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A Partner
of
TAGMI: An Interdisciplinary Decisions Support Tool
in Agricultural Water Management Outscaling for
the Volta River Basin
Barron, J., Kemp-Benedict, E., Morris. J., de Bruin, A., Wang, G., Fencl, A.
this work is based on the V1 ‘Targeting and scaling out’ project led by SEI in
partnership with INERA, University of Ouagadougou, CSIR-SARI and KNUST
Andes • Ganges • Limpopo • Mekong • Nile • Volta
MAIN MESSAGES
• The TAGMI (Targeting AG water Management Interventions) is an
online decision support tool developed for supporting investments and
action in smallholder farming in Volta and Limpopo
 It includes both biophysical and social economic conditions influencing oustcaling
 It integrates multiple sources of expertise and knowledge
 It provides a measure of strength of prediction
• TAGMI can guide on geographical location opportunities based on
given conditions. However , implementation of action need to be done
with ‘best practise in implementation ‘ for successful outcome
Andes • Ganges • Limpopo • Mekong • Nile • Volta
BACKGROUND
Volta and Limpopo Basin Stakeholders demand in 2009:
“…the question of what AWM intervention can work where and why”
V1-L1 purpose :
To develop and evidence a knowledge-based tool to assess and map the
likelihood that a given intervention will be successful in given locations, at
the basin scale
-three technologies, two basins
Andes • Ganges • Limpopo • Mekong • Nile • Volta
APPROACH 1
• Process of consultation : incorporate various sources of knowledge
• Decide what is relevant AWM technologies, what is ‘success’
Consultation 2012Consultation 2011 Synthesis
Full Irrigation
Rainfed
Andes • Ganges • Limpopo • Mekong • Nile • Volta
APPROACH 2
• Merge interdisciplinary factors
with Bayes approach
• Develop web based interface in
open source and accessible data
layer
Andes • Ganges • Limpopo • Mekong • Nile • Volta
1.RESULTS: current TAGMI predictions
SWC Small scale irrigation Small reservoirs
Andes • Ganges • Limpopo • Mekong • Nile • Volta
1.RESULTS: current TAGMI predictions
Soil Water Conservation # districts
(%)
Cropland (% )
Total BF: 2846941ha
Total GH: 5102661 ha
Strength of
prediction
Burkina Faso High/Med/Low 51/25/25 61/20/20 Low
Ghana High/Med/Low 45/39/16 48/6/46 Low
Small reservoirs
Burkina Faso High/Med/Low: 50/32/18 47/20/32 Low
Ghana High/Med/Low: 62/15/23 58/36/7 Low
Andes • Ganges • Limpopo • Mekong • Nile • Volta
1.RESULTS: current TAGMI predictions
Example data input and impact
Andes • Ganges • Limpopo • Mekong • Nile • Volta
2. RESULTS: testing TAGMI for small reservoirs
MAPS……. Decision in SR may not
be done at HH level;
mainly in 80s
Andes • Ganges • Limpopo • Mekong • Nile • Volta
2. RESULTS: testing TAGMI for Soil water conservation
TAGMI predictions match
actual adoption rates for
about half of the provinces
Andes • Ganges • Limpopo • Mekong • Nile • Volta
LESSONS
• Data on social-human layers are critical, but rarely
available
• High agreement between factors affecting outscaling
across technologies, countries and basins
• The importance of Best Practice In Implementation (‘Due
diligence’ )to achieve successful outscaling
• There is opportunity for outscaling of SWC , smallholder
irrigation and small reservoirs but prediction strength is low
Andes • Ganges • Limpopo • Mekong • Nile • Volta
RECOMMENDATIONS TO POTENTIAL USERS
• Consider carefully weighting of factors contributing
for success and the implications on map output
• Opportunities to verify a/o cross check TAGMI
prediction
• Improve data especially on human-social domains
• Identify potential geographic spaces only half the
story: more effort in design of appropriate
implementation
Andes • Ganges • Limpopo • Mekong • Nile • Volta
www.seimapping.org/TAGMI
We thank all contributors:
absent colleagues
farmers, boundary partners and participants in consultations and events
VBDC colleagues, and LBDC and L1 colleagues
funders

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TAGMI - an interdisciplinary decisions support tool in AWM outscaling for the Volta River basin

  • 1. A Partner of TAGMI: An Interdisciplinary Decisions Support Tool in Agricultural Water Management Outscaling for the Volta River Basin Barron, J., Kemp-Benedict, E., Morris. J., de Bruin, A., Wang, G., Fencl, A. this work is based on the V1 ‘Targeting and scaling out’ project led by SEI in partnership with INERA, University of Ouagadougou, CSIR-SARI and KNUST
  • 2. Andes • Ganges • Limpopo • Mekong • Nile • Volta MAIN MESSAGES • The TAGMI (Targeting AG water Management Interventions) is an online decision support tool developed for supporting investments and action in smallholder farming in Volta and Limpopo  It includes both biophysical and social economic conditions influencing oustcaling  It integrates multiple sources of expertise and knowledge  It provides a measure of strength of prediction • TAGMI can guide on geographical location opportunities based on given conditions. However , implementation of action need to be done with ‘best practise in implementation ‘ for successful outcome
  • 3. Andes • Ganges • Limpopo • Mekong • Nile • Volta BACKGROUND Volta and Limpopo Basin Stakeholders demand in 2009: “…the question of what AWM intervention can work where and why” V1-L1 purpose : To develop and evidence a knowledge-based tool to assess and map the likelihood that a given intervention will be successful in given locations, at the basin scale -three technologies, two basins
  • 4. Andes • Ganges • Limpopo • Mekong • Nile • Volta APPROACH 1 • Process of consultation : incorporate various sources of knowledge • Decide what is relevant AWM technologies, what is ‘success’ Consultation 2012Consultation 2011 Synthesis Full Irrigation Rainfed
  • 5. Andes • Ganges • Limpopo • Mekong • Nile • Volta APPROACH 2 • Merge interdisciplinary factors with Bayes approach • Develop web based interface in open source and accessible data layer
  • 6. Andes • Ganges • Limpopo • Mekong • Nile • Volta 1.RESULTS: current TAGMI predictions SWC Small scale irrigation Small reservoirs
  • 7. Andes • Ganges • Limpopo • Mekong • Nile • Volta 1.RESULTS: current TAGMI predictions Soil Water Conservation # districts (%) Cropland (% ) Total BF: 2846941ha Total GH: 5102661 ha Strength of prediction Burkina Faso High/Med/Low 51/25/25 61/20/20 Low Ghana High/Med/Low 45/39/16 48/6/46 Low Small reservoirs Burkina Faso High/Med/Low: 50/32/18 47/20/32 Low Ghana High/Med/Low: 62/15/23 58/36/7 Low
  • 8. Andes • Ganges • Limpopo • Mekong • Nile • Volta 1.RESULTS: current TAGMI predictions Example data input and impact
  • 9. Andes • Ganges • Limpopo • Mekong • Nile • Volta 2. RESULTS: testing TAGMI for small reservoirs MAPS……. Decision in SR may not be done at HH level; mainly in 80s
  • 10. Andes • Ganges • Limpopo • Mekong • Nile • Volta 2. RESULTS: testing TAGMI for Soil water conservation TAGMI predictions match actual adoption rates for about half of the provinces
  • 11. Andes • Ganges • Limpopo • Mekong • Nile • Volta LESSONS • Data on social-human layers are critical, but rarely available • High agreement between factors affecting outscaling across technologies, countries and basins • The importance of Best Practice In Implementation (‘Due diligence’ )to achieve successful outscaling • There is opportunity for outscaling of SWC , smallholder irrigation and small reservoirs but prediction strength is low
  • 12. Andes • Ganges • Limpopo • Mekong • Nile • Volta RECOMMENDATIONS TO POTENTIAL USERS • Consider carefully weighting of factors contributing for success and the implications on map output • Opportunities to verify a/o cross check TAGMI prediction • Improve data especially on human-social domains • Identify potential geographic spaces only half the story: more effort in design of appropriate implementation
  • 13. Andes • Ganges • Limpopo • Mekong • Nile • Volta www.seimapping.org/TAGMI We thank all contributors: absent colleagues farmers, boundary partners and participants in consultations and events VBDC colleagues, and LBDC and L1 colleagues funders

Notas do Editor

  1. Match: 15 No match: 17 adoptionPred High Med LowHigh 4 3 9Med 3 2 2Low 2 5 4
  2. (evidence: consultations)evidence: consultations, PGIS synthesis)Low strength in prediction (evidence: TAGMI outputs)