Call number:
AWI G1-02-0088
In:
Developments in plant and soil sciences, Volume 88
Description / Table of Contents:
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.
Type of Medium:
Monograph available for loan
Pages:
X, 190 Seiten
,
Illustrationen
ISBN:
0-7923-6339-6
Series Statement:
Developments in plant and soil sciences 88
URL:
http://digitale-objekte.hbz-nrw.de/storage/2011/11/21/file_8/4354468.pdf
Language:
English
Note:
Contents
Preface
1. Introduction
1.1 The problem of scale transfer
1.2 Aims and scope
1.3 Definitions
1.4 Contents of this book
2. Upscaling
2.1 A classification of upscaling methods
2.2 Averaging of observations or output variables
2.2.1 Exhaustive Information
2.2.2 Design based methods
2.2.3 Geostatistical prediction
2.2.4 Deterministic functions
2.2.5 Combinations and auxiliary information
2.3 Finding representative parameters or input variables
2.3.1 Exhaustive information
2.3.2 Deterministic functions
2.3.3 Indirect stochastic methods
2.3.4 Direct stochastic methods
2.3.5 Inverse modelling
2.4 Averaging of model equations
2.4.1 Deterministic: temporal or volume averaging
2.4.2 Stochastic: ensemble averaging
2.5 Model simplification
2.5.1 Lumped conceptual modelling
2.5.2 Meta-modelling
3. Downscaling
3.1 A classification of downscaling methods
3.2 Empirical functions
3.2.1 Deterministic functions
3.2.2 Conditional stochastic functions
3.2.3 Unconditional stochastic functions
3.3 Mechanistic models
3.3.1 Deterministic functions
3.3.2 Conditional stochastic functions
3.3.3 Unconditional stochastic functions
3.4 Fine scale auxiliary information
3.4.1 Deterministic functions
3.4.2 Conditional stochastic functions
3.4.3 Unconditional stochastic functions
4. A simple DSS for upscaling and downscaling
4.1 Purpose and philosophy of the DSS
4.2 Functionality and options at startup
4.3 Definition of the research chain over the scales
4.3.1 Define a new research chain
4.3.2 Modify parts of research chain
4.4 Enter the DSS from the research chain
4.5 DSS Upscaling and Downscaling
Appendix: Random Variables and Stochastic Functions
Glossary
Contents
References
Index
Location:
AWI Reading room
Branch Library:
AWI Library
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