Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.553635
Title: Simulating the impacts of extreme climate events on crop productivity in current and future climates in India
Author: Gummadi, Sridhar
Awarding Body: University of Reading
Current Institution: University of Reading
Date of Award: 2011
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Abstract:
We need to understand the impacts of climate variability and change at a regional level on crop productivity in order to develop response strategies to the changing climate. This thesis seeks to investigate the impacts of extreme climate events on crops in current and future climates in India. The response of observed yield to present day climate variability was examined. Paddy rice and groundnut yields had a significant positive correlation with rainfall (r = 0.40, p < 0.05), while maximum temperature showed a strong negative relationship (-0.45); no such relationship was found for maize. The EPIC crop model simulated yields over regions of India were evaluated by forcing with observed climate data. Simulated yields were within ±20% of observed yields, significant positive correlations were noted between the EPIC simulated and detrended observed crop yields (paddy rice 0.38; groundnut 0.40 and maize 0.29). Significant negative relationships were found between yield and extreme precipitation (above 50 mm/day) and maximum temperature (above 33°C). Global coupled climate models (HadCM3, GFDL 2.1 and ECHAM5) were used to assess impacts of the SRES A2 projected future emission scenario on yield. Yields were 40% lower compared with IMD-forced values due to poor representation of the current climate. The PRECIS Regional Climate Model was used to examine the impact of the SRES A2 scenario in more detail at the regional scale. Groundnut and maize yield decreased by 40%, while paddy rice yield decreased by 35%.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.553635  DOI: Not available
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