Working with Dynamic Crop Models: Evaluation, Analysis, Parameterization, and Applications

Couverture
Elsevier, 10 mai 2006 - 462 pages
Mathematical models are being used more and more widely to study complex dynamic systems (global weather, ecological systems, hydrological systems, nuclear reactors etc. including the specific subject of this book, crop-soil systems). The models are important aids in understanding, predicting and managing these systems. Such models are complex and imperfect. One fundamental research direction is to seek a better understanding of how these systems function, and to propose mathematical expressions embodying that understanding. However, this is not sufficient. It is also essential to have tools (often mathematical and statistical methods) to aid in developing, improving and using the models built from those equations. The book is specifically concerned with the application of methods to crop models, but much of the material is also applicable to dynamic system models in other fields. The goal of this book is to fill that gap.

* State-of-the-art methods explained simply and illustrated specifically for crop models* Parameter estimation – applying statistical methods to the complex case of crop models, including Bayesian methods * Includes model evaluation, understanding and estimating prediction error* Offers a unique data assimilation by using the Kalman filter and beyond
 

Table des matières

Section II Applications
249
Statistical notions
429
Answers to Exercises
437

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À propos de l'auteur (2006)

Daniel Wallach focuses on the application of statistical methods of dynamic systems, specifically on agronomy models. He has published in Agriculture, Ecosystems and Environment; Journal of Agricultural, Biological and Environmental Statistics and European Journal of Agronomy.

David Makowski is an expert with the European Food Safety authority and the French Agency for Food, Environmental and Occupational Health and Safety and has authored 50 refereed articles and 10 book chapters on statistics, agricultural modeling and risk analysis.

Francois Brun specializes in agricultural modeling systems using the R language, and has published in Journal of Experimental Botany.

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