Working with Dynamic Crop Models: Evaluation, Analysis, Parameterization, and Applications / Edition 1

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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

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Product Details

  • ISBN-13: 9780444521354
  • Publisher: Elsevier Science
  • Publication date: 9/7/2006
  • Edition description: New Edition
  • Edition number: 1
  • Pages: 462
  • Product dimensions: 1.00 (w) x 6.14 (h) x 9.21 (d)

Meet the Author

est maître de conférence des universités, médecin des hôpitaux de Paris au service de dermatologie de l'hôpital Tarnier, Paris.

est maître de conférence des universités, médecin des hôpitaux de Paris au service de dermatologie de l'hôpital Tarnier, Paris.

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Table of Contents

1 The two forms of crop models
2 Evaluating crop models
3 Uncertainty and sensitivity analysis for crop models
4 Parameter estimation for crop models
5 Data assimilation with crop models
6 Representing and optimizing management decisions with crop models
7 Using crop models for multiple fields

8 Introduction to section II
9 Fundamental concepts of crop models illustrated by a comparative approach
10 Crop models with genotype parameters
11 Model assisted genetic improvement of crops
12 Parameterization and evaluation of a corn crop model
13 Evaluation of a model for kiwifruit
14 Sensitivity and uncertainty analysis of a static denitrification model
15 Sensitivity analysis of PASTIS, a model of nitrogen transport and transformation in the soil
16 Sensitivity analysis of GENESYS, a model for studying the effects of cropping system on gene flow
17 Data assimilation and parameter estimation for precision agriculture with the crop model STICS
18 Application of extended and ensemble Kalman filters to soil carbon estimation
19 Analyzing and improving corn irrigation strategies with MODERATO, a combination of a corn crop model and a decision model
20 Managing wheat for ethanol production. A multiple criteria approach

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