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Integrated Environmental Modelling to Solve Real World Problems: Methods, Vision and Challenges

Product Code: SP408
Series: GSL Special Publications - print copy
Author/Editor: Edited by A.T. Riddick, H. Kessler and J.R.A. Giles
Publication Date: 10 January 2017
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Special Publication 408

The discipline of Integrated Environmental Modelling (IEM) has developed in order to solve complex environmental problems, for example understanding the impacts of climate change on the physical environment. IEM provides methods to fuse or link models together, this in turn requires facilities to make models discoverable and also to make the outputs of modelling easily visualized.

The vision and challenges for IEM going forward are summarized by leading proponents. Several case studies describe the application of model fusion to a range of real-world problems including integrating groundwater and recharge models within the UK Environment Agency, and the development of ‘catastrophe’ models to predict better the impact of natural hazards. Communicating modelling results to end users who are often not specialist modellers is also an emerging area of research addressed within the volume. Also included are papers that highlight current developments of the technology platforms underpinning model fusion.

Published online 03/01/2017. Print copies available from 10/01/2017.

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Type: Book
Ten Digit ISBN:
Thirteen Digit ISBN: 978-1-86239-687-6
Publisher: GSL
Binding: Hardback
Pages: 274
Weight: 0.82 kg


RIDDICK, A., HUGHES, A., KESSLER, H. & GILES, J. Introduction to integrated environmental modelling to solve real world problems: methods, vision and challenges

Vision Strategic Requirements and Challenges

PEACH, D., RIDDICK, A., HUGHES, A., KESSLER, H., MATHERS, S., JACKSON, C. & GILES, J. Model fusion at the British Geological Survey: experiences and future trends

MOORE, R. V. & HUGHES, A. G. Integrated environmental modelling: achieving the vision

SUTHERLAND, J., TOWNEND, I. H., HARPHAM, Q. K. & PEARCE, G. R. From integration to fusion: the challenges ahead

Case Studies

FARRELL, R., VERVERS, M., DAVISON, P., HOWLETT, P. & WHITEMAN, M. Splicing recharge and groundwater flow models in the Environment Agency National Groundwater Modelling System

PASANEN, A. H. & OKKONEN, J. S. 3D geological models to groundwater flow models: data integration between GSI3D and groundwater flow modelling software GMS and FeFlow®

ROYSE, K. R., HILLIER, J. K., HUGHES, A., KINGDON, A., SINGH, A. & WANG, L. The potential for the use of model fusion techniques in building and developing catastrophe models

WILDHABER, M. L., DEY, R., WIKLE, C. K., MORAN, E. H., ANDERSON, C. J. & FRANZ, K. J. A stochastic bioenergetics model-based approach to translating large river flow and temperature into fish population responses: the pallid sturgeon example

WILDHABER, M. L., WIKLE, C. K., MORAN, E. H., ANDERSON, C. J., FRANZ, K. J. & DEY, R. Hierarchical stochastic modelling of large river ecosystems and fish growth across spatio-temporal scales and climate models: the Missouri River endangered pallid sturgeon example

LAXTON, J. L. Geological map fusion: OneGeology-Europe and INSPIRE

Social Aspects of Integrated Environmental Modelling

GLYNN, P. D. Integrated Environmental Modelling: human decisions, human challenges

GOBER, P., WHITE, D. D., QUAY, R., SAMPSON, D. A. & KIRKWOOD, C. W. Socio-hydrology modelling for an uncertain future, with examples from the USA and Canada

MAKROPOULOS, C. Thinking platforms for smarter urban water systems: fusing technical and socio-economic models and tools

Software Solutions and Methodology

CONRADS, P. A. & ROEHL, E. A. jr. The use of data-mining techniques for developing effective decision support systems: a case study of simulating the effects of climate change on coastal salinity intrusion

ROWE, E. C., WRIGHT, D. G., BERTRAND, N. & REIS, S. Fusing and disaggregating models, data and analysis tools for a dynamic science–society interface

KINGDON, A., GILES, J. R. A. & LOWNDES, J. P. Future of technology in NERC data models and informatics: outputs from InformaTEC

BEVEN, K. & LAMB, R. The uncertainty cascade in model fusion



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