Science forum Day 2 - Suan Pheng Kam - Integrated aquculture planning
Andes BFP
1.
2. King’s College, University of London, jerubiano@gmail.comCoCoon Matchmaking Meeting Cali, Colombia - 22-23 September, 2009
3. Outline What is the Andes BFP Work and products Network of partners
4. BFPANDES : Aim The aim of the BFPANDES is “to have the best available science used in the formulation and testing of land and water policy for better livelihoods in the Andes”. BFPANDES : Key issues Institutions. Are the institutions using and sharing the best available information and if not why not? Optimal allocation. What are the biophysical, knowledge and power/equity barriers to optimal least-conflict allocation of water? Sustainability. Which management interventions maximize economic returns (production), alleviate poverty whilst minimizing degradation of water, soil and environment?
5. The Andes ‘basin’ (all basins above 500 masl) and the 13 key sub-basins Context: Transnational, globally important Heterogeneous (hyper humid to hyper arid) Steep slopes, competing demands on land use Environmentally sensitive www.ambiotek.com/aguaandes
6. Silvia Benitez Water Conservation Programme Co-ordinator Carmen Candelo Reina Governance and Livelihoods Program Director Noel Trejos Chief Scientist in Integral Management John Pender Economist Meagan Keefe Agricultural Economist Jairo Valderrama Biologist Edwin Pajares Director of Natural Resource Sharing Program Alonso Moreno Natural Resource Sustainable Management Programme Mario Aquirre Senior Officer Water Program Ernesto Guhl Cam SEI, Cauca University, Valle University, CAN, Proyecto GEF Paramo, CIAT, UNAL, CONDESAN, Kings College London, Universidad Autonoma,deOccidente,
7. Where are the poor? Why they are poor? Which are the related factors? Which are the opportunities?
23. Composed representation of key characteristics of IEI-Col = ∑ (A+B+C+D+E)/5 A = No_Finance_Institutions B = Total_enrolled_Students (2005) C = Health_Investment (2006) D = Potable_Water_Investment (2006) E = Total_displaced_People_received (2001-2007) IEI-Ecu∑ (2(A+B)+C+D+E)/5 A = Iliteracy_rate B = Unsatisfied_Basic_Needs C = Global_malnutrition_in_kids<5 D = %_Poor_below_PovLine E = %_poor_below_extreme_PovLine IEI-Per = ∑ {(A+B+C+D+E+F) – (G+H+I)}/5 A = No_kids_primary_school_completed B = No_kids_primary_school_finished_on_time C = No_educated_kids_between_4&5 D = No_educated_kids_between_12&16 E = No_young_Secondary_School_completed F = No_young_Secondary_School_finished_on_time G = Malnutrition_rate (1999) H = pople_no_electricity I = Adult_Iliteracy_rate (2005) IEI-Bol = ∑ (A+B+C+D+E+F+G+H)/5 A = Education_Units B = No_of_teaching_rooms C = Human_Development_Index (2001) D = Yearly_Average_expenditure E = PerCapita_compsumption_USD-Year (2001) F = Social_Investments_USD (2006) G = Non_Social_Invest_USD (2006) H = No_Finance_Institutions Tough conditions, bigger effort Less difficult * * Standardize for the four countries, main capitals excluded
25. Methods : water availability Whole-Andes analysis of water availability at 1km spatial resolution using the FIESTA delivery model (http://www.ambiotek.com/fiesta) and long term climatologies from WORLDCLIM (1950-) and TRMM (1996-)
26. Results : water availability Total annual rainfall (mm) TRMM> <WorldClim trmm wclim
28. J F M A M J J A S O N D Rainfall (mm/month) - highly variable spatially and seasonally, hyper-humid to hyper-arid
29. How water is used, by whom and where? What are the current and potential benefits out of water?
30. Methods : water productivity Water productivity : often defined as the crop per drop or yield per unit of water use but in BFPANDES defined more broadly as the contribution of water to human wellbeing through production of food, energy and other goods and services Whole-Andes analysis of plant production based on dry matter production calculated from SPOT VGT (1998-2008), masked to exclude trees. Whole Andes analysis of production per unit rainfall (crop per drop) Precise digitisation of all dams in the Andes using Google Earth Dams Geowiki (http://www.kcl.ac.uk/schools/sspp/geography/research/emm/geodata/geowikis.html) Calculation of dam watersheds using HydroSHEDS
32. Dry matter production DMP (in g/ha/yr) <Averaged in 500m elev. bands Averaged by Catchment> Lowest elevations have highest productivity. Colombian and Ecuadorian Andean catchments have Highest productivity along with Eastern foothill catchments in the South
33. <Crop per drop of rainfall (RUE) (g/Ha./mm) [without trees]. Averaged by catchment Crop per drop > (g/Ha./mm) [without trees]. for areas with <500mm rainfall Lowest elevations have greatest crop per drop. Small lowland-dominated Pacific and Eastern foothill catchments have greatest crop per drop
34. DMP (in Dg/ha/day) DMP (in Dg/ha/day) Elevation(m) Rainfall (mm/yr) Crop per drop of rainfall (RUE) (g/Ha./mm) Rainfall (mm/yr) Rainfall (mm/yr)
35. Dams : points in the landscape at which water=productivity Tropics : land areas draining into dams by: Leo Saenz Developed the first georeferenced global database of dams (www.kcl.ac.uk/geodata) There are at least 29,000 large dams between 40N and 40S 57% in Asia, 23% in South America, 12% in Africa, 6.5 % in Asia and the Caribbean, 1.3 % Australia, 0.2 % Middle East. 80% are in the largest countries (China, India, Brazil, South Africa, Zimbabwe, Mexico) 33% of land area between 40S and 40N drains into a dam (capturing some 24% of rainfall and thissurface provides important environmental and ecosystem services to specific companies.
36. Water productivity : dams in the Andes Andes : 174 large dams Area draining into dams : 389,190 km2 (10.5% of land area) At least 80,300Mm3 of water storage capacity At least 20,000 MW HEP capacity Also used for drinking water, irrigation and industrial purposes
37. Environmental services : the role of cloudforests Peru/Bolivia % of water derived from cloud stripping
38. Tracing the impact of protected areas on water Assuming that water originating from protected areas is better than that originating elsewhere: As you travel downstream from the protected areas their contribution to flow diminishes as rivers are swamped with water from non-protected areas % of water originating in a protected area – WDPA 2009 (Colombia) [gl_pc_wc_fin] see www.kcl.ac.uk/geodata
39. Number of urban people drinking water originating in a protected area – WDPA 2009 (Colombia) [gl_sumurbpc] The beneficiaries can easily number millions of people. A strong case for PWS. see www.kcl.ac.uk/geodata
40. What have been made/attempted before? What is feasible to do from now on? With whom, where, how?
46. low evapo-transpiration The pan-tropical average cloud-forest water balance is 452 mm/yr cf 124 mm/yr for the tropics as a whole. This is a function of the climate in which the cloud forest sits not the cloud forest itself and would occur even in the absence of the forest. An ecosystem service: Cloud forests strip passing cloud/fog water very efficiently and this water ends up in the rivers. If the cloud forests are replaced by pasture, this stripping does not occur and the extra water is lost. This service is dependent on the ecosystem as well as the environment. Example of water from montane forests Peru/Bolivia % of water derived from cloud stripping
47. Potential for Aquaculture in the Andes Food Security - Is Aquacultureanalternative in Andean system? How this activity compete with others?
48. Products capacity built in local students, institutions/stakeholders through training, workshops and tools, (b) report, maps and baseline data diagnosing current status of water poverty, water productivity, environmental security and their social and institutional context along with likely future impacts (http://www.bfpandes.org) The AguAAndes Policy Support System – a web based tool for understanding the likely impact of particular scenarios of change and policy options on water and water poverty in any Andean catchment (http://www.policysupport.org/links/aguaandes).
49. The AGUAANDES POLICY SUPPORT SYSTEM SimTerra : the most detailed global databases, tiled + Detailed grid –based process models + Tools to test scenarios and policy options http://www.policysupport.org/links/aguaandes
58. Methods : Institutions Composed representation of a selection of key social, economical and political variables that helps answering where an intervention will face hash conditions, need higher effort and more investment. It also expresses which characteristics can be used as indicators of progress for development and poverty reduction strategies. It is made with the most reliable country data at municipal level. Methods for data processing include PCA, Cluster and Spatial Analyses.
59. COLOMBIA PERU ECUADOR BOLIVIA http://www.latin-focus.com/ http://www.bcb.gov.bo/webdocs/Diciembre2008/estadodeuda2008.pdf