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
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
Outline
1. Ra>onale and objec>ves 2. Methodology 3. Results 4. Summary and perspec>ves
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
THANK YOU
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
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