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Crop Insurance as a Risk Management Strategy in Bangladesh

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Table 5.2: Climate Change Scenarios for <strong>Bangladesh</strong><br />

Year Sea Level<br />

Rise<br />

(cm)<br />

Temperature Incre<strong>as</strong>e<br />

( 0 C)<br />

64<br />

Precipitation<br />

fluctuation compared<br />

to 1990 (%)<br />

B<strong>as</strong>ed on 2 nd IPCC projections (WB 2000)<br />

2030 30 +0.7 <strong>in</strong> monsoon; -3 <strong>in</strong> w<strong>in</strong>ter;<br />

+1.13 <strong>in</strong> w<strong>in</strong>ter +11 <strong>in</strong> monsoon<br />

2050 50 +1.11 <strong>in</strong> monsoon; -37 <strong>in</strong> w<strong>in</strong>ter;<br />

+1.8 <strong>in</strong> w<strong>in</strong>ter +28 <strong>in</strong> monsoon<br />

B<strong>as</strong>ed on 2 nd IPCC projections ( Agrawala et al. 2003)<br />

2030 +0.8 <strong>in</strong> monsoon; -1.2 <strong>in</strong> w<strong>in</strong>ter;<br />

+1.1 <strong>in</strong> w<strong>in</strong>ter +4.7 <strong>in</strong> monsoon<br />

2050 +1.1 <strong>in</strong> monsoon; -1.7 <strong>in</strong> w<strong>in</strong>ter;<br />

+1.6 <strong>in</strong> w<strong>in</strong>ter +11.8 <strong>in</strong> monsoon<br />

2100 +1.9 <strong>in</strong> monsoon; -3.0 <strong>in</strong> w<strong>in</strong>ter;<br />

+2.7 <strong>in</strong> w<strong>in</strong>ter +11.8 <strong>in</strong> monsoon<br />

Source: Where Land Meets the Sea – A profile of the Co<strong>as</strong>tal Zone of <strong>Bangladesh</strong>, 2004<br />

5.2.2 Effect on the Agriculture Sector: Direct effect<br />

Changes <strong>in</strong><br />

evaporation<br />

+0.9 <strong>in</strong> w<strong>in</strong>ter;<br />

+15.8 <strong>in</strong> monsoon<br />

0 <strong>in</strong> w<strong>in</strong>ter;<br />

+16.7 <strong>in</strong> monsoon<br />

Agriculture is considered <strong>as</strong> one of the major vulnerabilities that the country might face due<br />

to climate change. Yet IPCC (Lal et al., 2001) and other studies (e.g., Karim et al., 1996)<br />

show crop yields potentially <strong>in</strong>cre<strong>as</strong><strong>in</strong>g at a few degrees Celsius <strong>in</strong>cre<strong>as</strong>e <strong>in</strong> temperature.<br />

Beyond that, particularly <strong>as</strong> the CO2 fertilization saturates, yields could decre<strong>as</strong>e. For<br />

example, Karim et al. (1996) estimated that rice yields would <strong>in</strong>cre<strong>as</strong>e for about a 1.5 0 C<br />

<strong>in</strong>cre<strong>as</strong>e comb<strong>in</strong>ed with higher CO2 levels.<br />

Table 5.3: Change <strong>in</strong> rice yields <strong>in</strong> Asia under <strong>in</strong>crements of temperature and CO2 level<br />

Model used and<br />

ambient CO2<br />

levels<br />

% change <strong>in</strong> mean potential rice yield <strong>in</strong> Asia result<strong>in</strong>g from surface air<br />

temperature <strong>in</strong>crement of<br />

0 0 C +1 0 C +2 0 C +4 0 C<br />

ORYZA1 Model<br />

340 ppm 0.00 -7.25 -14.18 -31.00<br />

1.5 X CO2 23.31 12.29 5.60 -15.66<br />

2 X CO2 36.39 26.42 16.76 -6.99<br />

SIMRIW Model<br />

340 ppm 0.00 -4.58 -9.81 -26.15<br />

1.5 X CO2 12.99 7.81 1.89 -16.58<br />

2 X CO2 23.92 18.23 11.74 -8.54<br />

Source: Matthews et al. 1995<br />

Results reported by Karim et al. (undated) for <strong>Bangladesh</strong>’s Country Study are consistent <strong>as</strong><br />

shown <strong>in</strong> Tables 3. They estimated that rice yields would decl<strong>in</strong>e under two GCM scenarios<br />

(GFDL and CCCM). They estimated <strong>in</strong>cre<strong>as</strong>ed yields for higher CO2 alone (580 and 660<br />

ppmv), higher CO2 comb<strong>in</strong>ed with a 2 0 C <strong>in</strong>cre<strong>as</strong>e, positive and negative changes <strong>in</strong> yields for<br />

a 580 ppmv of CO2 comb<strong>in</strong>ed with a 4°C <strong>in</strong>cre<strong>as</strong>e, and mostly <strong>in</strong>cre<strong>as</strong>ed yields for a 660

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