Shortcuts
Top of page (Alt+0)
Page content (Alt+9)
Page menu (Alt+8)
Your browser does not support javascript, some WebOpac functionallity will not be available.
.
Default
.
PageMenu
-
Main Menu
-
Member Services
.
Purchase Suggestion
.
Exit Webopac
.
Search Menu
Simple Search
.
Advanced Search
.
Clear Search Sets
.
Refine Search Results
.
.
FOS Childrens Library
.
New Items Search
.
Bottom Menu
Help
About
.
Map
.
Exit Webopac
.
Languages
English
.
German
.
New Items Menu
New Items Search
.
New Items List
.
.................................
EBOOK CENTRAL
.
SCIENCE DIRECT (BUSINESS)
.
MASADER
.
UNWTO
.
SCOPUS
.
E-JOURNALS
.
DATABASE INFO. SYSTEM (DBIS)
.
LIBRARY WEBSITE
.
© LIBERO v6.4.1sp211215
Page content
You are here
:
>
Search Simple
Catalogue Tag Display
Catalogue Tag Display
MARC 21
Environmental modelling: finding simplicity in complexity
Tag
Description
020
$a9780470749111
084
$aTD195.E58 2013
245
$aEnvironmental modelling$bfinding simplicity in complexity$cJohn Wainwright, Mark Mulligan.
250
$a2nd ed.
260
$aChichester, West Sussex$aHoboken, NJ$bWiley$c2013
300
$axviii, 475 p.$bill., charts, maps$c25 cm.
505
$aModel Building; Chapter 1 Introduction; 1.1 Introduction; 1.2 Why model the environment?; 1.3 Why simplicity and complexity?; 1.4 How to use this book; 1.5 The book's web site; References; Chapter 2 Modelling and Model Building; 2.1 The role of modelling in environmental research; 2.2 Approaches to model building: chickens, eggs, models and parameters?; 2.3 Testing models; 2.4 Sensitivity analysis and its role; 2.5 Errors and uncertainty; 2.6 Conclusions; References. Chapter 3 Time Series: Analysis and Modelling3.1 Introduction; 3.2 Examples of environmental time series; 3.3 Frequency-size distribution of values in a time series; 3.4 White noises and Brownian motions; 3.5 Persistence; 3.6 Other time-series models; 3.7 Discussion and summary; References; Chapter 4 Non-Linear Dynamics, Self-Organization and Cellular Automata Models; 4.1 Introduction; 4.2 Self-organization in complex systems; 4.3 Cellular automaton models; 4.4 Case study: modelling rill initiation and growth; 4.5 Summary and conclusions; 4.6 Acknowledgements; References. Chapter 5 Spatial Modelling and Scaling Issues5.1 Introduction; 5.2 Scale and scaling; 5.3 Causes of scaling problems; 5.4 Scaling issues of input parameters and possible solutions; 5.5 Methodology for scaling physically based models; 5.6 Scaling land-surface parameters for a soil-erosion model: a case study; 5.7 Conclusion; References; Chapter 6 Environmental Applications of Computational Fluid Dynamics; 6.1 Introduction; 6.2 CFD fundamentals; 6.3 Applications of CFD in environmental modelling; 6.4 Conclusions; References. Chapter 7 Data-Based Mechanistic Modelling and the Emulation of Large Environmental System Models7.1 Introduction; 7.2 Philosophies of science and modelling; 7.3 Statistical identification, estimation and validation; 7.4 Data-based mechanistic (DBM) modelling; 7.5 The statistical tools of DBM modelling; 7.6 Practical example; 7.7 The reduced-order modelling of large computer-simulation models; 7.8 The dynamic emulation of large computer-simulation models; 7.9 Conclusions; References; Chapter 8 Stochastic versus Deterministic Approaches; 8.1 Introduction; 8.2 A philosophical perspective. 8.3 Tools and methods8.4 A practical illustration in Oman; 8.5 Discussion; References; Part II The State of the Art in Environmental Modelling; Chapter 9 Climate and Climate-System Modelling; 9.1 The complexity; 9.2 Finding the simplicity; 9.3 The research frontier; 9.4 Online material; References; Chapter 10 Soil and Hillslope (Eco)Hydrology; 10.1 Hillslope e-c-o-hydrology?; 10.2 Tyger, tyger ... ; 10.3 Nobody loves me, everybody hates me ... ; 10.4 Memories; 10.5 I'll avoid you as long as I can?; 10.6 Acknowledgements; References
650
$aEnvironmental sciences$xMathematical models.
700
$aWainwright, John,
700
$aMulligan, Mark,