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dc.contributor.authorHuang, Xiao
dc.contributor.authorNi, Shaoqiang
dc.contributor.authorWu, Chao
dc.contributor.authorZorn, Conrad
dc.contributor.authorZhang, Wenyuan
dc.contributor.authorYu, Chaoqing
dc.date.accessioned2021-01-28T12:20:14Z
dc.date.available2021-01-28T12:20:14Z
dc.date.created2020-09-19T21:43:43Z
dc.date.issued2020-08-21
dc.identifier.citationEnvironmental Modelling & Software. 2020, 134 .en_US
dc.identifier.issn1364-8152
dc.identifier.urihttps://hdl.handle.net/11250/2725188
dc.description.abstractAgroecosystem modelling has increasingly focused on the integration of soil biogeochemical processes and crop growth. However, few models are available that offer high computing efficiencies for region-scale simulations, integrated decision support tools, and a structure that allows for easy extension. This paper introduces a new modeling tool to fill this gap: the GDNDC (Gridded DNDC) system for gridded agro-biogeochemical simulations. Based on the established DeNitrification and DeComposition (DNDC) model version-95, its main advancements include (i) implementation of parallel computation to significantly reduce computation time across multiple scales; (ii) a built-in parameter optimization algorithm to improve the predictive accuracy, and (iii) several decision support tools. We demonstrate each of these for county-level maize growth simulations in Liaoning Province (China) and reveal the potential of this new modeling tool to guide both long-term policy decisions regarding optimal fertilizer application and near-term crop yield forecasting for reactive decisions required in times of drought.en_US
dc.language.isoengen_US
dc.publisherElsevier Ltd.en_US
dc.titleGDNDC: An integrated system to model water-nitrogen-crop processes for agricultural management at regional scalesen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionacceptedVersionen_US
dc.rights.holder© 2020 Published by Elsevier Ltden_US
dc.subject.nsiVDP::Datateknologi: 551en_US
dc.subject.nsiVDP::Computer technology: 551en_US
dc.subject.nsiVDP::Datateknologi: 551en_US
dc.subject.nsiVDP::Computer technology: 551en_US
dc.subject.nsiVDP::Datateknologi: 551en_US
dc.subject.nsiVDP::Computer technology: 551en_US
dc.source.pagenumber11en_US
dc.source.volume134en_US
dc.source.journalEnvironmental Modelling & Softwareen_US
dc.identifier.doi10.1016/j.envsoft.2020.104807
dc.identifier.cristin1831365
dc.relation.projectNorges forskningsråd: 281109en_US
dc.source.articlenumber104807en_US
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode2


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