Environmental modelling, software and decision support: state of the art and new perspective
Gespeichert in:
| Format: | Buch |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
Oxford [u.a.]
Elsevier Science
2008
|
| Ausgabe: | 1. ed. |
| Schriftenreihe: | Developments in integrated environmental assessment
3 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XVI, 369 S. graph. Darst. |
| ISBN: | 9780080568867 0080568866 |
Internformat
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Datensatz im Suchindex
| _version_ | 1804138594561949696 |
|---|---|
| adam_text | Titel: Environmental modelling, software and decision support
Autor: Jakeman, Anthony J.
Jahr: 2008
Contents
Preface v
1. Modelling and Software as Instruments for Advancing Sustainability i
A.J. Jakeman, S.H. Chen, A.E. Rizzoli, and A.A. Voinov i
1.1. Introduction i
1.2. Aims of the Summit 3
1.3. The Role of Modelling and Software 4
1.4. Common Problems in Modelling 6
1.5. Current State of the Art and Future Challenges in Modelling 8
1.5.1. Generic issues 8
1.5.2. Sectoral issues 9
1.6. Conclusions 11
References 12
2. Good Modelling Practice 15
N. Crout, T. Kokkonen, AJ. Jakeman, J.P. Norton, L.T.H. Newham, R. Anderson,
H. Assaf, B.F.W. Croke, N. Gaber, J. Gibbons, D. Holzworth, J. Mysiak, ). Reichl,
R. Seppelt, T. Wagener, and P. Whitfield 15
2.1. Introduction 16
2.2. Key Components of Good Modelling Practice 17
2.2.1. Model purpose 17
2.2.2. Model evaluation 18
2.2.3. Performance measures 19
2.2.4. Stating and testing model assumptions 20
2.2.5. Ongoing model testing and evaluation 23
2.3. Model Transparency and Dissemination 25
2.3.1. Terminology 25
2.3.2. Reporting 25
2.3.3. Model dissemination 26
2.4. A Definition of Good Modelling Practice 27
2.5. Progress Towards Good Modelling Practice 27
vili Contents
2.6. Recommendations 29
References 29
3. Bridging the Gaps Between Design and Use: Developing Tools to Support
Environmental Management and Policy 33
B.S. Mclntosh, C. Giupponi, A.A. Voinov, C. Smith, K.B. Matthews, M. Monticino,
M.J. Kolkman, N. Crossman, M. van Ittersum, D. Haase, A. Haase, J. Mysiak,
J.C.J. Groot, S. Sieber, P. Verweij, N. Quinn, P. Waeger, N. Gaber, D. Hepting,
H. Schölten, A. Sulis, H. van Delden, E. Gaddis, and H. Assaf 33
3.1. A Gap Between Design and Use? 34
3.2. Decision and Information Support Tool Review 35
3.3. Supporting Organisational Decision Making 36
3.4. Supporting Participatory and Collaborative Decision Making 38
3.5. The Nature and Extent of the Gap 39
3.6. Good Practice Guidelines for Involving Users in Development 41
3.6.1. Know the capabilities and limitations of DIST technologies 41
3.6.2. Focus on process not product 41
3.6.3. Understand roles, responsibilities and requirements 42
3.6.4. Work collaboratively 42
3.6.5. Build and maintain trust and credibility 43
3.7. Conclusions 44
Acknowledgements 45
References 45
4. Complexity and Uncertainty: Rethinking the Modelling Activity 49
M. Brugnach, C. Pahl-Wostl, K.E. Lindenschmidt, J.A.E.B. Janssen, T. Filatova,
A. Mouton, G. Holtz, P. van der Keur, and N. Gaber 49
4.1. Introduction 50
4.2. Uncertainty: Causes and Manifestations 51
4.2.1. Causes of uncertainty 51
4.2.2. Manifestation of uncertainty 52
4.3. A Conceptual Approach to Deal with Uncertainty and Complexity in Modelling 52
4.3.1. Prediction 53
4.3.2. Exploratory analysis 53
4.3.3. Communication 54
4.3.4. Learning 56
4.4. Examples 57
4.4.1. Prediction: model use in the development of the US clean air mercury
rule 57
4.4.2. Exploratory analysis: microeconomic modelling of land use change in
a coastal zone area 59
Contents ¡x
4.4.3. Communication: modelling water quality at different scales and
different levels of complexity 61
4.4.4. Learning: modelling for strategic river planning in the Maas, the
Netherlands 62
4.5. Conclusions 64
4.5.1. Models for prediction purposes 64
4.5.2. Models for exploratory purposes 65
4.5.3. Models for communication purposes 65
4.5.4. Models for learning purposes 65
Acknowledgements 66
References 66
5. Uncertainty in Environmental Decision Making: Issues, Challenges and
Future Directions 69
H.R. Maier, J.C. Ascough II, M. Wattenbach, C.S. Renschier, W.B. Labiosa, and
J.K. Ravalico 69
5.1. Introduction 69
5.2. Environmental Decision-making Process 71
5.3. Sources of Uncertainty 73
5.4. Progress, Challenges and Future Directions 76
5.4.1. Risk-based assessment criteria 76
5.4.2. Uncertainty in human input 77
5.4.3. Computational efficiency 78
5.4.4. Integrated software frameworks for decision making under
uncertainty 79
5.5. Conclusions 81
References 82
6. Environmental Policy Aid Under Uncertainty 87
J. Mysiak, J.D. Brown, J.M.L. Jansen, and N.W.T. Quinn 87
6.1. Introduction 87
6.2. Factors Influencing Perceptions of Uncertainty 89
6.3. Uncertainty in Decision Models 91
6.4. Uncertainty in Practical Policy Making 94
6.5. Reducing Uncertainty Through Innovative Policy Interventions 95
6.6. Discussion and Conclusions 96
References 97
x Contents
7. Integrated Modelling Frameworks for Environmental Assessment and
Decision Support 101
A.E. Rizzoli, G. Leavesley, J.C. Ascough, R.M. Argent, I.N. Athanasiadis, V. Brilhante,
F.H.A. Claeys, 0. David, M. Donatelli, P. Gijsbers, D. Havlik, A. Kassahun,
P. Krause, N.W.T. Quinti, H. Schölten, R.S. Sojda, and F. Villa 101
7.1. Introduction 102
7.1.1. A first definition 103
7.1.2. Why do we develop new frameworks? 103
7.1.3. A more insightful definition 104
7.2. A Generic Architecture for ElMFs 105
7.2.1. A vision 107
7.3. Knowledge Representation and Management 107
7.3.1. Challenges for knowledge-based environmental modelling 109
7.4. Model Engineering 110
7.4.1. Component-based modelling 112
7.4.2. Distributed modelling 114
7.5. Driving and Supporting the Modelling Process 114
7.5.1. The experimental frame 114
7.6. Conclusions 116
References 117
8. Intelligent Environmental Decision Support Systems 119
M. Sànchez-Marrè, K. Gibert, R.S. Sojda, J.P. Steyer, P. Struss, I. Rodríguez-Roda,
J. Comas, V. Brilhante, and E.A. Roehl 119
8.1. Introduction 120
8.1.1. Complexity of environmental systems 120
8.1.2. New tools for a new paradigm 121
8.2. Intelligent Environmental Decision Support Systems (IEDSS) 121
8.2.1. IEDSS development 123
8.3. About Uncertainty Management 125
8.4. Temporal Reasoning 126
8.4.1. Featuring the problem 128
8.4.2. Approaches to temporal reasoning 128
8.4.3. Case-based reasoning for temporal reasoning 129
8.5. Geographic Information and Spatial Reasoning 130
8.5.1. Understanding spatial reasoning 130
8.5.2. Kriging and variants 132
8.5.3. Representing change/time steps/feedback loops 132
8.5.4. Middleware, blackboards and communication protocols 133
8.5.5. Multiagent systems 133
8.6. Evaluation of IEDSS and Benchmarking 134
Contents xi
8.6.1. Benchmarking 136
8.7. Conclusions and Future Trends 138
References 139
9. Formal Scenario Development for Environmental Impact Assessment
Studies 145
Y. Liu, M. Mahmoud, H. Hartmann, S. Stewart, T. Wagener, D. Semmens, R. Stewart,
H. Gupta, D. Domínguez, D. Hülse, R. Letcher, B. Rashleigh, C. Smith, R. Street,
J. Ticehurst, M. Twery, H. van Delden, and D. White 145
9.1. Introduction 146
9.2. Terminology and Background 148
9.2.1. Terminology 148
9.2.2. Characteristics of scenarios 149
9.3. A Formal Approach to Scenario Development 153
9.3.1. Scenario definition 154
9.3.2. Scenario construction 154
9.3.3. Scenario analysis 156
9.3.4. Scenario assessment 156
9.3.5. Risk management 157
9.4. Monitoring and Post-audits 157
9.5. Discussions and Future Directions 158
9.5.1. Uncertainty issues 158
9.5.2. Potential obstacles to formal scenario development 159
9.5.3. Future recommendations 160
Acknowledgements 160
References 161
10. Free and Open Source Geospatial Tools for Environmental Modelling and
Management 163
A. Jolma, D.P. Ames, N. Horning, H. Mitasova, M. Neteler, A. Racicot, and T. Sutton 163
10.1. Introduction 164
10.2. Platform 165
10.3. Software Stack 167
10.3.1. Geospatial software stacks 167
10.3.2. System software 168
10.3.3. Geospatial data processing libraries 169
10.3.4. Data serving 170
10.3.5. User interface 172
10.3.6. End-user applications 173
10.4. Workflows for Environmental Modelling and Management 173
10.4.1. Case 1 - cartographic map production 174
xü Contents
10.4.2. Case 2 - web-based mapping 175
10.4.3. Case 3 - numerical simulation 176
10.4.4. Case4-environmental management 176
10.5. Discussion 178
10.6. Conclusion 179
Acknowledgements 179
References 179
11. Modelling and Monitoring Environmental Outcomes in Adaptive
Management 181
J.P. Norton and K.H. Reckhow 181
11.1. Adaptive Management and Feedback Control 181
11.2. Shared and Distinct Features of the Management and Control Problems 183
11.3. Adaptivity 186
11.3.1. Limitations of feedback and motivation for adaptivity 186
11.3.2. Adaptive control and its failings 187
11.4. Problems in Adaptive Management and Some Tools from Other Fields 188
11.4.1. A short list of problems in adaptive management 188
11.4.2. Difficulties in developing acceptable predictive models 188
11.4.3. Robustness to poor prediction via Model Predictive Control 189
11.4.4. Adaptive management and Bayesian analysis 190
11.4.5. Conflicts regarding ecological values and management goals 194
11.4.6. Inadequate attention to non-scientific information 195
11.4.7. Unwillingness by agencies to implement long-term policies 195
11.5. Open Challenges for Adaptive Management 196
11.5.1. Characterisation of uncertainty 196
11.5.2. Matching the model to system characteristics 197
11.5.3. Bottom-up and top-down modelling 197
11.6. Conclusions Preceding the Workshop 198
Acknowledgements 199
Appendix A. Summary of Workshop Discussion 199
References 202
12. Data Mining for Environmental Systems 205
K. Gibert, ). Spate, M. Sànchez-Marrè, loannis N. Athanasiadis, and ). Comas 205
12.1. Introduction 205
12.2. Data Mining Techniques 210
12.2.1. Preprocessing: data cleaning, outlier detection, missing value
treatment, transformation and creation of variables 210
12.2.2. Data reduction and projection 211
12.2.3. Visualisation 212
Contents X¡¡¡
12.2.4. Clustering and density estimation 212
12.2.5. Classification and regression methods 213
12.2.6. Association analysis 214
12.2.7. Artificial neural networks 215
12.2.8. Other techniques 215
12.2.9. Spatial and temporal aspects of environmental data mining 215
12.3. Guidelines for Good Data Mining Practice 216
12.3.1. Integrated approaches 219
12.4. Software-Existing and Under Development 220
12.5. Conclusions and Challenges for Data Mining of Environmental Systems 223
Acknowledgement 224
References 224
13. Generic Simulation Models for Facilitating Stakeholder Involvement in
Water Resources Planning and Management: A Comparison, Evaluation,
and Identification of Future Needs 229
H. Assaf, E. van Beek, C. Borden, P. Gijsbers, A. Jolma, S. Kaden, M. Kaltofen,
J.W. Labadie, D.P. Loucks, N.W.T. Quinn, J. Sieber, A. Sulis, W.J. Werick, and
D.M. Wood 229
13.1. Introduction 230
13.2. Model Characteristics and Comparisons 231
13.3. Stakeholder Invotvement 238
13.4. Enhancing Non-expert Modelling Accessibility 238
13.5. Reaching Out to Younger Generations 239
13.6. The Current State of the Art - Results of Workshop Discussion 240
13.6.1. On detail and complexity 240
13.6.2. On stakeholder participation and shared vision modelling 241
13.6.3. On applied technology 242
13.6.4. On development and continuity 243
13.6.5. On content 244
13.7. Overall Conclusion 244
Acknowledgements 245
References 245
14. Computational Air Quality Modelling 247
R. San José, A. Baklanov, R.S. Sokhi, K. Karatzas, and J.L. Pérez 247
14.1. Introduction 247
14.2. The Purpose of Air Quality Modelling 251
14.3. Urban Air Quality Information and Forecasting Systems 252
14.4. Integrated Modelling 254
14.5. Air Quality Modelling for Environment and Health Risk Assessments 255
xiv Contents
14.6. Air Quality Modelling as a Natural Part of Climate Change Modelling 255
14.7. Scales of Processes/Models and Scale-interaction Aspects 256
14.8. Chemical Schemes and Aerosol Treatment 257
14.9. Real-time Air Quality Modelling 260
14.10.Internet and Information Technologies for Air Quality Modelling 261
14.11. Application Category Examples 262
14.11.1. Web-based integration 262
14.11.2. Web-based wizards 263
14.11.3. Web services 263
References 264
15. Identification, Resolution and Apportionment of Contamination Sources 269
R. Tauler, P. Paatero, R.C. Henry, C. Spiegelman, E.S. Park, R.L. Poirot, M. Viana,
X. Querol, and P.K. Hopke 269
15.1. Introduction 269
15.2. Data Sets 270
15.3. Models and Methods 271
15.3.1. Principal component analysis and factor analysis 271
15.3.2. Alternatives to PCA based methods 272
15.3.3. Other related techniques 276
15.4. Some Applications 279
15.4.1. Combined Aerosol Trajectory Tools (CATT) 279
15.4.2. Source identification in southern California by non-parametric
regression 280
15.4.3. Comparison between PMF and PCA-MLRA performance 280
15.5. Conclusions 281
References 281
16. Regional Models of Intermediate Complexity (REMICs) - A New Direction in
Integrated Landscape Modelling 285
K.-O. Wenkel, R. Wieland, W. Mirschel, A. Schultz, C. Kampichler, A. Kirilenko, and
A. Voinov 285
16.1. Why Do We Need Better Models on a Landscape Scale? 285
16.2. The Way Forward 287
16.3. Landscape Models 288
16.3.1. Selection of landscape indicators 288
16.3.2. REMICs 288
16.3.3. Hybrid models 289
16.3.4. Complexity in landscape modelling 289
16.4. A Sample Modelling Tool 291
Contents
16.5. Conclusions 293
References 294
17. Challenges in Earth System Modelling: Approaches and Applications 297
DJ. Erickson, R.J. Oglesby, S. Elliott, W. Steffen, and G. Brasseur 297
17.1. Introduction 297
17.2. Key Challenges (1) 298
17.2.1. Atmosphere modelling 299
17.2.2. Land modelling 299
17.2.3. Ocean modelling 301
17.3. Key Challenges (2) 302
17.3.1. Overall discussion 302
17.3.2. Biogeochemical modelling needs 302
17.3.3. Methodologies for employing output from Earth system models 302
17.4. Conclusions 305
References 305
18. Uncertainty and Sensitivity Issues in Process-based Models of Carbon and
Nitrogen Cycles in Terrestrial Ecosystems 307
G.R. Larocque, J.S. Bhatti, A.M. Gordon, N. Luckai, M. Wattenbach, J. Liu, C. Peng,
P.A. Arp, S. Liu, C.-F. Zhang, A. Komarov, P. Grabarnik, J. Sun, and T. White 307
18.1. Introduction 308
18.2. Uncertainty 308
18.2.1. Uncertainty in measurements 309
18.2.2. Model uncertainty 310
18.2.3. Scenario uncertainty and scaling 319
18.3. Model Validation 320
18.4. Sensitivity Analysis 322
18.5. Conclusions 322
Acknowledgements 324
References 324
19. Model-Data Fusion in Studies of the Terrestrial Carbon Sink 329
G.A. Alexandrov, D. Chan, M. Chen, K. Gurney, K. Higuchi, A. Ito, CD. Jones,
A. Komarov, K. Mabuchi, D.M. Matross, F. Veroustraete, and W.W. Verstraeten 329
19.1. Introduction 330
19.2. The Major Obstacles 331
19.3. The Solutions 332
19.3.1. The use of FLUXNETdata 332
19.3.2. The use of atmospheric C02 concentration measurements 335
xvi Contents
19.3.3. The use of remote sensing data 339
19.4. The Way Forward 340
Acknowledgements 341
References 341
20. Building a Community Modelling and Information Sharing Culture 345
A. Voinov, R.R. Hood, I.D. Daues, H. Assaf, and R. Stewart 345
20.1. Introduction 345
20.2. Open Source and Hacker Culture 347
20.3. Knowledge Sharing and Intellectual Property Rights 350
20.4. Software Development and Collaborative Research 352
20.5. Open Source Software vs. Community Modelling 353
20.6. Pros and Cons of Open-Source Modelling 357
20.7. Open Data 360
20.8. Teaching 361
20.9. Conclusions and Recommendations 362
References 365
Index 367
|
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| building | Verbundindex |
| bvnumber | BV035296121 |
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| ctrlnum | (OCoLC)470964040 (DE-599)OBVAC07007108 |
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| dewey-ones | 550 - Earth sciences |
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| dewey-tens | 550 - Earth sciences |
| discipline | Geologie / Paläontologie Umwelt |
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| genre | (DE-588)4143413-4 Aufsatzsammlung gnd-content |
| genre_facet | Aufsatzsammlung |
| id | DE-604.BV035296121 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T21:30:40Z |
| institution | BVB |
| isbn | 9780080568867 0080568866 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-017101069 |
| oclc_num | 470964040 |
| open_access_boolean | |
| owner | DE-M49 DE-BY-TUM |
| owner_facet | DE-M49 DE-BY-TUM |
| physical | XVI, 369 S. graph. Darst. |
| publishDate | 2008 |
| publishDateSearch | 2008 |
| publishDateSort | 2008 |
| publisher | Elsevier Science |
| record_format | marc |
| series | Developments in integrated environmental assessment |
| series2 | Developments in integrated environmental assessment |
| spelling | Environmental modelling, software and decision support state of the art and new perspective edited by Anthony J. Jakeman .... 1. ed. Oxford [u.a.] Elsevier Science 2008 XVI, 369 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Developments in integrated environmental assessment 3 Sciences de l'environnement - Simulation par ordinateur ram Environmental sciences Computer simulation Modellierung (DE-588)4170297-9 gnd rswk-swf Entscheidungsunterstützung (DE-588)4202171-6 gnd rswk-swf Computersimulation (DE-588)4148259-1 gnd rswk-swf Umweltwissenschaften (DE-588)4137364-9 gnd rswk-swf Umweltinformatik (DE-588)4762396-2 gnd rswk-swf (DE-588)4143413-4 Aufsatzsammlung gnd-content Umweltwissenschaften (DE-588)4137364-9 s Computersimulation (DE-588)4148259-1 s Entscheidungsunterstützung (DE-588)4202171-6 s DE-604 Umweltinformatik (DE-588)4762396-2 s Modellierung (DE-588)4170297-9 s 1\p DE-604 Jakeman, Anthony J. Sonstige oth Developments in integrated environmental assessment 3 (DE-604)BV035296082 3 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017101069&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Environmental modelling, software and decision support state of the art and new perspective Developments in integrated environmental assessment Sciences de l'environnement - Simulation par ordinateur ram Environmental sciences Computer simulation Modellierung (DE-588)4170297-9 gnd Entscheidungsunterstützung (DE-588)4202171-6 gnd Computersimulation (DE-588)4148259-1 gnd Umweltwissenschaften (DE-588)4137364-9 gnd Umweltinformatik (DE-588)4762396-2 gnd |
| subject_GND | (DE-588)4170297-9 (DE-588)4202171-6 (DE-588)4148259-1 (DE-588)4137364-9 (DE-588)4762396-2 (DE-588)4143413-4 |
| title | Environmental modelling, software and decision support state of the art and new perspective |
| title_auth | Environmental modelling, software and decision support state of the art and new perspective |
| title_exact_search | Environmental modelling, software and decision support state of the art and new perspective |
| title_full | Environmental modelling, software and decision support state of the art and new perspective edited by Anthony J. Jakeman .... |
| title_fullStr | Environmental modelling, software and decision support state of the art and new perspective edited by Anthony J. Jakeman .... |
| title_full_unstemmed | Environmental modelling, software and decision support state of the art and new perspective edited by Anthony J. Jakeman .... |
| title_short | Environmental modelling, software and decision support |
| title_sort | environmental modelling software and decision support state of the art and new perspective |
| title_sub | state of the art and new perspective |
| topic | Sciences de l'environnement - Simulation par ordinateur ram Environmental sciences Computer simulation Modellierung (DE-588)4170297-9 gnd Entscheidungsunterstützung (DE-588)4202171-6 gnd Computersimulation (DE-588)4148259-1 gnd Umweltwissenschaften (DE-588)4137364-9 gnd Umweltinformatik (DE-588)4762396-2 gnd |
| topic_facet | Sciences de l'environnement - Simulation par ordinateur Environmental sciences Computer simulation Modellierung Entscheidungsunterstützung Computersimulation Umweltwissenschaften Umweltinformatik Aufsatzsammlung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017101069&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV035296082 |
| work_keys_str_mv | AT jakemananthonyj environmentalmodellingsoftwareanddecisionsupportstateoftheartandnewperspective |