ABSTRACT
References ................................................................................................... 709
Simulation models are becoming readily available tools in agricultural and environmental engineering to design and evaluate management strategies which respect multiple criteria such as optimal crop production and preservation of soil and water quality. Nonetheless, the effectiveness with which these modeling tools can be adopted relies heavily on the knowledge of the system parameters, which today still constitutes an important issue for the scientific community. During the last decade, identification of system parameters from observations of the state variables of the dynamic system by means of inverse modeling procedures has gained much interest. With these methods, experimental data from a dynamic experiment are combined with a validated forward model and an appropriate optimization algorithm to estimate model parameters of the system. The inversion is generally based on the optimization of an objective function, which expresses the difference between the observed response of the system and the simulated response with the given model subject to a trial parameter set.
