Abstract computer simulations are widely used to support decision making and planning in the agriculture sector. The model structure and parameterization are important to achieve reliable results. On the one hand, many 1D crop growth models are using simplified hydrological processes and structures, e.g. by the use of a small number of soil layers or by the application of simple water flow approaches. On the other hand, in many hydrological models crop growth processes are poorly represented. Hence, fully coupled models with a high degree of process representation, would allow analysing the dynamic behaviour of the soil-plant interface in more detail.
We use the Python programming language to link two of such high process oriented independent models and to calibrate both models simultaneously. The Catchment Modelling Framework (CMF) simulates soil hydrology based on the Richards equation and the Van-Genuchten-Mualem retention curve. CMF is coupled with the Plant growth Modelling Framework (PMF), which predicts crop growth on the basis of radiation use efficiency, degree days, water shortage and dynamic root biomass allocation.
BYU ScholarsArchive Citation
Houska, T.; Multsch, S.; Kraft, P.; Frede, H.-G.; and Breuer, L.
"Monte Carlo based parameterization and uncertainty analysis of a coupled crop growth and hydrological model,"
Open Water Journal: Vol. 2
, Article 2.
Available at: http://scholarsarchive.byu.edu/openwater/vol2/iss1/2