Analysing the parameter sensitivity of the agro-ecosystem model MONICA for different crops

Abstract Sensitivity analysis (SA) has become an important tool for analysing eco-system models and for supporting the calibration activities of models. A sensitivity analysis assessment is carried out on the agro-ecosystem model MONICA for the crops winter wheat, spring barley, silage maize, sugar beet, clover grass ley and winter rape, using cutting-edge tools (Python and HPC techniques) in combination with robust and widely used methods. The aim of SA is to identify model parameters that have a considerable impact on above-ground biomass with regard to a future model calibration and an improved understanding of model response patterns. First, the Morris method was applied to identify a subset of relevant model parameters. Here, we identified 28 generally important parameters from a set of 117 analysed parameters. In the second step, these parameters were used as input for the Extended Fourier Amplitude Sensitivity Test (FAST) method. The calculation of the total sensitivity indices provided a reliable sensitivity measure for the parameters of the MONICA model. The analysis of the relevant parameter sets for the considered crops revealed that the set of important parameters differed for each crop, but for all crops the parameters related to photosynthesis and plant development had a dominant effect on above-ground biomass.

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