Credit hours
In-class work per week |
Practice per week |
Credits |
Duration |
Total |
2 |
2 |
8 |
15 weeks |
120 hours |
Instructor
Fábio Ricardo Marin
Quirijn de Jong van Lier
Objective
Enable students to process, analyze, quantify and simulate physical and biological processes in
agricultural systems with an emphasis on the use of computational resources. Present the principles and
main techniques of process-based modeling in agrohydrological and crop modeling and enable students
to understand and develop numerical computational models. Basic concepts of dynamic simulation of
agricultural systems and modeling methods including sensitivity analysis, parameter estimation,
stochastic analysis and model evaluation. Application of models in the analysis of agricultural systems.
Content
1) Types of models: statistical, empirical, deterministic, mechanistic models. Dynamic and static models.
Macroscopic and microscopic models. Diagrammatic representation used in the analysis of agricultural
systems. 2) Modeling tools: conservation laws and principles; differential and integral equations,
numerical simulation. Discrete and continuous modeling. 3) Finite difference numerical methods:
Newton-Raphson, Euler, Runge-Kutta, Crank-Nicolson. 4) Stochastic process modeling concepts:
distributions, covariance, random variables, correlated random variables. Uncertainty. 5) Evaluation and
benchmarking of models. Model sensitivity to parameters. Comparison between simulation and real
data. Comparison between models. Cross validation. 6) Development of a model based on a process of
interest and the presentation of modeling results in the form of a seminar at the end of the semester.
Bibliography
Campbell, G.S. & Norman, J.M. 1998. An introduction to environmental biophysics. Springer, 285p.
Goudriaan, J, & Van Laar, H.H. Modelling Potential Crop Growth Processes. Kluwer Academic Publishers,
London. 1994.
Hanks, J., & Ritchie, J.T. Modeling Plant and Soil Systems. American Society of Agronomy, 1991.
Harte, J. Consider a Spherical Cow: A Course in Environmental Problem Solving. University Science
Books. Sausalito, CA. 1988.
Nieder, R., & Benbi, D. Handbook of Processes and Modeling in the Soil-Plant System. CRC Press, 2003.
Overman, Allen R., e Richard V. Scholtz III. Mathematical Models of Crop Growth and Yield. CRC Press,
2002.
Teh, C. Introduction to Mathematical Modeling of Crop Growth: How the Equations are Derived and
Assembled into a Computer Program. BrownWalker Press. Boca Raton. 2006.
Wallach, D., D. Makowski, and J. W. Jones (Eds.). Working with Dynamic Crop Models: Evaluation,
Analysis, Parameterization, and Applications. Elsevier. New York. ISBN 0-444-52135-6. 2006.
Wit, C.T. de & Goudriaan, J. Simulation of Ecological Processes. Pudoc, Wageningen. 1978.