Dealing with uncertainty in crop models

Code: 9781786765260
Publication date: 02/12/2019
Extent: 30 pages

Contributions by: Daniel Wallach, INRA, France

Chapter synopsis: There is increasing awareness in crop modeling of the importance of uncertainty. The modeler needs uncertainty information to prioritize improvements, while the user needs uncertainty information to make informed decisions. This chapter introduces the concept of model uncertainty, considering such factors as model structure, inputs and parameters. The chapter then looks at ways to reduce uncertainty in crop modelling and looks ahead to future trends in the area. Finally, the chapter provides detailed guidance on further reading on the subject.

DOI: 10.19103/AS.2019.0061.21
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Table of contents 1 Introduction 2 Model uncertainty 3 Prediction uncertainty 4 Reducing uncertainty 5 Case studies 6 Future trends 7 Conclusion 8 Where to look for further information 9 References

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