identifying optimized use of fresh and saline water for irrigation on salt affected rice systems in...
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By A.M. Radanileson, O. Angeles, T. Li, A.K. Rahman, D. Gaydon Revitalizing the Ganges Coastal Zone Conference 21-23 October 2014, Dhaka, Bangladesh http://waterandfood.org/ganges-conference/TRANSCRIPT
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Iden%fying op%mized use of fresh and saline water for irriga%on on salt affected rice systems in Bangladesh using ORYZA ver.3
Radanielson A.M. , O. Angeles, T.Li, A.K. Rahman, D. Gaydon.
Revitalizing the Ganges coastal zones conference Dhaka Oct 21-‐23, 2014
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Outline
1. Ra>onale and objec>ves 2. Methodology 3. Results 4. Summary and perspec>ves
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Rice produc%on challenges in Bangladesh
• Rice demand brought by increasing popula>on: – By 2030, 40.0 M tons of rice for about 190 M popula>on
• Limited resources : land, water, labour • Environmental constraints aggravated by climate change – Soil salinity – Sea level rise – Extreme weather events
Farmers livelihood
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Opportuni%es to improve rice produc%on in salt-‐affected areas
• Over 30% of cropped land is saline
• Saline-‐tolerant rice varie>es are available
• Need a suitable management for produc>ve and sustainable cropping systems
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Objec%ves
1. Evaluate irriga>on water management op>ons to reduce salinity-‐stress on rice produc>on – Calibra>on and valida>on of a modified version of the rice model ORYZA ver.3
– Scenario analyses to evaluate performance of management strategies using different sowing dates, adapted virtual varie>es and the mixing fresh-‐saline water as an irriga>on approach targeted to op>mize yield and water produc>vity
2. Iden>fy poten>al adapta>ve strategies for salt-‐affected rice systems
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Input: Weather Soil Crop management Cul>var parameters
Output: Crop phenology LA index Crop N status Biomass produc>on Crop Yield
Phenology Assimila%on Biomass produc%on
Biomass par%%oning Water balance N balance
Dynamics of salinity in soil
The model ORYZA and its improvement
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Iden>fica>on of suitable irriga>on strategy to manage saline and fresh water availability for increasing salt affected areas produc>vity
Site: Satkhira BARI experiment sta>on Variety: BR47
Boro Rice: 2013 and 2014
Irriga>on water: 1. Freshwater 2. Mixture 1:1 ra>o of fresh and saline
water (AFS1:1) 3. Mixture of 2:1 of fresh and saline
water (AFS2:1) 4. Saline water
Experiments for model calibra%on and valida%on
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Satkhira 2013 Satkhira 2014
Variability of soil salinity with irriga%on water
• Salinity range: 1-‐ 16 dS m-‐1
• Con>nuous increase of soil salinity over the crop growth
0
4
8
12
16
0 50 100 150
Soil salin
ity at 1
5 cm
dep
th(dS m
-‐1)
Days after sowing
2:1 ratio
1:1 ratio
Saline water
Fresh water0
4
8
12
16
0 50 100 150
Soil salin
ity at 1
5 cm
dep
th(dS m
-‐1)
Days after sowing
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Iden>fica>on of suitable irriga>on strategy to manage saline and fresh water availability for increasing salt affected areas produc>vity
Site: Infanta Laguna (Farmer’s field) Variety: BR47 Dry season: 2013 and 2014 Irriga>on water: 1. Freshwater 2. Alternate fresh and saline water (AFS1) 3. Alternate fresh and saline water (AFS2) 4. Saline water
Experiments for model calibra%on and valida%on
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Variability of soil salinity with irriga%on water
Infanta 2013 Infanta 2014
• Salinity range: 1-‐ 15 dS m-‐1
• The soil salinity of alternate fresh-‐saline water irriga>on with 2-‐week interval was not significantly different from fresh water irrigated treatment.
0
5
10
15
50 80 110 140
Soil salin
ity at 1
5 cm
dep
th
(dS m
-‐1)
Days after sowing
0
5
10
15
30 60 90 120
Soil salinity
at 1
5 cm
dep
th
(dS m
-‐1)
Days after sowing
Fresh Water
Saline Water
AFS2
AFS1
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Oryza ver.3’s ability to simulate BRRI Dhan 47 performance
Yield 7.5t/ha RMSEn: 20.19
Yield 5-‐6t/ha RMSEn : 13.10
0
3000
6000
9000
12000
15000
0 30 60 90 120 150
Dry biom
ass (kg/ha
)
Day after sowing
0
3000
6000
9000
12000
15000
0 50 100 150
Dry biom
ass (kg/ha
)
Day after sowing
0
3000
6000
9000
12000
15000
0 50 100 150
Dry biom
ass (kg/ha
)
Day after sowing
0
3000
6000
9000
12000
15000
0 50 100 150
Dry biom
ass (kg/ha
)
Day after sowing
Simulated above ground biomass Observed above gorund biomass
Simulated yield Observed grain yield
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Model ability in salinity effects simula%on on BR47 yield under Satkhira condi%ons
0
2
4
6
8
10
0 2 4 6 8 10
Sim
ulat
ed (t
/ha)
Measured (t/ha)
Rice Yields
Y = 0.77 x + 220.4 r2 0.61 P(t) 0.18 EF 0.97 RMSE 344 RMSE n 9.8% n = 63
A model reproduces experimental data best when α is 1, β is 0, R2 is 1, P(t) is larger than 0.05 (indica>ng observed and simulated data are the same at the 95% confidence level), and the RMSE is similar to standard devia>on of experimental measurements.
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Scenario simula%ons
Factors:
• Satkhira weather data over 15 years: 2000 -‐2014 • Virtual varie>es: BR47 with long, medium, and short crop dura>on
• Sowing dates: weekly from Dec 1 to Feb 10 • Irriga>on water management
– Fresh water – Saline water – 1: 1 ra>o fresh to saline water – 2: 1 ra>o fresh to saline water
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Variability of yields and water produc%vity among varie%es
0
0.05
0.1
0.15
0.2
0.25
Tran
spire
d water produ
ctivity
(m
m/kg)
Variety X water irrigation management
0
1000
2000
3000
4000
5000
Grain yield (t/ha)
Varieties X Irrigation water management
• Higher yield was observed for long dura>on variety • Higher water produc>vity was observed for medium dura>on variety
• Op>mized produc>vity for medium variety under mixture 2 :1 ra>o
SW FW 2W 1W SHORT
SW FW 2W 1W LONG
SW FW 2W 1W MEDIUM
SW FW 2W 1W SHORT
SW FW 2W 1W LONG
SW FW 2W 1W MEDIUM
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Trends of yield and water produc%vity over sowing dates
0.1
0.12
0.14
0.16
0.18
0.2
5 12 19 26 33 40 336 343 350 357 364
Tran
spire
d water produ
ctivity
(mm/kg)
Date of sowing (Julian day)
2000
2100
2200
2300
2400
2500
5 12 19 26 33 40 336 343 350 357 364
Grain yield (kg/ha)
Date of sowing (Julian day)
• Windows of cropping calendar tested was op>mized for a yield mean
• Efficient water use and higher yield were observed for third week of December and second week of January
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Summary and perspec%ves • ORYZA ver.3 has good ability to simulate rice produc>on under saline
condi>ons • The model is now calibrated with BRRI Dhan 47 • Alterna>ng saline water with freshwater in 2-‐week interval or mixing 2
parts of freshwater with 1 part of saline water are poten>al irriga>on approaches in rice cul>va>on along saline areas where freshwater is limited
• Op>mized water produc>vity and higher yield were enhanced using medium and long dura>on varie>es established at around 3rd week of December (357) and 1st week of January (12) under Satkhira, Bangladesh condi>ons
• Matching the assessment with current farmers’ prac>ces will generate useful informa>on on prac>cal strategies for op>miza>on
• Mapping of sites with available and limited freshwater source will be useful in es>ma>ng yield poten>al and targe>ng appropriate technologies
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THANK YOU
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Variability of simulated yields
Factors Df SS MS F value Pr(>F)
Year 13 1874169209 144166862 115.6612 <2e-16 *** Date of sowing 10 8257068 825707 0.6624 0.7603
Treatment 3 2697853515 899284505 721.472 <2e-16 *** Variety 2 947924737 473962368 380.2474 <2e-16 ***
Error 5297 6602487508 1246458
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0
5
10
15
20
25
01-‐Jan-‐13 11-‐Apr-‐13 20-‐Jul-‐13 28-‐Oct-‐13 05-‐Feb-‐14 16-‐May-‐14
Underground water
River water
Ponded water
Soil at 15 cm depth
Salinity build-‐up in Satkhira site