A flexible (modular, generic and mixed procedural object oriented) and integrative (replaceable, expandable, independent and interactive) software tool for the setup of adapted crop models.
Multsch S., Kraft, P., Frede, H.-G., Breuer, L. 2011 Development and application of the generic Plant growth Modeling Framework (PMF) Modelling and Simulation. _Modelling and Simulation Society of Australia and New Zealand, December 2011, pp. 995-1001. ISBN: 978-0-9872143-1-7 full text
Kraft, P., Multsch, S., Vaché, K.B., Frede, H.-G. Breuer, L. 2010. Using Python as a coupling platform for integrated catchment models. Advances in Geosciences 27, 51-56. full text
Houska, T., Multsch, S., Kraft, P., Frede, H.-G. and Breuer, L.: Monte Carlo-based calibration and uncertainty analysis of a coupled plant growth and hydrological model, Biogeosciences, 11(7), 2069–2082, https://doi.org/10.5194/bg-11-2069-2014, 2014.
Kellner, J., Multsch, S., Houska, T., Kraft, P., Müller, C. and Breuer, L.: A coupled hydrological-plant growth model for simulating the effect of elevated CO2 on a temperate grassland, Agricultural and Forest Meteorology, 246, 42–50, https://doi.org/10.1016/j.agrformet.2017.05.017 , 2017.
Kellner, J., Houska, T., Manderscheid, R., Weigel, H., Breuer, L., Kraft, P., 2019: Response of maize biomass and soil water fluxes on elevated CO 2 and drought – from field experiments to process‐based simulations. Global Change Biology. https://doi.org/10.1111/gcb.14723
The use of crop models as part of scientific research models or economic farm tools leads to a wide range of applications. On the one hand they need to be simple; on the other hand they should be complex enough to simulate a variety of growth mechanisms. The development of entirely new models for different questions requires a lot of coding and work such as changes in the model structure, the inclusion of alternative process descriptions or the implementation of additional functionality. Often, added model components do not really fit to the model philosophy of the originally developed base model.
We therefore developed a flexible (modular, generic and mixed procedural object oriented) and integrative (replaceable, expandable, independent and interactive) software tool for the setup of adapted crop models. The Plant growth Modeling Framework (PMF) is based on the Unified Modeling Language and implemented in Python, a high level object-oriented programming language. PMF provides the code flexibility to rapidly exchange and compare different process mechanisms. An interface facilitates a straightforward coupling with other models.