Your SlideShare is downloading. ×
0
Supervisors Prof GPW Jewitt Prof H. Mahoo Integrated Scenario Approach in addressing climate change uncertainties in Wami ...
<ul><li>Introduction </li></ul><ul><li>Goal & Objectives </li></ul><ul><li>Methods </li></ul><ul><li>Data Analysis </li></...
Introduction <ul><li>Climate change is recognized as a risk to peoples’ livelihoods  in Sub-Saharan Africa (IPCC 2007) </l...
Climate Change Projections  <ul><li>By 2080, approx. 1300 million exposed to hunger scenarios </li></ul><ul><li>Africa, wi...
Definition of Scenarios <ul><li>Scenarios  present a series of pictures or images of how the world could look like under d...
Scenario applications: Physical, Social & Economic <ul><li>Frazier et al., 2010: balance creation between community growth...
Justification <ul><li>Climate change related problems are having major impacts on water, land and natural resources; which...
Key Goal of Research Paper <ul><li>Addressing uncertainties in Wami/Ruvu catchment using scenario planning </li></ul>
<ul><li>Assessment of major driving forces </li></ul><ul><li>Scenario planning used to create avenues of change for increa...
Map showing river/lake basins in Tanzania and 7 catchments of Wami/Ruvu Basin   Study Area Dar es salaam Arusha
Study Area description <ul><li>Temperatures in Tanzania range between 24°C - 34°C  </li></ul><ul><li>Mean annual rainfall ...
Target Group <ul><li>6 Villages chosen upstream, downstream & middle stream </li></ul><ul><li>199 Household surveys conduc...
<ul><li>  </li></ul>Participatory Scenario  Procedure Establish scenario team Team proposes goals & outlines Team quantifi...
<ul><li>  </li></ul>
<ul><li>  </li></ul>
<ul><li>  </li></ul>
Data Analysis Tools <ul><li>Statistical Packages Analyses for Quantitative data </li></ul><ul><li>Content Analysis-Qualita...
Outline of Results <ul><li>Trends in water resources, land and farm productivity </li></ul><ul><li>Statistics of relations...
Water resources/Land uses/ Productivity  <ul><li>Decline in water levels in Wami & Ruvu river Systems </li></ul><ul><li>In...
SPSS Analyses   <ul><li>Relationship between climate change & main actors/drivers of change </li></ul><ul><li>Pearson chi-...
Major Driving Actors from Scenario Procedure Driving force Better  Moderate Worse Finances 72 0 12 Drought 42 36 6 Climate...
III. Driving forces highly ranked by scenario participants Driving forces Worse (%) Moderate(%) Better(%) Drought  18 54 0...
Categories of Scenarios  2030 Developed Actors/ Factors Status of Actors/Factors State of stagnation In transition Managin...
<ul><li>Explanation for each of the scenarios storylines developed and what it meant for the participants </li></ul><ul><l...
Sustainable Follow-up Activities  by participants
<ul><li>Major relationships identified between changing land uses, water resources, climate change and agricultural produc...
Acknowledgements <ul><li>Un iversity of KwaZulu-Natal, South Africa-Training </li></ul><ul><li>Sokoine University of Agric...
Thanks!
Upcoming SlideShare
Loading in...5
×

Ojoyi: Integrated scenario approach in addressing climate change uncertainties in Wami Ruvu Catchment, Tanzania

947

Published on

Published in: Technology
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
947
On Slideshare
0
From Embeds
0
Number of Embeds
1
Actions
Shares
0
Downloads
7
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Transcript of "Ojoyi: Integrated scenario approach in addressing climate change uncertainties in Wami Ruvu Catchment, Tanzania"

  1. 1. Supervisors Prof GPW Jewitt Prof H. Mahoo Integrated Scenario Approach in addressing climate change uncertainties in Wami Ruvu Catchment, Tanzania Mercy Mwanikah Ojoyi
  2. 2. <ul><li>Introduction </li></ul><ul><li>Goal & Objectives </li></ul><ul><li>Methods </li></ul><ul><li>Data Analysis </li></ul><ul><li>Results </li></ul><ul><li>Discussions </li></ul><ul><li>Conclusions </li></ul><ul><li>Acknowledgements </li></ul>Outline of Research Paper
  3. 3. Introduction <ul><li>Climate change is recognized as a risk to peoples’ livelihoods in Sub-Saharan Africa (IPCC 2007) </li></ul><ul><li>Sub-Saharan Africa is experiencing significant variability in temperature, rainfall, LGP resulting to frequent floods & droughts (Thornton et al. 2006) </li></ul><ul><li>Some of the sectors affected include: agriculture, water catchments & natural ecosystem functions (NAPA 2007) </li></ul><ul><li>Pressure is exerted on land leading to negative rapid changes on resources thus affecting people’s livelihoods </li></ul>
  4. 4. Climate Change Projections <ul><li>By 2080, approx. 1300 million exposed to hunger scenarios </li></ul><ul><li>Africa, will be heavily compromised by CC Impacts </li></ul><ul><li>Decrease in LGPs </li></ul><ul><li>Reduction in yields by 2020 </li></ul><ul><li>Decrease in crop net revenues by 90% by 2100 </li></ul><ul><li>Impacts of CC will be strongest in North and South for Sub-Saharan Africa </li></ul><ul><li>(Source: IPCC 2007, Parry et al , 2004) </li></ul>
  5. 5. Definition of Scenarios <ul><li>Scenarios present a series of pictures or images of how the world could look like under different conditions </li></ul><ul><li>Source: (Alcamo 2001; Kemp-Benedict, 2004; IPCC 2007) </li></ul>
  6. 6. Scenario applications: Physical, Social & Economic <ul><li>Frazier et al., 2010: balance creation between community growth & resilience to natural hazards </li></ul><ul><li>Enfors et al., 2008: water management strategies in Pangani </li></ul><ul><li>Biggs et al., 2007: platforms for sharing new knowledge </li></ul><ul><li>Davis, 2002 : identification of opportunities & risks </li></ul><ul><li>Peterson et. al., 2003: identify solutions to complex threats </li></ul><ul><li>Alcamo 2001: addressing complex issues </li></ul><ul><li>Wollenberg et al., 2000: decision making for community forests </li></ul>
  7. 7. Justification <ul><li>Climate change related problems are having major impacts on water, land and natural resources; which eventually affects livelihoods. </li></ul><ul><li>However, there exists a huge gap on how to bridge sectoral gaps on local knowledge with current technology into an informed decision with the emerging climatic impacts felt </li></ul><ul><li>How can we strengthen trust into local‘s validity? </li></ul>
  8. 8. Key Goal of Research Paper <ul><li>Addressing uncertainties in Wami/Ruvu catchment using scenario planning </li></ul>
  9. 9. <ul><li>Assessment of major driving forces </li></ul><ul><li>Scenario planning used to create avenues of change for increased productivity through integrated processes </li></ul>Specific Objectives
  10. 10. Map showing river/lake basins in Tanzania and 7 catchments of Wami/Ruvu Basin   Study Area Dar es salaam Arusha
  11. 11. Study Area description <ul><li>Temperatures in Tanzania range between 24°C - 34°C </li></ul><ul><li>Mean annual rainfall varies from below 500 mm to over 2500 mm annually </li></ul><ul><li>The region faces major climatic impacts e.g. frequent floods, increased dry spells, changing rain fall seasons </li></ul><ul><li>This influences length of growing seasons affecting food security that consequently affects people’s livelihoods </li></ul><ul><li>Participatory approach can enhance effective use and management of resources within the catchment, while providing a window for positive change through resilience </li></ul>
  12. 12. Target Group <ul><li>6 Villages chosen upstream, downstream & middle stream </li></ul><ul><li>199 Household surveys conducted for key themes </li></ul><ul><li>84 farmers and their agricultural village experts selected for the scenario procedure </li></ul>
  13. 13. <ul><li>  </li></ul>Participatory Scenario Procedure Establish scenario team Team proposes goals & outlines Team quantifies driving forces Ranks driving forces Revision of outline and storylines Team revises storylines General review of scenarios Team revises scenarios Presentation Repetition of steps Adopted from SCENES (Story and Simulation Approach to scenario development, Alcamo 2001)
  14. 14. <ul><li>  </li></ul>
  15. 15. <ul><li>  </li></ul>
  16. 16. <ul><li>  </li></ul>
  17. 17. Data Analysis Tools <ul><li>Statistical Packages Analyses for Quantitative data </li></ul><ul><li>Content Analysis-Qualitative surveys </li></ul><ul><li>SAS (Story & Simulation Approach-Alcamo 2001 Adopted) </li></ul>
  18. 18. Outline of Results <ul><li>Trends in water resources, land and farm productivity </li></ul><ul><li>Statistics of relationships between climate change and main actors </li></ul><ul><li>Major driving actors from scenario procedures </li></ul><ul><li>Highly ranked actors </li></ul><ul><li>Scenario categories </li></ul><ul><li>Interpretation & applications </li></ul><ul><li>Follow-up activities proposed </li></ul><ul><li>Conclusions </li></ul>
  19. 19. Water resources/Land uses/ Productivity <ul><li>Decline in water levels in Wami & Ruvu river Systems </li></ul><ul><li>Increased dry spells : short lived ‘ masika’ rains; </li></ul><ul><li>fewer or lack of ‘ vuli’ rains </li></ul><ul><li>Population statistics have increased over the years: exerting pressure on water resources </li></ul><ul><li>The frequency of floods and droughts has risen </li></ul><ul><li>Rapid Change in land uses realized </li></ul><ul><li>Decrease in food security for the region due to changes in seasonality (unreliable ‘vuli’ rains, fewer ‘masika’ rains) </li></ul><ul><li>Sources: NAPA 2006, United Republic of Tanzania Government reports, Shongwe et al.,2009, Paavola 2008 </li></ul>
  20. 20. SPSS Analyses <ul><li>Relationship between climate change & main actors/drivers of change </li></ul><ul><li>Pearson chi-square tests: P Value =0.000: shows high level of significance </li></ul><ul><li>Drivers of change: Human activities </li></ul><ul><li> Natural Factors </li></ul><ul><li> Culture & Traditions </li></ul><ul><li> </li></ul>
  21. 21. Major Driving Actors from Scenario Procedure Driving force Better Moderate Worse Finances 72 0 12 Drought 42 36 6 Climate change 78 6 0 Hand hoe use 6 14 66 Agricultural inputs 72 0 1 2 Knowledge and extension services 66 0 18 Changes in planting seasonality 24 6 54 Seed usage and availability 72 0 12 Irrigation 18 0 66
  22. 22. III. Driving forces highly ranked by scenario participants Driving forces Worse (%) Moderate(%) Better(%) Drought 18 54 0 Knowledge and extension services 0 42 36 Agricultural practice 18 48 12 Environmental protection 0 36 42 Financial constraints 6 30 42
  23. 23. Categories of Scenarios 2030 Developed Actors/ Factors Status of Actors/Factors State of stagnation In transition Managing thro’ Experience State of Stability Drought Increase/decrease Increase Increase Decrease Decrease Knowledge and accessibility to technology High level of awareness/low level of awareness Low Low Relatively high Very high Agricultural productivity High/Low High Low High High Environmental Conservation Weak environmental conservation/advanced environmental conservation Weak Weak Advanced Advanced Economics Stable/low low low better Stable
  24. 24. <ul><li>Explanation for each of the scenarios storylines developed and what it meant for the participants </li></ul><ul><li>Relevance of scenarios to climate change resilience for Wami Ruvu Catchment </li></ul><ul><li>Significance of Scenario approach used for the community </li></ul><ul><li>Scenarios and Resilience development </li></ul><ul><li>Applications </li></ul><ul><li>Management of risks and uncertainties </li></ul><ul><li>Future Planning: development, budget planning, resource distribution, e.t.c. </li></ul><ul><li>Development pathways proposed </li></ul>Scenario Interpretation & Significance
  25. 25. Sustainable Follow-up Activities by participants
  26. 26. <ul><li>Major relationships identified between changing land uses, water resources, climate change and agricultural productivity </li></ul><ul><li>Scenario as a tool was very practical in identification of major factors influencing changes in the agro-landscape </li></ul><ul><li>SAS approach used was helpful in integration of stakeholder ideas at all stages of the scenario development process </li></ul><ul><li>The four scenario categories identified uncertainties in each category and helped in developing a development pathway for the future of Wami Ruvu Catchment </li></ul><ul><li>The results of the scenario process provided useful windows for positive change in the catchment </li></ul>Conclusions
  27. 27. Acknowledgements <ul><li>Un iversity of KwaZulu-Natal, South Africa-Training </li></ul><ul><li>Sokoine University of Agriculture, Tanzania-Training </li></ul><ul><li>Wami Ruvu Basin Water Office, Tanzania-Financial </li></ul><ul><li>Collaborative Research for East Africa Territorial Integration; -Research Financial support </li></ul><ul><li>UNESCO-IHE for Study Financial support </li></ul><ul><li>AfricaAdapt- Travel support to the meeting </li></ul>
  28. 28. Thanks!
  1. A particular slide catching your eye?

    Clipping is a handy way to collect important slides you want to go back to later.

×