3rd Africa Rice Congress Theme 2: Rice Intensification and diversification Mini-symposium: determinants of agricultural productivity in Africa's rice based-systems Author: Balde and Muller

1. Climate Change in the Senegal
River Valley and implications for
rice cropping systems
BALDE A.B. (AfricaRice); MULLER B. (Cirad/AfricaRice);
VAN Oort P.(AfricaRice); NDIAYE O. (ANACIM); STUERZ S. (Hohenheim
University); SOW A. (AfricaRice); DIACK B.S. (SAED);
DINGKUHN M. (Cirad/IRRI)
Study funded by ANR ESCAPE and CCAFS

2. Introduction (1)
• Irrigated rice is
important crop in Sahel
• More than 70 000 ha in
Senegal River valley
• Rice double cropping
possible
Sterile spikelets
Climate and sowings
• Cold (November-March) and hot (April-October) extreme temperatures
are risks -> sterility
• Recommended sowing periods were elaborated in 90s (Dingkhun and al.,
1995) based on 1950-80 climate data and RIDEV1 model
• 15 Feb - 15 March for Dry Season
• 01 July – 15 August for Wet Season

3. Introduction (2)
RIDEV1 1950-80 sterility analysis
(Dingkhun, 1995)
BUT farmers say …
% Sterility
Saint-Louis
Sterility
(cold)
Rosso
« sowing date are more and more out of the
recommended sowing windows, and that
works : even sowing in September farmers
get good yields! »
« It looks like the climate have changed »
Questions :
Did farmer’s practices change (% of farmers)?
Why ? Due to climate ? others constraints ?
Matam
Did climate change ? How ?
What can we learn from those evolutions ?
Tillaberi
Sowing
date
1 year
Sterility
(heat)
Are recommended sowing periods still valid ?
How to protect farmers against climatic risks ?

4. Objectives
Final objective is to define the most adapted sowing windows for recommended irrigated
rice varieties of Senegal River Valley (and Niger River Valley in Mali) in order to reduce
climate risks and then maximize production, and to assess the “residual” risks related to
those sowing windows ;
- for “present” climate
- also for “future” one using data coming from climatic scenario
Second main objective is to assess if cropping systems have changed in the last years and if it
is the case, to understand why ?
Third main objective is to have a crop model (or several) able to correctly simulate
developments and yields of recommended irrigated rice varieties in Senegal River Valley
(and Niger River Valley in Mali)
Fourth: capacity building for production and management of climatic risks
Fifth : to elaborate insurance systems based on scientific results (risks analysis)

5. Material and Methods
Focus-groups and surveys:
to understand possible changes in farmer’s practices and their
constraints, and their eventual evolutions during the last years
to understand farmers climate perception
Climate (temperature) analysis :
Podor (16.35N/15.02W) temperature data from 1950 to 2011.
Modeling analysis : RIDEV V2
to assess through RIDEV2 crop model simulations the impacts of climate
since 30 years for different sowing dates
-> Case of Sahel 108 cultivar ; Podor weather data (Tmin, Tmax, Mean Hum,
and Rg) from 1950 to 2010
Sowing every 15 days
RIDEV2 : to simulate Phenology and Heat & cold sterility
Calibration/Validation
Simulations

6. Results (1) : from focus and surveys
 Due to several constraints (delay for inputs, credit, machines) many farmers are
sowing later than before, i.e. outside the recommended sowing windows : this is
particularly the case for wet season cropping (July/August -> November)
 All interwied farmers mentioned difficulty and delay to get inputs, credits and
machines as their main constraint
 Some farmers having sowed late (September) obtained good results
 Many farmers are now sowing regularly at the beginning of September and have
good yields since few years.
 Exception 2011: “bad yields” (farmers words) for those late sowing
 “Since 2000 yields are decreasing” ; except in the dry season of 2008 with 7t/ha
(exceptional year)
 “Dry season yields are better than wet season ones” (for 90% of farmers)

7. Results (2) : from focus and surveys
 Farmers notice climate “changes”: on average 94.5% and 72% of interviewed
farmers say respectively that rainfall and temperature pattern have changed.
 “the cold period shifted (delayed) by about 1 month” : October/NovemberFebruary/March -> November-March/April
 “the cold comes latter”, “excepted in 2011 it came as before”
 “the February-April period is very hieratic, with small cold and hot periods”
 “rainfall increased in the last 5-7 years, except in 2011”
(Podor rainfall data shown an annual average of 175, 200 and 270 mm respectively
between 1980-1989, 1990-1999 and 2000-2010)

8. Results (3) : temperatures analysis
42
41
40
39
38
37
36
35
34
33
32
31
30
1950-1980
1970-1990
Month TMAX
+1°C to +3°C / reference period
1950-1980
but quite similar than 1990-2000
1
2
3
4
5
6
26
24
22
20
18
16
14
12
10
8
6
4
2
0
7
8
9
10
1990-2000
2001-2011
11
1950-1980
1970-1990
1990-2000
2001-2011
2
3
4
5
6
7
8
9
10
11
12
1950-1980
1970-1990
Month TMIN
+1°C to +2°C / reference period
1950-1980
but quite similar than 1990-2000
1
12
Days TMAX>40°C more than
reference period 1950-1980
but quite similar than 1990-2000
1
26
25
24
23
22
21
20
19
18
17
16
15
14
2
12
11
10
9
8
7
6
5
4
3
2
1
0
3
4
5
6
7
8
9
10
11
1990-2000
2001-2011
12
Days TMIN<14°C less than
reference period 1950-1980
but quite similar than 1990-2000
1950-1980
1970-1990
1990-2000
2001-2011
1
2
3
4
5
6
7
8
9
10
11
12

9. Results (4) : 2011 temp. analysis
35
34
33
32
31
30
29
28
27
26
25
24
23
22
TMEAN
2011
2006-10
2000-10
1990-99
1
4
7
10
13
16
19
22
25
28
31
26
25
24
23
22
21
20
19
18
17
16
15
14
TMIN
2011
2006-10
2000-10
1990-99
34
1
4
7
10
13
16
19
22
25
28
31
34
Oct.-Nov. 2011 is rather hot ! Only end of December is colder than other years .. So ..???
TMIN
<18°C
11
10
9
TMIN
<14°C
6
5
8
7
2011
6
2006-10
5
4
2011
2006-10
3
2000-10
2000-10
4
1990-99
3
2
2
1990-99
1
1
0
0
1
4
7
10
13
16
19
22
25
28
31
34
0
3
6
9
12
15
18
21
24
27
30
33
36

10. Results (5) : model validation (Ndiaye, Fanaye)
(b)
Flowering
140
120
100
80
60
Maturity
60
Model parameters
(Ndiaye site, MD):
Tbase=10.6°C
Topt=31.7°C
SumBVP=748
SumRPR=400
SumMATU=409
CritsterCold1=10.6°C
CritsterCold2=18.7°C
CritsterHeat=33°C
80
Simulated
160
y = 1.02x + 1.087
R² 1200.845 140
=
100
110
60
(c)
Sterility is underestimated
by the model
(with present calibration;
can be improved)
80
100
Sterility
100
90
80
70
60
50
40
30
20
10
0
0
y = 1.047x - 1.289
R² =140
0.823 160
120
60
Observed
Simulated
Simulated
(a)
20
40
Observed
y = 0.572x - 1.219
R² = 0.473
60
Observed
80
100

11. Results (6) : simulated cycles and sterilities
Crop duration decreased (- 5-10 days)
but variable through sowing dates
(from 90 to 137 DAS)
Compared to 1950-1980, cycles are shorter in
recent years
For both Wet and Dry Season (WS, DS) sterility
(out of recomandated calendar) globally
decreased
However differences are small
For 15 September small sowing sterility
difference exists
It is still very dangerous to sow after this date

12. Results (7) : Focus on 15 Sept sowing date
(Simulations from 1980 to 2010)
The evolution of sterility (for 15 Sept sowing date) is going down through years
Same with DAS to Flowering
In the past flowering period met low temperature that make high Stercold2

13. Conclusions (1)
Present climate is different than during the reference period (1950-80)
used for elaboration of sowing recommendations with RIDEV1 :
temperatures clearly increased ; less cold days
But it seems that the climate (at least Temp) is already “different” since
20 years .. not only from 2000 as farmers say (“it recently changed”)
And up to now we don’t understand the specificity of 2011 ?
We need more data to check climate evolution for all SRV (we are
waiting for St Louis, Matam, Bakel data)
Sterility is underestimated by the model and quite low
Due to temperatures increase cycles are shorter (- 5-10 days) now
(no “genetic change” in Sahel 108)

14. Conclusions (2)
Cold stress risks are lower, particularly for late 15 September
sowing : it seems possible to sow up to this date
but not recommended to sow after this date
Risks due to high temperatures might be higher : must be analyzed
with more accuracy
We need to check more the model functioning
(we have several fields and experiments data)
We need to go back to farmers with simulations results in order to
improve our understanding
If climate seems to be more favorable, why farmers say yields are
lower ? …

15. Conclusions (3)
Still many work to do to clearly understand the evolution of things
Once we will be sure that our model functions well, we will see
how to elaborate new sowing recommendations and how to
develop temperatures based indicators for insurance

16. Thank you for your
attention!
Alpha Bocar BALDE
a.balde@cgiar.org