems:
The example of TAGMI
Dr Jennie Barron ([email protected])
Stockholm Environment Institute (SEI) University of York, UK
LSE seminar ILRI , Nairobi 8th May 2014
‘Business of research’ changing ? 1. Knowledge exist Multiple knowledge systems 2. Real solutions in real time Impact , relevance
3. Engage outside comfort zone ‘Science objectivity’
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Agricultural development discourse , e.g. Volta
Douxchamps et al 2014
Technologies promoted
Focus - Concept
Main actors
1960 1980 2000 1960 1960
TODAY: Agriculture back in national to global policies
• Agriculture is now key on more complex policy agenda o Sustainable o Climate smart o Energy
• Policies lag behind practice o No clear vision of the future of agriculture (Limpopo basin)
• Agriculture contributes to
o Meeting the broader policy goals o But, roles of smallholder farmers not well articulated (Limpopo basin)
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TODAY : Good (research) knowledge and evidence in technical fixes?
Example Ag. water synthesis in Limpopo (n=1400 references)
-100
0
100
200
300
400
500
Reducedtillage
In-situ waterretention
Evaporationsuppressants
Nutrient only Waterharvesting with
storage
Croppingsystem andAgroforestry
Combinationof two or moreinterventions
Yiel
d ch
ange
(%)
Improved AWM technology
n= 85
n= 190
n= 130
n= 247
n= 58
n= 195
n= 428
Magombeyi et al (forthcoming) : Agricultural water management systematic review and yield benefits for Limpopo
Yield response to ag. water technologies
TODAY : Good (research) knowledge and evidence in technical fixes?
Example Ag. water synthesis in Limpopo (n=1400 references)
-100
0
100
200
300
400
500
Reducedtillage
In-situ waterretention
Evaporationsuppressants
Nutrient only Waterharvesting with
storage
Croppingsystem andAgroforestry
Combinationof two or moreinterventions
Yiel
d ch
ange
(%)
Improved AWM technology
n= 85
n= 190
n= 130
n= 247
n= 58
n= 195
n= 428
Magombeyi et al (forthcoming) : Agricultural water management systematic review and yield benefits for Limpopo
Research opportunities
Yield increase potential
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www.seimapping.org/tagmi
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
• Reviews, literature
search
• Consultations (PGIS), MSc
theses
• Meetings, presentations,
dialogue • Consultations
National public,
(private) , NGOs
LBDC, VBDC , CPWF
Existing academic
knowledge
Farmers , local
community
MERGED KNOWLEDGE
In TAGMI model
Pooling knowledge in a consultative research process
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STEP 1: Process of consultation : incorporate various sources of knowledge
Consultation 2012 Consultation 2011 Synthesis
Farmer 81%
Farmer/
Community …
CBO 1%
Extension 5%
Public Service
s 2% Local
govt 6%
NGO 1%
Farmer 2%
CBO 5%
Public Services
9% Local govt 17%
NGO 5%
Nat govt 6%
Nat research
52%
Reg mgmnt
2%
Intl research
2%
CBO 3% Public
Services
7% Local govt 19% NGO
12%
Nat govt 11%
Nat researc
h 34%
Reg researc
h 5%
Reg mgmnt
8%
Intl researc
h 1%
CBO 2%
Public Services
4% Local govt 27%
NGO 23%
Nat govt 12%
Nat research
26%
Reg research
2%
Reg mgmnt
3%
Intl research
1%
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
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STEP 3: Merge interdisciplinary factors with Bayes approach
STEP 3: Merge interdisciplinary factors with Bayes approach
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STEP 3: Merge interdisciplinary factors with Bayes approach
STEP 4: Develop web based interface in open source and accessible data layers
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http://www.seimapping.org/tagmi/index.php
Example: Data input and impact
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RESULTS: Current TAGMI predictions Volta
SWC Small scale
irrigation Small
reservoirs
1.RESULTS: current TAGMI predictions
# districts
High/Med/Low
Cropland Total BF: 2846941ha
Total GH: 5102661 ha
High/Med/Low
Strength
prediction
Small reservoirs
Burkina Faso 50%/32/18 47/20/32 Low
Ghana 62%/15/23 58/36/7 Low
RESULTS: Current TAGMI predictions Volta
Example: Small reservoirs out-scaling potentials
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RESULTS: Testing climate change impact on potential
Volta basin: Potential out-scaling small reservoirs under CC
Current rainfall
Burkina Faso 2 846 941 44/33/24 45/41/15 43/32/25 45/38/17 41/34/26 45/36/19
Ghana 5 102 661 56/23/21 50/26/24 53/24/23 41/19/40 51/23/26 35/20/45
Present-day Driest scenario Wettest scenario
Volta Total cropland (ha)* # districts (%)
High/Med/low
Cropland (%) # districts (%)
High/Med/low
Cropland (%) # districts (%)
High/Med/low
Cropland (%)
Current rainfall
-20%
Current rainfall
+50%
Indicator 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:
Poor soil management/ fertility
CPWF L3:
Improving market access
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Can we calibrate / validate ?
TAGMI predictions match actual adoption rates for about half of the provinces
Weighting the factors differently : Does it matter on the results?
Sensitivity : Does the world view matter?
DfID livelihood framework Social-ecological system
Ostrom (2009)
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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
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
• Requests from funders and development agents for possible development
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www.seimapping.org/TAGMI
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
Thank you!