Climate change impact analysis using bias-corrected multiple global climate models on rice and wheat yield
Rice and wheat, two staple food grain crops, play a key role in farmers' income and food security. The response of these crops towards climate change is heterogeneous and uncertain. Therefore, it becomes essential to analyse the impact of climate change on these crops. An investigation was perf...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IWA Publishing
2021-06-01
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| Series: | Journal of Water and Climate Change |
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| Online Access: | http://jwcc.iwaponline.com/content/12/4/1282 |
| _version_ | 1818858590791794688 |
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| author | Madhuri Dubey Ashok Mishra Rajendra Singh |
| author_facet | Madhuri Dubey Ashok Mishra Rajendra Singh |
| author_sort | Madhuri Dubey |
| collection | DOAJ |
| description | Rice and wheat, two staple food grain crops, play a key role in farmers' income and food security. The response of these crops towards climate change is heterogeneous and uncertain. Therefore, it becomes essential to analyse the impact of climate change on these crops. An investigation was performed to analyse the impact of climate change on rice and wheat yield and to quantify the uncertainties in the yield predictions in West Bengal, India. The climatic projections from eight global climate models were used to simulate the rice and wheat yields in all districts of West Bengal. A quantile mapping method was used to correct systematic biases of daily rainfall, solar radiation and temperature. The corrected data were then used for driving crop environment and resource synthesis models for yield simulations. Results reveal that rice yield is expected to reduce by 7–9% in the 2020s, 8–14% in the 2050s and 8–15% in the 2080s, whereas wheat yield is expected to go down by 18–20% in the 2020s, 20–28% in the 2050s and 18–33% in the 2080s. These reductions signify that rice and wheat yield is more likely to decline under the future climate change condition, which may affect the regional food sustainability. HIGHLIGHTS
GCMs are used to assess the effect of climate change on rice and wheat yield.;
Quantile mapping method is used to correct bias of GCMs outputs.;
DSSAT-CERES for rice and wheat is used for yield prediction.;
Rice and wheat yield is expected to reduce, respectively, up to 15 and 33% by the end of the 21st century in West Bengal.;
Study prompts to develop adaptation for regional food sustainability.; |
| first_indexed | 2024-12-19T08:58:43Z |
| format | Article |
| id | doaj.art-47e9729cd194441fa101651a1d1ded23 |
| institution | Directory Open Access Journal |
| issn | 2040-2244 2408-9354 |
| language | English |
| last_indexed | 2024-12-19T08:58:43Z |
| publishDate | 2021-06-01 |
| publisher | IWA Publishing |
| record_format | Article |
| series | Journal of Water and Climate Change |
| spelling | doaj.art-47e9729cd194441fa101651a1d1ded232022-12-21T20:28:32ZengIWA PublishingJournal of Water and Climate Change2040-22442408-93542021-06-011241282129610.2166/wcc.2020.191191Climate change impact analysis using bias-corrected multiple global climate models on rice and wheat yieldMadhuri Dubey0Ashok Mishra1Rajendra Singh2 Department of Agricultural and Food Engineering, IIT, Kharagpur 721302, India Department of Agricultural and Food Engineering, IIT, Kharagpur 721302, India Department of Agricultural and Food Engineering, IIT, Kharagpur 721302, India Rice and wheat, two staple food grain crops, play a key role in farmers' income and food security. The response of these crops towards climate change is heterogeneous and uncertain. Therefore, it becomes essential to analyse the impact of climate change on these crops. An investigation was performed to analyse the impact of climate change on rice and wheat yield and to quantify the uncertainties in the yield predictions in West Bengal, India. The climatic projections from eight global climate models were used to simulate the rice and wheat yields in all districts of West Bengal. A quantile mapping method was used to correct systematic biases of daily rainfall, solar radiation and temperature. The corrected data were then used for driving crop environment and resource synthesis models for yield simulations. Results reveal that rice yield is expected to reduce by 7–9% in the 2020s, 8–14% in the 2050s and 8–15% in the 2080s, whereas wheat yield is expected to go down by 18–20% in the 2020s, 20–28% in the 2050s and 18–33% in the 2080s. These reductions signify that rice and wheat yield is more likely to decline under the future climate change condition, which may affect the regional food sustainability. HIGHLIGHTS GCMs are used to assess the effect of climate change on rice and wheat yield.; Quantile mapping method is used to correct bias of GCMs outputs.; DSSAT-CERES for rice and wheat is used for yield prediction.; Rice and wheat yield is expected to reduce, respectively, up to 15 and 33% by the end of the 21st century in West Bengal.; Study prompts to develop adaptation for regional food sustainability.;http://jwcc.iwaponline.com/content/12/4/1282ceresglobal climate modelquantile mapping method |
| spellingShingle | Madhuri Dubey Ashok Mishra Rajendra Singh Climate change impact analysis using bias-corrected multiple global climate models on rice and wheat yield Journal of Water and Climate Change ceres global climate model quantile mapping method |
| title | Climate change impact analysis using bias-corrected multiple global climate models on rice and wheat yield |
| title_full | Climate change impact analysis using bias-corrected multiple global climate models on rice and wheat yield |
| title_fullStr | Climate change impact analysis using bias-corrected multiple global climate models on rice and wheat yield |
| title_full_unstemmed | Climate change impact analysis using bias-corrected multiple global climate models on rice and wheat yield |
| title_short | Climate change impact analysis using bias-corrected multiple global climate models on rice and wheat yield |
| title_sort | climate change impact analysis using bias corrected multiple global climate models on rice and wheat yield |
| topic | ceres global climate model quantile mapping method |
| url | http://jwcc.iwaponline.com/content/12/4/1282 |
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