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...

Full description

Saved in:
Bibliographic Details
Published in:Environmental modelling & software : with environment data news Vol. 134; p. 104807
Main Authors: Huang, Xiao, Ni, Shaoqiang, Wu, Chao, Zorn, Conrad, Zhang, Wenyuan, Yu, Chaoqing
Format: Journal Article
Language:English
Published: Oxford Elsevier Ltd 01.12.2020
Elsevier Science Ltd
Subjects:
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
China
GDNDC
Optimal fertilization
Parallel computation
Parameter optimization
Decision support
ISSN:1364-8152, 1873-6726
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:1364-8152
1873-6726
DOI:10.1016/j.envsoft.2020.104807