Upscaling and downscaling methods for environmental research /

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作者：edited by Marc F.P. Bierkens, Peter A. Finke and Peter de Willigen.

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ISBN：9780792363392

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简介

Environmental studies typically involve the combination of dynamic models with data sources at various spatial and temporal scales. Also, the scale of the model output is rarely in tune with the scale at which decision-makers require answers or implement environmental measures. Consequently, the question has been raised how to obtain results at the appropriate scale. Models, usually developed at the scale of a research project, have to be applied to larger areas (extrapolation), with incomplete data coverage (interpolation) and to different supports (upscaling and downscaling) to facilitate studies for decision-makers. This book gives an overview of the various problems involved, and focuses on a description of upscaling and downscaling methods that are known to exist. Furthermore, this book is the first in its kind in that it contains a decision support system that advises the practitioner on which upscaling or downscaling method to use in his specific context. This book is meant for an audience of MSc- and PhD-students, applied researchers and practitioners in soil science, hydrology, (agro) ecology, agronomy and the environmental sciences in general.

Table Of Contents:
Preface ix

Introduction 1(18)

The problem of scale transfer 1(5)

Aims and scope 6(1)

Definitions 7(9)

Contents of this book 16(3)

Upscaling 19(92)

A classification of upscaling methods 19(9)

Averaging of observations or output variables 28(22)

Exhaustive Information 32(2)

Design based methods 34(4)

Geostatistical prediction 38(4)

Deterministic functions 42(3)

Combinations and auxiliary information 45(5)

Finding representative parameters or input variables 50(32)

Exhaustive information 60(4)

Deterministic functions 64(3)

Indirect stochastic methods 67(5)

Direct stochastic methods 72(6)

Inverse modelling 78(4)

Averaging of model equations 82(13)

Deterministic: temporal or volume averaging 87(4)

Stochastic: ensemble averaging 91(4)

Model simplification 95(16)

Lumped conceptual modelling 101(4)

Meta-modelling 105(6)

Downscaling 111(34)

A classification of downscaling methods 111(8)

Empirical functions 119(12)

Deterministic functions 120(2)

Conditional stochastic functions 122(4)

Unconditional stochastic functions 126(5)

Mechanistic models 131(7)

Deterministic functions 131(2)

Conditional stochastic functions 133(3)

Unconditional stochastic functions 136(2)

Fine scale auxiliary information 138(7)

Deterministic functions 138(3)

Conditional stochastic functions 141(1)

Unconditional stochastic functions 142(3)

A simple DSS for upscaling and downscaling 145(12)

Purpose and philosophy of the DSS 145(1)

Functionality and options at startup 146(3)

Definition of the research chain over the scales 149(5)

Define a new research chain 149(3)

Modify parts of research chain 152(2)

Enter the DSS from the research chain 154(1)

DSS Upscaling and Downscaling 155(2)
Appendix: Random Variables and Stochastic Functions 157(20)
Glossary 177(4)
References 181(6)
Index 187

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