A systematic approach to identifying key parameters and processes in agroecosystem models

摘要

Highlights?The parametric sensitivity of the Landscape-DNDC agroecosystem biogeochemistry model is quantified.?23% of the model's biogeochemistry parameters are responsible for 87% of output sensitivity.?The temporal scale of the analysis is shown to affect the relative importance of the parameters.?The parameterisation of the processes that describe soil microbial dynamics is key to model predictions.AbstractProcess-based agroecosystem biogeochemistry models are widely used to quantify the flow of water and nutrients in agricultural ecosystems and they have become important tools in the effort to address the twin challenges of reducing greenhouse gas emissions and improving agricultural sustainability. Model parameters require careful calibration, as they affect the simulated processes and outputs. Sensitivity analysis (SA) is commonly used to quantify the impacts of parameters on outputs, and guide