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Improving Representation of Crop Growth and Yield in the Dynamic Land Ecosystem Model and Its Application to China


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dc.contributorHanqin Tian; tianhan@auburn.eduen_US
dc.creatorZhang, Jingting
dc.creatorTian, Hanqin
dc.creatorYang, Jia
dc.creatorPan, Shufen
dc.date.accessioned2022-07-29T17:06:13Z
dc.date.available2022-07-29T17:06:13Z
dc.date.created2018
dc.identifier10.1029/2017MS001253en_US
dc.identifier.urihttps://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2017MS001253en_US
dc.identifier.urihttps://aurora.auburn.edu/handle/11200/50322
dc.identifier.urihttp://dx.doi.org/10.35099/aurora-390
dc.description.abstractTo accurately assess the roles of agriculture in securing food security and maintaining environmental sustainability, it is essential to improve the representation of crop growth, development, and yield formation in global land models that traditionally focus on energy, water, carbon, and nitrogen exchanges between land and the atmosphere. In this study, a process-based agricultural module has been coupled with the Dynamic Land Ecosystem Model (DLEM-AG2.0) for assessing how multiple environmental factors (climate change, atmospheric CO2 concentration, tropospheric O-3, and nitrogen deposition) and human activities (land use/cover change, nitrogen fertilizer use, and irrigation) have affected the crop growth, development, yield, carbon (C), nitrogen (N), and water cycles in agroecosystems. Here we describe the model structure for simulating crop growth, development, and yield formation in the DLEM-AG2.0, and then we validate the model using field observations and a national yield survey for three major crops (wheat, maize, and rice) in China during 1980-2012. Results show that the DLEM-AG2.0 is capable of simulating the dynamic processes of phenological development, leaf growth expansion, biomass accumulation, biomass allocation, and yield formation for wheat, maize, and rice with normalized root mean square errors of the simulations of less than 20%. Our model-based yield estimation for the three major crops at the national scale for the period 1980-2012 is generally consistent with the national yield survey in China. The crop representation in the DLEM-AG2.0 is flexible for extrapolating to a global scale after rigorous testing with both site-specific and regional observations. Further advancement of agricultural modeling within the global land modeling framework will require consideration of human perception and behavior for adapting and mitigating global change.en_US
dc.formatPDFen_US
dc.relation.ispartofJournal of Advances in Modeling Earth Systemsen_US
dc.relation.ispartofseries1942-2466en_US
dc.rights© 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.subjectcarbon sequestrationen_US
dc.subjectChinaen_US
dc.subjectclimate-changeen_US
dc.subjectcrop modelingen_US
dc.subjectcrop yielden_US
dc.subjectdlem-ag20en_US
dc.subjectglobal changeen_US
dc.subjectgreenhouse-gas intensityen_US
dc.subjectleaf-areaen_US
dc.subjectnet primary productionen_US
dc.subjectnitrous-oxide emissionsen_US
dc.subjectphotosynthetic apparatusen_US
dc.subjectstomatal conductanceen_US
dc.subjecttemperature variabilityen_US
dc.subjectwheat rotation systemsen_US
dc.titleImproving Representation of Crop Growth and Yield in the Dynamic Land Ecosystem Model and Its Application to Chinaen_US
dc.typeCollectionen_US
dc.type.genreJournal Article, Academic Journalen_US
dc.citation.volume10en_US
dc.citation.issue7en_US
dc.citation.spage1680en_US
dc.citation.epage1707en_US
dc.description.statusPublisheden_US
dc.description.peerreviewYesen_US
dc.creator.orcidhttps://orcid.org/0000-0002-1806-4091en_US

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