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Farmers' perceptions of rainfall and agronomic trends in Allada plateau in southern Benin

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Farmers' perceptions of rainfall and agronomic

trends in Allada plateau in southern Benin

Allé Ulrich

1

, Guibert Hervé

2

, Baron Christian

2

, Agbossou K. Euloge

1

, Afouda A. Abel

1

1

Université d’Abomey – Calavi, Bénin;

2

CIRAD, France

Co

ntex

t

Metho

ds

Resul

ts

Climate indices

= z-anomalie year i

= value of the variable year i

= interannual value of historical period = interannual average of historical period

 Humid season  Hot season

 Strong wind’ season  Dry season

 Fresh season

 Weak speed season

Analysis of perceptions of climate change

201 farmers surveyed = 3 random picks x 67 villages selected

according to the size of their agricultural population

The farmers surveyed have relatively long experience, with

an average age of 51 years, and 27 years as farm leader. They

have lived long enough in their village (average 41 years) to

understand climate change.

Crop simulation with SARRA-H

The SARRA-H crop model has been calibrated during

experiments with maize varieties used in the Allada Plateau

region. It was used to define optimal crop calendar windows

for the two rainy seasons*. In this study, the last figure of the

poster shows yield evolution trends during the period

1970-2010 of two rainy seasons obtained from rainfall data of

Niaouli and Ouidah rainfall stations. These trends have been

estimated with the maximum potential yield simulated for

each year by varying sowing dates every 10 days for each of

the two rainy seasons.

poster: Double rainy season associated risk analysis of crop management: maize case study in South

Benin, CSA, 2015, Montpellier France

Inter-annual variability of climatic variables

Rainfall Index (1951-2010): case of Niaouli station;

same trend for Ouidah

Strong inter-annual variability lined with a strong ten-year signal

characterized by 3 sub-periods: P1 = 1951-1970; wet period

P2 = 1971-1990; dry period

P3 = 1991-2010; recovery period

Maximum instantaneous wind speed index

(1961-2010) at Cotonou Airport station

Wind attenuation by 0.031 m/s per year. Break observed at the

beginning of 1970’s for all seasons of the year

Mean instantaneous temperature index (1953-2010) at Cotonou Airport station

Temperature increase by 0.047 °C per year. Break observed at the beginning of 1980’s for all seasons of the year

Maximum potential yield index of maize: case of Niaouli station

Potential yield decrease by 21kg/ha/year during first rainy season (March-July) Yield increase by

15kg/ha/year during second rainy season

(September-November)

Comparison between perceptions and calculated rainfall and agronomic trends

-3 -2 -1 0 1 2 3 i Years

P1 P2 P3 1st(mars-july) rainy season (september-november) 2nd rainy season

Variables Perception P1 to P2 P2 to P3 Perception P1 to P2 P2 to P3

Seasonal rainfall - - + - - +

Mean daily Rainfall + - + + - +

Number of rainy days - - - - - +

Frequency of long dry spell

+ + + + + -

Onset of the rainy season - - + + = +

End of the rainy season + = - + + -

Variables Dry season 1 (january-mars) Rainy season 1 (mars-july) Dry season 2 (july-august) Rainy season 2 (september-november) Temperature Perception + - + - Trends + + + +

Wind speed Perception - + + +

Trends - - - -

Comparison between perceptions and calculated temperature and wind speed trends

Convergence rate between perceptions and observed rainfall trends for the 1st

rainy season:

67% between P1 and P2 period 50% between P2 and P3 period

Convergence rate between perceptions and observed rainfall trends for the 2nd

rainy season:

67% between P1 and P2 period 34% between P2 and P3 period

Observed temperature increases are felt only during dry seasons Farmers often cite wind

increases, whereas observations show the contrary

Discussion

Farmers perceive a steady decline in agricultural yield from the 1970’s whereas crop simulations show two opposite trends between the 1st (decrease) and the 2nd (increase) rainy seasons

Farmers are still affected by the changes that occurred during the 1971-1990 drought period, and do not

perceive the rain recovery period (1990-2000). The increase in agricultural yield during the 2

nd

season is not

perceived by the farmers. This globally pessimistic vision of climate is comparable to that noticed in Burkina

Faso, Uganda and Zimbabwe. The rain recovery years between 1990 and 2000 in the study area is expressed

by rain intensification more than occurrence, particularly for the first rainy season. The opposite yield trends

between the two rainy seasons can be explained by the inverse rain distribution trends between the

seasons*. Based on the assumption that farmer perception is strongly influenced by yield trends, we can

infer that the absence of perception of rain recovery is linked to the opposite (simulated) yield trends for

each of the two rainy seasons.

* Allé C.S.U.Y., Afouda A.A, AGBOSSOU K.E., Guibert H., 2013. Évolution des descripteurs intra-saisonniers des saisons pluvieuses au sud-Bénin entre 1951 et 2010. American Journal of Scientific Research, Vol. 94, pp.55-68 ; ISSN 2301-2005

Rural populations in West Africa depend largely on rainfed agriculture despite

numerous uncertainties on the consequences of global warming on the African

climate. It is thus fundamental to ponder on the adaptation options to climate

change that would reduce the vulnerability of these rural populations. However,

a person’s perception of the risk will have an impact on the strategies that he

will adopt. The present study confronts the perceptions that farmers have of

climate changes to climatic trends that have been observed since 1950.

-4 -3 -2 -1 0 1 2 3 4 1971 1981 1991 2001 i

Years (First long season)

-3 -2 -1 0 1 2 3 i Years -3 -2 -1 0 1 2 3 i Years 2°0'E 2°30'E 6°30‘N 7°0‘N Rain gauge Climate station Surveyed villages Districts 0 8 16 km

Allada plateau in southern Benin, surveyed villages and climate stations

Climate data (Precipitation, temperatures, winds

Climate data

(Precipitation, mesures of adaptation to climate change

Agronomic datas (Potentials yields simulated) Identification of climate change Identification of Farmers’ perceptions to climate change Identification of agronomics trends of climate change

Confrontation

Confrontation

-4 -3 -2 -1 0 1 2 3 4 1971 1981 1991 2001 i

Years (Second short season)

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