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Modelling Aspects of Water Framework Directive Implementation [Pehme köide]

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  • Formaat: Paperback / softback, 350 pages, kõrgus x laius x paksus: 234x156x18 mm
  • Sari: Water Framework Directive Series
  • Ilmumisaeg: 30-Apr-2010
  • Kirjastus: IWA Publishing
  • ISBN-10: 1843392232
  • ISBN-13: 9781843392231
Teised raamatud teemal:
Modelling Aspects of Water Framework Directive ImplementationSuurem pilt
  • Formaat: Paperback / softback, 350 pages, kõrgus x laius x paksus: 234x156x18 mm
  • Sari: Water Framework Directive Series
  • Ilmumisaeg: 30-Apr-2010
  • Kirjastus: IWA Publishing
  • ISBN-10: 1843392232
  • ISBN-13: 9781843392231
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781843392231.html
Märksõnad:
Special Offer: Water Framework Directive Series Set. To buy all four titles including Volume 3 and save £100, visit: http://iwapublishing.com/books/9781780400013/water-framework-directive -series-set



Modelling Aspects of Water Framework Directive Implementation: Volume 1 is a concrete outcome from the Harmoni-CA concerted action as part of a 4-volume series of Guidance Reports that guide water professionals through the implementation process of the Water Framework Directive, with a focus on the use of ICT-tools (and in particular modelling). They are complementary to the Guidance Documents produced by the EU Directorate General for Environment. 





Water resources planning and management and the development of appropriate policies require methodologies and tools that are able to support systematic, integrative and multidisciplinary assessments at various scales. It also requires the quantification of various uncertainties in both data and models, and the incorporation of stakeholders participation and institutional mechanisms into the various tools and risk assessment methodologies, to help decision makers understand and evaluate alternative measures and decisions. 





The other three volumes in the Water Framework Directive Series are: 



Water Framework Directive: Model supported Implementation - A Water Managers Guide edited by Fred Hattermann and Zbigniew W Kundzewicz  Integrated Assessment for WFD implementation: Data, economic and human dimension - Volume 2, edited by Peter A. Vanrolleghem Decision support for WFD implementation - Volume 3, edited by Peter A. Vanrolleghem.   





Visit the IWA WaterWiki to read and share material related to this title: http://www.iwawaterwiki.org/xwiki/bin/view/Articles/IntegratedAssessmentforWaterFrameworkDirectiveImplementation  
Authors for this volume xiii
Preface xv
Guidance Report I.1 Quality assurance in model-based water management: Better modelling practices
1(92)
Abstract
1(1)
Keywords
1(1)
1 Why Quality Assurance for Model-based Water Management?
1(8)
1.1 Problems in modelling
1(1)
1.2 Examples of poor quality of the modelling process
2(1)
1.2.1 Bloopers in modelling
2(2)
1.2.2 Lack of documentation of model capabilities and limitations
4(1)
1.2.3 Miscommunication and lack of public participation
4(1)
1.3 Context and objectives of this guidance document
5(4)
2 On Quality Assurance
9(8)
2.1 On quality
9(1)
2.2 Quality approaches in a historical perspective
9(2)
2.3 Quality assurance and ISO
11(1)
2.3.1 The International Organization for Standardization (ISO)
11(1)
2.3.2 ISO standards history
11(1)
2.3.3 ISO families of standards
12(1)
2.3.4 ISO 9000 quality standards in general
13(1)
2.3.5 Are ISO 9000 quality standards sufficient for modelling?
14(1)
2.4 On standards and guidelines
15(1)
2.4.1 Informal standards versus formal standards
15(1)
2.4.2 ISO and modelling standards
15(2)
3 State-of-the-art QA for Model-based Water Management
17(10)
3.1 Quality Assurance defined for modelling
17(1)
3.2 Guiding principles - three different approaches
17(2)
3.3 Type of QA guidelines for modelling
19(1)
3.3.1 Classification
19(1)
3.3.2 Development stage and prevalence of QA guidelines
20(1)
3.4 Existing guidelines
21(1)
3.5 Discussion of QA in water resources modelling
21(1)
3.5.1 Key aspects in QA guidelines
21(5)
3.5.2 Organisational requirements for QA guidelines to be effective
26(1)
4 Modelling Knowledge Base and Support Tool
27(24)
4.1 QA in the HarmoniQuA approach
27(2)
4.2 Design considerations of modelling KB and MoST
29(1)
4.3 Modelling KB in MoST
30(1)
4.3.1 MoST and Quality Assurance (QA)
30(1)
4.3.2 Structure and guiding principles of the Knowledge Base (KB)
31(2)
4.3.3 Terminology and glossary
33(1)
4.4 Modelling guidance
34(1)
4.4.1 Decomposition
34(1)
4.4.2 Steps and tasks
35(1)
4.4.3 Examples of description of tasks
36(3)
4.4.4 Methods
39(1)
4.5 Modelling Support Tool, MoST
40(1)
4.5.1 Introduction to MoST
40(1)
4.5.2 Starting MoST
40(1)
4.5.3 Setting-up modelling projects
41(1)
4.5.4 Guiding modelling projects
42(3)
4.5.5 Monitor modelling projects
45(4)
4.5.6 Reporting modelling projects
49(1)
4.5.7 Training material and help
50(1)
5 References
51(2)
6 Appendices
53(40)
Appendix A Functional requirements and design
53(1)
A.1 Modelling KB and associated tools
53(5)
A.2 Modelling Support Tool, MoST
58(3)
Appendix B Details of HarmoniQuA's modelling guidelines
61(1)
B.1 Terminology
61(4)
B.2 Steps and tasks of HarmoniQuA's modelling guidelines
65(7)
B.3 Details of the task `Determine requirements' (Step 1)
72(8)
B.4 Details of the task `Validation' (Step 4)
80(3)
B.5 Methods described in HarmoniQuA's modelling guidelines
83(10)
Guidance Report I.2 Model calibration and validation in model-based water management
93(98)
Abstract
93(1)
Keywords
93(1)
About this Guideline
94(1)
1 Executive Summary
95(4)
2 Calibration Framework
99(3)
3 Model Parameterisation and Choice of Calibration Parameters
102(7)
3.1 Principle of parameter parsimony
103(1)
3.2 Parameterisation methodologies
104(2)
3.3 Sensitivity analysis
106(2)
3.4 Use of prior information
108(1)
4 Calibration Data and Choice of Calibration Objectives
109(10)
4.1 Data requirements
110(1)
4.2 Numerical performance measures
111(4)
4.3 Scaling issues
115(1)
4.4 Weighting observations and aggregating performance measures
116(3)
5 Calibration Methods
119(4)
5.1 Manual calibration
120(1)
5.2 Automatic calibration
121(1)
5.3 Expert systems
122(1)
5.4 Recommendations
122(1)
6 Optimisation Algorithms
123(10)
6.1 Optimisation problem
124(1)
6.2 Local optimisation procedures
124(2)
6.3 Global optimisation procedures
126(3)
6.4 Recommendations
129(3)
6.5 Computational requirements
132(1)
7 Multi-objective Optimisation
133(5)
7.1 Optimisation problem
134(1)
7.2 Optimisation using aggregation
135(1)
7.3 Optimisation using Pareto dominance
136(1)
7.4 Single vs. multi-objective optimisation
137(1)
8 Model Validation
138(6)
8.1 Hierarchical test scheme
139(1)
8.1.1 Split-sample test
139(3)
8.1.2 Differential split-sample test
142(1)
8.1.3 Proxy-basin test
142(1)
8.1.4 Proxy-basin, differential split-sample test
143(1)
8.2 Validation tests based on model residuals
143(1)
9 Uncertainty Assessment
144(4)
9.1 Uncertainty sources
144(1)
9.2 Parameter non-uniqueness
145(2)
9.3 Uncertainty propagation
147(1)
10 Application Examples
148(27)
10.1 Lumped, conceptual rainfall-runoff model (MIKE 11/NAM)
148(1)
10.1.1 Model description
148(2)
10.1.2 Model setup
150(1)
10.1.3 Calibration parameters
150(1)
10.1.4 Calibration methods
151(1)
10.1.5 Results
152(2)
10.2 Groundwater model (MODFLOW)
154(1)
10.2.1 Model description
154(1)
10.2.2 Model parameterisation
155(2)
10.2.3 Calibration objectives
157(1)
10.2.4 Calibration parameters
157(1)
10.2.5 Calibration method
158(1)
10.2.6 Results
159(1)
10.3 Distributed, integrated model (MIKE SHE)
160(1)
10.3.1 Model description
160(1)
10.3.2 Model parameterisation
161(2)
10.3.3 Calibration objectives
163(1)
10.3.4 Calibration parameters
163(1)
10.3.5 Calibration method
164(1)
10.3.6 Results
164(1)
10.4 Water quality model (ESWAT)
165(1)
10.4.1 Model description
166(1)
10.4.2 Model setup
167(1)
10.4.3 Calibration objectives
167(2)
10.4.4 Calibration parameters
169(1)
10.4.5 Calibration method
170(1)
10.4.6 Results
171(4)
11 References
175(6)
12 Software
181(10)
12.1 Pest
181(3)
12.2 UCODE_2005
184(2)
12.3 Autocal
186(2)
12.4 Globe
188(3)
Guidance Report I.3 Review of sensitivity analysis methods
191(80)
Abstract
191(1)
Keywords
191(1)
1 Introduction
192(5)
1.1 Aims and objectives
192(1)
1.2 Target audience
192(1)
1.3 Benefits of sensitivity analysis
192(1)
1.4 What is sensitivity analysis?
193(1)
1.5 Sensitivity analysis and the Water Framework Directive
194(1)
1.6 Content and overview
195(2)
2 Decision Tree for Choosing a Sensitivity Analysis
197(5)
2.1.1 Sensitivity aim/setting
197(2)
2.1.2 Computational cost
199(3)
3 Detailed Methodology
202(30)
3.1 Examples
204(1)
3.1.1 Example 1
204(1)
3.1.2 Example 2
204(1)
3.2 Experimental design of SA (sampling)
205(1)
3.2.1 Screening design
205(1)
3.2.2 Random sampling
205(1)
3.2.3 Latin Hypercube sampling (LHS)
206(1)
3.2.4 Correlation control
206(1)
3.2.5 Quasi-random sampling with low-discrepancy sequences
206(1)
3.3 Methods of sensitivity analysis
207(1)
3.3.1 Graphical methods and visualisation
207(8)
3.3.2 Screening methods
215(2)
3.3.3 Local methods
217(2)
3.3.4 Global methods
219(10)
3.3.5 Sensitivity and model emulators
229(3)
4 Case Studies
232(8)
4.1 Modelling floodplain hydrological processes
232(1)
4.2 Flood inundation models
233(2)
4.3 Water quality modelling
235(5)
5 Conclusions
240(1)
6 Glossary
241(6)
7 References
247(7)
8 Appendix
254(17)
8.1 Screening methods
254(1)
8.1.1 Morris
254(1)
8.2 Local methods
255(1)
8.2.1 The finite difference method
255(1)
8.2.2 Direct method for sensitivity analysis
256(1)
8.2.3 Green function's method
257(1)
8.3 Global methods
258(1)
8.3.1 Variance based methods
258(5)
8.3.2 Regression analysis
263(1)
8.3.3 Regionalised sensitivity analysis
263(1)
8.3.4 Entropy
264(1)
8.3.5 Sensitivity and model emulators
265(6)
Guidance Report I.4 Uncertainty analysis in model-based water management
271
Abstract
271(1)
Keywords
271(1)
1 Why is Uncertainty Assessment Important?
271(11)
1.1 Uncertainty and risk in decision making
271(3)
1.2 Water Framework Directive - requirements
274(1)
1.3 A motivating example
275(3)
1.4 Context and objective of this document
278(4)
2 When is Uncertainty Assessment Required?
282(4)
2.1 The modelling process
282(2)
2.2 Uncertainty aspects
284(2)
3 What is Uncertainty?
286(7)
3.1 Definitions
286(3)
3.2 Taxonomy of imperfect knowledge
289(2)
3.3 Sources of uncertainty
291(1)
3.4 Nature of uncertainty
291(1)
3.5 The uncertainty matrix
292(1)
4 Methodologies for Uncertainty Assessment
293(26)
4.1 Data uncertainty
294(2)
4.2 Error propagation equations
296(2)
4.3 Expert elicitation
298(2)
4.4 Extended peer review (review by stakeholders)
300(1)
4.5 Inverse modelling (parameter estimation)
301(2)
4.6 Inverse modelling (predictive uncertainty)
303(1)
4.7 Monte Carlo Analysis
304(2)
4.8 Multiple model simulation
306(2)
4.9 NUSAP
308(2)
4.10 Quality assurance
310(2)
4.11 Scenario analysis
312(2)
4.12 Sensitivity analysis
314(1)
4.13 Stakeholder involvement
315(2)
4.14 Uncertainty matrix
317(2)
5 How to Select the Appropriate Methodology for Uncertainty Assessment
319(2)
5.1 Introduction
319(1)
5.2 Methodologies according to modelling process and level of ambition
319(2)
5.3 Methodologies according to source and type of uncertainty
321(1)
6 Illustrative Cases
321(8)
6.1 Case 1: Designing measures - nutrient load/comprehensive modelling
321(2)
6.2 Case 2: Designing measures - water scarcity/basic modelling
323(1)
6.3 Case 3: Implementation - Real-time forecasting (of Case 2)
323(6)
6.4 Case 4: Evaluation - Post project appraisal (of Case 1)
329(1)
7 References
329