Crop-DNDC integrates detailed crop growth algorithms with DNDC to simulate C, N and water cycles.

CropDNDCcrop growthCNwater cycles



Initial contribute: 2020-01-02


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Application-focused categoriesNatural-perspectiveLand regions

Detailed Description

English {{currentDetailLanguage}} English

Quoted from: Zhang, Yu, Changsheng Li, Xiuji Zhou, and Berrien Moore III. "A simulation model linking crop growth and soil biogeochemistry for sustainable agriculture." Ecological modelling 151, no. 1 (2002): 75-108. 

Fig. 1 shows the overall structure of the model. The major considerations for the model development include: (1) the dynamics of crop growth and its responses to climatic conditions and farming practices; (2) interactions of crop growth with soil biogeochemical processes, and (3) the overall behavior of the model in simulating crop yield and trace gas emissions responding to climate conditions and management practices. The model consists of three submodels. Climatic submodel calculates water dynamics and soil temperature profile. Crop submodel simulates crop phenological development, leaf area index (LAI), photosynthesis, respiration, assimilate allocation, rooting processes and nitrogen uptake. Soil biogeochemistry submodel predicts decomposition, nitrification, denitrification and trace gas emissions. Crop growth interacts with soil climatic and biogeochemical submodels in terms of water and nitrogen uptake, water and nitrogen stress on crop growth, and the amount and quality of crop residue incorporated in the soil at the end of the growing season. Thus the model tightly couples crop growth with soil biogeochemical and climatic components, and simulates C, N and water cycles in agroecosystems with a relatively complete scope. The input data include climate drivers, soil features, crop parameters and farming practices. The output includes soil carbon and nitrogen pools and fluxes, crop production, nitrate leaching and trace gas emissions. The primary time step of the simulation is 1 day. Spatially, state variables are expressed as mass per unit area (such as kg/ha) or relative content (fraction), they may represent a site, a field or an area where its size depends on the degree of homogeneity of the area and the representativeness of the input data. Soil profile is divided into numerous layers and simulation is conducted layer by layer.


Fig. 1. The overall structure of the Crop-DNDC model.



Crop-DNDC team (2020). Crop-DNDC, Model Item, OpenGMS,


Initial contribute : 2020-01-02



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