Literature DB >> 25829290

An integrated crop model and GIS decision support system for assisting agronomic decision making under climate change.

M D M Kadiyala1, S Nedumaran2, Piara Singh2, Chukka S2, Mohammad A Irshad2, M C S Bantilan2.   

Abstract

The semi-arid tropical (SAT) regions of India are suffering from low productivity which may be further aggravated by anticipated climate change. The present study analyzes the spatial variability of climate change impacts on groundnut yields in the Anantapur district of India and examines the relative contribution of adaptation strategies. For this purpose, a web based decision support tool that integrates crop simulation model and Geographical Information System (GIS) was developed to assist agronomic decision making and this tool can be scalable to any location and crop. The climate change projections of five global climate models (GCMs) relative to the 1980-2010 baseline for Anantapur district indicates an increase in rainfall activity to the tune of 10.6 to 25% during Mid-century period (2040-69) with RCP 8.5. The GCMs also predict warming exceeding 1.4 to 2.4°C by 2069 in the study region. The spatial crop responses to the projected climate indicate a decrease in groundnut yields with four GCMs (MPI-ESM-MR, MIROC5, CCSM4 and HadGEM2-ES) and a contrasting 6.3% increase with the GCM, GFDL-ESM2M. The simulation studies using CROPGRO-Peanut model reveals that groundnut yields can be increased on average by 1.0%, 5.0%, 14.4%, and 20.2%, by adopting adaptation options of heat tolerance, drought tolerant cultivars, supplemental irrigation and a combination of drought tolerance cultivar and supplemental irrigation respectively. The spatial patterns of relative benefits of adaptation options were geographically different and the greatest benefits can be achieved by adopting new cultivars having drought tolerance and with the application of one supplemental irrigation at 60days after sowing.
Copyright © 2015 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Climate change factors; Crop simulation; DSSAT; Virtual cultivars; Yield

Mesh:

Year:  2015        PMID: 25829290     DOI: 10.1016/j.scitotenv.2015.03.097

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  3 in total

1.  Studying of drought phenomena and vegetation trends over South Asia from 1990 to 2015 by using AVHRR and NASA's MERRA data.

Authors:  Shahzad Ali; Zhen Tian Xu; Malak Henchirli; Kalisa Wilson; Jiahua Zhang
Journal:  Environ Sci Pollut Res Int       Date:  2019-12-16       Impact factor: 4.223

2.  Improving the use of crop models for risk assessment and climate change adaptation.

Authors:  Andrew J Challinor; Christoph Müller; Senthold Asseng; Chetan Deva; Kathryn Jane Nicklin; Daniel Wallach; Eline Vanuytrecht; Stephen Whitfield; Julian Ramirez-Villegas; Ann-Kristin Koehler
Journal:  Agric Syst       Date:  2018-01       Impact factor: 5.370

3.  Simulating nitrogen management impacts on maize production in the U.S. Midwest.

Authors:  Kamaljit Banger; Emerson D Nafziger; Junming Wang; Umar Muhammad; Cameron M Pittelkow
Journal:  PLoS One       Date:  2018-10-22       Impact factor: 3.240

  3 in total

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