Working with Dynamic Crop Models book cover

Working with Dynamic Crop Models

Evaluation, Analysis, Parameterization, and Applications

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.

Audience
Researchers and graduate students in agronomy, agricultural and biological engineering, agricultural economics and agricultural statistics. Teachers of advanced courses in modeling of biological systems.

Hardbound, 462 Pages

Published: May 2006

Imprint: Elsevier

ISBN: 978-0-444-52135-4

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 models7 Using crop models for multiple fieldsSECTION II APPLICATIONS 8 Introduction to section II9 Fundamental concepts of crop models illustrated by a comparative approach 10 Crop models with genotype parameters 11 Model assisted genetic improvement of crops12 Parameterization and evaluation of a corn crop model13 Evaluation of a model for kiwifruit14 Sensitivity and uncertainty analysis of a static denitrification model15 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 flow17 Data assimilation and parameter estimation for precision agriculture with the crop model STICS18 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 model20 Managing wheat for ethanol production. A multiple criteria approach

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