345-9 The Paradigm of Climate Change Impacts and Adaptation in Farming Systems, Income and Poverty of Western Indo-Gangetic Basin.

Poster Number 108

See more from this Division: Special Sessions
See more from this Session: AgMIP Poster Session
Wednesday, November 5, 2014
Long Beach Convention Center, Exhibit Hall ABC
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Gokul Paudel, CIMMYT, Kathmandu, (Non U.S.), NEPAL
Poster Presentation
  • ASA_-AgMIP_Poster_CIMMYT_Karnal-IGB.pdf (1.2 MB)
  • The paradigm of climate change impacts and adaptation in farming systems, income and poverty of western Indo-Gangetic Basin


    G.Paudel1, B.Singh2, N.Subash3, G.Baigoria4, A.McDonald1

    1International Maize and Wheat Improvement Centre, CIMMYT, Kathmandu, Nepal

    2International Maize and Wheat Improvement Centre, CIMMYT, New Delhi, India

    3PDFSR, Indian Council of Agricultural Research, ICAR, Uttar Pradesh, India

    4University of Nebraska-Lincoln, USA


    Indo-Gangetic Basin (IGB), the cereal basket of India, Bangladesh and Nepal, accountable for supplying food for more than a billion populations, is already embedded by forefront question of decline in crop productivity due to climatic variability [Lobell et al., 2012, Mishra et al., 2013] and appropriate adaptation strategies are likely to overcome the exacerbating poverty in the region. The overall objective of this study was to quantify, yet accurate, assessment of climate change impacts and adaptation in farming population of western Indo-Gangetic Basin (IGB). A household survey collected farming system data in 2010 from 100 farms for Cereal System Initiatives for South Asia (CSISA) project, from Karnal district, Haryana state of India consisting primarily rice and wheat were used for calibration of models. Outputs from five commonly used GCMs obtained from Coupled Model Intercomparision Project (CMIP5) [Taylor et al., 2009] were used to evaluate plausible change in rice and wheat yield. Agricultural Production System Simulator (APSIM) and Decision Support System for Agrotechnology Transfer (DSSAT) cropping system models were used for projecting rice and wheat yields during mid period century (2040-2069). Changes in yield for minor crops like sugarcane, sorghum, maize and livestock were estimated from secondary literatures. The socio-economic scenario parameters were obtained from Representative Agriculture Pathways (RAPs) [Valdivia and Antle, 2014]. Farming system assessment was done by using explicit Trade-off Analysis for Multi-dimensional Impact assessment (TOA-MD) model [Antle, 2011, Antle et al., 2014] with and without adaptation. Potential adaptation strategies tested were; short duration high yielding rice variety, advance sowing for wheat, improved cultivars for minor crops, and, better herd management and increase in feed supply for livestock. The outputs from 5 GCMs for RCP 8.5 emission scenario predicted erratic rainfall, increase in temperature and decrease in precipitation. The DSSAT model simulated 1-7% gain in wheat productivity for four GCMs, whereas, APSIM simulated < 1% gain in one of the GCM. The simulated rice productivity declined in APSIM by 1-23%, whereas, DSSAT simulated gain in yield in one of the GCM by 2%. Nevertheless, both of the model simulated >50% gains in crop productivity during adaptations. Farming system assessment showed some gain in net farm income due to constricted supply and higher price projected by the IMPACT model during climate change, however, the gains were such minimal with no impact in poverty level however. The TOA-MD projected the adoption rate of >73% for all the climatic scenarios. The farmers could increase their net farm returns by >55%. The poverty level could limit to 5-6% with 40-50% increase in per-capita income. The paradigm of climate change impacts and adaptation focused on adoption of adaptation packages in farming population of western IGB

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