Mitigating climate change impact on soybean productivity in India: a simulation study
Field experiments with soybean were conducted over a period of 1990–1998 in diverse Indian locations ranging in latitude, longitude, and elevation. These locations provided a wide range of environments for testing and validation of the crop growth (CROPGRO) model considered in this study with observ...
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Veröffentlicht in: | Agricultural and forest meteorology 2004-01, Vol.121 (1), p.113-125 |
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creator | Mall, R.K Lal, M Bhatia, V.S Rathore, L.S Singh, Ranjeet |
description | Field experiments with soybean were conducted over a period of 1990–1998 in diverse Indian locations ranging in latitude, longitude, and elevation. These locations provided a wide range of environments for testing and validation of the crop growth (CROPGRO) model considered in this study with observed changes in soils, rainfall and other weather parameters. Model predicted satisfactorily the trends of days to flowering, maturity and grain yields. The deviations of simulated results were within ±15% of the measurements.
Validated CROPGRO model has been used to simulate the impact of climate change on soybean production in India. The projected scenarios for the Indian subcontinent as inferred from three state-of-the-art global climate models (GCMs) have been used in the present study. There was a decrease (ranging between about 10 and 20%) in soybean yield in all the three future scenarios when the effect of rise in surface air temperature at the time of the doubling of CO
2 concentration was considered. The results obtained on the mitigatory option for reducing the negative impacts of temperature increases indicate that delaying the sowing dates would be favorable for increased soybean yields at all the locations in India. Sowing in the second season would also be able to mitigate the detrimental effects of future increases in surface temperature due to global warming at some locations. |
doi_str_mv | 10.1016/S0168-1923(03)00157-6 |
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Validated CROPGRO model has been used to simulate the impact of climate change on soybean production in India. The projected scenarios for the Indian subcontinent as inferred from three state-of-the-art global climate models (GCMs) have been used in the present study. There was a decrease (ranging between about 10 and 20%) in soybean yield in all the three future scenarios when the effect of rise in surface air temperature at the time of the doubling of CO
2 concentration was considered. The results obtained on the mitigatory option for reducing the negative impacts of temperature increases indicate that delaying the sowing dates would be favorable for increased soybean yields at all the locations in India. Sowing in the second season would also be able to mitigate the detrimental effects of future increases in surface temperature due to global warming at some locations.</description><identifier>ISSN: 0168-1923</identifier><identifier>EISSN: 1873-2240</identifier><identifier>DOI: 10.1016/S0168-1923(03)00157-6</identifier><identifier>CODEN: AFMEEB</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Agricultural and forest climatology and meteorology. Irrigation. Drainage ; Agronomy. Soil science and plant productions ; Biological and medical sciences ; Climate change ; Crop simulation model ; Fundamental and applied biological sciences. Psychology ; General agronomy. Plant production ; Global climate models ; Impact mitigation ; Sowing dates ; Soybean</subject><ispartof>Agricultural and forest meteorology, 2004-01, Vol.121 (1), p.113-125</ispartof><rights>2003 Elsevier B.V.</rights><rights>2004 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c517t-bb886d479fb6fe8cf5341b5ad9bba1cd9fc956de205627b89dfce2c680053b953</citedby><cites>FETCH-LOGICAL-c517t-bb886d479fb6fe8cf5341b5ad9bba1cd9fc956de205627b89dfce2c680053b953</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0168192303001576$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=15369994$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Mall, R.K</creatorcontrib><creatorcontrib>Lal, M</creatorcontrib><creatorcontrib>Bhatia, V.S</creatorcontrib><creatorcontrib>Rathore, L.S</creatorcontrib><creatorcontrib>Singh, Ranjeet</creatorcontrib><title>Mitigating climate change impact on soybean productivity in India: a simulation study</title><title>Agricultural and forest meteorology</title><description>Field experiments with soybean were conducted over a period of 1990–1998 in diverse Indian locations ranging in latitude, longitude, and elevation. These locations provided a wide range of environments for testing and validation of the crop growth (CROPGRO) model considered in this study with observed changes in soils, rainfall and other weather parameters. Model predicted satisfactorily the trends of days to flowering, maturity and grain yields. The deviations of simulated results were within ±15% of the measurements.
Validated CROPGRO model has been used to simulate the impact of climate change on soybean production in India. The projected scenarios for the Indian subcontinent as inferred from three state-of-the-art global climate models (GCMs) have been used in the present study. There was a decrease (ranging between about 10 and 20%) in soybean yield in all the three future scenarios when the effect of rise in surface air temperature at the time of the doubling of CO
2 concentration was considered. The results obtained on the mitigatory option for reducing the negative impacts of temperature increases indicate that delaying the sowing dates would be favorable for increased soybean yields at all the locations in India. Sowing in the second season would also be able to mitigate the detrimental effects of future increases in surface temperature due to global warming at some locations.</description><subject>Agricultural and forest climatology and meteorology. Irrigation. Drainage</subject><subject>Agronomy. Soil science and plant productions</subject><subject>Biological and medical sciences</subject><subject>Climate change</subject><subject>Crop simulation model</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>General agronomy. 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Validated CROPGRO model has been used to simulate the impact of climate change on soybean production in India. The projected scenarios for the Indian subcontinent as inferred from three state-of-the-art global climate models (GCMs) have been used in the present study. There was a decrease (ranging between about 10 and 20%) in soybean yield in all the three future scenarios when the effect of rise in surface air temperature at the time of the doubling of CO
2 concentration was considered. The results obtained on the mitigatory option for reducing the negative impacts of temperature increases indicate that delaying the sowing dates would be favorable for increased soybean yields at all the locations in India. Sowing in the second season would also be able to mitigate the detrimental effects of future increases in surface temperature due to global warming at some locations.</abstract><cop>Amsterdam</cop><cop>Oxford</cop><cop>New York, NY</cop><pub>Elsevier B.V</pub><doi>10.1016/S0168-1923(03)00157-6</doi><tpages>13</tpages></addata></record> |
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subjects | Agricultural and forest climatology and meteorology. Irrigation. Drainage Agronomy. Soil science and plant productions Biological and medical sciences Climate change Crop simulation model Fundamental and applied biological sciences. Psychology General agronomy. Plant production Global climate models Impact mitigation Sowing dates Soybean |
title | Mitigating climate change impact on soybean productivity in India: a simulation study |
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