4.5 Article

A new module to simulate surface crop residue decomposition: Description and sensitivity analysis

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ECOLOGICAL MODELLING
卷 480, 期 -, 页码 -

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ELSEVIER
DOI: 10.1016/j.ecolmodel.2023.110327

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Surface residues; Crop residues; Crop modeling; Sensitivity analysis; Conservation agriculture

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A new simulation module was developed to explicitly simulate the decomposition of surface residues, and a sensitivity analysis was conducted to compare the results with a benchmark model. The new module showed higher concordance in simulating different crop residues and time periods compared to the benchmark model.
In the agroecosystem, surface crop residues are widely recognized as affecting many processes such as soil water dynamics, crop growth, nitrogen and carbon cycling. For this reason, developing models that simulate the effect of surface residues and their decomposition is crucial, especially while modeling conservation agriculture. To date, even though many cropping systems and C-oriented models differently simulate the evolution of surface residue biomass, a comprehensive approach is still missing. In this study, we developed a new simulation module that explicitly simulates the decomposition of surface residues, by including all the variables and processes that are relevant for agroecosystem's simulation. This module has been later integrated into the ARMOSA cropping system model. To quantify the contribution of each parameter to the simulated outputs (i.e., decomposed biomass), a sensitivity analysis (SA) was conducted, comparing the result with the APSIM model used as a benchmark. The SA was conducted on four different crop residues (maize, rye, soybean and wheat) over three different years. In addition, for each crop residue, we verified whether parameters changed their relevance depending on the considered time period. The most critical parameters of the new module reflected the importance of air temperature, soil water content and residue biomass in the decomposition process. The po-tential decomposition rate had minor importance, highlighting that, when setting crop-specific values, other environment-related parameters are more relevant for the actual decomposition rate. In the case of APSIM model, the potential decomposition rate and the optimum temperature for this process resulted in the first two ranks. Finally, concordance coefficients were used to compare SA outputs: compared to APSIM, the new model showed higher concordance passing from one crop residue to another, even when comparing the different simulation periods within the same crop. In summary, this work presented a novelty in surface crop residue representation and provided a deep survey of the module behavior and characteristics.

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