4.7 Article

Climate change impact uncertainty assessment and adaptations for sustainable maize production using multi-crop and climate models

期刊

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
卷 29, 期 13, 页码 18967-18988

出版社

SPRINGER HEIDELBERG
DOI: 10.1007/s11356-021-17050-z

关键词

Sowing time; Maize hybrids; CERES-Maize; CSM-IXIM; APSIM-Maize; Phenology; LAI; TDM; Yield; Climate variability; Adaptation; Sustainable maize production

资金

  1. INRES, University of Bonn, Germany

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Future climate change poses significant threats to sustainable maize production in arid and semi-arid regions, but these impacts can be minimized through the adoption of modern agricultural tools. Research indicates that rising temperatures in the future may lead to reduced maize yields, but adjusting planting dates and utilizing heat and drought-resistant hybrids could help mitigate these effects.
Future climate scenarios are predicting considerable threats to sustainable maize production in arid and semi-arid regions. These adverse impacts can be minimized by adopting modern agricultural tools to assess and develop successful adaptation practices. A multi-model approach (climate and crop) was used to assess the impacts and uncertainties of climate change on maize crop. An extensive field study was conducted to explore the temporal thermal variations on maize hybrids grown at farmer's fields for ten sowing dates during two consecutive growing years. Data about phenology, morphology, biomass development, and yield were recorded by adopting standard procedures and protocols. The CSM-CERES, APSIM, and CSM-IXIM-Maize models were calibrated and evaluated. Five GCMs among 29 were selected based on classification into different groups and uncertainty to predict climatic changes in the future. The results predicted that there would be a rise in temperature (1.57-3.29 degrees C) during the maize growing season in five General Circulation Models (GCMs) by using RCP 8.5 scenarios for the mid-century (2040-2069) as compared with the baseline (1980-2015). The CERES-Maize and APSIM-Maize model showed lower root mean square error values (2.78 and 5.41), higher d-index (0.85 and 0.87) along reliable R-2 (0.89 and 0.89), respectively for days to anthesis and maturity, while the CSM-IXIM-Maize model performed well for growth parameters (leaf area index, total dry matter) and yield with reasonably good statistical indices. The CSM-IXIM-Maize model performed well for all hybrids during both years whereas climate models, NorESM1-M and IPSL-CM5A-MR, showed less uncertain results for climate change impacts. Maize models along GCMs predicted a reduction in yield (8-55%) than baseline. Maize crop may face a high yield decline that could be overcome by modifying the sowing dates and fertilizer (fertigation) and heat and drought-tolerant hybrids.

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