Abstract
Maize is an important cereal food crop whose productivity is highly vulnerable to climate change driven weather parameters. In the present study the calibrated and validated DSSAT-CERES-Maize model (v 4.7.5) was used to simulate maize (cv PMH1 and PMH2) yield under viable adaptive options using the bias corrected weather data from ensemble global circulation model under four scenarios (RCP’s 2.6, 4.5, 6.0 and 8.5) in four agroclimatic zones (AZ) of Punjab, India. The adaptive strategies considered during future time slices; end century (EC: 2030–2050), mid century (MC: 2050–2070) and late century (LC: 2070–2090) were shifted sowing date integrated with three doses of nitrogen (145 kg ha−1, 165 kg ha−1 and 185 kg ha−1). Amongst the cultivars, PMH1 performed well at all the locations except AZ IV and Abohar lying in AZ V while PMH2 cultivar was not able to perform well under any of the future scenarios with adaptation measures. Under low emission (RCP 2.6) scenario, increase in yield was simulated in AZ II by 11–38% (PMH1) for the combined adaptation measures and upto 15% (PMH2) for shift in sowing dates alone, in AZ III by 7–35% (PMH1) at all the locations and upto 33% for PMH2 at Patiala only, in AZ V upto 32% (PMH1) and 37% (PMH2). Under two stabilization scenarios (RCPs 4.5 and 6.0) increase in yield was observed in AZ II by 14–43% for PMH1 and no increase for PMH2, in AZ III (except Amritsar) by 18–97% for PMH1 and 7–57% for PMH2, in AZ V by 8–23% for PMH1 and by 8–30% for PMH2 during EC only. The high emission (RCP 8.5) scenario observed no significant yield increment during the MC and EC time periods. During the twenty-first century in Punjab, sowing of maize during 2nd week June in all the AZ except (Ludhiana: 3rd week June and Faridkot: 2nd week May) coupled with nitrogen @ 165 kg ha−1 or 185 kg ha−1 was found to be an appropriate adaptive strategy for sustainable cultivation of maize crop.
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Data availability
The datasets generated during and/or analysed during the current study are not publicly available because it is currently being used for further research purpose so can’t be made available but are available from the corresponding author on reasonable request.
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Acknowledgements
The simulated GCM data used in the study was obtained from site http://gismap.ciat.cgiar.org/MarkSimGCM/ for different agroclimatic zones of Punjab (India).
Funding
This work was supported by The CRIDA, Hyderabad sponsored research project: All India Coordinated Research Project on Agrometeorology- National Innovations on Climate Resilient Agriculture (AICRPAM-NICRA) and Dr. Prabhjyot-Kaur received this support.
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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by [Prabhjyot Kaur, S S Sandhu and Jatinder Kaur], [Shivani Kothiyal] and [Shivani Kothiyal]. The first draft of the manuscript was written by [Shivani Kothiyal] and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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Kothiyal, S., Prabhjyot-Kaur, Sandhu, S.S. et al. Modelling viable adaptive options under climate change scenarios to increase maize productivity in Indian Punjab. Arab J Geosci 16, 403 (2023). https://doi.org/10.1007/s12517-023-11516-9
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DOI: https://doi.org/10.1007/s12517-023-11516-9