Presentation by O Ndiaye, at the CCAFS Workshop on Institutions and Policies to Scale out Climate Smart Agriculture held between 2-5 December 2013, in Colombo, Sri Lanka

1. Institutions and Policies for Scaling Out Climate Smart Agriculture “, 2-3 December 2013 Colombo, Sri Lanka

2. MOTIVATIONS
 Short rainy season : 4 months
 Strong climate variability (strongest in the world and at all time scales)
 Huge socio-economical impacts :
 Health : malaria, meningitis
 Agriculture : (90% in Senegal) rain fed and pastoralism
 limited economic resources
Sahel
GHCN Series: 12-20N, 18W-30E

3. Annual cycle of rainfall
(monthly mean 1950-1997)
800
700
600
500
Min
400
Mean
Max
300
200
100
0
May
June
July
Aug
Sept
Oct

4. EXTREME EVENTS
EX : Ouagadougou, Burkina-Faso, 1st of September 2009

5. BURKINA-FASO : OUAGADOUGOU
Courteously by Nakoulma Guillaume

6. BUILDING A TEAM OF STAKEHOLDERS :
MULTI-DISCIPLINARY APPROACH.

National Level :
 National Weather Service (ANACIM)
 Ministry of agriculture (DA)
 Initiative Prospective Agriculture and Rural (IPAR)
 Ecological Monitoring Center (CSE)
 national agricultural research institute (ISRA)
 National department of water resource management (DGPRE)
 ENDA Energie

Local extension services and NGO in Kaffrine :
 agricultural advisers and extension (ANCAR)
 Service Départemental du développement Rural (SDDR),
 NGO : Volunteers from Red Cross (CR), Africare (PRODIAK), World Vision (WV),

Farmers organizations :
 National Farmers (Japandoo, CNCR, FONGS, … ), Individual farmers,
 Organization of women producers (GPF), Peanuts-Seed producers Cooperation (CPSA)

Communication :
 community and rural radio,
 National TV, Private radios and TVs (Sud FM, Wal Fadjri, )

7. Multi modeling approaches
Ocean
Atmosphere
Fcst->SST
AGCM
SEA SURFACE
TEMPERATURE
STATISTICAL
RELATIONSHIP
Model Output Statistics
Using wind
(Statistical Correction)
PREDICTION :
Rainfall

8. Problems of true versus false onset
Same period of onset but followed by dry spell which affect any planning
True Start
False Start
8

9. Building on local knowledge:
High humidity and high temperatures can explain some of
their indicators  “Stronger monsoon”
Doing quite the same thing BUT
Better observing system
More reliable storage capacity (numbers, maps, computers,
…)
« When the wind change direction to fetch the
rain » = Wind change from harmatan to monsoon
during onset

10. DOCUMENTING FARMERS DECISION SYSTEM :
WHAT DECISONS FARMERS are MAKING TO MANAGE
THEIR CROPPING SYSTEM AND WHY ?
•
•
•
•
•
•
•
WHAT
Field preparation :
Selecting the crop :
Planting :
Weeding :
Applying fertilizer,
pesticide, …
Harvesting :
Storage :
WHY
Finance
Technology
Heritage
Sociology
Habits
Beliefs
Environment
Climate/weather

11. Before
Seasonal forecast
 varieties
Onset forecast
 farm preparation
Training workshop
Indigenous knowledge
Discussion and meetings
During the Crop season
Nowcasting
 flooding saving life (thunder)
Daily forecast
 use of fertilizer / pesticide
Ten-day forecast
 weeding, field work
Maturity/end
Ten-day forecast
 optimum
harvesting period
Field Visits
10 days experts meeting :
monitoring the season
Evaluation
Lessons drawn

12. team work : farmers, climatologist, World Vision, Agriculture expert, sociologist

13. TALKING THE SAME LANGUAGE : “WHAT 1
MM OF RAIN MEANS”

14. Seed growers
Local working Group
(Customize Climate information)
Farmers
Rural radio
Extensions
services
Text messaging
Agriculture
Pest Disease
Control
Forestry
Social gatherings
Bulletin
Community
Rural radio
Local
authority
Nowcasting
Local Pluri-disciplinary
Working Group
Livestock
Weather forecast
Climate information
Seasonal forecast

16. WHAT DID WE LEARN
First step : building trust (social dimension : using indigeneous
knowledge)
Giving not only useful BUT useable forecast
(tailored for specific user needs : local language)
Long term and multi-stakeholders partnership (each
institution has part of the solution for food security)
Communicating the forecast in easy to use term
(easy to understand, can translate into action and to be evaluated)
Dynamic process : need to better understand
farmers decision system (farmers active participation : rain guage,
indigenous knowledge …)

17. CONCLUSION OR CHALLENGES
 Spatial scale of the forecast : down to farm
 Up-scaling other sites (government representative demand)
 Alternative :
 dry (bad news !) =>give them hope (climate insurance, alternative)
 wet but there is no extra resources : so what ? (engage
seed/fertilizer producers, bank (CMS), corporation, … )
 High rate of adoption by farmers and local administration
(official )
SOLUTION :  whole package with other partners (WFP)
① Climate services (forecast + technology => advices)
② Climate insurance (dry/bad forecast + courage)
③ Access to finance, resources (wet//good forecast)

19. PRELIMINARY VERIFICATION 2012
(by farmers and extensions)
Extra seasonal rainfall :
Early warning issued on the May 16th for rain on the next 8 days
It did rain on the 21st May 2012 (save a lot on crop left outside)
True Onset :
Forecast made on 9/10 May updated 10 June : 18 to 24 June 2012
First significant rainfall : 19 June (all kaffrine) (03Jun)
Seasonal forecast :
Forecast (9-10 May) : Normal to below normal (500 – 900 mm)
Recorded rain in kaffrine : 576-1075 mm (Normal to above normal)
Early Warning System : ( 10 day, 1-2 day, 30mm to 3 hour)
21 forecasts (all time scales) only 4 went way off
problem of spatial coverage of the forecast kaffrine is too wide !