Spatial variability of climate change impacts on yield of rice and wheat in the Indian Ganga Basin

A. Mishra, R. Singh, N.S. Raghuwanshi, C. Chatterjee, J. Froebrich

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38 Citations (Scopus)

Abstract

Indian Ganga Basin (IGB), one of the most densely populated areas in the world, is facing a significant threat to food grain production, besides increased yield gap between actual and potential production, due to climate change. We have analyzed the spatial variability of climate change impacts on rice and wheat yields at three different locations representing the upper, middle and lower IGB. The DSSAT model is used to simulate the effects of climate variability and climate change on rice and wheat yields by analyzing: (i) spatial crop yield response to current climate, and (ii) impact of a changing climate as projected by two regional climate models, REMO and HadRM3, based on SRES A1B emission scenarios for the period 2011-2040. Results for current climate demonstrate a significant gap between actual and potential yield for upper, middle and lower IGB stations. The analysis based on RCM projections shows that during 2011-2040, the largest reduction in rice and wheat yields will occur in the upper IGB (reduction of potential rice and wheat yield respectively by 43.2% and 20.9% by REMO, and 24.8% and 17.2% by HadRM3). In the lower IGB, however, contrasting results are obtained, with HadRM3 based projections showing an increase in the potential rice and wheat yields, whereas, REMO based projections show decreased potential yields. We discuss the influence of agro-climatic factors; variation in temperature, length of maturity period and leaf area index which are responsible for modeled spatial variability in crop yield response within the IGB. (C) 2013 Elsevier B.V. All rights reserved.
Original languageEnglish
Pages (from-to)S132-S138
JournalScience of the Total Environment
Volume468-469
DOIs
Publication statusPublished - 2013

Keywords

  • food-production
  • adaptation
  • simulation
  • temperature
  • northern
  • models

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