GDNDC: An integrated system to model water-nitrogen-crop processes for agricultural management at regional scales

Agroecosystem 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 extensi...

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Vydáno v:Environmental modelling & software : with environment data news Ročník 134; s. 104807
Hlavní autoři: Huang, Xiao, Ni, Shaoqiang, Wu, Chao, Zorn, Conrad, Zhang, Wenyuan, Yu, Chaoqing
Médium: Journal Article
Jazyk:angličtina
Vydáno: Oxford Elsevier Ltd 01.12.2020
Elsevier Science Ltd
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ISSN:1364-8152, 1873-6726
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Abstract Agroecosystem 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 modelling 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 modelling 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. •Parallel computing mode realized in GDNDC to improve the computing efficiency for regional-scale simulation.•Multiple modules are coupled into GDNDC to enable complete end-to-end simulation for decision support.•Coupler is developed in GDNDC to integrate different modules by coordinating the information exchange.•GDNDC presents a new structure of agricultural modelling system for easy maintenance and extension.
AbstractList Agroecosystem 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 modelling 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 modelling 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.
Agroecosystem 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 modelling 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 modelling 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. •Parallel computing mode realized in GDNDC to improve the computing efficiency for regional-scale simulation.•Multiple modules are coupled into GDNDC to enable complete end-to-end simulation for decision support.•Coupler is developed in GDNDC to integrate different modules by coordinating the information exchange.•GDNDC presents a new structure of agricultural modelling system for easy maintenance and extension.
ArticleNumber 104807
Author Zorn, Conrad
Wu, Chao
Zhang, Wenyuan
Huang, Xiao
Yu, Chaoqing
Ni, Shaoqiang
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  email: chaoqingyu@gmail.com
  organization: Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing, China
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Snippet Agroecosystem modelling has increasingly focused on the integration of soil biogeochemical processes and crop growth. However, few models are available that...
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StartPage 104807
SubjectTerms Agricultural ecosystems
Agricultural management
agroecosystems
Algorithms
Biogeochemistry
China
Computation
computer software
corn
Crop growth
Crop yield
Crops
Decision support
Decision support systems
Denitrification
Drought
Fertilizer application
GDNDC
issues and policy
Optimal fertilization
Optimization
Parallel computation
Parallel processing
Parameter optimization
Simulation
soil
Title GDNDC: An integrated system to model water-nitrogen-crop processes for agricultural management at regional scales
URI https://dx.doi.org/10.1016/j.envsoft.2020.104807
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