1. BFP‐ANDES
– Leader: Mark Mulligan, KCL
– Coordinator: Jorge Rubiano, UNAL
• WP1(POV): G. Hyman, A. Farrow, G. Lema (CIAT)
WP1(POV): G Hyman A Farrow G Lema (CIAT)
• WP2(AVAIL): M. Mulligan (KCL), J..G. Leon (UNAL)
• WP3(PROD): M. Kirby (CSIRO), J. Selvaraj (UNAL)
• WP4(INST): D. White (CIAT), V. Vargas (UNAL)
• WP5(INTERV) M S
M. Saravia (CONDESAN,BC), incl. prev. CP projects
i (CONDESAN BC) i l CP j
• WP6(KNOW): N. Niederhauser (CIAT)
• + tied PhD, MSc and UG students
AIM: To have the best available science used in the
formulation and testing of land and water policy for
better livelihoods, in cases where currently it is not
better livelihoods in cases where currently it is not
Brief for presentation:
– What Andes BFP is intended to achieve? And for whom?
– Expected Research products
– How you intend to get outputs?
2. Team Experience
• Extensive knowledge of the region
• Poverty mapping and analysis
• Water accounting and productivity
Water accounting and productivity
• Institutions and interventions
• L l t k h ld
Local stakeholders and networks
d t k
• Spatial hydrological modelling and GIS
• Global datasets
• Policy support systems and knowledge
Policy support systems and knowledge
systems
4. Basin(s) Context
• High but variable rainfall steep slopes spatial
High but variable rainfall, steep slopes, spatial
heterogeneity, climate change
• Poverty sometimes related to lack of water, sometimes of
y ,
excess water:
– Hazards to productivity : (landslides, soil erosion/degradation,
nutrient losses)
nutrient losses)
– Downstream impacts : (sedimentation, water quality losses,
flooding, supply to major cities)
.... with impacts on health and poverty sometimes through food.
• Competing land‐use demands on steep‐lands
• E i ti
Existing and proposed major dam projects, inter‐basin
d d j d j t i t b i
transfers, mining...
• Payments for environmental services and other non ag.
Payments for environmental services and other non ag.
livelihood options
5. ‘Clients’
• Farmers, (basin) communities, interested citizens
a e s, (bas ) co u t es, te ested c t e s
• Local government (policy advisors)
• National government (policy advisors)
National government (policy advisors)
• Universities, research orgs (e.g. IDEAM)
• Commercial : Water/HEP companies
Commercial : Water/HEP companies
• International Conservation NGOs (CI, WWF, TNC)
• International organisations (CP/CGIAR,CARE,
International organisations (CP/CGIAR CARE
Oxfam)
• International donors (WB, IADB,DfID,GTZ..)
International donors (WB, IADB,DfID,GTZ..)
10. “The
“Th researchers … h
h have already th
l d thrown
much darkness on this subject, and it is
probable that if they continue [their
investigations] we shall soon know nothing
at all about it. “ (Mark Twain)
11. Unintended
‘Client’ Needs consequences
• Simplification of a complex problem
• Accessible baseline data and information
baseline data and information
• Accessible tools for testing effects of alternative policy
options (interventions) and their intended and
unintended consequences
• Accessible knowledge on impacts of climate change
• Accessible knowledge of (seasonal) downstream
ibl k l d f( l) d
impacts of land use change on water supply to
cities/dams
/
• Accessible spatial planning tools for optimisation in a
highly heterogeneous and connected environment
• An Institutional framework for evidence‐based policy
implementation
12. Products
• Capacity built in local institutions/stakeholders (and
Capacity built in local institutions/stakeholders (and
networks e.g. CONDESAN)
• Students engaged and trained
engaged and trained
• Report diagnosing current status of water poverty,
water productivity, environmental security and
water productivity environmental security and
social and institutional context incl. gender
• Maps of long term average water availability and
of long term average water availability and
trends
• Maps of resource sensitivity to land use and
Maps of resource sensitivity to land use and
climate change
• Maps of the poverty outcomes of changing access
Maps of the poverty outcomes of changing access
to water
15. Products
• Maps of the sensitivity of food production to climate
(variability and change) and land use change
• D b
Database of institutions and intervention projects
fi i i di i j
and likely outcomes of a range of these in the basin
• S
Summary of points of contact and types of
f i t f t t dt f
data/information required by institutions
• Andes BFP portal on IDIS
Andes BFP portal on IDIS
Much of the above integrated into:
M h f th b i t t di t
• CPWF‐ANDES PSS (Web‐based Policy Support
System) for impact assessment of policy
System) for impact assessment of policy
interventions (bilingual)
16. Why a PSS?
Premise is that policies are better when based on the science (natural
Premise is that policies are better when based on the science (natural
and social), so how do we get the analysts to look at the science? ‐
make it easy.
What is a PSS (Policy Support System) :
•combines best available data and knowledge of process (models),
•integrated spatial database and test‐bed for user policies or
interventions
•leaving the simplest possible messages without losing the important
•leaving the simplest possible messages without losing the important
complexity of the data and the science,
• flexible and dynamic project legacy in addition to static data and
publications,
bli ti
•Visual and informative to a wide range of audiences, a learning and
thinking tool
•Clearly defined output requiring specific inputs (sub‐models) from
each WP in the BFP,
17. CPWF ANDES BFP PSS : Approach
Like science in general, most classic PSS are poorly used in the policy
Like science in general most classic PSS are poorly used in the policy
framework
Why?
‐ th
they may not address the end users concerns
t dd th d
‐ they are technically difficult to work with
‐ they are insufficiently visual
‐ they have few or poor means of dealing with uncertainty
h h f f d li ih i
‐ they require a lot of data
The CPWF‐ANDES PSS APPROACH
‐ link tightly with institutions and interventions at design stage
‐ Web and geobrowser‐based, simple scenarios (models may be
complex but outputs are simple)
‐ Using visual power of Google Earth etc.
‐ Uncertainty analyses inbuilt – results grey out as uncertainty
increases
‐ Self‐parameterising for any basin by connection to KCL geodata portal
18. An Example : The DserveA model
Testing complete March 2008
Testing complete March 2008
Embedded geobrowser interface, self‐parameterising, ‘global extent, local
scale’, online, always up to date, results shared with stakeholder community
23. Proposed system diagram for Andes BFP PSS....
Water and climate
Climate Scenarios
Indicators of wellbeing and
Climate
poverty
Markets (prices)
Ag. Profit and loss
Water
W t Runoff Population
Environmental flows
balance Water availability
Erosion Water quality
Nature conservation
Nature conservation
Contamination
Farmer decision
making
g
Ag. Productivity Interventions
Crop Land use planning
Land use Ecosystem protection
growth
Dams
Irrigation
Yield Crop type
Water transfer
PES
Livestock Soil management (e.g. fertilisers)
Yield Ag. Profit and loss Slope management (e.g. slope
(grazing)
reduction)